Abstract
Integrity is an indispensable requirement for the application of high-precision GNSS/INS integrated navigation related to life safety. Integrated navigation is threatened by multiple risk sources in urban envirenments. The classical Autonomous Integrity Monitoring Extrapolation (AIME) algorithm is based on sliding window with fixed averaging time length. It is difficult for the algorithm to satisfy the response time and sensitivity of integrity monitoring for different types of risk sources An improved AIME algorithm based on the residual chi-square test method (RCTM) and the classical AIME method is proposed in this paper. This method combines RCTM and AIME with non-fixed averaging time to construct test statistics, which is used to adjust detection sensitivity and response time for different types of failures. Compared with the classical AIME algorithm, the proposed method can effectively detect multiple failures, improve the monitoring response time by at least 11%, and reduce the horizontal protection level by about 9.4%.
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Acknowledgement
This research was jointly funded by the National Key Research and Development Program (No. 2021YFB3901300), the National Natural Science Foundation of China (Nos. 61773132, 61633008, 61803115, 62003109), the 145 High-tech Ship Innovation Project sponsored by the Chinese Ministry of Industry and Information Technology, the Heilongjiang Province Research Science Fund for Excellent Young Scholars (No. YQ2020F009), and the Fundamental Research Funds for Central Universities (Nos. 3072019CF0401, 3072020CFT0403).
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Ye, Q., Gu, Y., Li, L., Du, F., Li, R. (2024). Integrity Monitoring for GNSS/INS Integrated Navigation Based on Improved AIME. In: Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC 2024) Proceedings. CSNC 2024. Lecture Notes in Electrical Engineering, vol 1094. Springer, Singapore. https://doi.org/10.1007/978-981-99-6944-9_46
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DOI: https://doi.org/10.1007/978-981-99-6944-9_46
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