Cognitive Radar Target Tracking Algorithm based on Waveform Selection
Lingzhao Zhang, Min Jiang · 2021
Aiming at the tracking problem of maneuvering target, a waveform library based on LFM signal is established from the perspective of waveform selection of cognitive radar. The maneuvering target was modeled by constant velocity model (CV) and constant acceleration model (CA), and the signal was filtered by interactive multi-model (IMM) based on Kalman filter. From the perspective of information theory, based on maximizing the mutual information between the target predicted state and the measured state, the optimal waveform library was established. The simulation results show that the waveform library can improve the tracking performance of radar, reduce the redundant waveform and reduce the computation.