Journal articles on the topic 'Seamless positioning and navigation'
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1
Basiri, Anahid, Pouria Amirian, Adam Winstanley, Stuart Marsh, Terry Moore, and Guillaume Gales. "Seamless Pedestrian Positioning and Navigation Using Landmarks." Journal of Navigation 69, no. 1 (June 22, 2015): 24–40. http://dx.doi.org/10.1017/s0373463315000442.
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Many navigation services, such as car navigation services, provide users with praxic navigational instructions (such as “turn left after 200 metres, then turn right after 150 metres”), however people usually associate directions with visual cues (e.g. “turn right at the square”) when giving navigational instructions in their daily conversations. Landmarks can play an equally important role in navigation and routing services. Landmarks are unique and easy-to-recognise and remember features; therefore, in order to remember when exploring an unfamiliar environment, they would be assets. In addition, Landmarks can be found both indoors and outdoors and their locations are usually fixed. Any positioning techniques which use landmarks as reference points can potentially provide seamless (indoor and outdoor) positioning solutions. For example, users can be localised with respect to landmarks if they can take a photograph of a registered landmark and use an application for image processing and feature extraction to identify the landmark and its location. Landmarks can also be used in pedestrian-specific path finding services. Landmarks can be considered as an important parameter in a path finding algorithm to calculate a route passing more landmarks (to make the user visit a more tourist-focussed area, pass along an easier-to-follow route, etc.). Landmarks can also be used as a part of the navigational instructions provided to users; a landmark-based navigation service makes users sure that they are on the correct route, as the user is reassured by seeing the landmark whose information/picture has just been provided as a part of navigational instruction. This paper shows how landmarks can help improve positioning and praxic navigational instructions in all these ways.
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Cho, Seong Yun, and Chan Gook Park. "MEMS Based Pedestrian Navigation System." Journal of Navigation 59, no. 1 (December 15, 2005): 135–53. http://dx.doi.org/10.1017/s0373463305003486.
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In this paper we present a micro-electrical mechanical system (MEMS) based pedestrian navigation system (PNS) for seamless positioning. The sub-algorithms for the PNS are developed and the positioning performance is enhanced using the modified receding horizon Kalman finite impulse response filter (MRHKF). The PNS consists of a biaxial accelerometer and a biaxial magnetic compass mounted on a shoe. The PNS detects a step using a novel technique during the stance phase and simultaneously calculates walking information. Step length is estimated using a neural network whose inputs are the walking information. The azimuth is calculated using the magnetic compass, the walking information and the tilt compensation algorithm. Using the proposed sub-algorithms, seamless positioning can be accomplished. However, the magnetic compass based azimuth may have an error that varies according to the surrounding magnetic field. In this paper, the varying error is compensated using the MRHKF filter. Finally, the performance enhanced seamless positioning is achieved, and the performance is verified by experiment.
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Xu, Tian Lai. "Seamless INS/GPS Integration Based on Support Vector Machines." Applied Mechanics and Materials 336-338 (July 2013): 277–80. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.277.
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The combination of Inertial Navigation System (INS) and Global Positioning System (GPS) provides superior performance in comparison with either a stand-alone INS or GPS. However, the positioning accuracy of INS/GPS deteriorates with time in the absence of GPS signals. A least squares support vector machines (LS-SVM) regression algorithm is applied to INS/GPS integrated navigation system to bridge the GPS outages to achieve seamless navigation. In this method, LS-SVM is trained to model the errors of INS when GPS is available. Once the LS-SVM is properly trained in the training phase, its prediction can be used to correct the INS errors during GPS outages. Simulations in INS/GPS integrated navigation showed improvements in positioning accuracy when GPS outages occur.
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Wang, Changqiang, Aigong Xu, Xin Sui, Yushi Hao, Zhengxu Shi, and Zhijian Chen. "A Seamless Navigation System and Applications for Autonomous Vehicles Using a Tightly Coupled GNSS/UWB/INS/Map Integration Scheme." Remote Sensing 14, no. 1 (December 22, 2021): 27. http://dx.doi.org/10.3390/rs14010027.
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Seamless positioning systems for complex environments have been a popular focus of research on positioning safety for autonomous vehicles (AVs). In particular, the seamless high-precision positioning of AVs indoors and outdoors still poses considerable challenges and requires continuous, reliable, and high-precision positioning information to guarantee the safety of driving. To obtain effective positioning information, multiconstellation global navigation satellite system (multi-GNSS) real-time kinematics (RTK) and an inertial navigation system (INS) have been widely integrated into AVs. However, integrated multi-GNSS and INS applications cannot provide effective and seamless positioning results for AVs in indoor and outdoor environments due to limited satellite availability, multipath effects, frequent signal blockages, and the lack of GNSS signals indoors. In this contribution, multi-GNSS-tightly coupled (TC) RTK/INS technology is developed to solve the positioning problem for a challenging urban outdoor environment. In addition, ultrawideband (UWB)/INS technology is developed to provide accurate and continuous positioning results in indoor environments, and INS and map information are used to identify and eliminate UWB non-line-of-sight (NLOS) errors. Finally, an improved adaptive robust extended Kalman filter (AREKF) algorithm based on a TC integrated single-frequency multi-GNSS-TC RTK/UWB/INS/map system is studied to provide continuous, reliable, high-precision positioning information to AVs in indoor and outdoor environments. Experimental results show that the proposed scheme is capable of seamlessly guaranteeing the positioning accuracy of AVs in complex indoor and outdoor environments involving many measurement outliers and environmental interference effects.
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Jiang, Wei, Yong Li, Chris Rizos, Baigen Cai, and Wei Shangguan. "Seamless Indoor-Outdoor Navigation based on GNSS, INS and Terrestrial Ranging Techniques." Journal of Navigation 70, no. 6 (July 11, 2017): 1183–204. http://dx.doi.org/10.1017/s037346331700042x.
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We describe an integrated navigation system based on Global Navigation Satellite Systems (GNSS), an Inertial Navigation System (INS) and terrestrial ranging technologies that can support accurate and seamless indoor-outdoor positioning. To overcome severe multipath disturbance in indoor environments, Locata technology is used in this navigation system. Such a “Locata-augmented” navigation system can operate in different positioning modes in both indoor and outdoor environments. In environments where GNSS is unavailable, e.g. indoors, the proposed system is designed to operate in the Locata/INS “loosely-integrated” mode. On the other hand, in outdoor environments, all GNSS, Locata and INS measurements are available, and all useful information can be fused via a decentralised Federated Kalman filter. To evaluate the proposed system for seamless indoor-outdoor positioning, an indoor-outdoor test was conducted at a metal-clad warehouse. The test results confirmed that the proposed navigation system can provide continuous and reliable position and attitude solutions, with the positioning accuracy being better than five centimetres.
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Zou, Deyue, Shutong Niu, Shuhao Chen, Binhong Su, Xinyi Cheng, Jie Liu, Yunfeng Liu, and Yang Li. "A smart city used low-latency seamless positioning system based on inverse global navigation satellite system technology." International Journal of Distributed Sensor Networks 15, no. 9 (September 2019): 155014771987381. http://dx.doi.org/10.1177/1550147719873815.
