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1
Bosser, Pierre, Joël Van Baelen, and Olivier Bousquet. "Routine Measurement of Water Vapour Using GNSS in the Framework of the Map-Io Project." Atmosphere 13, no. 6 (June 2, 2022): 903. http://dx.doi.org/10.3390/atmos13060903.
Повний текст джерелаАнотація:
The "Marion Dufresne Atmospheric Program - Indian Ocean" (MAP-IO) project is a research program that aims to collect long-term atmospheric observations in the under-instrumented Indian and Austral Oceans. As part of this project, a Global Navigation Satellite System (GNSS) antenna was installed on the research vessel (R/V) Marion Dufresne in October 2020. GNSS raw data is intended to be used to retrieve Integrated Water Vapour (IWV) content along the Marion Dufresne route, which cruises more than 300 days per year in the tropical and austral Indian Ocean. This paper presents a first assessment of this GNSS-based IWV retrieval, based on the analysis of 9 months of GNSS raw data acquired along the route of the R/V Marion Dufresne in the Indian Ocean. A first investigation of GNSS raw data collected during the first 5 months of operation has highlighted the bad positioning of the antenna on the R/V that makes it prone to interference. Changing the location of the antenna has been shown to improve the quality of the raw data. Then, ship-borne GNSS-IWV are compared with IWV estimates deduced using more conventional techniques such as European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), ground-launched radiosondes and permanent ground GNSS stations operating close to the route of the R/V Marion Dufresne. The rms difference of 2.79 kg m−2 shows a good match with ERA5 and subsequently improved after the change in location of the GNSS antenna (2.49 kg m−2). The match with ground-based permanent GNSS stations fluctuates between 1.30 and 3.63 kg m−2, which is also shown to be improved after the change in location of the GNSS antenna. However, differences with ground-launched radiosondes still exhibit large biases (larger than 2 kg m−2). Finally, two operational daily routine analyses (at day+1 and day+3) are presented and assessed: the rms of the differences are shown to be quite low (1 kg m−2 for the day+1 analyses, 0.7 kg m−2 for the day+3 analysis), which confirms the quality of these routine analysis. These two routine analyses are intended to provide a continuous monitoring of water vapour above the Indian Ocean and deliver ship-borne IWV with a low latency for the entire scientific community.
2
Li, Tuan, Hongping Zhang, Zhouzheng Gao, Xiaoji Niu, and Naser El-sheimy. "Tight Fusion of a Monocular Camera, MEMS-IMU, and Single-Frequency Multi-GNSS RTK for Precise Navigation in GNSS-Challenged Environments." Remote Sensing 11, no. 6 (March 13, 2019): 610. http://dx.doi.org/10.3390/rs11060610.
Повний текст джерелаАнотація:
Precise position, velocity, and attitude is essential for self-driving cars and unmanned aerial vehicles (UAVs). The integration of global navigation satellite system (GNSS) real-time kinematics (RTK) and inertial measurement units (IMUs) is able to provide high-accuracy navigation solutions in open-sky conditions, but the accuracy will be degraded severely in GNSS-challenged environments, especially integrated with the low-cost microelectromechanical system (MEMS) IMUs. In order to navigate in GNSS-denied environments, the visual–inertial system has been widely adopted due to its complementary characteristics, but it suffers from error accumulation. In this contribution, we tightly integrate the raw measurements from the single-frequency multi-GNSS RTK, MEMS-IMU, and monocular camera through the extended Kalman filter (EKF) to enhance the navigation performance in terms of accuracy, continuity, and availability. The visual measurement model from the well-known multistate constraint Kalman filter (MSCKF) is combined with the double-differenced GNSS measurement model to update the integration filter. A field vehicular experiment was carried out in GNSS-challenged environments to evaluate the performance of the proposed algorithm. Results indicate that both multi-GNSS and vision contribute significantly to the centimeter-level positioning availability in GNSS-challenged environments. Meanwhile, the velocity and attitude accuracy can be greatly improved by using the tightly-coupled multi-GNSS RTK/INS/Vision integration, especially for the yaw angle.
3
Hu, Jiahuan, Ding Yi, and Sunil Bisnath. "A Comprehensive Analysis of Smartphone GNSS Range Errors in Realistic Environments." Sensors 23, no. 3 (February 2, 2023): 1631. http://dx.doi.org/10.3390/s23031631.
Повний текст джерелаАнотація:
Precise positioning using smartphones has been a topic of interest especially after Google decided to provide raw GNSS measurement through their Android platform. Currently, the greatest limitations in precise positioning with smartphone Global Navigation Satellite System (GNSS) sensors are the quality and availability of satellite-to-smartphone ranging measurements. Many papers have assessed the quality of GNSS pseudorange and carrier-phase measurements in various environments. In addition, there is growing research in the inclusion of a priori information to model signal blockage, multipath, etc. In this contribution, numerical estimation of actual range errors in smartphone GNSS precise positioning in realistic environments is performed using a geodetic receiver as a reference. The range errors are analyzed under various environments and by placing smartphones on car dashboards and roofs. The distribution of range errors and their correlation to prefit residuals is studied in detail. In addition, a comparison of range errors between different constellations is provided, aiming to provide insight into the quantitative understanding of measurement behavior. This information can be used to further improve measurement quality control, and optimize stochastic modeling and position estimation processes.
4
Qian, Kun, Jian-Guo Wang, and Baoxin Hu. "Novel Integration Strategy for GNSS-Aided Inertial Integrated Navigation." GEOMATICA 69, no. 2 (June 2015): 217–30. http://dx.doi.org/10.5623/cig2015-205.
Повний текст джерелаАнотація:
The conventional integration mechanism in GNSS (Global Navigation Satellite Systems) aided inertial integrated positioning and navigation system is mainly based on the continuous outputs of the navigation mechanization, the associated error models for navigation parameters, the biases of the inertial measurement units (IMU), and the error measurements. Its strong dependence on the a priori error characteristics of inertial sensors may suffer with the low-cost IMUs, e.g. the MEMS IMUs due to their low and unstable performance. This paper strives for a significant breakthrough in a compact and general integration strategy which restructures the Kalman filter by deploying a system model on the basis of 3D kinematics of a rigid body and performing measurement update via all sensor data inclusive of the IMU measurements. This novel IMU/GNSS Kalman filter directly estimates navigational parameters instead of the error states. It enables the direct use of the IMU's raw outputs as measurements in measurement updates of Kalman filter instead of involving the free inertial navigation calculation through the conventional integration mechanism. This realization makes all of the sensors in a system no longer to be differentiated between core and aiding sensors. The proposed integration strategy can greatly enhance the sustainability of low-cost navigation systems in poor GNSS and/or GNSS denied environment compared to the conventional aided error-state-based inertial navigation integration mechanism. The post-processed solutions are presented to show the success of the proposed multisensor integrated navigation strategy.
5
Guo, Lei, Fuhong Wang, Jizhang Sang, Xiaohu Lin, Xuewen Gong, and Wanwei Zhang. "Characteristics Analysis of Raw Multi-GNSS Measurement from Xiaomi Mi 8 and Positioning Performance Improvement with L5/E5 Frequency in an Urban Environment." Remote Sensing 12, no. 4 (February 24, 2020): 744. http://dx.doi.org/10.3390/rs12040744.
Повний текст джерелаАнотація:
Achieving continuous and high-precision positioning services via smartphone under a Global Navigation Satellite System (GNSS)-degraded environment is urgently demanded by the mass market. In 2018, Xiaomi launched the world’s first dual-frequency GNSS smartphone, Xiaomi Mi 8. The newly added L5/E5 signals are more precise and less prone to distortions from multipath reflections. This paper discusses the characteristics of raw dual-frequency GNSS observations from Xiaomi Mi 8 in urban environments; they are characterized by high pseudorange noise and frequent signal interruption. The traditional dual-frequency ionosphere-free combination is not suitable for Xiaomi Mi 8 raw GNSS data processing, since the noise of the combined measurements is much larger than the influence of the ionospheric delay. Therefore, in order to reasonably utilize the high precision carrier phase observations, a time differenced positioning filter is presented in this paper to deliver continuous and smooth navigation results in urban environments. The filter first estimates the inter-epoch position variation (IEPV) with time differenced uncombined L1/E1 and L5/E5 carrier phase observations and constructs the state equation with IEPV to accurately describe the user’s movement. Secondly, the observation equations are formed with uncombined L1/E1 and L5/E5 pseudorange observations. Then, kinematic experiments in open-sky and GNSS-degraded environments are carried out, and the proposed filter is assessed in terms of the positioning accuracy and solution availability. The result in an open-sky environment shows that, assisted with L5/E5 observations, the root mean square (RMS) of the stand-alone horizontal and vertical positioning errors are about 1.22 m and 1.94 m, respectively, with a 97.8% navigation availability. Encouragingly, even in a GNSS-degraded environment, smooth navigation services with accuracies of 1.61 m and 2.16 m in the horizontal and vertical directions are obtained by using multi-GNSS and L5/E5 observations.
6
Ma, Fangwu, Jinzhu Shi, Liang Wu, Kai Dai, and Shouren Zhong. "Consistent Monocular Ackermann Visual–Inertial Odometry for Intelligent and Connected Vehicle Localization." Sensors 20, no. 20 (October 10, 2020): 5757. http://dx.doi.org/10.3390/s20205757.
