Data Fusion Approach With MMW Radar and IR Sensor Based on MEKF

This paper develops a technique for fusing data from millimeter wave (MMW) radar and infrared (IR) sensor to track maneuvering target. Modified extended Kalman filter (MEKF) is simple yet very effective in accounting for the measurement nonlinearities. The idea of fusion is to combine MEKF with pseudo sequential filter to obtain optimum state estimates. The maneuvering target is tracked with MMW radar utilizing MEKF, and then the filtering results are fused with data from IR sensor through pseudo sequential filter. In this way, the global state is updated at the fusion centre. Based on the current statistical model, the performance of the fusion filter is evaluated via simulation. The results show that the fusion approach based on MEKF can significantly improve the accuracy of state estimation.