3D LiDAR Aided GNSS/INS Integration Fault Detection, Localization and Integrity Assessment in Urban Canyons

نویسندگان

چکیده

The performance of Global Navigation Satellite System (GNSS) and Inertial (INS) integrated navigation can be severely degraded in urban canyons due to the non-line-of-sight (NLOS) signals multipath effects. Therefore, achieve a high-precision robust system, real-time fault detection localization algorithms are needed ensure integrity. Currently, residual chi-square test is used for positioning domain, but it has poor sensitivity when faults disappear. Three-dimensional (3D) light ranging (LiDAR) good complex environments. First, LiDAR aided algorithm proposed. A statistic constructed by mean deviation matched targets, dynamic threshold sliding window. Second, solve problem that measurement noise estimated prior modeling with certain error, estimation based on adaptive filter proposed according position deviations targets. Finally, integrity system assessed. error bound innovatively verified real data. We conduct two experiments vehicle going through viaduct floor hole, which, represent mid deep canyons, respectively. experimental results show terms detection, could detected response time disappearance reduced 70.24% canyons. Thus, improved. In localization, compared optimal fading factor (OFFAF) extended Kalman (EKF). most effective, Root Mean Square Error (RMSE) east north 12.98% 35.1% Regarding assessment, overbound errors relative EKF value bounds reduced.

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2022

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs14184641