Multi-sensor system fusion estimation based on improved Kalman filtering

Weimin Song; Chuanbo Wen

doi:10.1117/12.3009149

27 October 2023 Multi-sensor system fusion estimation based on improved Kalman filtering

Weimin Song, Chuanbo Wen

Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 129220G (2023) https://doi.org/10.1117/12.3009149
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China

Abstract

For the sampling points of sensors at different moments, a sequential asynchronous algorithm to improve multi-sensor fusion is proposed after using the idea of sequential discretization to achieve fusion estimation of position states. It is assumed that the system uses N sensors with different sampling rates for the observed position states. Among them, a multi-rate Kalman filter is designed to estimate the target position at multiple scales with multiple sampling rates. The equation of state between the different sampling points during each sampling moment of the fusion cycle can be obtained as well as the measurement equation at this point in the cycle. Using an optimized linear Kalman filtering algorithm, a sequential fusion process of signals observed by asynchronous sampling is investigated in one cycle to achieve a good estimation of the target position. The effectiveness of the improved algorithm is verified by a numerical example simulation, and the advantages of the algorithm in terms of less computation, good real-time performance and high estimation of fusion accuracy are evident.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Weimin Song and Chuanbo Wen "Multi-sensor system fusion estimation based on improved Kalman filtering", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 129220G (27 October 2023); https://doi.org/10.1117/12.3009149

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