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People have to move between indoor and outdoor frequently in city scenarios. The global navigation satellite system signal cannot provide reliable indoor positioning services. To solve the problem, this article proposes a seamless positioning system based on an inverse global navigation satellite system signal, which can extend the global navigation satellite system service into the indoor scenario. In this method, a signal source is arranged at a key position in the room, and the inverse global navigation satellite system signal is transmitted to the global navigation satellite system receiver to obtain a preset positioning result. The indoor positioning service is continued with the inertial navigation system after leaving the key position. The inverse global navigation satellite system seamless positioning system proposed in this article can unify indoor and outdoor positioning using the same receiver. The receiver does not need to re-receive navigation information when the scene changes, which avoids the switching process. Through the design of signal layer coverage, the receiver is in a warm start state, and the users can quickly fix the position when the scenario changes, realizing quick access in a true sense. This enables the ordinary commercial global navigation satellite system receiver to obtain indoor positioning capability without modification, and the algorithm can perform accurate positioning indoors and outdoors without switching.
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Li, Ningbo, Lianwu Guan, Yanbin Gao, Shitong Du, Menghao Wu, Xingxing Guang, and Xiaodan Cong. "Indoor and Outdoor Low-Cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System." Remote Sensing 12, no. 19 (October 8, 2020): 3271. http://dx.doi.org/10.3390/rs12193271.
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Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.
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Li, Ningbo, Lianwu Guan, Yanbin Gao, Zhejun Liu, Ye Wang, and Hanxiao Rong. "A Low Cost Civil Vehicular Seamless Navigation Technology Based on Enhanced RISS/GPS between the Outdoors and an Underground Garage." Electronics 9, no. 1 (January 8, 2020): 120. http://dx.doi.org/10.3390/electronics9010120.
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Vehicles have to rely on satellite navigation in an open environment. However, satellite navigation cannot obtain accurate positioning information for vehicles in the interior of underground parking lots, as they comprise a semi-enclosed navigation space. Therefore, vehicular navigation needs to take into consideration both outdoor and indoor environments. Actually, outdoor navigation and indoor navigation require different positioning methods, and it is of great importance to choose a reasonable navigation and positioning algorithm solution for vehicles. Fortunately, the integrated navigation of the Global Positioning System (GPS) and the Micro-Electro-Mechanical System (MEMS) inertial navigation system could solve the problem of switching navigation algorithms in the entrance and exit of underground parking lots. This paper proposes a low cost vehicular seamless navigation technology based on the reduced inertial sensor system (RISS)/GPS between the outdoors and an underground garage. Specifically, the enhanced RISS is a positioning algorithm based on three inertial sensors and one odometer, which could achieve a similar location effect as the full model integrated navigation, reduce the costs greatly, and improve the efficiency of each sensor.
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Yue, Peng, Yue Xu, Rui Xue, and Zedong Liang. "A Fusion Localization Algorithm with Adaptive Kalman Gain for Port Container Seamless Positioning." Wireless Communications and Mobile Computing 2022 (September 7, 2022): 1–19. http://dx.doi.org/10.1155/2022/7459408.
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BeiDou Navigation Satellite System (BDS) has provided high-precision, reliable positioning, navigation, and timing services anywhere in the world since the end of 2020. However, the positioning performance of BDS does not behave well like the other global navigation satellite systems (GNSS) in the transition areas indoor and outdoor, particularly in container ports, because the navigation signals are blocked and reflected by containers. In order to solve the above problem, as the pulse radio ultra-wideband (UWB) has the characteristics of high positioning accuracy, high multipath resolution, large bandwidth, and high communication rate, it is used as the Beidou auxiliary system, and the two are combined. In addition, the positioning algorithm greatly affects BDS/UWB integrated positioning performance. The single Newton iterative least square (LS) positioning algorithm does not take into account the continuity of position in time, leading to disordered positioning results and large positioning errors. For obtaining high positioning accuracy, the Kalman filter (KF) is introduced to process the output results of the LS algorithm, and a fusion localization algorithm of the Newton iterative least square and Kalman filter (LS-KF) with adaptive Kalman gain is proposed in this paper. The fusion algorithm can solve effectively the problem that the Kalman gain approaches a stable state after multiple observation epochs, resulting in a constant ratio between the predicted and the measured states. Besides, the algorithm can be used to assess the confidence of each measurement state, determine the Kalman gain adaptive adjustment factor according to the obtained confidence, and further adjust the Kalman gain through the adaptive factor. Theoretical analysis and simulation results show that the proposed algorithm can improve the overall positioning accuracy and anti-interference ability.
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Chen, Weina, Qinghua Zeng, Jianye Liu, and Huizhe Wang. "Seamless autonomous navigation based on the motion constraint of the mobile robot." Industrial Robot: An International Journal 44, no. 2 (March 20, 2017): 178–88. http://dx.doi.org/10.1108/ir-06-2016-0171.
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Purpose The purpose of this paper is to propose a seamless autonomous navigation method based on the motion constraint of the mobile robot, which is able to meet the practical need of maintaining the navigation accuracy during global positioning system (GPS) outages. Design/methodology/approach The seamless method uses the motion constraint of the mobile robot to establish the filter model of the system, in which the virtual observation about the speed is used to overcome the shortage of the navigation accuracy during GPS outages. The corresponding motion constraint model of the mobile robot is established. The proposed seamless navigation scheme includes two parts: the micro inertial navigation system (MINS)/GPS-integrated filter model and the motion constraint filter model. When the satellite signals are good, the system works on the MINS/GPS-integrated mode. If some obstacles block the GPS signals, the motion constraint measurement equation will be effective so as to improve the navigation accuracy of the mobile robot. Findings Three different vehicle tests of the mobile robot show that the seamless navigation method can overcome the shortage of the navigation accuracy during GPS outages, so as to improve the navigation performance in practical applications. Originality/value A seamless navigation system based on the motion constraint of the mobile robot is proposed to overcome the shortage of the navigation accuracy during GPS outages, thus improving the adaptability of the robot navigation.
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Xu, Tian Lai, and Yang Tian. "Research on Seamless INS/GPS Integrated Navigation Algorithm." Advanced Materials Research 299-300 (July 2011): 1178–81. http://dx.doi.org/10.4028/www.scientific.net/amr.299-300.1178.
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This paper proposed and discussed an INS/GPS integrated navigation method based on radial basis function neural network (RBFNN) to fuse INS and GPS data. When GPS signals were available, an adaptive Kalman filter was used to improve the estimation accuracy of INS errors, and then the RBFNN structure was trained to mimic the dynamical error model of INS. If GPS signals were unavailable, the trained RBFNN structure was utilized to bridge the GPS outages to achieve seamless navigation. Simulations in INS/GPS integrated navigation system showed the proposed method can reduce the positioning error during GPS outages.
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Di Pietra, V., N. Grasso, M. Piras, and P. Dabove. "CHARACTERIZATION OF A MOBILE MAPPING SYSTEM FOR SEAMLESS NAVIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 227–34. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-227-2020.
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Abstract. Mobile Mapping Systems (MMS) are multi-sensor technologies based on SLAM procedure, which provides accurate 3D measurement and mapping of the environment as also trajectory estimation for autonomous navigation. The major limits of these algorithms are the navigation and mapping inconsistence over the time and the georeferencing of the products. These issues are particularly relevant for pose estimation regardless the environment like in seamless navigation. This paper is a preliminary analysis on a proposed multi-sensor platform integrated for indoor/outdoor seamless positioning system. In particular the work is devoted to analyze the performances of the MMS in term of positioning accuracy and to evaluate its improvement with the integration of GNSS and UWB technology. The results show that, if the GNSS and UWB signal are not degraded, using the correct weight to their observations in the Stencil estimation algorithm, is possible to obtain an improvement in the accuracy of the MMS navigation solution as also in the global consistency of the final point cloud. This improvement is measured in about 7 cm for planimetric coordinate and 34 cm along the elevation with respect to the use of the Stencil system alone.
