Maneuvering Targets Radar Detection Based on Minimum Entropy

‍ ‍The changing speed of the maneuvering target causes the time-varying Doppler modulation for the radar echo， that is， the Doppler frequency migration （DFM）. In the process of coherent integration， signals containing DFM will be defocused in the Doppler domain. So， the integration gain will decrease， and the target will be difficult to detect. The current research on compensation for DFM is mostly focused on uniform acceleration targets， which only contains second-order velocity components. However， compensation algorithms containing third-order and higher-order motions need to be further improved. This paper uses the minimum entropy as the cost function and uses the iterative optimization method to propose a general high-order motion compensation algorithm. The algorithm is verified by simulation and measured data， and it is proved that it can efficiently and accurately estimate the high-order motion components of the maneuvering target， thereby effectively compensating for the defocus problem caused by DFM， increasing the integration gain， and completing the coherent integration detection for the maneuvering target.