Journal articles: 'Assisted GNSS'

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Cheng, Li, Yonghong Dai, Wenfei Guo, and Jiansheng Zheng. "Structure and Performance Analysis of Signal Acquisition and Doppler Tracking in LEO Augmented GNSS Receiver." Sensors 21, no. 2 (January 13, 2021): 525. http://dx.doi.org/10.3390/s21020525.

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Due to the low signal power, the Global Navigation Satellite System (GNSS) signal is vulnerable to interference and even cannot be captured or tracked in harsh environments. As an alternative, the Low Earth Orbit (LEO) satellite has been widely used in the navigation field due to the advantages of low cost and strong signals. It is becoming a significant component of the new combined navigation system with GNSS. The combination of an LEO Doppler signal and GNSS observables can improve the positioning accuracy and high-precision positioning convergence time of the GNSS receiver. However, the GNSS signal receiving capability cannot be improved from this data fusion level. We propose a novel assisted structure where GNSS signal acquisition and Doppler tracking are assisted by LEO Doppler positioning. The receiver uses the LEO signal to achieve Doppler positioning firstly. Then, the coarse position with the GNSS navigation messages received from LEO, as well as the estimated clock information, is used to assist in the acquisition and tracking of GNSS. In this way, the GNSS receiver’s sensitivity can get the benefit from this integrated system. The paper presents the structure of the assisted receiver and analyzes the assisted GNSS signal acquisition and carrier tracking performance in detail. Simulation experiments of this assisted structure are carried out to verify its superiority of acquisition and tracking sensitivity in comparison with standalone GNSS receivers. Theoretical analysis and experimental results show that the proposed acquisition method can achieve 90% detection probability at a carrier-to-noise ratio (C/N0) of 15 dB-Hz, which is about 8 dB higher than the conventional acquisition method without assistance; the proposed tracking method can track weak signals of 5 dB-Hz, which is about 4 dB higher than the conventional method. Therefore, this novel LEO-assisted receiver has significantly improved weak signal acquisition and tracking sensitivity.

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Partsinevelos, Panagiotis, Dimitrios Chatziparaschis, Dimitrios Trigkakis, and Achilleas Tripolitsiotis. "A Novel UAV-Assisted Positioning System for GNSS-Denied Environments." Remote Sensing 12, no. 7 (March 27, 2020): 1080. http://dx.doi.org/10.3390/rs12071080.

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Global Navigation Satellite Systems (GNSS) are extensively used for location-based services, civil and military applications, precise time reference, atmosphere sensing, and other applications. In surveying and mapping applications, GNSS provides precise three-dimensional positioning all over the globe, day and night, under almost any weather conditions. The visibility of the ground receiver to GNSS satellites constitutes the main driver of accuracy for GNSS positioning. When this visibility is obstructed by buildings, high vegetation, or steep slopes, the accuracy is degraded and alternative techniques have to be assumed. In this study, a novel concept of using an unmanned aerial system (UAS) as an intermediate means for improving the accuracy of ground positioning in GNSS-denied environments is presented. The higher elevation of the UAS provides a clear-sky visibility line towards the GNSS satellites, thus its accuracy is significantly enhanced with respect to the ground GNSS receiver. Thus, the main endeavor is to transfer the order of accuracy of the GNSS on-board the UAS to the ground. The general architecture of the proposed system includes hardware and software components (i.e., camera, gimbal, range finder) for the automation of the procedure. The integration of the coordinate systems for each payload setting is described, while an error budget analysis is carried out to evaluate and identify the system’s critical elements along with the potential of the proposed method.

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Huang, Bin, Zheng Yao, Xiaowei Cui, and Mingquan Lu. "Angle-of-Arrival Assisted GNSS Collaborative Positioning." Sensors 16, no. 6 (June 20, 2016): 918. http://dx.doi.org/10.3390/s16060918.

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Hochegger, G., and R. Leitinger. "Model assisted inversion of GNSS occultation data." Physics and Chemistry of the Earth, Part C: Solar, Terrestrial & Planetary Science 26, no. 5 (January 2001): 325–30. http://dx.doi.org/10.1016/s1464-1917(01)00007-1.

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Roncella, R., G. Forlani, and F. Diotri. "A MONTE CARLO SIMULATION STUDY ON THE DOME EFFECT." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 53–60. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-53-2021.

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Abstract. A dome-shape deformation has been found to affect the photogrammetric surface reconstruction in several real and simulated experiments. Its origin has been recognised in inaccurate estimation of the camera parameters and many papers already concentrated on conditions to avoid its development, especially as far as block design is concerned. This paper presents a Monte Carlo simulation to investigate surface reconstruction elevation errors in UAV (Unmanned Aerial Vehicle) photogrammetric blocks. The simulation tests are designed to find out the effect of block shape, camera axis inclination, side-lap, cross strips addition and block control by GCP or GNSS-assisted on the extent of the deformations. The main findings are: i) that GNSS-assisted blocks are generally more robust compared to GCP-controlled ones; ii) that, in GNSS-assisted blocks, unless a mix of nadiral and inclined strips is present, at least one fixed GCP must be provided; iii) that cross strip can conveniently be slimmed to save flight time and processing time; iv) that the effectiveness of GNSS deteriorate as the block shape slims out.

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Li, Binghao, Jiahuang Zhang, Andrew G. Dempster, and Chris Rizos. "Open Source GNSS Reference Server for Assisted-Global Navigation Satellite Systems." Journal of Navigation 64, no. 1 (November 26, 2010): 127–39. http://dx.doi.org/10.1017/s037346331000038x.

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Assisted-Global Navigation Satellite Systems (A-GNSS), or Assisted-Global Positioning Systems (A-GPS) in particular, are now commonly accepted as an effective way to reduce the time-to-first-fix (TTFF) in GNSS-unfriendly environments, e.g. in areas of weak GNSS signals. Today's location-based service (LBS) devices such as GPS-enabled mobile phones and personal digital assistants (PDA) rely on A-GPS; however, such commercial devices are equipped with an integrated A-GPS chip that makes customisation very difficult. The Open Source GNSS Reference Server (OSGRS) provided by the University of New South Wales is an open source Java application that can generate the necessary data for A-GPS clients. The GNSS Reference Interface Protocol (GRIP), based on extensible mark-up language (XML), is employed as the OSGRS interface protocol. This paper describes the current status of OSGRS: a client simulator is available open-source; client software which supports four different types of A-GPS-enabled receivers has been developed and used to test OSGRS. The performance of the OSGRS is analysed based on intensive tests. The challenges for OSGRS and future work are also discussed.

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Shen, Wei, Zhisong Yang, Chaoyu Yang, and Xin Li. "A LiDAR SLAM-Assisted Fusion Positioning Method for USVs." Sensors 23, no. 3 (February 1, 2023): 1558. http://dx.doi.org/10.3390/s23031558.

