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arXiv · 1705.04557

CFAR Adaptive Matched Detector for Target Detection in Non-Gaussian Noise With Inverse Gamma Texture

Shiwen Lei·Andreas Jakobsson·Zhiqin Zhao
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Abstract

In this paper, we propose an adaptive matched detector of a signal corrupted by a non-Gaussian noise with an inverse gamma texture. The detector is formed using a set of secondary data measurements, and is analytically shown to have a constant false alarm rate. The analytic performance is validated using Monte Carlo simulations, and the proposed detector is shown to offer preferable performance as compared to the related one-step generalized likelihood ratio test (1S-GLRT) and the adaptive subspace detector (ASD).

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Shiwen Lei, Andreas Jakobsson, Zhiqin Zhao. 2017-05-12. CFAR Adaptive Matched Detector for Target Detection in Non-Gaussian Noise With Inverse Gamma Texture. https://arxiv.org/abs/1705.04557

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