Spatial Target Tracking Algorithm Based on Heterogeneous Sensors Data Fusion

The track of Spatial targets is basically non-linear, which makes the cost of using homogeneous sensors for space target tracking significantly increase. Data fusion using heterogeneous sensors can achieve information complementarity, thereby improving recognition ability. In this paper, two heterogeneous data of radar and infrared are fused at the measurement level, and then the data are extended Kalman filter. The simulation example is given. The results show that this is an effective method for heterogeneous data fusion to track space targets.