Abstract:

In a multi sensor data fusion system, it is difficult to accurately model sensor bias. Even after registration, there is residual bias in some degree. Residual bias has the same magnitude as random measurement noise, what is different is that the residual bias is slow time varying. Most literature on residual bias are relatively simple, lack of effective analysis and modeling tools. As a result, it is difficult to improve the estimation accuracy by data fusion. A mathematical model of residual bias is presented, and a residual compensation track fusion algorithm is proposed. The proposed method transfers the residual bias to target state vectors, then estimates and compensates the residual bias. Simulation results show that the residual compensation algorithm can effectively deal with residual effects, which greatly improves the accuracy of target state estimation, especially for those maneuver targets. Finally, real radar data simulation is carried out and verifies that the residual compensation algorithm is applied to practical engineering environment.