Clutter Sensing STAP Method for Vehicle-Mounted Rotating Antenna Radar

Space-time adaptive processing (STAP) methods can effectively suppress clutter signals in vehicle-mounted rotating antenna radars, but their performance significantly degrades under heterogeneous clutter environments. To address this issue, this paper proposes a clutter sensing STAP method for vehicle-mounted rotating antenna radars. The proposed method first constructs a mathematical model between the echo signals of the vehicle-mounted rotating antenna radar and the radar cross-section (RCS) of clutter patches. Then, it uses space-time beam scanning to estimate the RCS of clutter patches in different azimuths, which serves as prior information to construct the prior clutter-noise covariance matrix (CNCM) of the cell under test. Finally, the colored loading method is used to fuse the prior CNCM and the sample covariance matrix to assist STAP in achieving clutter suppression. Simulation results show that dynamically acquired prior clutter information can effectively enhance the clutter suppression performance of STAP under heterogeneous clutter environments.