Multi-mode Composite Track Estimation Method Based on Distributed Measurement Fusion
Keqiang Xia, Xing Meng, Chunyan Du, Na Fu, Jianping Chen, Ganhua Li, Lv Ji-Yuan · 2021
In the multi-mode track fusion algorithm, the commonly used method based on state fusion is relatively small in calculation, but it is not the optimal estimation. The centralized filter fusion method based on measurement is the optimal, but the measurement equation has high dimension, and the calculation is large. In this paper, the extended measurement method is used to unify the dimensionality of distributed measurement data, and a distributed measurement fusion algorithm adapted to track estimation is designed, which can effectively reduce the computation cost, improve the reliability and fault-tolerant ability, and achieve the optimal estimation of state data. The simulation results of active and passive radar composite guidance show that the algorithm is simple in calculation and fast in convergence, and can guarantee the high precision optimal estimation of target trajectory.