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Confronted with unmanned surface vessel (USV) operations where GNSS signals are unavailable due to obscuration and other factors, a LiDAR SLAM-assisted fusion positioning method for USVs is proposed to combine GNSS/INS positioning with LiDAR-SLAM. When the USV works in wide-open water, the carrier phase differential GNSS/INS loosely coupled integration strategy is applied to fuse and calibrate the positioning data, and the positioning information of the USV is obtained through the coordinate conversion process. The system uses a dynamic switching strategy to enter to LiDAR-SLAM positioning when GNSS signals are not available, compensating the LiDAR data with precise angle information to ensure accurate and stable positioning. The experiments show that compared with the traditional Kalman filter and adaptive Kalman filter fusion algorithms, the positioning error is reduced by 55.4% and 43.5%. The velocity error is also limited by 78.2% and 57.9%. The standard deviation and the root mean square error are stable within 0.1 m, indicating that our method has better data stability, while the probability of positioning anomaly is effectively controlled.

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Ye, Ping, Xing Qun Zhan, and Gang Du. "INS-Assisted GNSS Signal Tracking Modeling and Assessment." Advanced Materials Research 271-273 (July 2011): 603–8. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.603.

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To improve the tracking performance of GNSS receiver in signal-attenuated environments, phase lock loop (PLL) and delay lock loop (DLL) assisted with Inertial Navigation System (INS) measurements are considered. Combining inertial navigation principles with signal processing, this paper proposes a simplified but efficient mathematical model of INS-assisted second-order tracking loops. Compared with unaided GNSS receiver, the tracking behavior of INS-assisted receiver is quantitatively analyzed, and the kind of INS suitable to guarantee the tracking condition is determined. The results indicate that an INS with 1 deg/h gyro drift is necessary to support PLL, and MEMS inertial sensor with 100 deg/h gyro drift is sufficient to aid DLL to keep favored tracking ability.

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Chang, Qiang, Qun Li, Hong Tao Hou, and Xiang Hui Zeng. "Peer-to-Peer Cooperative Positioning between GNSS Receivers." Applied Mechanics and Materials 341-342 (July 2013): 614–20. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.614.

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Global navigation satellite system (GNSS)-like the Global Positioning System (GPS) and the future Chinese Beidou system-can deliver very good position estimates under optimum conditions. However, especially in critical positioning scenarios like urban canyons or indoor environments the performance loss would be very high or GNSS based positioning is even not possible. Based on the concept of Cooperative Positioning in acquiring real-time positioning information of mobile robots, GNSS Peer-to-Peer Cooperative Positioning (P2P-CP) technology is proposed to overcome the shortage of GNSS positioning. Terrestrial ranging and communication modular are equipped with GNSS receivers to construct real-time CP network. The terrestrial ranging and communication modular respectively used for distance measurement and communication between nearby GNSS receivers, distributed algorithms are applied to fuse pseudorange and neighbors nodes distance to calculate the nodes position. Current research results of GNSS CP show that this new positioning strategy gets equal or better precision with less time cost compared with Assisted GNSS (AGNSS).

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Ioli, F., L. Pinto, and F. Ferrario. "LOW-COST DGPS ASSISTED AERIAL TRIANGULATION FOR SUB-DECIMETRIC ACCURACY WITH NON-RTK UAVS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 25–32. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-25-2021.

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Abstract. The possibility of equipping UAVs with lightweight GNSS receivers in order to estimate the camera position within a photogrammetric block allows for a reduction of the number of Ground Control Points (GCP), saving time during the field work and decreasing operational costs. Additionally, this makes it possible to build photogrammetric models even in morphologically complex areas or in emergency situations. This work is proposing a non-intrusive and low-cost procedure to retrieve the coordinates of the camera projection centre with decimetric accuracy. The method was designed and tested with the quadcopter DJI Matrice 210 V2 drone equipped with a DJI ZENMUSE X5S camera and an Emlid reach M, a low-cost, single-frequency (L1) GNSS receiver. GNSS observations are post-processed in PPK in order to obtain the UAV trajectory. Synchronization between the camera and the GNSS receiver is achieved by looking at the camera triggering timestamps in flight telemetry data, without requiring an electronic connection between camera and the GNSS that may be troublesome with commercial UAVs. Two surveys were carried out, respectively to calibrate and validate the procedure. The validation test evidenced the possibility of obtaining the coordinates of the camera projection centres with decimetric accuracy. The centre of projections can then be employed for GNSS-assisted aerial triangulation as input of the bundle block adjustment. Provided that at least one GCP is used, it is possible to reach centimetric accuracy on the ground.

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Gu, Nianzu, Fei Xing, and Zheng You. "Visual/Inertial/GNSS Integrated Navigation System under GNSS Spoofing Attack." Remote Sensing 14, no. 23 (November 25, 2022): 5975. http://dx.doi.org/10.3390/rs14235975.

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Visual/Inertial/GNSS (VIG) integrated navigation and positioning systems are widely used in unmanned vehicles and other systems. This VIG system is vulnerable to of GNSS spoofing attacks. Relevant research on the harm that spoofing causes to the system and performance analyses of VIG systems under GNSS spoofing are not sufficient. In this paper, an open-source VIG algorithm, VINS-Fusion, based on nonlinear optimization, is used to analyze the performance of the VIG system under a GNSS spoofing attack. The influence of the visual inertial odometer (VIO) scale estimation error and the transformation matrix deviation in the transition period of spoofing detection is analyzed. Deviation correction methods based on the GNSS-assisted scale compensation coefficient estimation method and optimal pose transformation matrix selection are proposed for VIG-integrated system in spoofing areas. For an area that the integrated system can revisit many times, a global pose map-matching method is proposed. An outfield experiment with a GNSS spoofing attack is carried out in this paper. The experiment result shows that, even if the GNSS measurements are seriously affected by the spoofing, the integrated system still can run independently, following the preset waypoint. The scale compensation coefficient estimation method, the optimal pose transformation matrix selection method and the global pose map-matching method can depress the estimation error under the circumstances of a spoofing attack.

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Zhou, Yilin, Ewelina Rupnik, Paul-Henri Faure, and Marc Pierrot-Deseilligny. "GNSS-Assisted Integrated Sensor Orientation with Sensor Pre-Calibration for Accurate Corridor Mapping." Sensors 18, no. 9 (August 24, 2018): 2783. http://dx.doi.org/10.3390/s18092783.

