Airborne Radar STAP using Sparse Recovery of Clutter Spectrum

• DOI: 10.48550/arxiv.1008.4185
• Publication Date: 2010-01-01
• Authors: Ke Sun; Hao Zhang; Gang Li; Huadong Meng; Xiqin Wang
• Keywords: FOS: Computer and information sciences; Computer Science - Information Theory; Information Theory (cs.IT); 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Space-time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Statistical-based STAP methods generally need sufficient statistically independent and identically distributed (IID) training data to estimate the clutter characteristics. However, most actual scenarios appear only locally stationary lack IID data. In this paper, by exploiting intrinsic sparsity of distribution angle-Doppler domain, new algorithm called SR-STAP proposed, which uses technique sparse recovery space-time spectrum. Joint with several samples also used improve estimation performance. Finally, covariance matrix (CCM) corresponding filter are designed based on estimated Both Mountaintop simulated experiments have illustrated fast convergence rate approach. Moreover, less dependent prior knowledge, so it more robust mismatch knowledge than knowledge-based methods. Due these advantages, has great potential application scenarios.