22 October 1993 Adaptive multiscan matched filter receiver for dim target detection in nonstationary clutter environments
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Abstract
In the signal detection problem in nonstationary cluttered backgrounds using data from an imaging sensor, the receiver structure must generally be adapted to the local clutter statistics. Typically, the receive:r is implemented as a linear matched filter and the local adaptation consists of estimating and inverting a local covariance matrix to obtain the optimum weight vector. The local estimates of the inverse covariance matrix can be obtained in a variety of ways, but is generally a computationally expensive procedure and is prone to inaccuracies whenever estimation windows overlap clutter region boundaries. In the present paper we describe a simple but effective adaptive detection procedure which avoids some of the difficulties associated with existing schemes. This procedure employs a simple least mean-square (LMS) algorithm to adapt a linear matched filter to maximize local SNR. We describe a particular multiscan version of this algorithm with improved convergence properties. In particular, by implementing multiple parallel scanning patterns it's possible to avoid potential convergence problems at region boundaries associated with conventional single-scan adaptive approaches. Finally, we describe the performance of this scheme and compare its performance with competing approaches. We demonstrate performance approaching that achievable when perfect knowledge of local clutter statistics are available.
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James W. Modestino, Kenneth A. Melendez, "Adaptive multiscan matched filter receiver for dim target detection in nonstationary clutter environments", Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); doi: 10.1117/12.157762; https://doi.org/10.1117/12.157762
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