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With the development of unmanned aerial vehicles (UAVs) and global navigation satellite system (GNSS), the accurate camera positions at exposure can be known and the GNSS-assisted bundle block adjustment (BBA) approach is possible for integrated sensor orientation (ISO). This study employed ISO approach for camera pose determination with the objective of investigating the impact of a good sensor pre-calibration on a poor acquisition geometry. Within the presented works, several flights were conducted on a dike by a small UAV embedded with a metric camera and a GNSS receiver. The multi-lever-arm estimation within the BBA procedure makes it possible to merge image blocks of different configurations such as nadir and oblique images without physical constraints on camera and GNSS antenna positions. The merged image block achieves a better accuracy and the sensor self-calibrated well. The issued sensor calibration is then applied to a less preferable acquisition configuration and the accuracy is significantly improved. For a corridor acquisition scene of about 600 m , a centimetric accuracy is reached with one GCP. With the provided sensor pre-calibration, an accuracy of 3.9 c m is achieved without any GCP.

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Zhao, Shuai, Yilan Zhou, and Tengchao Huang. "A Novel Method for AI-Assisted INS/GNSS Navigation System Based on CNN-GRU and CKF during GNSS Outage." Remote Sensing 14, no. 18 (September 9, 2022): 4494. http://dx.doi.org/10.3390/rs14184494.

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In the fields of positioning and navigation, the integrated inertial navigation system (INS)/global navigation satellite systems (GNSS) are frequently employed. Currently, high-precision INS typically utilizes fiber optic gyroscopes (FOGs) and quartz flexural accelerometers (QFAs) rather than MEMS sensors. But when GNSS signals are not available, the errors of high-precision INS also disperse rapidly, similar to MEMS-INS when GNSS signals would be unavailable for a long time, leading to a serious degradation of the navigation accuracy. This paper presents a new AI-assisted method for the integrated high-precision INS/GNSS navigation system. The position increments during GNSS outage are predicted by the convolutional neural network-gated recurrent unit (CNN-GRU). In the process, the CNN is utilized to quickly extract the multi-dimensional sequence features, and GRU is used to model the time series. In addition, a new real-time training strategy is proposed for practical application scenarios, where the duration of the GNSS outage time and the motion state information of the vehicle are taken into account in the training strategy. The real road test results verify that the proposed algorithm has the advantages of high prediction accuracy and high training efficiency.

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Ardizzon, Francesco, Laura Crosara, Nicola Laurenti, Stefano Tomasin, and Nicola Montini. "Authenticated Timing Protocol Based on Galileo ACAS." Sensors 22, no. 16 (August 21, 2022): 6298. http://dx.doi.org/10.3390/s22166298.

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Global navigation satellite systems (GNSSs) provide accurate positioning and timing services in a large gamut of sectors, including financial institutions, Industry 4.0, and Internet of things (IoT). Any industrial system involving multiple devices interacting and/or coordinating their functionalities needs accurate, dependable, and trustworthy time synchronization, which can be obtained by using authenticated GNSS signals. However, GNSS vulnerabilities to time-spoofing attacks may cause security issues for their applications. Galileo is currently developing new services aimed at providing increased security and robustness against attacks, such as the open service navigation message authentication (OS-NMA) and commercial authentication service (CAS). In this paper, we propose a robust and secure timing protocol that is independent of external time sources, and solely relies on assisted commercial authentication service (ACAS) and OS-NMA features. We analyze the performance of the proposed timing protocol and discuss its security level in relation to malicious attacks. Lastly, experimental tests were conducted to validate the proposed protocol.

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Jiménez-Martínez, María Jesús, Mercedes Farjas-Abadia, and Nieves Quesada-Olmo. "An Approach to Improving GNSS Positioning Accuracy Using Several GNSS Devices." Remote Sensing 13, no. 6 (March 17, 2021): 1149. http://dx.doi.org/10.3390/rs13061149.

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Single point positioning (SPP) mode, related to pseudorange measurements, limits the level of accuracy to several meters in open sky and to several dozens of meters in urban canyons. This paper explores the effect of using a large number of SPP observations from low-cost global navigation system (GNSS) receivers, smartphones, and handheld GNSS units. Data segmentation and bootstrapping statistical methods were used to obtain the deviation, which can describe the accuracy of the large sample. The empirical test recording data showed that the error may achieve a sub-meter horizontal accuracy by the simple process of increasing the measurements of smartphones and handheld GNSS units. However, the drawback is the long period of time required. To reduce the satellite tracking time, a least squares solution network was applied over all the recorded data, assisted by the external geometric conditions. The final goal was to obtain the absolute positioning and associated deviations of one vertex from three or five GNSS receivers positioned on a network. The process was tested in three geodetic network examples. The results indicated that the enhanced SPP mode was able to improve its accuracy. Errors of several meters were reduced to values close to 50 cm in 25–37 min periods.

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Morelli, L., F. Menna, A. Vitti, and F. Remondino. "ACTION CAMS AND LOW-COST MULTI-FREQUENCY ANTENNAS FOR GNSS ASSISTED PHOTOGRAMMETRIC APPLICATIONS WITHOUT GROUND CONTROL POINTS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W1-2022 (December 8, 2022): 171–76. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w1-2022-171-2022.

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Abstract. In civil, architectural and environmental fields photogrammetry is one of the most common solutions for deriving geometric information about many kind of objects of interest. Photogrammetric surveys suffer for the need of ground control points (GCPs), well distributed over the survey area, to scale and georeference the produced 3D data. The placement of GCPs is both time-consuming and sometimes infeasible because of environmental constraints, such as vegetation on river sides. For aerial surveys with unmanned aerial vehicles (UAV), several studies have been proposed to use the UAV GNSS antenna to reduce or eliminate the need of GCPs. This technique, called GNSS-aided photogrammetry, has been little explored for terrestrial applications despite its potential in reducing surveying time, or for integrating terrestrial and aerial surveying. This gap has been partly caused by the high cost of topographic-grade GNSS, but in recent years the market has offered receivers, such as the ublox ZED-F9P, which can achieve high accuracy at low cost. In this work we propose a simple and fast GNSS-aided methodology for terrestrial photogrammetric surveys using low-cost GNSS and image sensors. The final aim is to create a general procedure to minimize survey costs and time, and derive a scaled and georeferenced 3D information without GCPs.

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Prešeren, P. Pavlovčič, and B. Stopar. "Wavelet Neural Network employment for continuous GNSS orbit function construction: Application for the Assisted-GNSS principle." Applied Soft Computing 13, no. 5 (May 2013): 2526–36. http://dx.doi.org/10.1016/j.asoc.2012.11.034.

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LaForest, Hasheminasab, Zhou, Flatt, and Habib. "New Strategies for Time Delay Estimation During System Calibration for UAV-Based GNSS/INS-Assisted Imaging Systems." Remote Sensing 11, no. 15 (August 1, 2019): 1811. http://dx.doi.org/10.3390/rs11151811.

