Multisensor Unscented Filter Algorithm Based on Data Compression

A novel multisensor multitarget unscented filter algorithm based on data compression,SD-DCUKF,is proposed for the centralized multsisensor multitarget tracking problem of nonlinear system in clutter.In the new algorithm,the measurements from multiple sensors are first combined according to the rule of generalized S-D assignment algorithm and the optimal partition can be achieved.In order to reduce the computation burden,a new coarse association rule is proposed for S-D assignment.Then in the optimal partition,the measurements from the same target are dealt with by use of the method of data compression.Based on these,UKF is used for the propagation of state distribution in nonlinear system and the SD-DCUKF algorithm is derived.According to the simulation results,the accuracy and robustness of proposed algorithm are improved compared with the MSJPDA/EKF algorithm.Furthermore,the method of coarse association proposed makes the computation time decrease by 62 percent.