A novel waveform selection method for cognitive radar during target tracking based on the wind driven optimization technique

In recent years, the cognitive radar (CR) with waveform diversity has exhibited significant performance improvements over the traditional fixed waveform radar and has become an area of vigorous research and development. A novel waveform selection strategy based on wind driven optimization (WDO) technique is proposed in this paper. Firstly, the predicted tracking Cramér-Rao Lower Bounds (CRLB) model is built based the Interacting Multiple Model Particle Filter (IMMPF) method. Then the waveform selection model between the waveform parameters and the tracking performance is introduced. Finally, the WDO technique is used to minimize the predicted CRLB for the waveform selection. The tracking accuracy is demonstrated in the Monte Carlo simulations. The results are validated through the comparison with other methods.