Clutter Mitigation in Airborne Radar Using Deterministic Subspace Clutter and Direct Data Domain

Space-time adaptive processing is a useful technique for clutter mitigation in airborne radars. space-time adaptive processing algorithms usually require estimation of interference covariance matrix with limited training data and high complexity in processing. To overcome these problems, in this paper, deterministic clutter subspace and the direct data domain method are introduced. Two methods are presented. In the first proposed method, filter coefficients are calculated by estimating airborne radar parameters and also calculation of interference covariance matrix. The sensitivity of estimated parameters is also computed. By extending clutter subspace, the suggested method could get more robust against parameter estimation. In the other proposed method, the direct data domain is employed for calculating the coefficients vector by reducing the size of filters. Finally, the performance of the suggested algorithms is improved by utilizing other methods such as using more taps and deterministic clutter subspace.