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Li, L., Q. Huang, K. Xu, G. Guo, and R. Chen. "VEHICLE POSITIONING IN UNDERGROUND SPACE USING A SMART PHONE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-3/W1-2022 (April 22, 2022): 81–87. http://dx.doi.org/10.5194/isprs-archives-xlvi-3-w1-2022-81-2022.
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Abstract. Smartphones is a good choice for vehicle navigation since many navigation sensors are built-in with low cost advantage. However, it cannot provide reliable positioning information in underground space since GNSS is not available and IMU drift quickly. In this manuscript, a mixed navigation scheme for smartphone consumer is presented. It combines GNSS, INS, Non-Holonomic Constraint (NHC) and Bluetooth Low Energy (BLE) to provide reliable seamless navigation in both outdoors and underground. Some important problems including smartphone boresight misalignment, HNC level arm, GNSS and BLE time lag are discussed in the manuscript. The testing results show 3.1% /D horizontal positioning error in tunnel in INS/NHC positioning mode, and approximately 1 meter accuracy in underground parking garage in INS/NHC/BLE mode.
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Guo, Chunlei, Cuizhi Liu, and Erhu Wei. "Design of three-dimensional visualization indoor navigation system in smart city construction." E3S Web of Conferences 283 (2021): 02025. http://dx.doi.org/10.1051/e3sconf/202128302025.
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In recent years, smart city has attracted more and more attention because of its high intelligence and informatization. In the future, smart community, smart parking lot and smart exhibition hall will enter people's life. In these smart services, indoor navigation and positioning technology is the basic technology. High precision indoor and outdoor seamless positioning technology plays a vital role in people's future life, is the science and technology source power to promote public innovation and entrepreneurship, and is an important part of supporting the national strategic needs. At present, indoor navigation is still facing challenges such as high cost, poor adaptability and poor endurance. In this paper, combined with threedimensional( 3D) visualization technology, indoor navigation is designed and applied. The results show that the indoor navigation system combines indoor positioning and artificial intelligence to achieve multichannel positioning and reduce power consumption, which can be widely used in the construction of smart city and bring convenience to people's life.
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Chiou, Yih Shyh, and Fuan Tsai. "Localization Experiments Based on Inertial Sensors for Navigation Applications." Applied Mechanics and Materials 764-765 (May 2015): 550–54. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.550.
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Robust and accurate positioning systems with seamless outdoor and indoor coverage have been receiving a great deal of attention. In outdoor environments, as radio signals transmitted from base stations or satellites are jammed or shielded, to estimate an accurate location using only the absolute positioning scheme remains a difficult problem regarding location accuracy. In order to overcome the drawback of the ranging scheme based on the radio signals, this paper presents a positioning approach based on inertial-measurement-unit (IMU) observations to estimate the location of a mobile terminal (MT). For the location-estimation technique, the positioning experiment is handled by the dead-reckoning (DR) algorithm. By processing the observations from the IMU, it is possible to estimate the movement of an MT (car). In terms of the IMU-based approach, although the experimental results demonstrate that the positioning scheme using the DR algorithm causes the error propagation, the approach can work in short period of time for navigation applications.
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Nakagawa, M., T. Kamio, H. Yasojima, and T. Kobayashi. "GEOFENCING-BASED LOCALIZATION FOR 3D DATA ACQUISITION NAVIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 319–24. http://dx.doi.org/10.5194/isprs-archives-xli-b4-319-2016.
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Users require navigation for many location-based applications using moving sensors, such as autonomous robot control, mapping route navigation and mobile infrastructure inspection. In indoor environments, indoor positioning systems using GNSSs can provide seamless indoor-outdoor positioning and navigation services. However, instabilities in sensor position data acquisition remain, because the indoor environment is more complex than the outdoor environment. On the other hand, simultaneous localization and mapping processing is better than indoor positioning for measurement accuracy and sensor cost. However, it is not easy to estimate position data from a single viewpoint directly. Based on these technical issues, we focus on geofencing techniques to improve position data acquisition. In this research, we propose a methodology to estimate more stable position or location data using unstable position data based on geofencing in indoor environments. We verify our methodology through experiments in indoor environments.
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Nakagawa, M., T. Kamio, H. Yasojima, and T. Kobayashi. "GEOFENCING-BASED LOCALIZATION FOR 3D DATA ACQUISITION NAVIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 319–24. http://dx.doi.org/10.5194/isprsarchives-xli-b4-319-2016.
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Users require navigation for many location-based applications using moving sensors, such as autonomous robot control, mapping route navigation and mobile infrastructure inspection. In indoor environments, indoor positioning systems using GNSSs can provide seamless indoor-outdoor positioning and navigation services. However, instabilities in sensor position data acquisition remain, because the indoor environment is more complex than the outdoor environment. On the other hand, simultaneous localization and mapping processing is better than indoor positioning for measurement accuracy and sensor cost. However, it is not easy to estimate position data from a single viewpoint directly. Based on these technical issues, we focus on geofencing techniques to improve position data acquisition. In this research, we propose a methodology to estimate more stable position or location data using unstable position data based on geofencing in indoor environments. We verify our methodology through experiments in indoor environments.
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Machaj, Juraj, Peter Brida, and Michal Mlynka. "Impact of Used Communication Technology on the Navigation System for Hybrid Environment." Journal of Computer Networks and Communications 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/731015.
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This paper deals with navigation of mobile device in outdoor and indoor environment by only navigation system or application. In the paper, the navigation system is proposed in the light of seamless navigation service. Main parts of the system from positioning point of view are based on GPS and WifiLOC system. WifiLOC is an indoor positioning system based on Wi-Fi technology. The proposal of the system will be described in detail. The system is implemented at the University of Zilina as a pilot, noncommercial project; therefore it is called University Mobile Navigation System (UMNS). The navigation system can be characterized as real-time system, that is, the system operations cannot be significantly delayed. Since delay of the system depends significantly on communication platform used for map information downloading or communication with the localization server. We decided to investigate an impact of the used communication platform on the time needs for some of the functions implemented in navigation system. Measurements were performed in the real-world application. Next experiment is focused on testing of the accuracy of used indoor positioning system. Outdoor positioning accuracy is not tested because GPS is utilized in outdoor, and this system was already exhaustively investigated.
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Wang, Dongsheng, Yongjie Lu, Lei Zhang, and Guoping Jiang. "Intelligent Positioning for a Commercial Mobile Platform in Seamless Indoor/Outdoor Scenes based on Multi-sensor Fusion." Sensors 19, no. 7 (April 9, 2019): 1696. http://dx.doi.org/10.3390/s19071696.
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Many traffic occasions such as tunnels, subway stations and underground parking require accurate and continuous positioning. Navigation and timing services offered by the Global Navigation Satellite System (GNSS) is the most popular outdoor positioning method, but its signals are vulnerable to interference, leading to a degraded performance or even unavailability. The combination of magnetometer and Inertial Measurement Unit (IMU) is one of the commonly used indoor positioning methods. Within the proposed mobile platform for positioning in seamless indoor and outdoor scenes, the data of magnetometer and IMU are used to update the positioning when the GNSS signals are weak. Because the magnetometer is susceptible to environmental interference, an intelligent method for calculating heading angle by magnetometer is proposed, which can dynamically calculate and correct the heading angle of the mobile platform in a working environment. The results show that the proposed method of calculating heading angle by magnetometer achieved better performance with interference existence. Compared with the uncorrected heading angle, the corrected accuracy results could be improved by 60%, and the effect was more obvious when the interference was stronger. The error of overall positioning trajectory and true trajectory was within 2 m.
