Motion model-assisted GNSS/MEMS-IMU integrated navigation system for land vehicle

Sun, Yaowen; Li, Zengke; Yang, Zhehua; Shao, Kefan; Chen, Wangqi

doi:10.1007/s10291-022-01318-z

Cited by 13 publications

(4 citation statements)

References 33 publications

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“…Therefore, a distance filter is applied to remove the aforementioned disturbing measurements. The filtered measurement is L k C. Then, the constant turn rate and velocity (CTRV) model [30] is used to correct the distortion in The global map is managed using an Octree [31] for efficient voxel queries, where the point cloud belonging to a voxel is stored in the corresponding cell. The voxel-related properties, such as the mean and covariance of the local point cloud, the curvature, and the number of the points, are stored in a hash table [32], denoted as H, for fast information extraction.…”

Section: System Overviewmentioning

confidence: 99%

3D Environment Mapping with a Variable Resolution NDT Method

et al. 2022

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With the continuous development of the 3D LiDAR (Light Detection And Ranging) mapping algorithm and its application in various fields, the size of the point cloud map becomes a bottleneck that limits the 3D LiDAR mapping algorithm from running for a long time. In this paper, a 3D LiDAR mapping method based on scan-to-map and variable resolution NDT (normal-distributions transform) registration is proposed. When updating the global map, variable resolution processing can reduce the size of the global map and improve the accuracy of map construction. In addition, the size of the map created by the mapping algorithm is proportional to the size of the space and does not grow infinitely over time. The mapping experiments using a rotating LiDAR in the room, corridor, and outdoor environments show that the algorithm has higher mapping accuracy and smaller map size than without considering the variable resolution strategy. The experimental results of the map construction for a long time in an appropriate test area illustrate that the map built by the algorithm does not grow infinitely with time in the fixed space. In summary, by adjusting the map resolution adaptively according to the curvature of different areas in the 3D LiDAR mapping process, the proposed variable resolution strategy can maintain the size of the global map almost proportional to the size of the space. Moreover, the mapping accuracy can be improved as well.

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Section: System Overviewmentioning

confidence: 99%

3D Environment Mapping with a Variable Resolution NDT Method

et al. 2022

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“…To solve the problem of improper handling of errors in GNSS/IMU fusion, Yang et al [ 19 ] proposed an improved nonholonomic robust adaptive Kalman filter and the results demonstrated the improved accuracy. Similarly, Sun et al [ 20 ] proposed a motion-model-assisted fusion algorithm based on GNSS/MEMS that detected gross errors through a constant yaw rate and velocity model and the chi-square test. Moreover, Jiang et al [ 21 ] realized the GNSS/PDR fusion positioning based on Kalman filter and graph optimization, finding that graph optimization can significantly improve positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

An Effective GNSS/PDR Fusion Positioning Algorithm on Smartphones for Challenging Scenarios

Zhang,

Yu,

et al. 2024

Sensors

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The location-based smartphone service brings new development opportunities for seamless indoor/outdoor positioning. However, in complex scenarios such as cities, tunnels, overpasses, forests, etc., using only GNSS on smartphones cannot provide stable and reliable positioning results. Usually, additional sensors are needed to assist GNSS. This paper investigates the GNSS positioning algorithm assisted by pedestrian dead reckoning (PDR) in complex scenarios. First, we introduce a step detection algorithm based on the peak–valley of acceleration modulus, and the Weinberg model and the Mahony algorithm in PDR are used to estimate step length and heading. On this basis, we evaluated the performance of GNSS/PDR fusion positioning in an open scenario, a semiopen scenario, and a blocked scenario, respectively. Finally, we develop a GNSS/PDR real-time positioning software, called China University of Mining and Technology-POSitioning (CUMT-POS) version 1.0, on the Android 10 platform. By comparing GNSS solutions, PDR solutions, GNSS/PDR solutions, and real-time kinematic (RTK) solutions, we verify the potential auxiliary ability of PDR for GNSS positioning in complex environments, proving that multisource sensor fusion positioning significantly improves reliability and stability. Our research can help the realization of urban informatization and smart cities.

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“…Although SINS/GNSS is the most common navigation mode for land vehicle navigation systems, it has some limitations in complex and harsh urban environments. In these environments, GNSS signals can be blocked by buildings, bridges and trees, or affected by multipath effects in canyons and tunnels [6][7][8][9][10]. As a result, GNSS may not be able to output valid navigation information, and the positioning accuracy of the SINS/GNSS integrated navigation system may not meet the specific requirements of UGV.…”

Section: Introductionmentioning

confidence: 99%

A SINS/GNSS/2D-LDV integrated navigation scheme for unmanned ground vehicles

Xiang,

Zhang,

Wang

et al. 2023

Meas. Sci. Technol.

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In recent years, unmanned autonomous driving technology has attracted increasing attention from people, and become a research hotspot. Currently, the integration of strapdown inertial navigation system (SINS) and global navigation satellite systems (GNSSs) is the most common and effective navigation and positioning scheme for unmanned ground vehicles (UGVs) and unmanned aerial vehicles. However, this integrated system is unable to maintain a reliable positioning solution in challenging environments due to the inherent weakness of GNSS signals and the accumulation of SINS positioning errors over time. To address this issue, this paper proposes an integrated scheme based on an asynchronous Kalman filter for SINS, GNSS and two-dimensional (2D) laser Doppler velocimeter (LDV). In the proposed scheme, the SINS and 2D-LDV are tightly coupled to improve the robustness of the integrated system, and the error parameters between the 2D-LDV and the SINS are calibrated in real time during the validity of the GNSS signal. In addition, the designed asynchronous Kalman filter method evaluates the validity of the GNSS and 2D-LDV measurements in real time based on Mahalanobis distance of innovation vector and statistical property principle. Two groups of long-distance, high-mobility vehicle experiments conducted in challenging environments verify the validity of the proposed scheme. The experimental results show that the proposed SINS/GNSS/2D-LDV integrated navigation scheme has good environmental adaptability and reliability, and can maintain high horizontal and vertical positioning accuracy despite frequent GNSS signal failures, which can meet the needs of UGVs.

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Motion model-assisted GNSS/MEMS-IMU integrated navigation system for land vehicle

Cited by 13 publications

References 33 publications

3D Environment Mapping with a Variable Resolution NDT Method

3D Environment Mapping with a Variable Resolution NDT Method

An Effective GNSS/PDR Fusion Positioning Algorithm on Smartphones for Challenging Scenarios

A SINS/GNSS/2D-LDV integrated navigation scheme for unmanned ground vehicles

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