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The need for accurate 3D spatial information is growing rapidly in many of today’s key industries, such as precision agriculture, emergency management, infrastructure monitoring, and defense. Unmanned aerial vehicles (UAVs) equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS) and consumer-grade digital imaging sensors are capable of providing accurate 3D spatial information at a relatively low cost. However, with the use of consumer-grade sensors, system calibration is critical for accurate 3D reconstruction. In this study, ‘consumer-grade’ refers to cameras that require system calibration by the user instead of by the manufacturer or other high-end laboratory settings, as well as relatively low-cost GNSS/INS units. In addition to classical spatial system calibration, many consumer-grade sensors also need temporal calibration for accurate 3D reconstruction. This study examines the accuracy impact of time delay in the synchronization between the GNSS/INS unit and cameras on-board UAV-based mapping systems. After reviewing existing strategies, this study presents two approaches (direct and indirect) to correct for time delay between GNSS/INS recorded event markers and actual time of image exposure. Our results show that both approaches are capable of handling and correcting this time delay, with the direct approach being more rigorous. When a time delay exists and the direct or indirect approach is applied, horizontal accuracy of 1–3 times the ground sampling distance (GSD) can be achieved without either the use of any ground control points (GCPs) or adjusting the original GNSS/INS trajectory information.

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Jaud, Marion, Stéphane Bertin, Mickaël Beauverger, Emmanuel Augereau, and Christophe Delacourt. "RTK GNSS-Assisted Terrestrial SfM Photogrammetry without GCP: Application to Coastal Morphodynamics Monitoring." Remote Sensing 12, no. 11 (June 11, 2020): 1889. http://dx.doi.org/10.3390/rs12111889.

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The present article describes a new and efficient method of Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) assisted terrestrial Structure-from-Motion (SfM) photogrammetry without the need for Ground Control Points (GCPs). The system only requires a simple frame that mechanically connects a RTK GNSS antenna to the camera. The system is low cost, easy to transport, and offers high autonomy. Furthermore, not requiring GCPs enables saving time during the in situ acquisition and during data processing. The method is tested for coastal cliff monitoring, using both a Reflex camera and a Smartphone camera. The quality of the reconstructions is assessed by comparison to a synchronous Terrestrial Laser Scanner (TLS) acquisition. The results are highly satisfying with a mean error of 0.3 cm and a standard deviation of 4.7 cm obtained with the Nikon D800 Reflex camera and, respectively, a mean error of 0.2 cm and a standard deviation of 3.8 cm obtained with the Huawei Y5 Smartphone camera. This method will be particularly interesting when simplicity, portability, and autonomy are desirable. In the future, it would be transposable to participatory science programs, while using an open RTK GNSS network.

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Blay, Ryan, Boyi Wang*, and Dennis M. Akos. "Deriving Accurate Time from Assisted GNSS Using Extended Ambiguity Resolution." NAVIGATION 68, no. 1 (February 25, 2021): 217–29. http://dx.doi.org/10.1002/navi.412.

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Huang, Grant, Mikel M. Miller, and David Akopian. "Inference of network delays for SUPL 3.0-based assisted GNSS." GPS Solutions 21, no. 2 (July 22, 2016): 651–61. http://dx.doi.org/10.1007/s10291-016-0549-6.

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Abdolkarimi, Elahe Sadat, Mohammad Reza Mosavi, Sadra Rafatnia, and Diego Martin. "A Hybrid Data Fusion Approach to AI-Assisted Indirect Centralized Integrated SINS/GNSS Navigation System During GNSS Outage." IEEE Access 9 (2021): 100827–38. http://dx.doi.org/10.1109/access.2021.3096422.

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Tang, Chengkai, Lingling Zhang, Yi Zhang, and Houbing Song. "Factor Graph-Assisted Distributed Cooperative Positioning Algorithm in the GNSS System." Sensors 18, no. 11 (November 2, 2018): 3748. http://dx.doi.org/10.3390/s18113748.

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The development of smart cities calls for improved accuracy in navigation and positioning services; due to the effects of satellite orbit error, ionospheric error, poor quality of navigation signals and so on, it is difficult for existing navigation technology to achieve further improvements in positioning accuracy. Distributed cooperative positioning technology can further improve the accuracy of navigation and positioning with existing GNSS (Global Navigation Satellite System) systems. However, the measured range error and the positioning error of the cooperative nodes exhibit larger reductions in positioning accuracy. In response to this question, this paper proposed a factor graph-aided distributed cooperative positioning algorithm. It establishes the confidence function of factor graphs theory with the ranging error and the positioning error of the coordinated nodes and then fuses the positioning information of the coordinated nodes by the confidence function. It can avoid the influence of positioning error and ranging error and improve the positioning accuracy of cooperative nodes. In the simulation part, the proposed algorithm is compared with a mainly coordinated positioning algorithm from four aspects: the measured range error, positioning error, convergence speed, and mutation error. The simulation results show that the proposed algorithm leads to a 30–60% improvement in positioning accuracy compared with other algorithms under the same measured range error and positioning error. The convergence rate and mutation error elimination times are only 1 / 5 to 1 / 3 of the other algorithms.

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Ye, Ping, Xingqun Zhan, and Chunming Fan. "Novel optimal bandwidth design in INS-assisted GNSS Phase Lock Loop." IEICE Electronics Express 8, no. 9 (2011): 650–56. http://dx.doi.org/10.1587/elex.8.650.

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Isshiki, Hiroshi. "Wide-lane Assisted Long Baseline High Precision Kinematic Positioning by GNSS." Journal of Global Positioning Systems 4, no. 1&2 (December 31, 2005): 65–75. http://dx.doi.org/10.5081/jgps.4.1.65.

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Pérez-Ruiz, M., J. Carballido, J. Agüera, and J. A. Gil. "Assessing GNSS correction signals for assisted guidance systems in agricultural vehicles." Precision Agriculture 12, no. 5 (November 26, 2010): 639–52. http://dx.doi.org/10.1007/s11119-010-9211-4.

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Shults, Roman, Azhar Ormambekova, Yurii Medvedskij, and Andriy Annenkov. "GNSS-Assisted Low-Cost Vision-Based Observation System for Deformation Monitoring." Applied Sciences 13, no. 5 (February 22, 2023): 2813. http://dx.doi.org/10.3390/app13052813.

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This paper considers an approach to solve the structure monitoring problem using an integrated GNSS system and non-metric cameras with QR-coded targets. The system is defined as a GNSS-assisted low-cost vision-based observation system, and its primary application is for monitoring various engineering structures, including high-rise buildings. The proposed workflow makes it possible to determine the change in the structure geometric parameters under the impact of external factors or loads and in what follows to predict the displacements at a given observation epoch. The approach is based on the principle of relative measurements, implemented to find the displacements between pairs of images from non-metric cameras organized in a system of interconnected chains. It is proposed to determine the displacement between the images for different epochs using the phase correlation algorithm, which provides a high-speed solution and reliable results. An experimental test bench was prepared, and a series of measurements were performed to simulate the operation of one vision-based observation system chain. A program for processing the sequence of images in the MatLab programming environment using the phase correlation algorithm was implemented. An analysis of the results of the experiment was carried out. The analysis results allowed us to conclude that the suggested approach can be successfully implemented in compliance with the requirements for monitoring accuracy. The simulation of the vision-based observation system operation with accuracy estimation was performed. The simulation results proved the high efficiency of the suggested system.