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Lee, Jong Ki, Dorota A. Grejner-Brzezinska, and Charles Toth. "Network-based Collaborative Navigation in GPS-Denied Environment." Journal of Navigation 65, no. 3 (March 23, 2012): 445–57. http://dx.doi.org/10.1017/s0373463312000069.
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Global Positioning System (GPS) has been used as a primary source of navigation in land and airborne applications. However, challenging environments cause GPS signal blockage or degradation, and prevent reliable and seamless positioning and navigation using GPS only. Therefore, multi-sensor based navigation systems have been developed to overcome the limitations of GPS by adding some forms of augmentation. The next step towards assured robust navigation is to combine information from multiple ground-users, to further improve the chance of obtaining reliable navigation and positioning information. Collaborative (or cooperative) navigation can improve the individual navigation solution in terms of both accuracy and coverage, and may reduce the system's design cost, as equipping all users with high performance multi-sensor positioning systems is not cost effective. Generally, ‘Collaborative Navigation’ uses inter-nodal range measurements between platforms (users) to strengthen the navigation solution. In the collaborative navigation approach, the inter-nodal distance vectors from the known or more accurate positions to the unknown locations can be established. Therefore, the collaborative navigation technique has the advantage in that errors at the user's position can be compensated by other known (or more accurate) positions of other platforms, and may result in the improvement of the navigation solutions for the entire group of users. In this paper, three statistical network-based collaborative navigation algorithms, the Restricted Least-Squares Solution (RLESS), the Stochastic Constrained Least-Squares Solution (SCLESS) and the Best Linear Minimum Partial Bias Estimation (BLIMPBE) are proposed and compared to the Kalman filter. The proposed statistical collaborative navigation algorithms for network solution show better performance than the Kalman filter.
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Di Pietra, Vincenzo, Paolo Dabove, and Marco Piras. "Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation." Sensors 20, no. 21 (November 5, 2020): 6292. http://dx.doi.org/10.3390/s20216292.
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The growth of location-based services (LBS) has increased rapidly in last years, mainly due to the possibility to exploit low-cost sensors installed in portable devices, such as smartphones and tablets. This work aims to show a low-cost multi-sensor platform developed by the authors in which an ultra-wideband (UWB) indoor positioning system is added to a classical global navigation satellite systems–inertial navigation system (GNSS-INS) integration, in order to acquire different synchronized data for further data fusion analysis in order to exploit seamless positioning. The data fusion is based on an extended Kalman filter (EKF) and on a geo-fencing approach which allows the navigation solution to be provided continuously. In particular, the proposed algorithm aims to solve a navigation task of a pedestrian user moving from an outdoor space to an indoor environment. The methodology and the system setup is presented with more details in the paper. The data acquired and the real-time positioning estimation are analysed in depth and compared with ground truth measurements. Particular attention is given to the UWB positioning system and its behaviour with respect to the environment. The proposed data fusion algorithm provides an overall horizontal and 3D accuracy of 35 cm and 45 cm, respectively, obtained considering 5 different measurement campaigns.
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Xu, Yuan, Xi Yuan Chen, Qing Hua Li, and Hao Qian Huang. "A New Method of Seamless Navigation for the INS/WSN-Integrated System." Applied Mechanics and Materials 556-562 (May 2014): 3272–76. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3272.
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This work presents a new method using Kalman filter (KF) and Least Squares Support Vector Machine (LS-SVM) for the inertial navigation systems (INS)/wireless sensors network (WSN) integrated navigation. In this mode, when the ultrasonic-based WSN is working well, LS-SVM is trained for the mapping between the position measured by INS and the corresponding error. Once the ultrasonic-based WSN is outage, the LS-SVM is used to predict the error of position, which is the unavailable measurement vector of the integrated filter when the ultrasonic-based WSN is outage. Thus, the filter in this mode is able to work where there is no data from the ultrasonic devices. The results show that the proposed method is able to provide continuous navigation information when the data of indoor positioning system is outage, and it is effective to reduce the probability of the estimating outliers.
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Li, Xun, Jinling Wang, and Tao Li. "Seamless Positioning and Navigation by Using Geo-Referenced Images and Multi-Sensor Data." Sensors 13, no. 7 (July 12, 2013): 9047–69. http://dx.doi.org/10.3390/s130709047.
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Gao, Zhouzheng, Lin Chen, Yu Min, Jie Lv, and You Li. "Evaluation on Nonholonomic Constraints and Rauch–Tung–Striebel Filter-Enhanced UWB/INS Integration." Mathematical Problems in Engineering 2020 (October 13, 2020): 1–14. http://dx.doi.org/10.1155/2020/7274181.
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Precise and seamless positioning is becoming a basic requirement for the Internet of Things (IoT). However, there is a gap for precise positioning in Global Navigation Satellite System- (GNSS-) denied indoor areas. Thus, a multisensor integration system based on ultrawide-band (UWB), inertial navigation system (INS), nonholonomic constraints (NHCs), and Rauch–Tung–Striebel (RTS) smoother is proposed. In this system, the UWB performs as the major precise positioning system, while the INS bridges the UWB-degraded and UWB-denied periods. Meanwhile, the NHC restrains the drifts of INS, while the RTS smoother further upgrades the navigation accuracy. The contributions of this article are as follows. First, it presents the robust least square- (RLS-) based UWB positioning. The proposed method is effective in mitigating the impact of the effect of non-line-of-sight (NLOS), which is one of the most significant error sources for UWB positioning. Second, it derives the mathematical model of the UWB/INS/NHC/RTS integration, which is new compared to the existing approaches. Results illustrate that the proposed system can provide centimeter-level positioning accuracy, millimeter-level velocimetry accuracy, and accuracy of better than 0.05 and 0.15 degrees for horizontal and vertical attitude angles, respectively. Even in the scenario with short-term UWB outages (30 s), simulation results show that the three-dimensional position still can be better than 20 cm. Such accuracy values reach the state-of-the-art for indoor positioning using UWB and INS.
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Zhu, Zhuangsheng, and Shibo Wang. "A Novel Step Length Estimator Based on Foot-Mounted MEMS Sensors." Sensors 18, no. 12 (December 15, 2018): 4447. http://dx.doi.org/10.3390/s18124447.
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Pedestrian Dead Reckoning (PDR)-based pedestrian navigation technology is an important part of indoor and outdoor seamless positioning services. To improve the performance of PDR, we have conducted research on a step length estimator. Firstly, based on the basic theory of inertial navigation, we analyze in detail the errors in traditional Strapdown Inertial Navigation Systems (SINSs) caused by the unique motion state of pedestrians. Then, according to the fact that the inertial data from the foot can directly reflect the gait characteristics, we conduct a step length estimator that does not rely on SINS. The experimental results show that accuracy of the proposed method is between 0.6% and 1.4% with a standard deviation of 0.25%.
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Zhang, Chengwei, Na Zhang, and Bingqian Chen. "Research and Application on Cooperative Positioning Technology in Substation Project based on BDS and UWB." Journal of Physics: Conference Series 2260, no. 1 (April 1, 2022): 012008. http://dx.doi.org/10.1088/1742-6596/2260/1/012008.
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Abstract This article mainly discovers and studies a cooperative positioning technology which combines Beidou Navigation Satellite System (BDS) and Ultra Wide Band (UWB) technology. BDS is mainly used for precise positioning in outdoor environments, and UWB technology can be widely used for positioning in both indoor and outdoor environments. This article firstly proposes a combined positioning technology based on BDS and UWB positioning technology, and proposes appropriate technical schemes and solutions for outdoor, indoor and indoor-outdoor transition areas. After considering the actual situation of the substation project, a coordinate conversion method that can be applied in the actual engeerning project is proposed to realize the unification of different coordinate systems and meet the needs of seamless positioning of indoor and outdoor panoramic views of the substation project. Finally, the field test results proves the effectiveness of proposed method.