Повний текст джерелаАнотація:
The observability of the scale direction in visual–inertial odometry (VIO) under degenerate motions of intelligent and connected vehicles can be improved by fusing Ackermann error state measurements. However, the relative kinematic error measurement model assumes that the vehicle velocity is constant between two consecutive camera states, which degrades the positioning accuracy. To address this problem, a consistent monocular Ackermann VIO, termed MAVIO, is proposed to combine the vehicle velocity and yaw angular rate error measurements, taking into account the lever arm effect between the vehicle and inertial measurement unit (IMU) coordinates with a tightly coupled filter-based mechanism. The lever arm effect is firstly introduced to improve the reliability for information exchange between the vehicle and IMU coordinates. Then, the process model and monocular visual measurement model are presented. Subsequently, the vehicle velocity and yaw angular rate error measurements are directly used to refine the estimator after visual observation. To obtain a global position for the vehicle, the raw Global Navigation Satellite System (GNSS) error measurement model, termed MAVIO-GNSS, is introduced to further improve the performance of MAVIO. The observability, consistency and positioning accuracy were comprehensively compared using real-world datasets. The experimental results demonstrated that MAVIO not only improved the observability of the VIO scale direction under the degenerate motions of ground vehicles, but also resolved the inconsistency problem of the relative kinematic error measurement model of the vehicle to further improve the positioning accuracy. Moreover, MAVIO-GNSS further improved the vehicle positioning accuracy under a long-distance driving state. The source code is publicly available for the benefit of the robotics community.
7
Chang, Guobin, Chao Chen, Yuanxi Yang, and Tianhe Xu. "Tikhonov Regularization Based Modeling and Sidereal Filtering Mitigation of GNSS Multipath Errors." Remote Sensing 10, no. 11 (November 14, 2018): 1801. http://dx.doi.org/10.3390/rs10111801.
Повний текст джерелаАнотація:
In Global Navigation Satellite System (GNSS) relative positioning applications, multipath errors are non-negligible. Mitigation of the multipath error is an important task for precise positioning and it is possible due to the repeatability, even without any rigorous mathematical model. Empirical modeling is required for this mitigation. In this work, the multipath error modeling using carrier phase measurement residuals is realized by solving a regularization problem. Two Tikhonov regularization schemes, namely with the first and the second order differences, are considered. For each scheme, efficient numerical algorithms are developed to find the solutions, namely the Thomas algorithm and Cholesky rank-one update algorithm for the first and the second differences, respectively. Regularization parameters or Lagrange multipliers are optimized using the bootstrap method. In experiment, data on the first day are processed to construct a multipath model for each satellite (except the reference one), and then the model is used to correct the measurement on the second day, namely following the sidereal filtering approach. The smoothness of the coordinates calculated using the corrected measurements is improved significantly compared to those using the raw measurement. The efficacy of the proposed method is illustrated by the actual calculation.
8
Yun, Jeonghyeon, Cheolsoon Lim, and Byungwoon Park. "Inherent Limitations of Smartphone GNSS Positioning and Effective Methods to Increase the Accuracy Utilizing Dual-Frequency Measurements." Sensors 22, no. 24 (December 15, 2022): 9879. http://dx.doi.org/10.3390/s22249879.
Повний текст джерелаАнотація:
Xiaomi Mi8 with a Broadcom BCM47755 chip, an Android smartphone that supports multi-constellation (GPS, GLONASS, Galileo, BeiDou, and QZSS) and dual-frequency (L1/E1 and L5/E5), was launched in May 2018. Unlike previously released smartphones, it was technically expected to provide robust precise positioning with a fast ambiguity resolution, which led many researchers to be overly optimistic about the applicability of high-accuracy techniques such as real-time kinematic (RTK) systems and precise point positioning (PPP) of smartphones. The global navigation satellite system (GNSS) raw measurement quality of Android smartphones is, however, inherently far lower than that of general GNSS receivers due to their structure, which accordingly makes it difficult for them to be realized. Considering inherent limitations of smartphones such as low-quality antenna, frequent cycle slips, and the duty cycle, a practical strategy including L5 measurements, pseudo-range corrections for L5, and a weighting method is proposed in this paper. The results show that the proposed methods of L5 differential GNSS (DGNSS) and Doppler-based filtering can guarantee a positioning accuracy of 1.75 m horizontally and 4.56 m vertically in an Android device, which is comparable to the performance of commercial low-cost receivers.
9
Xu, Hongfu, Haiyong Luo, Zijian Wu, Fan Wu, Linfeng Bao, and Fang Zhao. "Towards Predicting the Measurement Noise Covariance with a Transformer and Residual Denoising Autoencoder for GNSS/INS Tightly-Coupled Integrated Navigation." Remote Sensing 14, no. 7 (March 31, 2022): 1691. http://dx.doi.org/10.3390/rs14071691.
Повний текст джерелаАнотація:
The tightly coupled navigation system is commonly used in UAV products and land vehicles. It adopts the Kalman filter to combine raw satellite observations, including the pseudorange, pseudorange rate and Doppler frequency, with the inertial measurements to achieve high navigational accuracy in GNSS-challenged environments. The accurate estimation of measurement noise covariance can ensure the quick convergence of the Kalman filter and the accuracy of the navigation results. Existing tightly coupled integrated navigation systems employ either constant noise covariance or simple noise covariance updating methods, which cannot accurately reflect the dynamic measurement noises. In this article, we propose an adaptive measurement noise estimation algorithm using a transformer and residual denoising autoencoder (RDAE), which can dynamically estimate the covariance of measurement noise. The residual module is used to solve the gradient degradation problem. The DAE is adopted to learn the essential characteristics from the noisy ephemeris data. By introducing the attention mechanism, the transformer can effectively learn the time and space dependency of long-term ephemeris data, and thus dynamically adjusts the noise covariance with the predicted factors. Extensive experimental results demonstrate that our method can achieve sub-meter positioning accuracy in the outdoor open environment. In a GNSS-degraded environment, our proposed method can still obtain about 3 m positioning accuracy. Another test on a new dataset also confirms that our proposed method has reasonable robustness and adaptability.
10
Jing, Ce, Guanwen Huang, Qin Zhang, Xin Li, Zhengwei Bai, and Yuan Du. "GNSS/Accelerometer Adaptive Coupled Landslide Deformation Monitoring Technology." Remote Sensing 14, no. 15 (July 23, 2022): 3537. http://dx.doi.org/10.3390/rs14153537.
Повний текст джерелаАнотація:
Global Navigation Satellite System (GNSS) positioning technology has become the most effective method for real-time three-dimensional landslide monitoring. However, the GNSS observation signal is easily affected by the presence of a complex landslide environment with high occlusion and strong interference, in which case its accuracy and reliability cannot meet the requirements of landslide deformation monitoring. Although the accelerometers have strong autonomous working capacities and can complement the GNSS landslide monitoring technology, regular GNSS/accelerometer coupled deformation monitoring technology relies on high-quality GNSS measurement information in order to obtain high-precision accelerometer-reckoned results, derived by accurately estimating the baseline shift error (BSE). When the GNSS signal suffers severe interference, the GNSS monitoring error will be partially absorbed by the BSE component after Kalman filtering, resulting in the divergence of the deformation solution. In this study, an abnormal observation variance inflation model was used to process the simulated landslide monitoring data (GNSS and accelerometer raw observation) for three typical scenes—GNSS signal normally locked, signal partially lost, and short-term interruption. The results were as follows: (1) When the GNSS signal was normally locked, the accuracy was comparable to that of the coupled solution employing an accelerometer (the Root Mean Square (RMS) values in the East (E), North (N) and Upward (U) directions were 0.11 cm, 0.33 cm, and 0.30 cm, respectively). (2) When the GNSS signal was partially lost, the accelerometer could effectively suppress the low-precision float solution of the GNSS, but here, the accuracy of the coupled solution would also decrease with the duration of the floats (the RMS values were E—1.21 cm, N—0.31 cm, and U: 0.58—cm, respectively, when the floats lasted for 10 s, and increased to E—3.09 cm, N—0.39 cm, and U—1.14 cm when they lasted for 20 s, wherein E was the main simulated sliding direction). (3) When the GNSS signal was interrupted for a short time, the accuracy of the coupled solution gradually decreased during continuous interruption, and decreased more quickly during the sliding period of the landslide (when the interruption persisted for 10 s, the RMS values in the simulated landslide stability period were E—0.61 cm, N—0.24 cm, and U—0.25 cm, respectively, while in the simulated landslide sliding period they reached E—4.10 cm, N—6.84 cm, and U—2.30 cm). However, raw observations of the accelerometer could still effectively be used to assist in identifying the real state of the landslide, thereby providing auxiliary information pertinent to early landslide disaster warning.
11
Shi, Bo, Mengke Wang, Yunpeng Wang, Yuntian Bai, Kang Lin, and Fanlin Yang. "Effect Analysis of GNSS/INS Processing Strategy for Sufficient Utilization of Urban Environment Observations." Sensors 21, no. 2 (January 17, 2021): 620. http://dx.doi.org/10.3390/s21020620.
Повний текст джерелаАнотація:
The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch–Tung–Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment.
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Lou, Yidong, Fu Zheng, Shengfeng Gu, Charles Wang, Hailin Guo, and Yanming Feng. "Multi-GNSS precise point positioning with raw single-frequency and dual-frequency measurement models." GPS Solutions 20, no. 4 (October 29, 2015): 849–62. http://dx.doi.org/10.1007/s10291-015-0495-8.
Повний текст джерела
13
Vovasov, V. Y., and D. A. Sukharev. "Investigation of method of elimination of interference situation effect on GPS navigation receiver operation by smoothing of pseudorange measurements by pseudophase increment." Issues of radio electronics, no. 3 (April 26, 2020): 46–53. http://dx.doi.org/10.21778/2218-5453-2020-3-46-53.
