ARIMA assisted low-cost MEMS-INS/GNSS integrated navigation in GNSS denial environment

Ming Li; Hongzhou Chai

doi:10.1117/12.3019426

23 January 2024 ARIMA assisted low-cost MEMS-INS/GNSS integrated navigation in GNSS denial environment

Ming Li, Hongzhou Chai

Proceedings Volume 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023); 1297811 (2024) https://doi.org/10.1117/12.3019426
Event: 2023 4th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2023), 2023, wuhan, China

Abstract

Global Navigation Satellite System (GNSS) and low-cost Inertial Navigation System (INS) is commonly used in fields such as vehicle navigation. However, when the carrier is in a GNSS rejection environment, the navigation accuracy rapidly decreases and cannot meet the positioning accuracy requirements. Therefore, this paper uses the Autoregressive Integrated Moving Average model (ARIMA) to learn the positioning information of GNSS during normal operation, output predictive values in the case of GNSS unavailable, and fuse them with the MEMS-INS mechanical arrangement results through Kalman filtering. Vehicle experiments show that the proposed algorithm significantly improves the navigation performance compared to traditional GNSS/INS integrated navigation, reducing the maximum position error in the east and north directions by 76.4% and 69.2%, respectively, and increasing the root mean square error of position accuracy in the east, north, and up directions by an order of magnitude.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ming Li and Hongzhou Chai "ARIMA assisted low-cost MEMS-INS/GNSS integrated navigation in GNSS denial environment", Proc. SPIE 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023), 1297811 (23 January 2024); https://doi.org/10.1117/12.3019426

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