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Home > Our Work > MITRE Research Program > Best Paper Awards >

Detection of Weak Random Signals in IID Non-Gaussian Noise

2000 Award Winner

Kevin R. Kolodziejski, The MITRE Corporation
John W. Betz, The MITRE Corporation

ABSTRACT

This paper considers the detection of weak random signals in circularly symmetric, independent, identically distributed noise. Locally optimum detectors and ad hoc nonlinearities are considered, with asymptotic expressions provided for evaluation of detection performance. The analytical expressions are used to evaluate the robustness of detectors to mismatch in the noise models. Finite-sample Monte Carlo simulation results indicate the reliability of these asymptotic measures in case of practical interest. The results show that, as has been found for detection of weak known signals in non-Gaussian noise, reasonably configured ad hoc nonlinearities are nearly optimum and robust to modest errors in the noise statistics.

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Publication

Published in 2000. IEEE Transactions Communications, Vol. 48, No. 2, pp. 222-230.
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Additional Search Keywords

non-Gaussian noise, nonlinear detection, robustness, signal detection

 

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