Повний текст джерелаАнотація:
The wide application of high-precision GNSS (global navigation satellite system) positioning technologies for unmanned mobile object management requires the acquisition of solutions with subdecimeter accuracy and the reduction of the convergence period to such accuracy from the beginning of measurements to 20–25 minutes. Unfortunately, the accuracy of the obtained navigation solutions and the time of convergence to high-precision solutions are influenced by re-reflection of GNSS signals from the ground, buildings and structures, as well as interference from different sources of radio emissions of the urban environment. Therefore, it is an urgent task to implement methods of eliminating the influence of the interference situation on the operation of the navigation receiver of GNSS signals and investigating their effectiveness. The paper considers the results of investigation of the method of elimination of interference situation effect on GPS signal navigation receiver operation using smoothing of raw pseudorange measurements by pseudophase increment. Justification of the difference of measurement of pseudo-range by carrier phase and pseudo-range by code is given as a criterion of efficiency of estimation of interference situation influence in the area of navigation signals reception. As a result of the analysis of experimental studies, it has been shown that using the described method, starting from 900 seconds, the values of the smoothed parameter do not deviate from the averaged measurements over a long time interval by more than 0.1 meters, which indicates the efficiency of the method of smoothing by phase increments and is potentially promising for highly accurate measurements.
14
Vanek, Bálint, Márton Farkas, and Szabolcs Rózsa. "Position and Attitude Determination in Urban Canyon with Tightly Coupled Sensor Fusion and a Prediction-Based GNSS Cycle Slip Detection Using Low-Cost Instruments." Sensors 23, no. 4 (February 14, 2023): 2141. http://dx.doi.org/10.3390/s23042141.
Повний текст джерелаАнотація:
We present a position and attitude estimation algorithm of moving platforms based on the tightly coupled sensor fusion of low-cost multi baseline GNSS, inertial, magnetic and barometric observations obtained by low-cost sensors and affordable dual-frequency GNSS receivers. The sensor fusion algorithm is realized by an Extended Kalman Filter and estimates the states including GNSS receiver inter-channel biases, integer ambiguities and non-GNSS receiver biases. Tightly coupled sensor fusion increases the reliability of the position and attitude solution in challenging environments such as urban canyons by utilizing the inertial observations in case of GNSS outage. Moreover, GNSS observations can be efficiently used to mitigate IMU sensor drifts. Standard GNSS cycle slips detection methods, such as the application of triple differences or linear combinations such as Melbourne–Wübbena combination and the phase ionospheric residual extended TurboEdit method. However, these techniques are not well suited for the localization in quickly changing environments such as urban canyons. We present a new method of tightly coupled sensor fusion supported by a prediction based cycle slip detection technique, applied to a GNSS setup using three antennas leading to multiple moving baselines on the platform. Thus, not only the GNSS signal properties but also the dynamics of the moving platform are considered in the cycle slip detection. The developed algorithm is tested in an open-sky validation measurement and two sets of measurement in an urban canyon area. The sensor fusion algorithm processes the data sets using the proposed prediction-based cycle slip method, the loss-of-lock indicator-based, and for comparison, the Melbourne–Wübbena and the TurboEdit cycle slip detection methods are also included. The obtained position and attitude estimation results are compared to the internal solution of raw data source GNSS receivers and to the observations of a high-accuracy GNSS/INS unit including a fiber optic gyro. The validation test confirms the proper cycle slip detection in an ideal environment. The more challenging urban canyon test results show the reliability and the accuracy of the proposed method. In the case of the second urban canyon test, the proposed method improved the integer ambiguity resolution success rate by 19% and these results show the lowest horizontal and vertical coordinate distortion in comparison of the linear combination and the loss-of-lock-based cycle slip methods.
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Li, Fangchao, Jingxiang Gao, Panos Psimoulis, Xiaolin Meng, and Fuyang Ke. "A Novel Dynamical Filter Based on Multi-Epochs Least-Squares to Integrate the Carrier Phase and Pseudorange Observation for GNSS Measurement." Remote Sensing 12, no. 11 (May 29, 2020): 1762. http://dx.doi.org/10.3390/rs12111762.
Повний текст джерелаАнотація:
The high noise of pseudorange and the ambiguity of carrier phase observation restrain the GNSS (Global Navigation Satellite System) application in military, industrial, and agricultural, to name a few. Thus, it is crucial for GNSS technology to integrate the pseudorange and carrier phase observations. However, the traditional method proposed by Hatch has obtained only a low convergence speed and precision. For higher convergence speed and precision of the smoothed pseudorange, aiming to improve positioning accuracy and expand the application of GNSS, we introduced a new method named MELS (Multi-Epochs Least-Squares) that considered the cross-correlation of the estimating parameters inspired by DELS (Double-Epochs Least-Square). In this study, the ionospheric delay was compensated, and so its impact was limited to the performance of the filters, and then exploited the various filters to integrate carrier phase observation and pseudorange. We compared the various types of Hatch’s filter and LS (Least-Square) methods using simulation datasets, which confirmed that the types of LS method provided a smaller residual error and a faster convergence speed than Hatch’s method under various precisions of raw pseudorange. The experimental results from the measured GNSS data showed that LS methods provided better performance than Hatch’s methods at E and U directions and a lower accuracy at N direction. Nevertheless, the types of LS method and Hatch’s methods improved about 12% and 9–10% at the 3D direction, respectively, which illustrated the accumulating improvement at the enhanced directions was more than the decreased direction, proving that the types of LS method resulted to better performance than the Hatch’s filters. Additionally, the curve of residual and precision based on various LS methods illustrated that the MELS only provided a millimeter accuracy difference compared with DELS, which was proved by the simulated and measured GNSS datasets.
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Fukuda, Gen, Daisuke Hatta, Xiaoliang Guo, and Nobuaki Kubo. "Performance Evaluation of IMU and DVL Integration in Marine Navigation." Sensors 21, no. 4 (February 4, 2021): 1056. http://dx.doi.org/10.3390/s21041056.
Повний текст джерелаАнотація:
Global navigation satellite system (GNSS) spoofing poses a significant threat to maritime logistics. Many maritime electronic devices rely on GNSS time, positioning, and speed for safe vessel operation. In this study, inertial measurement unit (IMU) and Doppler velocity log (DVL) devices, which are important in the event of GNSS spoofing or outage, are considered in conventional navigation. A velocity integration method using IMU and DVL in terms of dead-reckoning is investigated in this study. GNSS has been widely used for ship navigation, but IMU, DVL, or combined IMU and DVL navigation have received little attention. Military-grade sensors are very expensive and generally cannot be utilized in smaller vessels. Therefore, this study focuses on the use of consumer-grade sensors. First, the performance of a micro electromechanical system (MEMS)-based yaw rate angle with DVL was evaluated using 60 min of raw data for a 50 m-long ship located in Tokyo Bay. Second, the performance of an IMU-MEMS using three gyroscopes and three accelerometers with DVL was evaluated using the same dataset. A gyrocompass, which is equipped on the ship, is used as a heading reference. The results proved that both methods could achieve less than 1 km horizontal error in 60 min.
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Lachapelle, Gérard, Paul Gratton, Jamie Horrelt, Erica Lemieux, and Ali Broumandan. "Evaluation of a Low Cost Hand Held Unit with GNSS Raw Data Capability and Comparison with an Android Smartphone." Sensors 18, no. 12 (November 29, 2018): 4185. http://dx.doi.org/10.3390/s18124185.
Повний текст джерелаАнотація:
A newly available portable unit with GNSS raw data recording capability is assessed to determine static and kinematic position accuracy in various environments. This unit is the GPSMap 66, introduced by Garmin in early September. It is all-weather and robust for field use, and comes with a helix antenna. The high sensitivity chipset is capable of acquiring and tracking signals in highly attenuated environments. It can track single frequency GPS, GPS + GLONASS or GPS + Galileo and record code, Doppler and carrier phase data every second in the RINEX format. The evaluation presented herein focusses on GPS and Galileo. Static and kinematic test results obtained under a wide range of realistic field conditions are reported. Differential GNSS methods and Precise Point Positioning (PPP) are used to assess absolute position accuracy in ITRF coordinates, which is sufficiently close to the GPS and Galileo reference frame for the current purpose. Under low multipath conditions, measurements are found to be sufficiently accurate to provide single epoch, bias free position accuracy of a few metres. Accuracy is a function of signal attenuation and multipath conditions. The use of an external geodetic antenna significantly reduces measurement noise and multipath in high multipath environments. Carrier phase measurements, available more or less continuously under open sky conditions, significantly improve performance in differential mode. Accuracy in vehicular mode using code and carrier phase differential RTK solution is at the level of a few to several dm. Tests were conducted in parallel with a Huawei P10 Android 8.0 smartphone. The code measurement noise of this unit was found to be significantly higher than that of the GPSMap 66, a major reason being its lower performance PIFA antenna; carrier phase was only available for short time intervals, significantly degrading differential position accuracy performance.
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Geng, Jianghui, Enming Jiang, Guangcai Li, Shaoming Xin, and Na Wei. "An Improved Hatch Filter Algorithm towards Sub-Meter Positioning Using only Android Raw GNSS Measurements without External Augmentation Corrections." Remote Sensing 11, no. 14 (July 15, 2019): 1679. http://dx.doi.org/10.3390/rs11141679.
