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Radar Adaptive Detection Architectures for Heterogeneous Environments

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Document pages: 13 pages

Abstract: In this paper, four adaptive radar architectures for target detection inheterogeneous Gaussian environments are devised. The first architecture relieson a cyclic optimization exploiting the Maximum Likelihood Approach in theoriginal data domain, whereas the second detector is a function of transformeddata which are normalized with respect to their energy and with the unknownparameters estimated through an Expectation-Maximization-based alternateprocedure. The remaining two architectures are obtained by suitably combiningthe estimation procedures and the detector structures previously devised.Performance analysis, conducted on both simulated and measured data, highlightsthat the architecture working in the transformed domain guarantees the constantfalse alarm rate property with respect to the interference power variations anda limited detection loss with respect to the other detectors, whose detectionthresholds nevertheless are very sensitive to the interference power.

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