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Hasheminasab, Seyyed Meghdad, Tian Zhou, and Ayman Habib. "GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields." Remote Sensing 12, no. 3 (January 21, 2020): 351. http://dx.doi.org/10.3390/rs12030351.

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Acquired imagery by unmanned aerial vehicles (UAVs) has been widely used for three-dimensional (3D) reconstruction/modeling in various digital agriculture applications, such as phenotyping, crop monitoring, and yield prediction. 3D reconstruction from well-textured UAV-based images has matured and the user community has access to several commercial and opensource tools that provide accurate products at a high level of automation. However, in some applications, such as digital agriculture, due to repetitive image patterns, these approaches are not always able to produce reliable/complete products. The main limitation of these techniques is their inability to establish a sufficient number of correctly matched features among overlapping images, causing incomplete and/or inaccurate 3D reconstruction. This paper provides two structure from motion (SfM) strategies, which use trajectory information provided by an onboard survey-grade global navigation satellite system/inertial navigation system (GNSS/INS) and system calibration parameters. The main difference between the proposed strategies is that the first one—denoted as partially GNSS/INS-assisted SfM—implements the four stages of an automated triangulation procedure, namely, imaging matching, relative orientation parameters (ROPs) estimation, exterior orientation parameters (EOPs) recovery, and bundle adjustment (BA). The second strategy— denoted as fully GNSS/INS-assisted SfM—removes the EOPs estimation step while introducing a random sample consensus (RANSAC)-based strategy for removing matching outliers before the BA stage. Both strategies modify the image matching by restricting the search space for conjugate points. They also implement a linear procedure for ROPs’ refinement. Finally, they use the GNSS/INS information in modified collinearity equations for a simpler BA procedure that could be used for refining system calibration parameters. Eight datasets over six agricultural fields are used to evaluate the performance of the developed strategies. In comparison with a traditional SfM framework and Pix4D Mapper Pro, the proposed strategies are able to generate denser and more accurate 3D point clouds as well as orthophotos without any gaps.

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Ioannides, Rigas T., L. Enrique Aguado, and Gary Brodin. "Diverse Signals Combinations for High-Sensitivity GNSS." Journal of Navigation 60, no. 3 (August 9, 2007): 497–515. http://dx.doi.org/10.1017/s0373463307004353.

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Indoor positioning imposes demanding requirements on the design of Global Navigation Satellite System (GNSS) sensors for both the acquisition and tracking functions. Although different combinations of coherent and non-coherent integration periods of a GNSS signal can be used to achieve reliable acquisition of the GNSS signals and indoors positioning, there are limitations to the extent that the integration period of the signal energy can be increased set by the receiver and satellite dynamics and the stability of the local oscillator. Assisting networks for GNSS applications (AGNSS) provide users with the capability of using long integration periods, enabling them to acquire indoor signals at low Carrier to Noise Ratio (CNR) values, where CNR is defined as the ratio of the received signal power over the noise density in units of dB-Hz. In this work we propose and evaluate the potential of a new method that will provide the user with an additional signal energy margin for accurate and reliable indoor positioning, with or without relying on assisted GNSS-type algorithms. The technique proposed here is based on the coherent and non-coherent combination of the energy of signals transmitted from the same GNSS satellite on different frequencies using the multiple open service signals that are to be provided by the Galileo system and under the GPS modernisation. This paper shows the improvement to the receiver acquisition and tracking performance using the proposed technique of combining energies at the L1, L2 and L5 bands for both data and pilot signals.

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Cledat, E., and D. A. Cucci. "MAPPING GNSS RESTRICTED ENVIRONMENTS WITH A DRONE TANDEM AND INDIRECT POSITION CONTROL." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W3 (August 18, 2017): 1–7. http://dx.doi.org/10.5194/isprs-annals-iv-2-w3-1-2017.

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The problem of autonomously mapping highly cluttered environments, such as urban and natural canyons, is intractable with the current UAV technology. The reason lies in the absence or unreliability of GNSS signals due to partial sky occlusion or multi-path effects. High quality carrier-phase observations are also required in efficient mapping paradigms, such as Assisted Aerial Triangulation, to achieve high ground accuracy without the need of dense networks of ground control points. In this work we consider a drone tandem in which the first drone flies outside the canyon, where GNSS constellation is ideal, visually tracks the second drone and provides an indirect position control for it. This enables both autonomous guidance and accurate mapping of GNSS restricted environments without the need of ground control points. We address the technical feasibility of this concept considering preliminary real-world experiments in comparable conditions and we perform a mapping accuracy prediction based on a simulation scenario.

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Moussa, Mohamed, Adel Moussa, and Naser El-Sheimy. "Steering Angle Assisted Vehicular Navigation Using Portable Devices in GNSS-Denied Environments." Sensors 19, no. 7 (April 4, 2019): 1618. http://dx.doi.org/10.3390/s19071618.

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Recently, land vehicle navigation, and especially by the use of low-cost sensors, has been the object of a huge level of research interest. Consumer Portable Devices (CPDs) such as tablets and smartphones are being widely used by many consumers all over the world. CPDs contain sensors (accelerometers, gyroscopes, magnetometer, etc.) that can be used for many land vehicle applications such as navigation. This paper presents a novel approach for estimating steering wheel angles using CPD accelerometers by attaching CPDs to the steering wheel. The land vehicle change of heading is then computed from the estimated steering wheel angle. The calculated change of heading is used to update the navigation filter to aid the onboard Inertial Measurement Unit (IMU) through the use of an Extended Kalman Filter (EKF) in GNSS-denied environments. Four main factors that may affect the steering wheel angle accuracy are considered and modeled during steering angle estimations: static onboard IMU leveling, inclination angle of the steering wheel, vehicle acceleration, and vehicle inclination. In addition, these factors are assessed for their effects on the final result. Therefore, three methods are proposed for steering angle estimation: non-compensated, partially-compensated, and fully-compensated methods. A road experimental test was carried out using a Pixhawk (PX4) navigation system, iPad Air, and the OBD-II interface. The average Root Mean Square Error (RMSE) of the change of heading estimated by the proposed method was 0.033 rad/s. A navigation solution was estimated while changes of heading and forward velocity updates were used to aid the IMU during different GNSS signal outages. The estimated navigation solution is enhanced when applying the proposed updates to the navigation filter by 91% and 97% for 60 s and 120 s of GNSS signal outage, respectively, compared to the IMU standalone solution.

