Clutter Suppression for Sar Image Based on Waveform Design Method

摘要

A computational method for suppressing clutter and generating clear microwave images of targets is proposed in this paper. It is suitable of SAR for special applications. The nonlinear recursive model is introduced into the SAR operation principle, and the cubature Kalman filter (CKF) algorithm is used to estimate target and clutter responses in each azimuth position based on their states before, which are both assumed to be Gaussian distributions. Neyman-Pearson criteria based optimal waveforms are designed repeatedly as the sensor flight along its azimuth path and used as the transmitting signals. A clutter suppression filter is then designed and added to suppress the clutter response while maintaining most of the target response. Thus, with fewer disturbances from the clutter response, we can generate the SAR image with traditional azimuth matched filters. Simulations show that the clutter suppression filter significantly reduces the clutter response, and our algorithm greatly improves the signal-to-clutter plus noise ratio (SCNR) of the SAR image based on different clutter suppression filter parameters. As such, this new algorithm may be preferable for special target imaging when prior information on the target is available.