Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement

Target tracking is one of the key technologies in the military application of wireless sensor networks. This paper aims at the characteristics of wireless sensor network nodes, which have limited computing capacity but can conduct data fusion through wireless communication, to improve tracking accuracy from two aspects. On the one hand, an adaptive bias- compensated pseudo-measurement Kalman filter based on process noise is proposed, on the other hand, an adaptive weighted fusion algorithm based on innovation is proposed. Through multiple simulations, the proposed algorithms can significantly improve the tracking accuracy and robustness of the system on the premise of low computational complexity.

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