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Khadempir, Sara, Ali Ahmadpour, Mohammad T. Hamed Mosavian, Narges Ashraf, Fatemeh F. Bamoharram, Scott G. Mitchell, and Jesús M. de la Fuente. "A polyoxometalate-assisted approach for synthesis of Pd nanoparticles on graphene nanosheets: synergistic behaviour for enhanced electrocatalytic activity." RSC Advances 5, no. 31 (2015): 24319–26. http://dx.doi.org/10.1039/c5ra01084e.

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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.

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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.

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Luo, Xianzhi, Hongwei Zhao, and Hao Yan. "Design of Unambiguous Combined Tracking Loop for GNSS Complex Subcarrier Signal." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 1 (February 2018): 176–81. http://dx.doi.org/10.1051/jnwpu/20183610176.

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Complex subcarrier modulation signal, is a kind of BOC signal which is used complex exponential function as subcarrier, has been widely applied in GNSS(Global Navigation satellite system). The existence of multiple correlation peaks of the autocorrelation function of the complex subcarrier signal, will cause the acquisition error and tracking to the side peak when the signal is synchronized. To solve this problem, an unambiguous combined tracking loop for complex subcarrier signals is proposed. In this loop architecture, the main loop completes the coarse synchronization with BPSK-like algorithm, and the assisted loop realizes the accurate tracking together main loop. In this paper, the dual estimate tracking algorithm and the side-peak cancellation scheme are employed respectively in the assisted loop. The performance of tracking accuracy and anti-multipath capability of the proposed architecture is analyzed, and the practicability is verified by using the actual collected data. Simulation and experimental results show that the tracking structure proposed in this paper is practical and has good performance of anti-noise and anti-multipath.

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Yuan, Xie, Zhong Liang Deng, and Yu Zhang. "A Method of RAM-Based Frequency Acquisition for Base Station Positioning Receiver." Applied Mechanics and Materials 319 (May 2013): 517–22. http://dx.doi.org/10.4028/www.scientific.net/amm.319.517.

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Location based service (LBS) is more and more important nowadays. Assisted with GNSS, Base Station Positioning System (BSPS) can offer seamless outdoor & indoor positioning. The fading channel causes problems in signal acquisition. In this paper, a new method of RAM-based frequency acquisition is introduced, which can acquire the residual carrier frequency in fading channel accurately.

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LaForest, Lisa M., Tian Zhou, Seyyed Meghdad Hasheminasab, and Ayman Habib. "System Calibration Including Time Delay Estimation for GNSS/INS-Assisted Pushbroom Scanners Onboard UAV Platforms." Photogrammetric Engineering & Remote Sensing 87, no. 10 (October 1, 2021): 705–16. http://dx.doi.org/10.14358/pers.20-00084r3.

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Unmanned aerial vehicles (UAVs ) equipped with imaging sensors and integrated global navigation satellite system/inertial navigation system (GNSS/INS ) units are used for numerous applications. Deriving reliable 3D coordinates from such UAVs is contingent on accurate geometric calibration, which encompasses the estimation of mounting parameters and synchronization errors. Through a rigorous impact analysis of such systematic errors, this article proposes a direct approach for spatial and temporal calibration (estimating system parameters through a bundle adjustment procedure) of a GNSS/INS -assisted pushbroom scanner onboard a UAV platform. The calibration results show that the horizontal and vertical accuracies are within the ground sampling distance of the sensor. Unlike for frame camera systems, this article also shows that the indirect approach is not a feasible solution for pushbroom scanners due to their limited ability for decoupling system parameters. This finding provides further support that the direct approach is recommended for spatial and temporal calibration of UAV pushbroom scanner systems.

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Gallo, Eduardo, and Antonio Barrientos. "GNSS-Denied Semi-Direct Visual Navigation for Autonomous UAVs Aided by PI-Inspired Inertial Priors." Aerospace 10, no. 3 (February 25, 2023): 220. http://dx.doi.org/10.3390/aerospace10030220.

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This article proposes a method to diminish the horizontal position drift in the absence of GNSS (Global Navigation Satellite System) signals experienced by the VNS (Visual Navigation System) installed onboard a UAV (Unmanned Air Vehicle) by supplementing its pose estimation non-linear optimizations with priors based on the outputs of the INS (Inertial Navigation System). The method is inspired by a PI (Proportional Integral) control loop, in which the attitude and altitude inertial outputs act as targets to ensure that the visual estimations do not deviate past certain thresholds from their inertial counterparts. The resulting IA-VNS (Inertially Assisted Visual Navigation System) achieves major reductions in the horizontal position drift inherent to the GNSS-Denied navigation of autonomous UAVs. Stochastic high-fidelity Monte Carlo simulations of two representative scenarios involving the loss of GNSS signals are employed to evaluate the results and to analyze their sensitivity to the terrain type overflown by the aircraft. The authors release the C++ implementation of both the navigation algorithms and the high-fidelity simulation as open-source software.

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Liu, Di, Qingyuan Xia, Changhui Jiang, Chaochen Wang, and Yuming Bo. "A LSTM-RNN-Assisted Vector Tracking Loop for Signal Outage Bridging." International Journal of Aerospace Engineering 2020 (August 12, 2020): 1–11. http://dx.doi.org/10.1155/2020/2975489.

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Global Navigation Satellite System (GNSS) has been the most popular tool for providing positioning, navigation, and timing (PNT) information. Some methods have been developed for enhancing the GNSS performance in signal challenging environments (urban canyon, dense foliage, signal blockage, multipath, and none-line-of-sight signals). Vector Tracking Loop (VTL) was recognized as the most promising and prospective one among these technologies, since VTL realized mutual aiding between channels. However, momentary signal blockage from part of the tracking channels affected the VTL operation and the navigation solution estimation. Moreover, insufficient available satellites employed would lead to the navigation solution errors diverging quickly over time. Short-time or temporary signal blockage was common in urban areas. Aiming to improve the VTL performance during the signal outage, in this paper, the deep learning method was employed for assisting the VTL navigation solution estimation; more specifically, a Long Short-Term Memory-Recurrent Neural Network (LSTM-RNN) was employed to aid the VTL navigation filter (navigation filter was usually a Kalman filter). LSTM-RNN obtained excellent performance in time-series data processing; therefore, in this paper, the LSTM-RNN was employed to predict the navigation filter innovative sequence values during the signal outage, and then, the predicted innovative values were employed to aid the navigation filter for navigation solution estimation. The LSTM-RNN was well trained while the signal was normal, and the past innovative sequence was employed as the input of the LSTM-RNN. A simulation was designed and conducted based on an open-source Matlab GNSS software receiver; a dynamic trajectory with several temporary signal outages was designed for testing the proposed method. Compared with the conventional VTL, the LSTM-RNN-assisted VTL could keep the horizontal positioning errors within 50 meters during a signal outage. Also, conventional Support Vector Machine (SVM) and radial basis function neural network (RBF-NN) were compared with the LSTM-RNN method; LSTM-RNN-assisted VTL could maintain the positioning errors less than 20 meters during the outages, which demonstrated LSTM-RNN was superior to the SVM and RBF-NN in these applications.

