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Performance of Parametric and Covariance Based STAP Tests in Compound-Gaussian Clutter

✍ Scribed by James H. Michels; Muralidhar Rangaswamy; Braham Himed

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 267 KB
Volume: 12
Category: Article
ISSN: 1051-2004
DOI: 10.1006/dspr.2002.0437

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✦ Synopsis

The performance of a parametric space-time adaptive processing method is presented here. Specifically, we consider signal detection in additive disturbance containing compound-Gaussian clutter plus additive Gaussian thermal white noise. Performance is compared to the normalized adaptive matched filter and the Kelly GLRT receiver using simulated and measured data. We focus on the issues of detection and false alarm probabilities, constant false alarm rate, robustness with respect to clutter texture power variations, and reduced training data support.

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✍ James H. Michels; Braham Himed; Muralidhar Rangaswamy 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 196 KB

The performance of a recently proposed model-based space-time adaptive processing detection method is considered here and compared with several candidate algorithms. Specifically, we consider signal detection in additive disturbance consisting of compound-Gaussian clutter plus Gaussian thermal white