Multi-radar Data Fusion Method Based on Distributed BLUE

Aiming at the problem of the mixed tracking and fusion problem of linear system and nonlinear observation,a multi-radar data fusion method based on distributed Best Linear Unbiased Estimation(BLUE) filter is provided under the premise that three-dimensional BLUE filter of constant acceleration target motion model is derived.In which,the BLUE target states at cell radar are given in Cartesian coordinates.All the target states estimations are fused at fusion center.The advanced technique is compared with the traditional Nested Conditioning(NC) debiased conversion states fusion method and the Modified Measurement Conditioned(MMC) unbiased conversion states fusion method by taking the position Root-mean-square Error(RMSE),velocity RMSE and Average Normalized Estimation Error Squared(ANEES) as the fusion performance evaluation criterion.Simulation results show that the advanced technique is not sensitive with the variety of the process noise and measurement noise.Its position and velocity RMSE are smaller than the corresponding of NC and MMC based method.It has high fusion accuracy and reliability,even if the errors become larger.