Abstract:

The range dependent nature of the clutter power spectrum in non-side looking airborne radar systems results in a mismatch of the clutter covariance matrix computed from the secondary data relative to the true one, and poor performance of traditional spacetime adaptive processing (STAP) algorithms. Registrationbased compensation (RBC) is implemented based on a subsnapshot spectrum using temporal smoothing, the estimation accuracy of the clutter spectrum is limited due to temporal aperture loss. In view of this problem, the technique of iterative adaptive approach (IAA) for estimation of the spatialtemporal spectrum is introduced according to the sparsity, then the covariance matrix for the secondary cell is constructed and brought into registration, namely RBC with IAA (IAARBC). In this case, the clutter spectrum is obtained with higher accuracy because that aperture loss is not exist. Numerical examples shows that, in terms of signal to inference plus noise ratio improvement, better performance is obtained with the developed method compared to the traditional RBC method of using temporal smoothing, even in the presence of other interferers, such as targets.