Computationally Efficient Adaptive Sidelobe Blanker with Improved Mismatched Signals Rejection

Abstract:

This paper deals with the problem of adaptive signal detection in the presence of Gaussian noise with unknown covariance matrix. An improved adaptive sidelobe blanker (ASB) is proposed, which consists of an adaptive matched filter (AMF) followed by a whitened adaptive beamformer orthogonal rejection test (W-ABORT). A statistical characterization for the proposed two-stage test statistic is provided,under both noise-only and signal-plus-noise hypotheses. The associated probability of false alarm (Pfa) and probability of detection (Pd) are derived in closed form. The performance assessment confirms the effectiveness of the newly-proposed detection algorithms also in comparison to previously-proposed ones.

• Periodical: Applied Mechanics and Materials (Volumes 644-650)
• Pages: 4372-4377
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.644-650.4372
• Online since: September 2014
• Authors: Dai Yuan Zhang, Wen Bo Liu, Zhuo Zhu
• Keywords: Adaptive Detection, Constant False Alarm Rate (CFAR), Mismatched Signals

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