Radar maneuvering target tracking algorithm based on human cognition mechanism

Radar Maneuvering Targets Tracking (RMTT) in clutter is a quite challenging issue due to the errors in the models and the varying dynamics of the processes. Modern radar tracking system calls for the adaptive signal and data processing algorithm urgently to adapt the uncertainty of the environment. The mechanism of human cognition can help persons cope with the similar difficulties in visual tracking. Inspired by human cognition mechanism, a comprehensive method for RMTT is proposed. In the method, the model transition probability in Interacting Multiple Model (IMM) and the validation gate can be adjusted dynamically with target maneuver; the waveform in radar transmitter can vary with the perception of the environment. Experimental results in cluttered scenes show that the proposed algorithm is more accurate for perceiving the environment and targets, and the waveform selection algorithm is better than that with fixed waveform.