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.

Additional Metadata
Keywords Adversary target identification, blind compressive sensing (CS), electronic warfare (EW) receiver, sparse Bayesian learning (SBL), threat waveform recognition
Persistent URL dx.doi.org/10.1109/TAES.2017.2680686
Journal IEEE Transactions on Aerospace and Electronic Systems
Citation
Salari, S. (Soheil), Kim, I.-M. (Il-Min), Chan, F. (Francois), & Rajan, S. (2017). Blind Compressive-Sensing-Based Electronic Warfare Receiver. IEEE Transactions on Aerospace and Electronic Systems, 53(4), 2014–2015. doi:10.1109/TAES.2017.2680686