DocumentCode :
961687
Title :
Rao Test for Adaptive Detection in Gaussian Interference With Unknown Covariance Matrix
Author :
De Maio, A.
Author_Institution :
Univ. degli Studi di Napoli Federico II, Napoli
Volume :
55
Issue :
7
fYear :
2007
fDate :
7/1/2007 12:00:00 AM
Firstpage :
3577
Lastpage :
3584
Abstract :
This paper deals with the problem of detecting a signal known up to a scaling factor in the presence of Gaussian disturbance with unknown covariance matrix. A new detector based on the Rao test criterion is introduced and its invariance properties and constant false alarm rate (CFAR) behavior are studied. At the analysis stage, the performance of the new receiver is assessed, also in comparison with some classical adaptive radar detectors, both in the matched as well as in the mismatched signal case. Remarkably, the Rao test may achieve a matched detection performance which is commensurate with that of the generalized likelihood ratio test (GLRT)-based detectors if a sufficient number of training data is available. Moreover, it also exhibits better rejection capabilities of mismatched signals than the counterparts. In the last part of the work, a two-stage detector whose second stage coincides with the Rao test is devised. It represents a suitable means to restore the detection performance of the plain Rao test in the presence of a small number of training data. Finally, the performance of the aforementioned two-stage processor is analyzed in closed form and the CFAR behavior is proved.
Keywords :
Gaussian noise; adaptive radar; adaptive signal detection; covariance matrices; radar detection; radar signal processing; CFAR; Gaussian disturbance; Gaussian interference; Rao test; adaptive detection; adaptive radar detectors; constant false alarm rate; covariance matrix; generalized likelihood ratio test; scaling factor; signal detection; two-stage detector; Adaptive signal detection; Covariance matrix; Detectors; Interference; Performance analysis; Radar detection; Signal analysis; Signal detection; Testing; Training data; Adaptive radar detection; constant false alarm rate (CFAR) processing; radar signal processing;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2007.894238
Filename :
4244665
Link To Document :
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