Повний текст джерелаАнотація:
In May 2016, the availability of GNSS raw measurements on smart devices was announced by Google with the release of Android 7. It means that developers can access carrier-phase and pseudorange measurements and decode navigation messages for the first time from mass-market Android-devices. In this paper, an improved Hatch filter algorithm, i.e., Three-Thresholds and Single-Difference Hatch filter (TT-SD Hatch filter), is proposed for sub-meter single point positioning with raw GNSS measurements on Android devices without any augmentation correction input, where the carrier-phase smoothed pseudorange window width adaptively varies according to the three-threshold detection for ionospheric cumulative errors, cycle slips and outliers. In the mean time, it can also eliminate the inconsistency of receiver clock bias between pseudorange and carrier-phase by inter-satellite difference. To eliminate the effects of frequent smoothing window resets, we combine TT-SD Hatch filter and Kalman filter for both time update and measurement update. The feasibility of the improved TT-SD Hatch filter method is then verified using static and kinematic experiments with a Nexus 9 Android tablet. The result of the static experiment demonstrates that the position RMS of TT-SD Hatch filter is about 0.6 and 0.8 m in the horizontal and vertical components, respectively. It is about 2 and 1.6 m less than the GNSS chipset solutions, and about 10 and 10 m less than the classical Hatch filter solution, respectively. Moreover, the TT-SD Hatch filter can accurately detect the cycle slips and outliers, and reset the smoothed window in time. It thus avoids the smoothing failure of Hatch filter when a large cycle-slip or an outlier occurs in the observations. Meanwhile, with the aid of the Kalman filter, TT-SD Hatch filter can keep continuously positioning at the sub-meter level. The result of the kinematic experiment demonstrates that the TT-SD Hatch filter solution can converge after a few minutes, and the 2D error is about 0.9 m, which is about 64%, 89%, and 92% smaller than that of the chipset solution, the traditional Hatch filter solution and standard single point solution, respectively. Finally, the TT-SD Hatch filter solution can recover a continuous driving track in this kinematic test.
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Kriegel, Martin, Norbert Jakowski, Jens Berdermann, Hiroatsu Sato, and Mogese Wassaie Mersha. "Scintillation measurements at Bahir Dar during the high solar activity phase of solar cycle 24." Annales Geophysicae 35, no. 1 (January 13, 2017): 97–106. http://dx.doi.org/10.5194/angeo-35-97-2017.
Повний текст джерелаАнотація:
Abstract. Small-scale ionospheric disturbances may cause severe radio scintillations of signals transmitted from global navigation satellite systems (GNSSs). Consequently, small-scale plasma irregularities may heavily degrade the performance of current GNSSs such as GPS, GLONASS or Galileo. This paper presents analysis results obtained primarily from two high-rate GNSS receiver stations designed and operated by the German Aerospace Center (DLR) in cooperation with Bahir Dar University (BDU) at 11.6° N, 37.4° E. Both receivers collect raw data sampled at up to 50 Hz, from which characteristic scintillation parameters such as the S4 index are deduced. This paper gives a first overview of the measurement set-up and the observed scintillation events over Bahir Dar in 2015. Both stations are located close to one another and aligned in an east–west, direction which allows us to estimate the zonal drift velocity and spatial dimension of equatorial ionospheric plasma irregularities. Therefore, the lag times of moving electron density irregularities and scintillation patterns are derived by applying cross-correlation analysis to high-rate measurements of the slant total electron content (sTEC) along radio links between a GPS satellite and both receivers and to the associated signal power, respectively. Finally, the drift velocity is derived from the estimated lag time, taking into account the geometric constellation of both receiving antennas and the observed GPS satellites.
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Krzyżek, Robert. "MATHEMATICAL ANALYSIS OF THE ALGORITHMS USED IN MODERNIZED METHODS OF BUILDING MEASUREMENTS WITH RTN GNSS TECHNOLOGY." Boletim de Ciências Geodésicas 21, no. 4 (December 2015): 848–66. http://dx.doi.org/10.1590/s1982-21702015000400050.
Повний текст джерелаАнотація:
The use of RTN GNSS surveying technology (Real Time Kinematic Global Navigation Satellite System) for direct measurements of building structures is extremely difficult, and often impossible. Therefore, the real-time technology is supported by indirect methods of measurements. One such solution is the method of line-line intersection. Having determined the position (the coordinates) of the so-called base points on the extension of the wall faces of a building, and having calculated the coordinates of intersection of the lines of relationships between the base points, the coordinates of corners of a building structure are obtained, which are relatively unreliable. In order to increase the reliability of these coordinates, the author proposes to add an innovative solution called vector translation to the classical method of line-line intersection. This paper proves the thesis on the increased reliability of determining the coordinates of corners of buildings by conducting an appropriate mathematical analysis of these formulas, using the algorithm developed by the author. The performed analysis shows that this innovative solution results in a smaller difference between the adjusted coordinates relative to the theoretical ones, than the difference captured from the "raw" measurement results with respect to the theoretical values.
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Borejko, Tomasz, Krzysztof Marcinek, Krzysztof Siwiec, Paweł Narczyk, Adam Borkowski, Igor Butryn, Arkadiusz Łuczyk, et al. "NaviSoC: High-Accuracy Low-Power GNSS SoC with an Integrated Application Processor." Sensors 20, no. 4 (February 16, 2020): 1069. http://dx.doi.org/10.3390/s20041069.
Повний текст джерелаАнотація:
A dual-frequency all-in-one Global Navigation Satellite System (GNSS) receiver with a multi-core 32-bit RISC (reduced instruction set computing) application processor was integrated and manufactured as a System-on-Chip (SoC) in a 110 nm CMOS (complementary metal-oxide semiconductor) process. The GNSS RF (radio frequency) front-end with baseband navigation engine is able to receive, simultaneously, Galileo (European Global Satellite Navigation System) E1/E5ab, GPS (US Global Positioning System) L1/L1C/L5, BeiDou (Chinese Navigation Satellite System) B1/B2, GLONASS (GLObal NAvigation Satellite System of Russian Government) L1/L3/L5, QZSS (Quasi-Zenith Satellite System development by the Japanese government) L1/L5 and IRNSS (Indian Regional Navigation Satellite System) L5, as well as all SBAS (Satellite Based Augmentation System) signals. The ability of the GNSS to detect such a broad range of signals allows for high-accuracy positioning. The whole SoC (system-on-chip), which is connected to a small passive antenna, provides precise position, velocity and time or raw GNSS data for hybridization with the IMU (inertial measurement unit) without the need for an external application processor. Additionally, user application can be executed directly in the SoC. It works in the −40 to +105 °C temperature range with a 1.5 V supply. The assembled test-chip takes 100 pins in a QFN (quad-flat no-leads) package and needs only a quartz crystal for the on-chip reference clock driver and optional SAW (surface acoustic wave) filters. The radio performance for both wideband (52 MHz) channels centered at L1/E1 and L5/E5 is NF = 2.3 dB, G = 131 dB, with 121 dBc/Hz of phase noise @ 1 MHz offset from the carrier, consumes 35 mW and occupies a 4.5 mm2 silicon area. The SoC reported in the paper is the first ever dual-frequency single-chip GNSS receiver equipped with a multi-core application microcontroller integrated with embedded flash memory for the user application program.
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Zhang, Yun, Ziyu Yan, Shuhu Yang, Wanting Meng, Siqi Gu, Jin Qin, Yanling Han, and Zhonghua Hong. "Research on Shore-Based River Flow Velocity Inversion Model Using GNSS-R Raw Data." Remote Sensing 14, no. 5 (February 26, 2022): 1170. http://dx.doi.org/10.3390/rs14051170.
Повний текст джерелаАнотація:
Global navigation satellite system reflectometry technology (GNSS-R) is rarely used for river flow velocity inversion, and in particular, there is currently no research using the BeiDou Navigation Satellite System reflectometry technology (BDS-R) for river flow velocity inversion. In this paper, a carrier phase observation of river flow velocity inversion model is proposed. The interference phase is the integral of the Doppler frequency. The raw intermediate frequency (IF) data sets are processed through an open-loop method to obtain the Doppler frequency observation generated by river flow and then realize velocity inversion. The shore-based river current measurement was conducted on the south bank of Dashengguan Yangtze River in Nanjing city, Jiangsu Province, for nearly two hours on 22 April 2021. After realizing the inversion of river flow velocity in GPS L1, the combined inversion of BDS B1I GEO satellite and IGSO satellite is realized for the first time, which demonstrates the feasibility of river flow velocity inversion using BDS reflected signals. Compared with the real river flow velocity, the GPS L1 PRN 4 (1st period) inversion precision reaches up to 0.028 m/s (mean absolute error, MAE) and 0.036 m/s (root mean square error, RMSE). In parallel, BDS GEO 2 inversion precision can reach 0.048 m/s (MAE) and 0.063 m/s (RMSE), and BDS IGSO 10 inversion precision is 0.061 m/s (MAE) and 0.073 m/s (RMSE). These results illustrate that satellite elevation change rate and distance between specular points and current meter may have a negative effect on the accuracy of river flow velocity inversion. Specular points obstructed by obstacles or too far from the velocity meter may introduce uncertain error in both MAE and RMSE. Neither the satellite elevation nor the signal strength has an obvious correlation with inversion precision, which is consistent with the theoretical principle.
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Pepe, Massimiliano, Domenica Costantino, Gabriele Vozza, and Vincenzo Saverio Alfio. "Comparison of Two Approaches to GNSS Positioning Using Code Pseudoranges Generated by Smartphone Device." Applied Sciences 11, no. 11 (May 23, 2021): 4787. http://dx.doi.org/10.3390/app11114787.
Повний текст джерелаАнотація:
The release of Android 7.0 has made raw GNSS positioning data available on smartphones and, as a result, this has allowed many experiments to be developed to evaluate the quality of GNSS positioning using mobile devices. This paper investigates the best positioning, using pseudorange measurement in the Differential Global Navigation Satellite System (DGNSS) and Single Point Positioning (SPP), obtained by smartphones. The experimental results show that SPP can be comparable to the DGNSS solution and can generally achieve an accuracy of one meter in planimetric positioning; in some conditions, an accuracy of less than one meter was achieved in the Easting coordinate. As far as altimetric positioning is concerned, it has been demonstrated that DGNSS is largely preferable to SPP. The aim of the research is to introduce a statistical method to evaluate the accuracy and precision of smartphone positioning that can be applied to any device since it is based only on the pseudoranges of the code. In order to improve the accuracy of positioning from mobile devices, two methods (Tukey and K-means) were used and applied, as they can detect and eliminate outliers in the data. Finally, the paper shows a case study on how the implementation of SPP on GIS applications for smartphones could improve citizen science experiments.
