DocumentCode :
3602692
Title :
Design and Analysis of Invariant Receivers for Gaussian Targets
Author :
De Maio, Antonio ; Orlando, Danilo ; Farina, Alfonso ; Foglia, Goffredo
Author_Institution :
Dipt. di Ing. Elettr. e delle Tecnol. dell´Inf., Univ. degli Studi di Napoli “Federico II”, Naples, Italy
Volume :
9
Issue :
8
fYear :
2015
Firstpage :
1560
Lastpage :
1569
Abstract :
The purpose of this paper is to elaborate on the invariant framework proposed in “An invariant approach to adaptive radar detection under covariance persymmetry” (A. De Maio and D. Orlando, IEEE Trans. Signal Processing, vol. 63, no. 5, pp. 1297-1309, May 2015) so as to account for target fluctuations at the design stage. To this end, we assume that the radar cross section of the target is ruled by an exponential distribution (Swerling 1 target model) and derive the complete statistical characterization of a maximal invariant statistic. Hence, we exploit the obtained probability density functions to synthesize both the optimum and the locally optimum (in the low Signal-to-Interference-plus-Noise Ratio regime) invariant receivers. Finally, we discuss some invariant sub-optimum decision rules based on theoretically solid design criteria and analyze their performances in comparison with the benchmark invariant test.
Keywords :
adaptive radar; exponential distribution; radar detection; radar receivers; Gaussian targets; adaptive radar detection; covariance persymmetry; exponential distribution; invariant framework; invariant sub-optimum decision rules; locally optimum invariant receivers; maximal invariant statistic; probability density functions; radar cross section; target fluctuations; Covariance matrices; Interference; Radar cross-sections; Radar detection; Receivers; Adaptive radar detection; Swerling models; constant false alarm rate; invariance; maximal invariants; persymmetry;
fLanguage :
English
Journal_Title :
Selected Topics in Signal Processing, IEEE Journal of
Publisher :
ieee
ISSN :
1932-4553
Type :
jour
DOI :
10.1109/JSTSP.2015.2440183
Filename :
7115873
Link To Document :
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