DocumentCode :
514246
Title :
A robust adaptive detector for steering phase uncertainties
Author :
De Maio, A. ; De Nicola, S. ; Farina, A. ; Iommelli, S.
Author_Institution :
DIBET, Univ. degli Studi di Napoli Federico II, Naples, Italy
fYear :
2009
fDate :
12-16 Oct. 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper deals with adaptive detection of a signal with unknown complex amplitude and whose steering vector presents angle uncertainties. The background environment is assumed homogeneous and Gaussian with unknown covariance matrix. At the design stage, we devise a robust receiver accounting for the aforementioned uncertainty. To this end, we prove that the maximization of the concentrated likelihood function over the phase parameter shares an hidden convexity property. Specifically, exploiting some recent results concerning trigonometric polynomials, we formulate the apparently non-convex maximization over the phase as a Semidefinite Programming (SDP) convex optimization problem. At the analysis stage, we assess the performance of the new receiver in comparison with some classic detectors available in open literature.
Keywords :
mathematical programming; polynomials; radar detection; radar receivers; radar signal processing; adaptive signal detection; concentrated likelihood function; convex optimization problem; hidden convexity property; radar signal processing; robust adaptive detector; robust receiver accounting; semidefinite programming convex optimization; steering phase uncertainties; trigonometric polynomials; Adaptive signal detection; Covariance matrix; Detectors; Performance analysis; Phase detection; Polynomials; Radar detection; Robustness; Signal detection; Uncertainty; Radar Signal Processing; Robust Detection; Semidefinite Programming; bounded-CFAR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference - Surveillance for a Safer World, 2009. RADAR. International
Conference_Location :
Bordeaux
Print_ISBN :
978-2-912328-55-7
Type :
conf
Filename :
5438467
Link To Document :
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