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Li, Zhonghan, Yongbo Zhang, Yutong Shi, Shangwu Yuan, and Shihao Zhu. "Performance Enhancement of INS and UWB Fusion Positioning Method Based on Two-Level Error Model." Sensors 23, no. 2 (January 4, 2023): 557. http://dx.doi.org/10.3390/s23020557.
Повний текст джерелаАнотація:
In GNSS-denied environments, especially when losing measurement sensor data, inertial navigation system (INS) accuracy is critical to the precise positioning of vehicles, and an accurate INS error compensation model is the most effective way to improve INS accuracy. To this end, a two-level error model is proposed, which comprehensively utilizes the mechanism error model and propagation error model. Based on this model, the INS and ultra-wideband (UWB) fusion positioning method is derived relying on the extended Kalman filter (EKF) method. To further improve accuracy, the data prefiltering algorithm of the wavelet shrinkage method based on Stein’s unbiased risk estimate–Shrink (SURE-Shrink) threshold is summarized for raw inertial measurement unit (IMU) data. The experimental results show that by employing the SURE-Shrink wavelet denoising method, positioning accuracy is improved by 76.6%; by applying the two-level error model, the accuracy is further improved by 84.3%. More importantly, at the point when the vehicle motion state changes, adopting the two-level error model can provide higher computational stability and less fluctuation in trajectory curves.
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Golovan, A. A. "INS/Odometer Integration: Positional Approach." Giroskopiya i Navigatsiya 29, no. 2 (2021): 110–25. http://dx.doi.org/10.17285/0869-7035.0066.
Повний текст джерелаАнотація:
The problem of a strapdown inertial navigation system (SINS) integration with an odometer as part of an integrated navigation system is considered. The odometer raw measurement is considered as an increment of the distance traveled along the odometer ‘measuring’ axis. Models of the integration solution components for the case of threedimensional navigation are presented, among which are the models of inertial autonomous and kinematic odometer dead reckoning (DR), models of relevant error equations, the model of SINS position aiding based on the odometer DR data and using GNSS position and velocity, wherever possible. The models comprise objective components, which do not depend on the type of the inertial sensors used and their accuracy grade, and variable components, which take into account the properties of the navigation sensors used. The integration does not require zero velocity updates, known as ZUPT correction, which are commonly used in navigation application.
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Yan, Baorong, Yun Li, Wei Guo, and Yu Hua. "High-Accuracy Positioning Based on Pseudo-Ranges: Integrated Difference and Performance Analysis of the Loran System." Sensors 20, no. 16 (August 8, 2020): 4436. http://dx.doi.org/10.3390/s20164436.
Повний текст джерелаАнотація:
The Long Range Navigation (Loran) system as a backup of the Global Navigation Satellite System (GNSS) is a good choice. The dominant deterioration factors of position accuracy are the pseudo-range measurement errors and the geometric dilution of precision (GDOP). This paper focuses on the algorithm integrated difference with pseudo-ranges to improve the position accuracy. Firstly, the theoretical prediction of propagation delay and raw measurement are compared. The results show that the measured pseudo-range consists of a constant term and a temporal term, which reflect the propagation situation along the true path. Secondly, a position solution algorithm based on a pseudo-range and difference is presented, exceeding the limit of a single chain. Finally, some simulation tests are implemented utilizing the new proposed position algorithm to verify the differential performance. This method can reduce the GDOP conveniently through increasing the number of transmitters. In view of the amplitude and characteristics of errors in measurement, systematic error and random noise are distinguished and discussed. The absolute accuracy responds to the pseudo-range bias that is different from geometric distance and repeatable accuracy is mainly influenced by random noise. The difference method can improve the absolute accuracy via the correction degree without changing the geometry of the transmitters.
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Molin, José Paulo, and João Paulo Soto Veiga. "Spatial variability of sugarcane row gaps: measurement and mapping." Ciência e Agrotecnologia 40, no. 3 (June 2016): 347–55. http://dx.doi.org/10.1590/1413-70542016403046915.
Повний текст джерелаАнотація:
ABSTRACT Sugarcane is a very important crop in Brazil, used as food production and biofuel, providing 18% of the total primary energy in the country. An important requirement to high yield is a good uniformity in the sugarcane field, which is impaired due to row gaps that appear since the first year of sugarcane crop caused by planting failures, harvesting damages, machinery traffic, pests, diseases and others. The aim of this study is to develop a system based on a photoelectric sensor to scan the field, georeferencing gaps representing them as a map. A data logger integrates the data from the photoelectric sensors, an encoder and a Global Navigation Satellite System (GNSS) and measures the distance between plants, defining the gaps. Tests under controlled conditions, using regular obstacles simulating stalks, showed errors between 0.02 and 0.03 m under speeds varying from 1.3 to 3.0 m s-1 and obstacles ranging from 0.1 to 1.0 m of gap. Results of tests performed at sugar cane rows were close to manual measurement. Field tests were performed using sampling plots of 6.0 x 6.0 m (four crop rows) along the area, on newly planted and on ratoon areas, showed a good relation with manual measurements. The raw data provides the length of the individual gaps or its local percentage and the interpolation among punctual gaps produces a map highlighting areas with low and high gap intensity as a useful tool in the sugarcane management for decision making for local or integral replanting.
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Chen, Tianyang, Fangling Pu, Hongjia Chen, and Zhihong Liu. "WHUVID: A Large-Scale Stereo-IMU Dataset for Visual-Inertial Odometry and Autonomous Driving in Chinese Urban Scenarios." Remote Sensing 14, no. 9 (April 23, 2022): 2033. http://dx.doi.org/10.3390/rs14092033.
Повний текст джерелаАнотація:
In this paper, we present a challenging stereo-inertial dataset collected onboard a sports utility vehicle (SUV) for the tasks of visual-inertial odometry (VIO), simultaneous localization and mapping (SLAM), autonomous driving, object detection, and other computer vision techniques. We recorded a large set of time-synchronized stereo image sequences (2 × 1280 × 720 @ 30 fps RGB) and corresponding inertial measurement unit (IMU) readings (400 Hz) from a Stereolabs ZED2 camera, along with centimeter-level-accurate six-degree-of-freedom ground truth (100 Hz) from a u-blox GNSS-IMU navigation device with real-time kinematic correction signals. The dataset comprises 34 sequences recorded during November 2020 in Wuhan, the largest city of Central China. Further, the dataset contains abundant unique urban scenes and features of a complex modern metropolis, which have rarely appeared in previously released benchmarks. Results from milestone VIO/SLAM algorithms reveal that methods exhibiting excellent performance on established datasets such as KITTI and EuRoC perform unsatisfactorily when moved outside the laboratory to the real world. We expect our dataset to reduce this limitation by providing more challenging and diverse scenarios to the research community. The full dataset with raw and calibrated data is publicly available along with a lightweight MATLAB/Python toolbox for preprocessing and evaluation. The dataset can be downloaded in its entirety from the uniform resource locator (URL) we provide in the main text.
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Niemeier, Wolfgang, and Dieter Tengen. "Stochastic Properties of Confidence Ellipsoids after Least Squares Adjustment, Derived from GUM Analysis and Monte Carlo Simulations." Mathematics 8, no. 8 (August 8, 2020): 1318. http://dx.doi.org/10.3390/math8081318.
Повний текст джерелаАнотація:
In this paper stochastic properties are discussed for the final results of the application of an innovative approach for uncertainty assessment for network computations, which can be characterized as two-step approach: As the first step, raw measuring data and all possible influencing factors were analyzed, applying uncertainty modeling in accordance with GUM (Guide to the Expression of Uncertainty in Measurement). As the second step, Monte Carlo (MC) simulations were set up for the complete processing chain, i.e., for simulating all input data and performing adjustment computations. The input datasets were generated by pseudo random numbers and pre-set probability distribution functions were considered for all these variables. The main extensions here are related to an analysis of the stochastic properties of the final results, which are point clouds for station coordinates. According to Cramer’s central limit theorem and Hagen’s elementary error theory, there are some justifications for why these coordinate variations follow a normal distribution. The applied statistical tests on the normal distribution confirmed this assumption. This result allows us to derive confidence ellipsoids out of these point clouds and to continue with our quality assessment and more detailed analysis of the results, similar to the procedures well-known in classical network theory. This approach and the check on normal distribution is applied to the local tie network of Metsähovi, Finland, where terrestrial geodetic observations are combined with Global Navigation Satellite System (GNSS) data.
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Angrisano, Antonio, and Salvatore Gaglione. "Smartphone GNSS Performance in an Urban Scenario with RAIM Application." Sensors 22, no. 3 (January 20, 2022): 786. http://dx.doi.org/10.3390/s22030786.
Повний текст джерелаАнотація:
In an urban scenario, GNSS performance is strongly influenced by gross errors in the measurements, usually related to multipath and non-line-of-sight phenomena. The use of RAIM algorithms is a common approach to solve this issue. A significant amount of the existing GNSS receivers is currently mounted on smart devices, above all, smartphones. A typical drawback of these devices is the unavailability of raw measurements, which does not allow fully exploiting the GNSS potential; in particular, this feature limits the use of RAIM algorithms. Since 2016, for few smart devices, it has been finally possible to access GNSS raw measurements, allowing the implementation of specific algorithms and enabling new services. The Xiaomi Mi 8 is equipped with the Broadcom BCM47755 receiver, able to provide dual-frequency raw measurements from quad-constellation GPS, Glonass, Galileo, BeiDou. In this work, the performance in an urban area of the Xiaomi Mi8 GNSS was analyzed. An important issue of smartphone GNSS is related to the antenna, which is not able to protect from the multipath phenomenon; this issue has a large probability to emerge in hostile environments like urban areas. As a term of comparison, the high-sensitivity receiver NVS NV08C-CSM, connected to a patch antenna, was used. In particular, the considered receivers were placed in the same location, and their positions were estimated in single point positioning, applying a classical RAIM algorithm. An error analysis was carried out, and the obtained results demonstrated the effectiveness of RAIM when applied to Xiaomi Mi8 GNSS measurements.
