Abstract
For the target DOA estimation under active deception jamming environment with limited samples, a novel DOA estimation method based on the combination of Adaptive Polarization Filter(APF) and Block Sparse Bayesian Learning(BSBL) algorithm is proposed. First, the interference energy is suppressed using APF. Then, the proposed method constructs a sparse Bayesian model under active deception jamming environment. The target DOA is estimated using the BSBL algorithm based on the neighbor time sampling correlation. Simulated and measured data processing results prove that the proposed method reduces the influence of interference on the BSBL algorithm, and has higher spatial resolution and higher angle measurement accuracy, comparing with the method based on the combination of APF and subspace-based DOA algorithms or maximum likelihood DOA algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
