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Signal Processing
Volume 80, Issue 2, February 2000, Pages 365-371
 
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doi:10.1016/S0165-1684(99)00135-8    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2000 Elsevier Science B.V. All rights reserved.

Performance analysis of two structured covariance matrix estimators in compound-Gaussian clutter

Fulvio GiniCorresponding Author Contact Information, E-mail The Corresponding Author

Department of Information Engineering, University of Pisa, via Diotisalvi, 2 – 56126 Pisa, Italy

Received 12 March 1999;
revised 1 July 1999.
Available online 24 January 2000.

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Abstract

In this work we present a thorough performance analysis of two algorithms for estimating Toeplitz covariance matrices, the structured sample covariance matrix estimator (SCME) and the structured normalised SCME (NSCME), which are employed by adaptive radar detectors against Gaussian and compound-Gaussian clutter. Performance predictions are checked with real-life sea clutter data.

Zusammenfassung

In dieser Arbeit wird eine sorgfältige Analyse der Leistungsfähigkeit zweier Schätzalgorithmen für Toeplitz-Kovarianzmatrizen präsentiert: den Schätzer für die aus den strukturierten Abtastwerten gewonnene Kovarianzmatrix (SCME) und den strukturierten normalisierten Schätzer SCME (NSCME), die bei adaptiven Radardetektoren gegen Gaußsche und verbundgaußsche Störungen eingesetzt werden Die vorhergesagten Leistungsfähigkeiten werden mit wirklichen Daten von Seeklutter verglichen.

Résumé

Dans ce travail nous présentons une analyse complète des performances de deux algorithmes pour l'estimation des matrices de covariances de Toeplitz, de l'estimateur de matrices de covariances d'échantillons structurés (EMCS) et de EMCS normalisés structurés, qui sont employés par des détecteurs radars adaptatifs contre des entassements gaussiens et gaussiens composés. Les prédictions de performances sont vérifiées avec des données réelles d'entassements marins.

Author Keywords: Parameter estimation; Coherent non-Gaussian clutter; Performance analysis

Article Outline

1. Introduction
2. Problem statement and estimators description
3. Performance analysis
3.1. Numerical results
4. Concluding remarks
Acknowledgements
References









Signal Processing
Volume 80, Issue 2, February 2000, Pages 365-371
 
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