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Li, Weiqiang, Estel Cardellach, Serni Ribó, Santi Oliveras, and Antonio Rius. "Exploration of Multi-Mission Spaceborne GNSS-R Raw IF Data Sets: Processing, Data Products and Potential Applications." Remote Sensing 14, no. 6 (March 10, 2022): 1344. http://dx.doi.org/10.3390/rs14061344.
Повний текст джерелаАнотація:
Earth reflected Global Navigation Satellite System (GNSS) signals can be received by dedicated orbital receivers for remote sensing and Earth observation (EO) purposes. Different spaceborne missions have been launched during the past years, most of which can only provide the delay-Doppler map (DDM) of the power of the reflected GNSS signals as their main data products. In addition to the power DDM products, some of these missions have collected a large amount of raw intermediate frequency (IF) data, which are the bit streams of raw signal samples recorded after the analog-to-digital converters (ADCs) and prior to any onboard digital processing. The unprocessed nature of these raw IF data provides an unique opportunity to explore the potential of GNSS Reflectometry (GNSS-R) technique for advanced geophysical applications and future spaceborne missions. To facilitate such explorations, the raw IF data sets from different missions have been processed by Institute of Space Sciences (ICE-CSIC, IEEC), and the corresponding data products, i.e., the complex waveform of the reflected signal, have been generated and released through our public open-data server. These complex waveform data products provide the measurements from different GNSS constellations (e.g., GPS, Galileo and BeiDou), and include both the amplitude and carrier phase information of the reflected GNSS signal at higher sampling rate (e.g., 1000 Hz). To demonstrate these advanced features of the data products, different applications, e.g., inland water detection and surface altimetry, are introduced in this paper. By making these complex waveform data products publicly available, new EO capability of the GNSS-R technique can be further explored by the community. Such early explorations are also relevant to ESA’s next GNSS-R mission, HydroGNSS, which will provide similar complex observations operationally and continuously in the future.
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Fortunato, Marco, Michela Ravanelli, and Augusto Mazzoni. "Real-Time Geophysical Applications with Android GNSS Raw Measurements." Remote Sensing 11, no. 18 (September 11, 2019): 2113. http://dx.doi.org/10.3390/rs11182113.
Повний текст джерелаАнотація:
The number of Android devices enabling access to raw GNSS (Global Navigation Satellite System) measurements is rapidly increasing, thanks to the dedicated Google APIs. In this study, the Xiaomi Mi8, the first GNSS dual-frequency smartphone embedded with the Broadcom BCM47755 GNSS chipset, was employed by leveraging the features of L5/E5a observations in addition to the traditional L1/E1 observations. The aim of this paper is to present two different smartphone applications in Geoscience, both based on the variometric approach and able to work in real time. In particular, tests using both VADASE (Variometric Approach for Displacement Analysis Stand-alone Engine) to retrieve the 3D velocity of a stand-alone receiver in real-time, and VARION (Variometric Approach for Real-Time Ionosphere Observations) algorithms, able to reconstruct real-time sTEC (slant total electron content) variations, were carried out. The results demonstrate the contribution that mass-market devices can offer to the geosciences. In detail, the noise level obtained with VADASE in a static scenario—few mm/s for the horizontal components and around 1 cm/s for the vertical component—underlines the possibility, confirmed from kinematic tests, of detecting fast movements such as periodic oscillations caused by earthquakes. VARION results indicate that the noise level can be brought back to that of geodetic receivers, making the Xiaomi Mi8 suitable for real-time ionosphere monitoring.
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Gogoi, Neil, Alex Minetto, Nicola Linty, and Fabio Dovis. "A Controlled-Environment Quality Assessment of Android GNSS Raw Measurements." Electronics 8, no. 1 (December 21, 2018): 5. http://dx.doi.org/10.3390/electronics8010005.
Повний текст джерелаАнотація:
Raw Global Navigation Satellite System (GNSS) measurements have been available since 2016 in select Android smartphones. The availability of such observations allows smartphones users, in principle, to significantly improve the quality of GNSS-based positioning by applying customized and advanced positioning algorithms. However, the quality of such measurements is poor, mainly because of the low quality of smartphone hardware components and the nonideal environment in which phones are typically used. To overcome this problem and to separate the contribution of the hardware components and signal quality, dedicated test campaigns were carried out in a real environment and in a controlled-environment anechoic chamber using several different Android models. In addition, signal-processing techniques aimed at increasing the accuracy and precision of the solution were employed. Results show that the quality of the data captured in the anechoic chamber was significantly better than in real conditions. Furthermore, such analysis allows to underline certain phenomena in smartphones, such as the duty cycle, and to test the validity of anechoic environments for Android raw measurements.
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Benvenuto, Lorenzo, Paolo Dabove, Ilaria Ferrando, and Domenico Sguerso. "Preliminary Results on Tropospheric ZTD Estimation by Smartphone." Remote Sensing 13, no. 22 (November 13, 2021): 4567. http://dx.doi.org/10.3390/rs13224567.
Повний текст джерелаАнотація:
The Global Navigation Satellite System (GNSS) receiver is one of the many sensors embedded in smartphones. The early versions of the Android operating system could only access limited information from the GNSS, allowing the related Application Program Interface (API) to obtain only the location. With the development of the Android 7.0 (Nougat) operating system in May 2016, raw measurements from the internal GNSS sensor installed in the smartphone could be accessed. This work aims to show an initial analysis regarding the feasibility of Zenith Total Delay (ZTD) estimation by GNSS measurements extracted from smartphones, evaluating the accuracy of estimation to open a new window on troposphere local monitoring. Two different test sites have been considered, and two different types of software for data processing have been used. ZTDs have been estimated from both a dual-frequency and a multi-constellation receiver embedded in the smartphone, and from a GNSS Continuously Operating Reference Station (CORS). The results have shown interesting performances in terms of ZTD estimation from the smartphone in respect of the estimations obtained with a geodetic receiver.
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Weng, Duojie, Xingli Gan, Wu Chen, Shengyue Ji, and Yangwei Lu. "A New DGNSS Positioning Infrastructure for Android Smartphones." Sensors 20, no. 2 (January 15, 2020): 487. http://dx.doi.org/10.3390/s20020487.
Повний текст джерелаАнотація:
One’s position has become an important piece of information for our everyday lives in a smart city. Currently, a position can be obtained easily using smartphones that is equipped with low-cost Global Navigation Satellite System (GNSS) chipsets with accuracy varying from 5 m to 10 m. Differential GNSS (DGNSS) is an efficient technology that removes the majority of GNSS errors with the aid of reference stations installed at known locations. The sub-meter accuracy can be achieved when applying the DGNSS technology on the advanced receivers. In 2016, Android has opened the accesses of raw GNSS measurements to developers. However, most of the mid and low-end smartphones only provide the data using the National Marine Electronics Association (NMEA) protocol. They do not provide the raw measurements, and thus do not support the DGNSS operation either. We proposed a DGNSS infrastructure that correct the standalone GNSS position of smartphones using the corrections from the reference station. In the infrastructure, the position correction is generated considering the GNSS satellite IDs that contribute to the standalone solution in smartphones, and the position obtained is equivalent to the solution of using the range-domain correction directly. To serve a large number of smartphone users, a Client/Server architecture is developed to cope with a mass of DGNSS positioning requests efficiently. The comparison of the proposed infrastructure against the ground truth, for all field tests in open areas, showed that the infrastructure achieves the horizontal positioning accuracy better than 2 m. The improvement in accuracy can reach more than 50% for the test in the afternoon. The infrastructure brings benefits to applications that require more accuracy without requiring any hardware modifications.
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Gandolfi, Stefano, Paolo Macini, Luca Poluzzi, and Luca Tavasci. "GNSS measurements for ground deformations detection around offshore natural gas fields in the Northern Adriatic Region." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 89–93. http://dx.doi.org/10.5194/piahs-382-89-2020.
Повний текст джерелаАнотація:
Abstract. The study aims to evaluate ground deformations in a vast area characterized by the coexistence of intense anthropic activities and offshore natural gas production. Onshore subsidence can be studied by GNSS, InSAR, high precision leveling and extensometers that provide broad datasets for a fully integrated description of the phenomenon. At present, seafloor subsidence monitoring cannot be carried out by high precision leveling, and GNSS is the only reliable method, implemented by means of permanent stations installed on offshore hydrocarbon production facilities. In the Northern/Central Adriatic Sea gas production platforms, GNSS data are recorded since more than 15 years, allowing to estimate not only the average subsidence of the platform/seafloor, but also possible velocity variations due to underground fluids withdrawal. This study shows the comparison of 22 offshore GNSS permanent stations located in the study area. Raw data have been processed with two different software packages (GIPSY-OASIS and GAMIT-GLOBK) based on different approaches and considering different boundary conditions of geodetic and/or modeling nature. Main results point out the high accuracy of the GNSS technology considering also the impact of data processing. Finally, at selected permanent stations we also performed a comparison of results obtained by GNSS, InSAR and high precision leveling.
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Szombara, Stanisław, Marta Róg, Krystian Kozioł, Kamil Maciuk, Bogdan Skorupa, Jacek Kudrys, Tomáš Lepeška, and Michal Apollo. "The Highest Peaks of the Mountains: Comparing the Use of GNSS, LiDAR Point Clouds, DTMs, Databases, Maps, and Historical Sources." Energies 14, no. 18 (September 11, 2021): 5731. http://dx.doi.org/10.3390/en14185731.