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Kim, Hyunsung, Jaehee Kim, Young-Seok Kim, Mijung Kim, and Youngjoo Lee. "Energy-Efficient Wearable EPTS Device Using On-Device DCNN Processing for Football Activity Classification." Sensors 20, no. 21 (October 22, 2020): 6004. http://dx.doi.org/10.3390/s20216004.

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This paper presents an energy-optimized electronic performance tracking system (EPTS) device for analyzing the athletic movements of football players. We first develop a tiny battery-operated wearable device that can be attached to the backside of field players. In order to analyze the strategic performance, the proposed wearable EPTS device utilizes the GNSS-based positioning solution, the IMU-based movement sensing system, and the real-time data acquisition protocol. As the life-time of the EPTS device is in general limited due to the energy-hungry GNSS sensing operations, for the energy-efficient solution extending the operating time, in this work, we newly develop the advanced optimization methods that can reduce the number of GNSS accesses without degrading the data quality. The proposed method basically identifies football activities during the match time, and the sampling rate of the GNSS module is dynamically relaxed when the player performs static movements. A novel deep convolution neural network (DCNN) is newly developed to provide the accurate classification of human activities, and various compression techniques are applied to reduce the model size of the DCNN algorithm, allowing the on-device DCNN processing even at the memory-limited EPTS device. Experimental results show that the proposed DCNN-assisted sensing control can reduce the active power by 28%, consequently extending the life-time of the EPTS device more than 1.3 times.

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Setlak, Lucjan, and Rafał Kowalik. "The Basic Architecture of the System with the A-GNSS Receiver." MATEC Web of Conferences 292 (2019): 04010. http://dx.doi.org/10.1051/matecconf/201929204010.

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The paper presents the results of obtained research defining the accuracy of determining the position of a specific object (aircraft, UAV), equipped with a mobile receiver operating the navigation system A-GNSS. The Assisted GNSS technology is designed to improve the performance of the GNSS receiver by reducing the time needed for the receiver to calculate its location. It also increases the sensitivity of the received signal by the receiver, as a result, the accuracy of the determined position of a specific object can be improved. Thanks to its application, the radio-navigation receiver becomes compatible with the requirements of current standards, and what is associated with it this kind of technology has become an important part of the cellular industry. The aim of the article is to examine the solution of A-GPS system and to demonstrate its effectiveness in the process of determining the position of the UAV object. The paper presents aspects of the functionality of the A-GPS system solution work, mathematical model of object position determination using A-GNSS system and discusses the technology that is used for the integration of navigation systems with cellular network. In the final part of the work, based on the analysis of the research literature, the presented mathematical model and simulations, conclusions were formulated, which are reflected in practical applications.

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Jiang, San, and Wanshou Jiang. "On-Board GNSS/IMU Assisted Feature Extraction and Matching for Oblique UAV Images." Remote Sensing 9, no. 8 (August 7, 2017): 813. http://dx.doi.org/10.3390/rs9080813.

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Roggenbuck, Ole, and Jörg Reinking. "Sea Surface Heights Retrieval from Ship-Based Measurements Assisted by GNSS Signal Reflections." Marine Geodesy 42, no. 1 (January 2, 2019): 1–24. http://dx.doi.org/10.1080/01490419.2018.1543220.

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Habib, Ayman, Tian Zhou, Ali Masjedi, Zhou Zhang, John Evan Flatt, and Melba Crawford. "Boresight Calibration of GNSS/INS-Assisted Push-Broom Hyperspectral Scanners on UAV Platforms." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11, no. 5 (May 2018): 1734–49. http://dx.doi.org/10.1109/jstars.2018.2813263.

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Zou, Xiaojun, Baowang Lian, and Peng Wu. "Fault Identification Ability of a Robust Deeply Integrated GNSS/INS System Assisted by Convolutional Neural Networks." Sensors 19, no. 12 (June 18, 2019): 2734. http://dx.doi.org/10.3390/s19122734.

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The problem of fault propagation which exists in the deeply integrated GNSS (Global Navigation Satellite System)/INS (Inertial Navigation System) system makes it difficult to identify faults. Once a fault occurs, system performance will be degraded due to the inability to identify and isolate the fault accurately. After analyzing the causes of fault propagation and the difficulty of fault identification, maintaining correct navigation solution is found to be the key to prevent fault propagation from occurring. In order to solve the problem, a novel robust algorithm based on convolutional neural network (CNN) is proposed. The optimal expansion factor of the robust algorithm is obtained adaptively by utilizing CNN, thus the adverse effect of fault on navigation solution can be reduced as much as possible. At last, the fault identification ability is verified by two types of experiments: artificial fault injection and outdoor occlusion. Experiment results show that the proposed robust algorithm which can successfully suppress the fault propagation is an effective solution. The accuracy of fault identification is increased by more than 20% compared with that before improvement, and the robustness of deep GNSS/INS integration is also improved.

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Luo, Zhibin, Jicheng Ding, and Lin Zhao. "Adaptive Gain Control Method of a Phase-Locked Loop for GNSS Carrier Signal Tracking." International Journal of Antennas and Propagation 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/6841285.

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The global navigation satellite system (GNSS) has been widely used in both military and civil fields. This study focuses on enhancing the carrier tracking ability of the phase-locked loop (PLL) in GNSS receivers for high-dynamic application. The PLL is a very popular and practical approach for tracking the GNSS carrier signal which propagates in the form of electromagnetic wave. However, a PLL with constant coefficient would be suboptimal. Adaptive loop noise bandwidth techniques proposed by previous researches can improve PLL tracking behavior to some extent. This paper presents a novel PLL with an adaptive loop gain control filter (AGCF-PLL) that can provide an alternative. The mathematical model based on second- and third-order PLL was derived. The error characteristics of the AGCF-PLL were also derived and analyzed under different signal conditions, which mainly refers to the different combinations of carrier phase dynamic and signal strength. Based on error characteristic curves, the optimal loop gain control method has been achieved to minimize tracking error. Finally, the completely adaptive loop gain control algorithm was designed. Comparable test results and analysis using the new method, conventional PLL, FLL-assisted PLL, and FAB-LL demonstrate that the AGCF-PLL has stronger adaptability to high target movement dynamic.

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Visconti, Paolo, Marzia Luceri, Ramiro Velazquez, and De Fazio Roberto. "A remote-controlled global navigation satellite system based rover for accurate video-assisted cadastral surveys." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 4 (August 1, 2022): 3551. http://dx.doi.org/10.11591/ijece.v12i4.pp3551-3563.

