Blind Compressive-Sensing-Based Electronic Warfare Receiver

Soheil Salari, Il-Min Kim, François Chan, Sreeraman Rajan

Abstract: A new compressive-sensing (CS)-based electronic warfare (EW) receiver is designed to estimate the angle-Doppler of adversary targets whose waveforms are unknown. The proposed EW receiver uses a sparse Bayesian learning (SBL) framework, which is blind in the sense that the knowledge of the sparsity basis is not available. Furthermore, a pruning mechanism is proposed to reduce the computational cost and improve convergence speed of the blind-SBL. The convergence of the proposed method is analytically proved.