Повний текст джерелаАнотація:
Advances in remote data acquisition techniques have contributed to the flooding of society with spatial data sets and information. Widely available spatial data sets, including digital terrain models (DTMs) from aerial laser scanning (ALS) data, are finding more and more new applications. The article analyses and compares the heights of the 14 highest peaks of the Polish Carpathians derived from different data sources. Global navigation satellite system (GNSS) geodetic measurements were used as reference. The comparison primarily involves ALS data, and selected peaks’ GNSS measurements carried out with Xiaomi Mi 8 smartphones were also compared. Recorded raw smartphone GNSS measurements were used for calculations in post-processing mode. Other data sources were, among others, global and local databases and models and topographic maps (modern and old). The article presents an in-depth comparison of Polish and Slovak point clouds for two peaks. The results indicate the possible use of large-area laser scanning in determining the maximum heights of mountain peaks and the need to use geodetic GNSS measurements for selected peaks. For the Polish peak of Rysy, the incorrect classification of point clouds causes its height to be overestimated. The conclusions presented in the article can be used in the dissemination of knowledge and to improve positioning methods.
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Heirich, Oliver. "Bayesian Train Localization with Particle Filter, Loosely Coupled GNSS, IMU, and a Track Map." Journal of Sensors 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/2672640.
Повний текст джерелаАнотація:
Train localization is safety-critical and therefore the approach requires a continuous availability and a track-selective accuracy. A probabilistic approach is followed up in order to cope with multiple sensors, measurement errors, imprecise information, and hidden variables as the topological position within the track network. The nonlinear estimation of the train localization posterior is addressed with a novel Rao-Blackwellized particle filter (RBPF) approach. There, embedded Kalman filters estimate certain linear state variables while the particle distribution can cope with the nonlinear cases of parallel tracks and switch scenarios. The train localization algorithm is further based on a track map and measurements from a Global Navigation Satellite System (GNSS) receiver and an inertial measurement unit (IMU). The GNSS integration is loosely coupled and the IMU integration is achieved without the common strapdown approach and suitable for low-cost IMUs. The implementation is evaluated with real measurements from a regional train at regular passenger service over 230 km of tracks with 107 split switches and parallel track scenarios of 58.5 km. The approach is analyzed with labeled data by means of ground truth of the traveled switch way. Track selectivity results reach 99.3% over parallel track scenarios and 97.2% of correctly resolved switch ways.
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Xiong, Kai, Peng Zhou, and Chunling Wei. "Autonomous Navigation of Unmanned Aircraft Using Space Target LOS Measurements and QLEKF." Sensors 22, no. 18 (September 15, 2022): 6992. http://dx.doi.org/10.3390/s22186992.
Повний текст джерелаАнотація:
An autonomous navigation method based on the fusion of INS (inertial navigation system) measurements with the line-of-sight (LOS) observations of space targets is presented for unmanned aircrafts. INS/GNSS (global navigation satellite system) integration is the conventional approach to achieving the long-term and high-precision navigation of unmanned aircrafts. However, the performance of INS/GNSS integrated navigation may be degraded gradually in a GNSS-denied environment. INS/CNS (celestial navigation system) integrated navigation has been developed as a supplement to the GNSS. A limitation of traditional INS/CNS integrated navigation is that the CNS is not efficient in suppressing the position error of the INS. To solve the abovementioned problems, we studied a novel integrated navigation method, where the position, velocity and attitude errors of the INS were corrected using a star camera mounted on the aircraft in order to observe the space targets whose absolute positions were available. Additionally, a QLEKF (Q-learning extended Kalman filter) is designed for the performance enhancement of the integrated navigation system. The effectiveness of the presented autonomous navigation method based on the star camera and the IMU (inertial measurement unit) is demonstrated via CRLB (Cramer–Rao lower bounds) analysis and numerical simulations.
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Nan, Yang, Shirong Ye, Jingnan Liu, Bofeng Guo, Shuangcheng Zhang, and Weiqiang Li. "Signal-to-Noise Ratio Analyses of Spaceborne GNSS-Reflectometry from Galileo and BeiDou Satellites." Remote Sensing 14, no. 1 (December 22, 2021): 35. http://dx.doi.org/10.3390/rs14010035.
Повний текст джерелаАнотація:
In recent years, Global Navigation Satellite System Reflectometry (GNSS-R) technology has made considerable progress with the increasing of GNSS-R satellites in orbit, the improvements of GNSS-R data processing technology, and the expansion of its geophysical applications. Meanwhile, with the modernization and evolution of GNSS systems, more signal sources and signal modulation modes are available. The effective use of the signals at different frequencies or from new GNSS systems can improve the accuracy, reliability, and resolution of the GNSS-R data products. This paper analyses the signal-to-noise ratio (SNR) of the GNSS-R measurements from Galileo and BeiDou-3 (BDS-3) systems, which is one of the important indicators to measure the quality of GNSS-R data. The multi-GNSS (GPS, Galileo and BDS-3) complex waveform products generated from the raw intermediate frequency data from TechDemoSat-1 (TDS-1) satellite and Cyclone Global Navigation Satellite System (CYGNSS) constellation are used for such analyses. The SNR and normalized SNR (NSNR) of the reflected signals from Galileo and BDS-3 satellites are compared to these from GPS. Preliminary results show that the GNSS-R SNRs from Galileo and BDS-3 are ∼1–2 dB lower than the GNSS-R measurements from GPS, which could be due to the power of the transmitted power and the bandwidth of the receiver. In addition, the effect of coherent integration time on GNSS-R SNR is also assessed for different GNSS signals. It is shown that the SNR of the reflected signals can be improved by using longer coherent integration time (∼0.4–0.8 dB with 2 ms coherent integration and ∼0.6–1.2 dB with 4 ms coherent integration). In addition, it is also shown that the SNR can be improved more efficiently (∼0.2–0.4 dB) for reflected BDS-3 and Galileo signals than for GPS. These results can provide useful references for the design of future spaceborne GNSS-R instrument compatible with reflections from multi-GNSS constellations.
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Bosser, Pierre, Olivier Bock, Cyrille Flamant, Sandrine Bony, and Sabrina Speich. "Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC<sup>4</sup>A." Earth System Science Data 13, no. 4 (April 12, 2021): 1499–517. http://dx.doi.org/10.5194/essd-13-1499-2021.
Повний текст джерелаАнотація:
Abstract. In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.
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Igarashi, Sho, Yutaka Kaizu, Toshio Tsutsumi, Kenichi Furuhashi, and Kenji Imou. "Autonomous Driving Control of a Robotic Mower on Slopes Using a Low-Cost Two-Frequency GNSS Compass and an IMU." Journal of the ASABE 65, no. 6 (2022): 1179–89. http://dx.doi.org/10.13031/ja.15032.
Повний текст джерелаАнотація:
HighlightsIn this study, we developed an autonomous driving system for a robotic mower operating on a slope.RTK-GNSS, a GNSS compass, and an IMU were used as sensors for the robotic mower.Autonomous driving tests on a slope showed that the driving accuracy of the system was sufficient to meet the requirements of mowing work.Abstract. An autonomous driving control system for a robotic mower was designed using a low-cost dual-frequency global navigation satellite system (GNSS) compass, a low-cost dual-frequency real-time kinematic GNSS (RTK-GNSS), and an inertial measurement unit (IMU). The intended application is to save labor by autonomously mowing sloped terrains. To investigate the effectiveness of the prototype GNSS compass on an inclined terrain, the roll, pitch, and yaw angles were varied using an inclined stage, and the heading accuracy was evaluated. The root mean square (RMS) of the heading error was within 1.5° when the roll and pitch angles were both less than 45°. Autonomous driving tests were conducted on the slope of an agricultural dam with an incline of approximately 25°. The prototype GNSS compass was capable of continuous and consistent heading measurements even on the slope. The cross-track error for the set path was 7.2 cm RMS when starting near the top and driving down the slope. When the robot started near the bottom of the slope and ran up, the cross-track error was 6.6 cm RMS. For the mower and experimental conditions used in this study, this was sufficient accuracy for autonomous driving when mowing on a slope. Keywords: Heading angle, Inclination, MAVLink, Moving baseline, Robot operation system (ROS).
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Nguyen, Viet Khoi, Adria Rovira-Garcia, José Miguel Juan, Jaume Sanz, Guillermo González-Casado, The Vinh La, and Tung Hai Ta. "Measuring phase scintillation at different frequencies with conventional GNSS receivers operating at 1 Hz." Journal of Geodesy 93, no. 10 (October 2019): 1985–2001. http://dx.doi.org/10.1007/s00190-019-01297-z.
Повний текст джерелаАнотація:
Abstract Ionospheric scintillation causes rapid fluctuations of measurements from Global Navigation Satellite Systems (GNSSs), thus threatening space-based communication and geolocation services. The phenomenon is most intense in equatorial regions, around the equinoxes and in maximum solar cycle conditions. Currently, ionospheric scintillation monitoring receivers (ISMRs) measure scintillation with high-pass filter algorithms involving high sampling rates, e.g. 50 Hz, and highly stable clocks, e.g. an ultra-low-noise Oven-Controlled Crystal Oscillator. The present paper evolves phase scintillation indices implemented in conventional geodetic receivers with sampling rates of 1 Hz and rapidly fluctuating clocks. The method is capable to mitigate ISMR artefacts that contaminate the readings of the state-of-the-art phase scintillation index. Our results agree in more than 99.9% within ± 0.05 rad (2 mm) of the ISMRs, with a data set of 8 days which include periods of moderate and strong scintillation. The discrepancies are clearly identified, being associated with data gaps and to cycle-slips in the carrier-phase tracking of ISMR that occur simultaneously with ionospheric scintillation. The technique opens the door to use huge databases available from the International GNSS Service and other centres for scintillation studies. This involves GNSS measurements from hundreds of worldwide-distributed geodetic receivers over more than one Solar Cycle. This overcomes the current limitations of scintillation studies using ISMRs, as only a few tens of ISMRs are available and their data are provided just for short periods of time.