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Zhu, Feng, Xianlu Tao, Wanke Liu, Xiang Shi, Fuhong Wang, and Xiaohong Zhang. "Walker: Continuous and Precise Navigation by Fusing GNSS and MEMS in Smartphone Chipsets for Pedestrians." Remote Sensing 11, no. 2 (January 12, 2019): 139. http://dx.doi.org/10.3390/rs11020139.
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The continual miniaturization of mass-market sensors built in mobile intelligent terminals has inspired the development of accurate and continuous navigation solution for portable devices. With the release of Global Navigation Satellite System (GNSS) observations from the Android Nougat system, smartphones can provide pseudorange, Doppler, and carrier phase observations of GNSS. However, it is still a challenge to achieve the seamless positioning of consumer applications, especially in environments where GNSS signals suffer from a low signal-to-noise ratio and severe multipath. This paper introduces a dedicated android smartphone application called Walker that integrates the GNSS navigation solution and MEMS (micro-electromechanical systems) sensors to enable continuous and precise pedestrian navigation. Firstly, we introduce the generation of GNSS and MEMS observations, in addition to the architecture of Walker application. Then the core algorithm in Walker is given, including the time-differenced carrier phase improved GNSS single-point positioning and the integration of GNSS and Pedestrian Dead Reckoning (PDR). Finally, the Walker application is tested and the observations of GNSS and MEMS are assessed. The static experiment shows that, with GNSS observations, the RMS (root mean square) values of east, north, and up positioning error are 0.49 m, 0.37 m, and 1.01 m, respectively. Furthermore, the kinematic experiment verifies that the proposed method is capable of obtaining accuracy within 1–3 m for smooth and continuous navigation.
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Deng, Yuejin, Haojun Ai, Zeyu Deng, Wenxiu Gao, and Jianga Shang. "An Overview of Indoor Positioning and Mapping Technology Standards." Standards 2, no. 2 (May 6, 2022): 157–83. http://dx.doi.org/10.3390/standards2020012.
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Technologies and systems for indoor positioning, mapping, and navigation (IPMN) have rapidly developed over the latest decade due to advanced radio and light communications, the internet of things, intelligent and smart devices, big data, and so forth. Thus, a group of surveys for IPMN technologies, systems, standards, and solutions can be found in literature. However, currently there is no proposed solution that can satisfy all indoor application requirements; one of the biggest challenges is lack of standardization, even though several IPMN standards have been published by different standard developing organizations (SDOs). Therefore, this paper aims to re-survey indoor positioning and mapping technologies, in particular, the existing standards related to these technologies and to present guidance in the field. As part of our work, we provide an IPMN standards system architecture consisting of concepts, terms, models, indoor positioning technologies, software and tools, applications, services and policies, and indoor mapping and modelling; and, we present IPMN standards developed for our projects in practice, such as multi-source fusion positioning data interfaces; seamless cooperative positioning service interfaces; content model for indoor mapping and navigation, and specification for digital indoor map products.
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Zhang, Junjie, Kourosh Khoshelham, and Amir Khodabandeh. "Seamless Vehicle Positioning by Lidar-GNSS Integration: Standalone and Multi-Epoch Scenarios." Remote Sensing 13, no. 22 (November 10, 2021): 4525. http://dx.doi.org/10.3390/rs13224525.
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Accurate and seamless vehicle positioning is fundamental for autonomous driving tasks in urban environments, requiring the provision of high-end measuring devices. Light Detection and Ranging (lidar) sensors, together with Global Navigation Satellite Systems (GNSS) receivers, are therefore commonly found onboard modern vehicles. In this paper, we propose an integration of lidar and GNSS code measurements at the observation level via a mixed measurement model. An Extended Kalman-Filter (EKF) is implemented to capture the dynamic of the vehicle movement, and thus, to incorporate the vehicle velocity parameters into the measurement model. The lidar positioning component is realized using point cloud registration through a deep neural network, which is aided by a high definition (HD) map comprising accurately georeferenced scans of the road environments. Experiments conducted in a densely built-up environment show that, by exploiting the abundant measurements of GNSS and high accuracy of lidar, the proposed vehicle positioning approach can maintain centimeter-to meter-level accuracy for the entirety of the driving duration in urban canyons.
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NAMIE, Hiromune, and Hisashi MORISHITA. "Indoor/Outdoor Seamless Positioning Using Lighting Tags and GPS Cellular Phones for Personal Navigation." Journal of the Institute of Positioning, Navigation and Timing of Japan 2, no. 1 (2011): 7–12. http://dx.doi.org/10.5266/ipntj.2.7.
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Han, Wang, Liu, Zhang, Yang, and Li. "An Emergency Seamless Positioning Technique Based on ad hoc UWB Networking Using Robust EKF." Sensors 19, no. 14 (July 16, 2019): 3135. http://dx.doi.org/10.3390/s19143135.
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In this paper, a new emergency positioning technique is proposed based on ad hoc GNSS/UWB (Global Navigation Satellite System/Ultra-Wideband) network. The main innovations of the program are reflected in two aspects. First of all, a unified coordinate frame for indoor and outdoor environments is constructed dynamically with GNSS/UWB integration. In the outdoor environments, the high accuracy positioning can be achieved with GNSS/UWB equipment. The high-accuracy indoor coordinate is obtained by measuring the range observations between adjacent network nodes and outdoor GNSS/UWB nodes, and the range information of the UWB network is transmitted to the cloud server center. A network adjustment algorithm is proposed to improve the positioning accuracy of the UWB network. Secondly, a UWB indoor location algorithm based on robust EKF (Extended Kalman Filter) is proposed. By analyzing the transfer characteristics of gross error in EKF model, a new robust EKF model is established. The model is constructed based on the statistical characteristics of redundant observation components and prediction residual. The robust equivalent gain matrix is constructed, and the robust positioning solution of UWB is obtained with iteration. The global test is carried out first to further improve the real-time operation efficiency. Finally, a field indoor and outdoor seamless positioning experiment was carried out to verify the effectiveness of the proposed algorithm. The results show that the positioning accuracy of UWB emergency network nodes (anchors) can reach 0.35 m. Based on the network, the positioning accuracy of the tag can reach 0.38 m by applying the improved robust EKF positioning algorithm, which is improved by 20.83% and 73.43% compared with standard EKF and least square method, respectively.
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Islam, Saiful, Mohammad Zahidul H. Bhuiyan, Sarang Thombre, and Sanna Kaasalainen. "Combating Single-Frequency Jamming through a Multi-Frequency, Multi-Constellation Software Receiver: A Case Study for Maritime Navigation in the Gulf of Finland." Sensors 22, no. 6 (March 16, 2022): 2294. http://dx.doi.org/10.3390/s22062294.
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Today, a substantial portion of global trade is carried by sea. Consequently, the reliance on Global Navigation Satellite System (GNSS)-based navigation in the oceans and inland waterways has been rapidly growing. GNSS is vulnerable to various radio frequency interference. The objective of this research is to propose a resilient Multi-Frequency, Multi-Constellation (MFMC) receiver in the context of maritime navigation to identify any GNSS signal jamming incident and switch to a jamming-free signal immediately. With that goal in mind, the authors implemented a jamming event detector that can identify the start, end, and total duration of the detected jamming event on any of the impacted GNSS signal(s). By utilizing a jamming event detector, the proposed resilient MFMC receiver indeed provides a seamless positioning solution in the event of single-frequency jamming on either the lower or upper L-band. In addition, this manuscript also contains positioning performance analysis of GPS-L5-only, Galileo-E5a-only, and Galileo-E5b-only signals and their multi-GNSS combinations in a maritime operational environment in the Gulf of Finland. The positioning performance of lower L-band GNSS signals in a maritime environment has not been thoroughly investigated as per the authors’ knowledge.
