Blog
About

19
views
0
recommends
+1 Recommend
0 collections
    4
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Sparsity-Aware STAP Algorithms Using \(L_1\)-norm Regularization For Radar Systems

      Preprint

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          This article proposes novel sparsity-aware space-time adaptive processing (SA-STAP) algorithms with \(l_1\)-norm regularization for airborne phased-array radar applications. The proposed SA-STAP algorithms suppose that a number of samples of the full-rank STAP data cube are not meaningful for processing and the optimal full-rank STAP filter weight vector is sparse, or nearly sparse. The core idea of the proposed method is imposing a sparse regularization (\(l_1\)-norm type) to the minimum variance (MV) STAP cost function. Under some reasonable assumptions, we firstly propose a \(l_1\)-based sample matrix inversion (SMI) to compute the optimal filter weight vector. However, it is impractical due to its matrix inversion, which requires a high computational cost when in a large phased-array antenna. Then, we devise lower complexity algorithms based on conjugate gradient (CG) techniques. A computational complexity comparison with the existing algorithms and an analysis of the proposed algorithms are conducted. Simulation results with both simulated and the Mountain Top data demonstrate that fast signal-to-interference-plus-noise-ratio (SINR) convergence and good performance of the proposed algorithms are achieved.

          Related collections

          Most cited references 26

          • Record: found
          • Abstract: not found
          • Article: not found

          Covariance matrix estimation errors and diagonal loading in adaptive arrays

           B.D. Carlson (1988)
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Theory of Adaptive Radar

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              L1-L2 Optimization in Signal and Image Processing

                Bookmark

                Author and article information

                Journal
                1304.3874

                Numerical methods, Information systems & theory

                Comments

                Comment on this article