An enhanced MEMS-INS/GNSS integrated system with fault detection and exclusion capability for land vehicle navigation in urban areas |
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| Authors: | Ling Yang Yong Li Youlong Wu Chris Rizos |
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| Institution: | 1. Surveying and Geospatial Engineering, School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, Australia
2. School of Mechanical Engineering, Nanjing University of Science and Technology, 210094, Nanjing, China
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| Abstract: | We describe an enhanced quality control algorithm for the MEMS-INS/GNSS integrated navigation system. It aims to maintain the system’s reliability and availability during global navigation satellite system (GNSS) partial and complete data loss and disturbance, and hence to improve the system’s performance in urban environments with signal obstructions, tunnels, bridges, and signal reflections. To reduce the inertial navigation system (INS) error during GNSS outages, the stochastic model of the integration Kalman filter (KF) is informed by Allan variance analysis and the application of a non-holonomic constraint. A KF with a fault detection and exclusion capability is applied in the loosely and tightly coupled integration modes to reduce the adverse influence of abnormal GNSS data. In order to evaluate the performance of the proposed navigation system, road tests have been conducted in an urban area and the system’s reliability and integrity is discussed. The results demonstrate the effectiveness of different algorithms for reducing the growth of INS error. |
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