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Zhang, Fei Zhou, Jia Zhou Geng, and Peng Cheng. "Study on Specialized Emergency Navigation Terminal for Disaster Relief." Key Engineering Materials 467-469 (February 2011): 1991–96. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.1991.
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Aimed at the great demand dealing with our natural disaster, it is important to carry on integrated technologies like satellite navigation and positioning monitoring, embedded geographic information system and sensing technology etc. Also, to accomplish the seamless connection with nation’s disaster assessment system in various environments when the communication links are clear and accurate, to realize the disaster information obtained quickly and shared rapidly together with the reliable orientation navigation provided by the disaster terminal users and quick inquiry and effective adjustments for relief workers or relief supplies. Above integrated technologies have set a technological foundation for national disaster relief command system, which is of great importance when considering enhancing the ability for national emergency relief.
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Retscher, Guenther, Jonathan Kleine, and Lisa Whitemore. "Trilateration approaches for seamless out-/indoor GNSS and Wi-Fi smartphone positioning." Journal of Applied Geodesy 13, no. 1 (January 28, 2019): 47–61. http://dx.doi.org/10.1515/jag-2018-0022.
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Abstract More and more sensors and receivers are found nowadays in smartphones which can enable and improve positioning for Location-based Services and other navigation applications. Apart from inertial sensors, such as accelerometers, gyroscope and magnetometer, receivers for Wireless Fidelity (Wi-Fi) and GNSS signals can be employed for positioning of a mobile user. In this study, three trilateration methods for Wi-Fi positioning are investigated whereby the influence of the derivation of the relationship between the received signal strength (RSS) and the range to an Access Points (AP) are analyzed. The first approach is a straightforward resection for point determination and the second is based on the calculation of the center of gravity in a triangle of APs while weighting the received RSS. In the third method a differential approach is employed where as in Differential GNSS (DGNSS) corrections are derived and applied to the raw RSS measurements. In this Differential Wi-Fi (DWi-Fi) method, reference stations realized by low-cost Raspberry Pi units are used to model temporal RSS variations. In the experiments in this study two different indoor environments are used, one in a laboratory and the second in the entrance of an office building. The results of the second and third approach show position deviations from the ground truth of around 2 m in dependence of the geometrical point location. Furthermore, the transition between GNSS positioning outdoors and Wi-Fi localization indoors in the entrance area of the building is studied.
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Schischmanow, Adrian, Dennis Dahlke, Dirk Baumbach, Ines Ernst, and Magdalena Linkiewicz. "Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection." Sensors 22, no. 13 (June 23, 2022): 4745. http://dx.doi.org/10.3390/s22134745.
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We present a workflow for seamless real-time navigation and 3D thermal mapping in combined indoor and outdoor environments in a global reference frame. The automated workflow and partly real-time capabilities are of special interest for inspection tasks and also for other time-critical applications. We use a hand-held integrated positioning system (IPS), which is a real-time capable visual-aided inertial navigation technology, and augment it with an additional passive thermal infrared camera and global referencing capabilities. The global reference is realized through surveyed optical markers (AprilTags). Due to the sensor data’s fusion of the stereo camera and the thermal images, the resulting georeferenced 3D point cloud is enriched with thermal intensity values. A challenging calibration approach is used to geometrically calibrate and pixel-co-register the trifocal camera system. By fusing the terrestrial dataset with additional geographic information from an unmanned aerial vehicle, we gain a complete building hull point cloud and automatically reconstruct a semantic 3D model. A single-family house with surroundings in the village of Morschenich near the city of Jülich (German federal state North Rhine-Westphalia) was used as a test site to demonstrate our workflow. The presented work is a step towards automated building information modeling.
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Jung, Tae-Won, Chi-Seo Jeong, Soon-Chul Kwon, and Kye-Dong Jung. "Point-Graph Neural Network Based Novel Visual Positioning System for Indoor Navigation." Applied Sciences 11, no. 19 (October 2, 2021): 9187. http://dx.doi.org/10.3390/app11199187.
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Indoor localization is a basic element in location-based services (LBSs), including seamless indoor and outdoor navigation, location-based precision marketing, spatial recognition in robotics, augmented reality, and mixed reality. The popularity of LBSs in the augmented reality and mixed reality fields has increased the demand for a stable and efficient indoor positioning method. However, the problem of indoor visual localization has not been appropriately addressed, owing to the strict trade-off between accuracy and cost. Therefore, we use point cloud and RGB characteristic information for the accurate acquisition of three-dimensional indoor space. The proposed method is a novel visual positioning system (VPS) capable of determining the user’s position by matching the pose information of the object estimated by the improved point-graph neural network (GNN) with the pose information label of a voxel database object addressed in predefined voxel units. We evaluated the performance of the proposed system considering a stationary object in indoor space. The results verify that high positioning accuracy and direction estimation can be efficiently achieved. Thus, spatial information of indoor space estimated using the proposed novel VPS can aid in indoor navigation.
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Yu, Hui, Enrique Aguado, Gary Brodin, John Cooper, David Walsh, and Hal Strangeways. "UWB Positioning Systsem Design: Selection of Modulation and Multiple Access Schemes." Journal of Navigation 61, no. 1 (December 10, 2007): 45–62. http://dx.doi.org/10.1017/s037346330700450x.
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In densely-populated cities or indoor environments, limited visibility to satellites and severe multipath effects significantly affect the accuracy and reliability of satellite-based positioning systems. To meet the needs of “seamless navigation” in these challenging environments an advanced terrestrial positioning system is under development. This system is based upon Ultra-Wideband (UWB) technology, which is a promising candidate for this application due to good time domain resolution and immunity to multipath. This paper presents a detailed analysis of two key aspects of the UWB signal design that will allow it to be used as the basis of such a high performance positioning system: the modulation scheme and the multiple access technique. These two aspects are evaluated in terms of spectral efficiency and synchronisation performance over multipath channels. Thus this paper identifies optimal modulation and multiple access techniques for a long range, high performance terrestrial positioning system using UWB.
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Wang, Shengliang, Xianshu Dong, Genyou Liu, Ming Gao, Gongwei Xiao, Wenhao Zhao, and Dong Lv. "GNSS RTK/UWB/DBA Fusion Positioning Method and Its Performance Evaluation." Remote Sensing 14, no. 23 (November 23, 2022): 5928. http://dx.doi.org/10.3390/rs14235928.
