High-resolution clutter-power estimation for range-dependence compensation in conformal-array STAP

We consider space-time adaptive processing (STAP) when the radar returns are recorded by a conformal antenna array (CAA). The statistics of the secondary data snapshots used to estimate the optimum weight vector are not identically distributed with respect to range, thus preventing the STAP processor from achieving its optimum performance. The compensation of the range dependence requires the precise knowledge of the clutter power contained in the secondary data. We propose anew MVDR-based clutter power estimator applied to temporally-smoothed secondary data to obtain an accurate estimate of the expected clutter power This estimate allows one to perform an accurate range-dependence compensation leading to a valid estimate of the clutter covariance matrix. End-to-end performance analysis in terms of signal to inference plus-noise ratio loss shows promizing performance.