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<span>One of the main tasks of a cadastral surveyor is to accurately determine property boundaries by measuring control points and calculating their coordinates. This paper proposes the development of a remotely-controlled tracking system to perform cadastral measurements. A Bluetooth-controlled rover was developed, including a Raspberry Pi Zero W module that acquires position data from a VBOX 3iSR global navigation satellite system (GNSS) receiver, equipped with a specific modem to download real-time kinematic (RTK) corrections from the internet. Besides, the Raspberry board measures the rover speed with a hall sensor mounted on a track, adjusting the acquisition rate to collect data at a fixed distance. Position and inertial data are shared with a cloud platform, enabling their remote monitoring and storing. Besides, the power supply section was designed to power the different components included in the acquisition section, ensuring 2 hours of energy autonomy. Finally, a mobile application was developed to drive the rover and real-time monitor the travelled path. The tests indicated a good agreement between rover measurements and those obtained by a Trimble R10 GNSS receiver (+0.25% mean error) and proved the superiority of the presented system over a traditional metric wheel.</span>

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Triezani, Akbar Maulana, and Didit Andri Jatmiko. "Rancang Bangun Unmanned Surface Vehicle (USV) Dengan Sistem Navigasi Berbasis Kompas Dan Estimasi A-GPS." Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan 9, no. 1 (October 18, 2021): 23–36. http://dx.doi.org/10.34010/telekontran.v9i1.5607.

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Abstrak – Di zaman sekarang telah hadir suatu sistem yang dinamakan Global Navigation Satellite System (GNSS) untuk mengestimasi posisi sebuah wahana autonomous. Namun pada kenyataannya penerima GNSS kerap mengalami gangguan yang berhubungan dengan akurasi dan kestabilan pembacaan dengan penyebab utama terhalangnya penerima GNSS oleh objek-objek seperti awan tebal, gedung-gedung atau posisi di dalam ruangan. Pada penelitian ini, sistem estimasi posisi dari wahana akan menggunakan pembacaan posisi melalui salah satu fitur dari GNSS yaitu Assisted Global Positioning System (A-GPS) yang ada pada smartphone. Dalam perancangannya, wahana akan menggunakan kompas sebagai penentu arah gerak agar dapat mencapai waypoint dengan akurat. Tujuan pada penelitian ini adalah merancang sistem navigasi yang mampu membuat wahana mencapai waypoint dengan tingkat keandalan yang lebih baik menggunakan kompas dan estimasi dari A-GPS. Metode yang digunakan dalam penelitian ini yaitu menguji wahana untuk mencapai waypoint menggunakan perhitungan jarak dan bearing antara posisi wahana saat ini dan tujuan lalu membandingkan hasil dari sistem estimasi A-GPS dengan Global Positioning System (GPS). Hasil dari penelitian ini didapatkan sistem navigasi wahana menggunakan A-GPS mampu menghasilkan estimasi posisi yang lebih baik dibandingkan GPS dengan tingkat akurasi mencapai 1 hingga 3 meter untuk navigasi secara keseluruhan atau dengan rata-rata 1,5 meter untuk waypoint yang tercapai oleh wahana ketika bernavigasi. Wahana juga teruji mampu menyesuaikan arah gerak menuju waypoint menggunakan sensor kompas dengan simpangan terjauh dari bearing tujuan sebesar 3o. Konsep dari penelitian ini berasal dari premis sistem A-GPSang telah terintegrasi pada smartphone untuk mendapatkan data posisi yang paling relevan tanpa perlu khawatir jika penerima GNSS terhalang oleh cuaca ataupun dalam posisi di dalam ruangan. Maka dari itu, dengan menggabungkan kedua sistem pembacaan tersebut, dapat menghasilkan estimasi posisi yang lebih baik sehingga dapat meningkatkan keandalan dari sebuha wahana untuk bernavigasi secara autonomous. Selain itu, impact penelitian ini juga dapat diterpakan dalam berbagai sistem salah satunya untuk navigasi wahana autonomous. Kata kunci : Autonomous, A-GPS, Kompas, Navigasi, Waypoint.

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Yuan, Wenan, Daeun Choi, and Dimitrios Bolkas. "GNSS-IMU-assisted colored ICP for UAV-LiDAR point cloud registration of peach trees." Computers and Electronics in Agriculture 197 (June 2022): 106966. http://dx.doi.org/10.1016/j.compag.2022.106966.

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Bayat, Milad, and MA Amiri Atashgah. "An Augmented Strapdown Inertial Navigation System using Jerk and Jounce of Motion for a Flying Robot." Journal of Navigation 70, no. 4 (March 8, 2017): 907–26. http://dx.doi.org/10.1017/s0373463317000017.

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This paper offers an algorithm for enhancement of positioning accuracy of a quad-rotor flying robot, based on jerk and jounce of motion. The suggested method utilises the first and second numerical derivatives of the vehicle's acceleration and augments the mathematical model in the estimation process. For this purpose, the Kalman Filter (KF) is implemented for integration of a Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS). The required data are collected from a low-cost/quality Micro Electromechanical Sensors (MEMS) during an assisted flight. For increasing the precision and accuracy of the collected data, all instruments including accelerometers, gyroscopes and magnetometers are calibrated before the experiments. Moreover, to reduce and limit the measurement noises of the MEMS sensor, a low-pass filter is applied; this is while sensors in the autopilot are affected by high levels of noise and drift, which makes them inappropriate for accurate positioning. The experimental results exhibit an improvement in positioning and altitude sensing through augmentation of the loosely coupled SINS/GNSS navigation method.

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Zhang, Lingling, Chengkai Tang, Yi Zhang, and Houbing Song. "Inertial-Navigation-Aided Single-Satellite Highly Dynamic Positioning Algorithm." Sensors 19, no. 19 (September 27, 2019): 4196. http://dx.doi.org/10.3390/s19194196.

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Nowadays, research on global navigation satellite systems (GNSS) has reached a certain level of maturity to provide high-precision positioning services in many applications. Nonetheless, there are challenging GNSS-denial environments where a temporarily deployed single-satellite positioning system is a promising choice. To further meet the emergency call of highly dynamic targets in such situations, an augmented single-satellite positioning algorithm is proposed in this paper. First, the initial location of the highly dynamic target is found by real-time displacement feedback from the inertial navigation system (INS). Then, considering the continuity of position change, and taking advantage of the high accuracy and robustness of the unscented Kalman filter (UKF), target location is through iteration and fusion. Comparing this proposed method with the least-squares Newton-iterative Doppler single-satellite positioning system and the pseudorange rate-assisted method under synthetic error conditions, the positioning error of our algorithm was 10 % less than the other two algorithms. This verified the validation of our algorithm in the single-satellite system with highly dynamic targets.

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Journal articles on the topic 'Assisted GNSS'

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