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As a significant space–time infrastructure, the Global Navigation Satellite System (GNSS) provides high-precision positioning, navigation, and timing (PNT) information to users all over the world. However, GNSS real-time kinematic (RTK) mobile receiver signal attenuation is obvious in complex environments such as under trees, urban canyons, and indoors, among others, and it is incapable of meeting the demand of multi-level mass users for indoor and outdoor seamless positioning applications. The goal of this study was to address the limitations and vulnerabilities of the GNSS RTK positioning above-mentioned. First, we propose a GNSS RTK/UWB/DBA fusion positioning model and provide detailed algorithm steps for various types of observations. The performance of the GNSS RTK/UWB/DBA fusion positioning under various occlusion environments is then thoroughly evaluated using static and dynamic cart experiments. The experiment results show that as the elevation mask angle increases, the number of available GNSS satellites decreases and the ambiguity resolution success rate decreases; in comparison to GNSS RTK, the proposed GNSS RTK/UWB/DBA fusion positioning model can significantly improve the spatial geometry distribution of observations, reduce the position dilution of precision (PDOP) value, and improve the ambiguity resolution success rate. At an elevation mask angle of 50 degrees, GNSS RTK/UWB/DBA combination positioning can improve the ambiguity resolution success rate by 20% to 60%, and a positioning error less than 5 cm by 20% to 50%. It also indicates that the GNSS RTK/UWB/DBA fusion positioning model has higher positioning accuracy and can effectively improve the availability and reliability of GNSS RTK in a local harsh environment.
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Xiong, Yufeng, Yu Zhang, Xiaoting Guo, Chenguang Wang, Chong Shen, Jie Li, Jun Tang, and Jun Liu. "Seamless global positioning system/inertial navigation system navigation method based on square-root cubature Kalman filter and random forest regression." Review of Scientific Instruments 90, no. 1 (January 2019): 015101. http://dx.doi.org/10.1063/1.5079889.
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Triyono, Liliek, Prayitno, Mosiur Rahaman, Sukamto, and Amran Yobioktabera. "Smartphone-based Indoor Navigation for Guidance in Finding Location Buildings Using Measured WiFi-RSSI." JOIV : International Journal on Informatics Visualization 6, no. 4 (December 31, 2022): 829. http://dx.doi.org/10.30630/joiv.6.4.1528.
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This study investigates a Wi-Fi-based indoor navigation system to determine building locations. The system was developed using the fingerprint method from the Received Signal Strength Indication (RSSI) of each Access Point (AP). The main components of a smartphone-based system use data from Wi-Fi and the Global Positioning System (GPS). The system developed for navigation is designed and implemented as an element of a dynamic, seamless mobility planning and building location route guidance application. Building map data is collected from Google Map data and enhanced by coloring the geographic location of buildings displayed on mobile devices. Navigational aids collected from sensors provide trip orientation and position updates. The approach of measuring the distance between known positions is compared to those displayed in the application with the haversine formula to measure the accuracy of the position displayed. A series of experiments were conducted in the Politeknik Negeri Semarang area, Indonesia. The experiment results showed that the Wi-Fi-based indoor positioning system was accurate within 7.050 meters of the error for that location, thus proving the system's usefulness for determining the location of buildings in the campus area. The measurement has not adopted the maximum APs placement for signal coverage and strength, only using the existing APs positions. The temperature nor humidity was neither measured in each area where the AP was installed, which is discussed later. This system can help visitors without asking, even though they have only visited once.
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Cheng, Rung-Shiang, Wei-Jun Hong, Jheng-Syun Wang, and Kawuu W. Lin. "Seamless Guidance System Combining GPS, BLE Beacon, and NFC Technologies." Mobile Information Systems 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/5032365.
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Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study proposes a system based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoors and outdoors on smart phones, wishing to give user perfect smart life through this system. The proposed system is implemented on a smart phone and evaluated on a student campus environment. The experimental results confirm the ability of the proposed app to switch automatically from an outdoor mode to an indoor mode and to guide the user to requested target destination via the shortest possible route.
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Namie, Hiromune, Osamu Okamoto, Osamu Suzuki, and Akio Yasuda. "Short Studies on Indoor/Outdoor Seamless Positioning by Using Indoor MEssaging System (IMES) for Pedestrian Navigation." IEEJ Transactions on Industry Applications 138, no. 3 (2018): 180–85. http://dx.doi.org/10.1541/ieejias.138.180.
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Guo, Yu, Jiazhu Zheng, Shaoning Di, Guiqiu Xiang, and Fei Guo. "A Beacons Selection Method under Random Interference for Indoor Positioning." Remote Sensing 14, no. 17 (September 1, 2022): 4323. http://dx.doi.org/10.3390/rs14174323.
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GNSS is still not well applied in indoor environments. This is an important challenge for seamless positioning and navigation. Using other sensors to replace and connect is the mainstream practice at present. No matter what technology is used, the problem of real-time optimal station selection is faced in complex indoor environments. In this paper, we first verified the impact of random interference from walkers on positioning signals in an indoor environment. Based on this phenomenon, we proposed a novel real-time dynamic Beacons selection method (RD) in the field of indoor positioning. First, we introduced a machine learning algorithm for real-time anomaly detection of received signals from different Beacons. Then the Beacon selection is completed based on the real-time anomaly detection results and RSSI. In an indoor scene, we verified the positioning accuracy of three other methods when selecting various numbers of Beacons. Then we used the best selection strategies to compare with the RD method. Experiments showed that the RD method can use the least Beacons to obtain higher accuracy and stable positioning results. This paper provides a new idea for real-time optimal selection of signal sources in a complex indoor environment.
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Tsai, G. J., K. W. Chiang, and N. El-Sheimy. "INS-AIDED 3D LIDAR SEAMLESS MAPPING IN CHALLENGING ENVIRONMENT FOR FUTURE HIGH DEFINITION MAP." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W16 (September 17, 2019): 251–57. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w16-251-2019.
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<p><strong>Abstract.</strong> With advances in computing and sensor technologies, onboard systems can deal with a large amount of data and achieve real-time process continuously and accurately. In order to further enhance the performance of positioning, high definition map (HD map) is one of the game changers for future autonomous driving. Instead of directly using Inertial Navigation System and Global Navigation Satellite System (INS/GNSS) navigation solutions to conduct the Direct Geo-referencing (DG) and acquiring 3D mapping information, Simultaneous Localization and Mapping (SLAM) relies heavily on environmental features to derive the position and attitude as well as conducting the mapping at the same time. In this research, the new structure is proposed to integrate the INS/GNSS into LiDAR Odometry and Mapping (LOAM) algorithm and enhance the mapping performance. The first contribution is using the INS/GNSS to provide the short-term relative position information for the mapping process when the LiDAR odometry process is failed. The checking process is built to detect the divergence of LiDAR odometry process based on the residual from correspondences of features and innovation sequence of INS/GNSS. More importantly, by integrating with INS/GNSS, the whole global map is located in the standard global coordinate system (WGS84) which can be shared and employed easily and seamlessly. In this research, the designed land vehicle platform includes commercial INS/GNSS integrated product as a reference, relatively low-cost and lower grade INS system and Velodyne LiDAR with 16 laser channels, respectively. The field test is conducted from outdoor to the indoor underground parking lot and the final solution using the proposed method has a significant improvement as well as building a more accurate and reliable map for future use.</p>
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Tsai, G. J., Y. L. Chen, K. W. Chiang, and Y. C. Lai. "THE GENERATION OF BUILDING FLOOR PLANS USING PORTABLE AND UNMANNED AERIAL VEHICLE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 331–37. http://dx.doi.org/10.5194/isprs-archives-xli-b4-331-2016.
