Maximum likelihood, ESPRIT, and periodogram frequency estimation of radar signals in K-distributed clutter.
type: Item
instance of: scholarly article
title: Maximum likelihood, ESPRIT, and periodogram frequency estimation of radar signals in K-distributed clutter.
zbMATH Open document ID: 1034.94524
DOI: 10.1016/S0165-1684(00)00023-2
author: Monica Montanari
author: Lucio Verrazzani
author: Fulvio Gini
published in: Signal Processing
publication date: 2000-08-21T00:00:00Z
review text: The contribution of this paper is the derivation of the joint maximum likelihood (ML) estimator of complex amplitude and Doppler frequency of a radar target signal embedded in correlated non-Gaussian clutter modelled as a compound-Gaussian process. The estimation accuracy of the ML frequency estimator is investigated and compared with that of the well-known periodogram and ESPRIT estimators under various operational scenarios. The hybrid Cramér-Rao lower bound and a large sample closed-form expression for the mean square estimation error are also derived for the Swerling I target signal. Finally, numerical results obtained by Monte Carlo simulation are checked by means of measured sea clutter data for the general case of fluctuating target amplitude.
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 1493257
zbMATH Keywords: Parameter estimation
zbMATH Keywords: Radar signals
zbMATH Keywords: Non-Gaussian clutter
zbMATH Keywords: Doppler frequency
zbMATH Keywords: Performance analysis
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 1493257