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Ghiasi, Yusof, Claude R. Duguay, Justin Murfitt, Joost J. van der Sanden, Aaron Thompson, Hugo Drouin, and Christian Prévost. "Application of GNSS Interferometric Reflectometry for the Estimation of Lake Ice Thickness." Remote Sensing 12, no. 17 (August 23, 2020): 2721. http://dx.doi.org/10.3390/rs12172721.
Повний текст джерелаАнотація:
Lake ice thickness is a sensitive indicator of climate change largely through its dependency on near-surface air temperature and on-ice snow mass (depth and density). Monitoring of the seasonal variations and trends in ice thickness is also important for the operation of winter ice roads that northern communities rely on for the movement of goods as well as for cultural and leisure activities (e.g., snowmobiling). Therefore, consistent measurements of ice thickness over lakes is important; however, field measurements tend to be sparse in both space and time in many northern countries. Here, we present an application of L-band frequency Global Navigation Satellite System (GNSS) Interferometric Reflectometry (GNSS-IR) for the estimation of lake ice thickness. The proof of concept is demonstrated through the analysis of Signal-to-Noise Ratio (SNR) time series extracted from Global Positioning System (GPS) constellation L1 band raw data acquired between 8 and 22 March (2017 and 2019) at 14 lake ice sites located in the Northwest Territories, Canada. Dominant frequencies are extracted using Least Squares Harmonic Estimation (LS-HE) for the retrieval of ice thickness. Estimates compare favorably with in-situ measurements (mean absolute error = 0.05 m, mean bias error = −0.01 m, and root mean square error = 0.07 m). These results point to the potential of GPS/GNSS-IR as a complementary tool to traditional field measurements for obtaining consistent ice thickness estimates at many lake locations, given the relatively low cost of GNSS antennas/receivers.
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Zhang, Fan, Ye Wang, and Yanbin Gao. "A Novel Method of Fault Detection and Identification in a Tightly Coupled, INS/GNSS-Integrated System." Sensors 21, no. 9 (April 21, 2021): 2922. http://dx.doi.org/10.3390/s21092922.
Повний текст джерелаАнотація:
Fault detection and identification are vital for guaranteeing the precision and reliability of tightly coupled inertial navigation system (INS)/global navigation satellite system (GNSS)-integrated navigation systems. A variance shift outlier model (VSOM) was employed to detect faults in the raw pseudo-range data in this paper. The measurements were partially excluded or included in the estimation process depending on the size of the associated shift in the variance. As an objective measure, likelihood ratio and score test statistics were used to determine whether the measurements inflated variance and were deemed to be faulty. The VSOM is appealing because the down-weighting of faulty measurements with the proper weighting factors in the analysis automatically becomes part of the estimation procedure instead of deletion. A parametric bootstrap procedure for significance assessment and multiple testing to identify faults in the VSOM is proposed. The results show that VSOM was validated through field tests, and it works well when single or multiple faults exist in GNSS measurements.
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Liu, Y., S. H. Li, X. Xiao, and Q. W. Fu. "INS-aided GNSS spoofing detection based on two antenna raw measurements." Gyroscopy and Navigation 7, no. 2 (April 2016): 178–88. http://dx.doi.org/10.1134/s207510871602005x.
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Rataj, V., J. Galambošová, and M. Vašek. "Determining the guidance system accuracy with the support of a large GNSS dataset." Research in Agricultural Engineering 59, Special Issue (December 13, 2013): S65—S70. http://dx.doi.org/10.17221/60/2012-rae.
Повний текст джерелаАнотація:
Several methods are used presently to assess the accuracy of machinery guidance systems. However, these offer a limited number of records and are time and cost consuming. As the machinery is often equipped with a monitoring system for the management purposes, these data can be used. The aim of this work was to develop and verify a method to determine the accuracy of the machinery guidance systems based on a large dataset obtained from the machinery monitoring system. The proposed method uses the transformation of global navigation satellite systems (GNSS) data into a rectangular coordinate system SJTSK (National projection system – Krovak projection). Based on the geometry principle, the ideal line can be determined, and afterwards, the off-track error of each actual position can be calculated. After the verification of this method, it can be concluded that it brings benefits in terms of further use of the data from the monitoring systems, the estimation of the error based on a robust dataset, elimination of subjective and measurement method errors, as well as spatial localisation of the off-track errors at the field.
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Chen, Bo, Chengfa Gao, Yongsheng Liu, and Puyu Sun. "Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone." Sensors 19, no. 12 (June 25, 2019): 2835. http://dx.doi.org/10.3390/s19122835.
Повний текст джерелаАнотація:
The Global Navigation Satellite System (GNSS) positioning technology using smartphones can be applied to many aspects of mass life, and the world’s first dual-frequency GNSS smartphone Xiaomi MI 8 represents a new trend in the development of GNSS positioning technology with mobile phones. The main purpose of this work is to explore the best real-time positioning performance that can be achieved on a smartphone without reference stations. By analyzing the GNSS raw measurements, it is found that all the three mobile phones tested have the phenomenon that the differences between pseudorange observations and carrier phase observations are not fixed, thus a PPP (precise point positioning) method is modified accordingly. Using a Xiaomi MI 8 smartphone, the modified real-time PPP positioning strategy which estimates two clock biases of smartphone was applied. The results show that using multi-GNSS systems data can effectively improve positioning performance; the average horizontal and vertical RMS positioning error are 0.81 and 1.65 m respectively (using GPS, BDS, and Galileo data); and the time required for each time period positioning errors in N and E directions to be under 1 m is less than 30s.
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Wan, Wei, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao. "A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)." Earth System Science Data 14, no. 8 (August 5, 2022): 3549–71. http://dx.doi.org/10.5194/essd-14-3549-2022.
Повний текст джерелаАнотація:
Abstract. The currently available long-term snow depth data sets are either from point-scale ground measurements or from gridded satellite/modeled/reanalysis data with coarse spatial resolution, which limits the applications in climate models, hydrological models, and regional snow disaster monitoring. Benefitting from its unique advantages of cost-effective and high spatiotemporal resolution (∼ 1000 m2, hourly in theory), snow depth retrieval using the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has become a popular topic in recent years. However, due to complex environmental and observation conditions, developing robust and operational technology to produce long-term snow depth data sets using observations from various GNSS station networks is still challenging. The two objectives of this study are (1) to propose a comprehensive framework using raw data of the complex GNSS station networks to retrieve snow depth and control its quality automatically; and (2) to produce a long-term snow depth data set over northern China (i.e., GSnow-CHINA v1.0, 12 h or 24 h, 2013–2022) using the proposed framework and historical data from 80 stations. The data set has high internal consistency with regards to different GNSS constellations (mean r=0.98, RMSD = 0.99 cm, and nRMSD (snow depth > 5 cm) = 0.11), different frequency bands (mean r = 0.97, RMSD = 1.46 cm, and nRMSD (snow depth > 5 cm) = 0.16), and different GNSS receivers (mean r = 0.62). The data set also has high external consistency with the in situ measurements and the passive microwave (PMW) product, with a consistent illustration of the interannual snow depth variability. Additionally, the result show the potential of GNSS to derive hourly snow depth observations for better monitoring of snow disasters. The proposed framework to develop the data set provides comprehensive and supportive information for users to process raw data of ground GNSS stations with complex environmental conditions and various observation conditions. The resulting GSnow-CHINA v1.0 data set is distinguished from the current point-scale in situ data or coarse-gridded data, which can be used as an independent data source for validation purposes. The data set is also useful for regional climate research and other meteorological and hydrological applications. The algorithm and data files will be maintained and updated as more data become available in the future. The GSnow-CHINA v1.0 data set is available at the National Tibetan Plateau/Third Pole Environment Data Center via https://doi.org/10.11888/Cryos.tpdc.271839 (Wan et al., 2021).
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Uradziński, Marcin, and Mieczysław Bakuła. "Assessment of Static Positioning Accuracy Using Low-Cost Smartphone GPS Devices for Geodetic Survey Points’ Determination and Monitoring." Applied Sciences 10, no. 15 (July 31, 2020): 5308. http://dx.doi.org/10.3390/app10155308.
Повний текст джерелаАнотація:
Recent developments enable to access raw Global Navigation Satellite System (GNSS) measurements of mobile phones. Initially, researchers using signals gathered by mobile phones for high accuracy surveying were not successful in ambiguity fixing. Nowadays, GNSS chips, which are built in the latest smartphones, deliver code and primarily carrier phase observations available for detailed analysis in post-processing applications. Therefore, we decided to check the performance of carrier phase ambiguity fixing and positioning accuracy results of the latest Huawei P30 pro smartphone equipped with a dual-frequency GNSS receiver. We collected 3 h of raw static data in separate sessions at a known point location. For two sessions, the mobile phone was mounted vertically and for the third one—horizontally. At the same time, a high-class geodetic receiver was used for L1 and L5 signal comparison purposes. The carrier phase measurements were processed using commercial post-processing software with reference to the closest base station observations located 4 km away. Additionally, 1 h sessions were divided into 10, 15, 20 and 30 min separate sub-sessions to check the accuracy of the surveying results in fast static mode. According to the post-processing results, we were able to fix all L1 ambiguities based on Global Positioning System (GPS)-only satellite constellation. In comparison to the fixed reference point position, all three 1 h static session results were at centimeters level of accuracy (1–4 cm). For fast static surveying mode, the best results were obtained for 20 and 30 min sessions, where average accuracy was also at centimeters level.