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Indoor navigation or positioning systems have been widely developed for Location-Based Services (LBS) applications and they come along with a keen demand of indoor floor plans for displaying results even improving the positioning performance. Generally, the floor plans produced by robot mapping focus on perceiving the environment to avoid obstacles and using the feature landmarks to update the robot position in the relative coordinate frame. These maps are not accurate enough to incorporate to the indoor positioning system. This study aims at developing Indoor Mobile Mapping System (Indoor MMS) and concentrates on generating the highly accurate floor plans based on the robot mapping technique using the portable, robot and Unmanned Aerial Vehicles (UAV) platform. The proposed portable mapping system prototype can be used in the chest package and the handheld approach. In order to evaluate and correct the generated floor plans from robot mapping techniques, this study builds the testing and calibration field using the outdoor control survey method implemented in the indoor environments. Based on control points and check points from control survey, this study presents the map rectification method that uses the affine transformation to solve the scale and deformation problems and also transfer the local coordinate system into world standard coordinate system. The preliminary results illustrate that the final version of the building floor plan reach 1 meter absolute positioning accuracy using the proposed mapping systems that combines with the novel map rectification approach proposed. These maps are well geo-referenced with world coordinate system thus it can be applied for future seamless navigation applications including indoor and outdoor scenarios.
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Tsai, G. J., Y. L. Chen, K. W. Chiang, and Y. C. Lai. "THE GENERATION OF BUILDING FLOOR PLANS USING PORTABLE AND UNMANNED AERIAL VEHICLE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 331–37. http://dx.doi.org/10.5194/isprsarchives-xli-b4-331-2016.
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Indoor navigation or positioning systems have been widely developed for Location-Based Services (LBS) applications and they come along with a keen demand of indoor floor plans for displaying results even improving the positioning performance. Generally, the floor plans produced by robot mapping focus on perceiving the environment to avoid obstacles and using the feature landmarks to update the robot position in the relative coordinate frame. These maps are not accurate enough to incorporate to the indoor positioning system. This study aims at developing Indoor Mobile Mapping System (Indoor MMS) and concentrates on generating the highly accurate floor plans based on the robot mapping technique using the portable, robot and Unmanned Aerial Vehicles (UAV) platform. The proposed portable mapping system prototype can be used in the chest package and the handheld approach. In order to evaluate and correct the generated floor plans from robot mapping techniques, this study builds the testing and calibration field using the outdoor control survey method implemented in the indoor environments. Based on control points and check points from control survey, this study presents the map rectification method that uses the affine transformation to solve the scale and deformation problems and also transfer the local coordinate system into world standard coordinate system. The preliminary results illustrate that the final version of the building floor plan reach 1 meter absolute positioning accuracy using the proposed mapping systems that combines with the novel map rectification approach proposed. These maps are well geo-referenced with world coordinate system thus it can be applied for future seamless navigation applications including indoor and outdoor scenarios.
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Esmaeili Kelishomi, Aghil, A. H. S. Garmabaki, Mahdi Bahaghighat, and Jianmin Dong. "Mobile User Indoor-Outdoor Detection Through Physical Daily Activities." Sensors 19, no. 3 (January 26, 2019): 511. http://dx.doi.org/10.3390/s19030511.
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An automatic, fast, and accurate switching method between Global Positioning System and indoor positioning systems is crucial to achieve current user positioning, which is essential information for a variety of services installed on smart devices, e.g., location-based services (LBS), healthcare monitoring components, and seamless indoor/outdoor navigation and localization (SNAL). In this study, we proposed an approach to accurately detect the indoor/outdoor environment according to six different daily activities of users including walk, skip, jog, stay, climbing stairs up and down. We select a number of features for each activity and then apply ensemble learning methods such as Random Forest, and AdaBoost to classify the environment types. Extensive model evaluations and feature analysis indicate that the system can achieve a high detection rate with good adaptation for environment recognition. Empirical evaluation of the proposed method has been verified on the HASC-2016 public dataset, and results show 99% accuracy to detect environment types. The proposed method relies only on the daily life activities data and does not need any external facilities such as the signal cell tower or Wi-Fi access points. This implies the applicability of the proposed method for the upper layer applications.
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Alaoui, F. Taia, David Betaille, and Valerie Renaudin. "Pedestrian Dead Reckoning Navigation with the Help of A⁎-Based Routing Graphs in Large Unconstrained Spaces." Wireless Communications and Mobile Computing 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7951346.
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An A⁎-based routing graph is proposed to assist PDR indoor and outdoor navigation with handheld devices. Measurements are provided by inertial and magnetic sensors together with a GNSS receiver. The novelty of this work lies in providing a realistic motion support that mitigates the absence of obstacles and enables the calibration of the PDR model even in large spaces where GNSS signal is unavailable. This motion support is exploited for both predicting positions and updating them using a particle filter. The navigation network is used to correct for the gyro drift, to adjust the step length model and to assess heading misalignment between the pedestrian’s walking direction and the pointing direction of the handheld device. Several datasets have been tested and results show that the proposed model ensures a seamless transition between outdoor and indoor environments and improves the positioning accuracy. The drift is almost cancelled thanks to heading correction in contrast with a drift of 8% for the nonaided PDR approach. The mean error of filtered positions ranges from 3 to 5 m.
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Iwaszczuk, D., Z. Koppanyi, J. Pfrang, and C. Toth. "EVALUATION OF A MOBILE MULTI-SENSOR SYSTEM FOR SEAMLESS OUTDOOR AND INDOOR MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W2 (September 12, 2019): 31–35. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w2-31-2019.
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<p><strong>Abstract.</strong> Indoor mapping has been gaining importance recently. One of the main applications of indoor maps is personal navigation. For this application, the connection to the outdoor map is very important, as users typically enter the building from outside and navigate to their destination inside. Obtaining this connection, however, is challenging, as the georeferencing of indoor maps is difficult due to the weak or total lack of GPS signal which makes positioning impossible in general. One solution for this problem could be matching indoor and outdoor datasets. Unfortunately, this is difficult due to the very low or non-existing overlap between the indoor and outdoor datasets as well as the differences in different. To overcome this problem, we propose a mobile mapping system, which can seamlessly capture the outdoor and indoor scene. Our prototype system contains three laser scanners, six RGB cameras, two GPS receivers and one IMU. In this paper, we propose an approach to seamlessly map a building and define the requirements for the mapping system. We primarily describe the construction phase of this system. Finally, we evaluate the performance of our mapping system with regard to the defined requirements.</p>
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Bae, Tae-Suk. "Network-based RTK Performance for Drone Navigation." E3S Web of Conferences 94 (2019): 01006. http://dx.doi.org/10.1051/e3sconf/20199401006.
Full textAbstract:
The Real-time Kinematic (RTK) was predominantly used for the positioning of the ground applications including moving vehicles. Due to the limited baseline lengths, the Network-based RTK (NRTK) was introduced since late-1990s, and successfully applied to the high precision surveying purposes for more than a decade. We conducted the experiments to analyze the performance of the single-baseline RTK (SRTK) as well as the NRTK using one of the operational NRTK systems of Korea, which is the Virtual Reference Stations (VRS) technique. A total of 46 Continuously Operating Reference Stations (CORS) are used for both SRTK and NRTK to secure the redundancy of the baseline lengths. Since the CORS are quite evenly located at an average of 50-60 km, the analysis of error behavior is restricted in terms of seamless variation of baseline length. Therefore, on top of the existing CORS, we simulated the GNSS RINEX data of the rover (that is, the drone position) at a specific location to get the uniform distribution to the reference stations. Furthermore, the rover was generated for different altitude to evaluate the performance of vertical component of the NRTK system. The CORS GNSS data were obtained at 1 Hz in RINEX format, and the low-cost receiver (ublox) was used for the rover with same interval, single-frequency capability. The correction information from the NRTK server was simultaneously logged for post-processing using the open source software RTKLIB. The percentage of ambiguity resolution was quite reasonable up to 50 km, and drastically drops down as the baseline gets longer. The generated VRS was located with an offset of a few meters in a certain direction, and the horizontal errors also showed a similar pattern. The vertical error behavior due to the tropospheric model deficiency should also be analyzed further.