Abstract
AbstractThis paper proposes a unique compressed sensing based pathway to improve mixed noise cancellation in Passive Bistatic Radar (PBR). Mixed noise is considered as Additive White Gaussian Noise (AWGN) including Impulse Noise (IN). The proposed technique applies a best sparsifying basis that adapts to the structure of the problem and reduces the size of the measurement matrix drastically. According to simulation results, it has been confirmed that the proposed system gives higher state estimation capabilities as compared to the conventional LMS filtering techniques. Without loss of generality, the testing of the performance metric has been done over the FM signals. The paper explains the simulation methodology and the details.KeywordsPassive Bistatic Radar (PBR)Mixed noise cancellationCompressed sensing
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