Partially-Correlated χ2 Targets Detection Analysis of GTM-Adaptive Processor in the Presence of Outliers

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Author(s)

Mohamed B. El-Mashade 1,*

1. Electrical Engineering Dept., Faculty of Engineering, Al Azhar University, Nasr City, Cairo, Egypt.

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.12.10

Received: 19 Jul. 2014 / Revised: 22 Aug. 2014 / Accepted: 26 Sep. 2014 / Published: 8 Nov. 2014

Index Terms

Adaptive radar detectors, post-detection integration, Swerling fluctuation models, partially-correlated χ2 fluctuating targets, target multiplicity environments

Abstract

This paper addresses the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. It presents the performance analysis, in its exact form, of GTM-CFAR processor when the operating environment is contaminated with extraneous targets and the radar receiver post-detection integrates M pulses of exponentially correlated targets. Mathematical formulas for the detection and false alarm probabilities are derived, in the absence as well as in the presence of spurious targets which are fluctuating in accordance with the so-called moderately fluctuating χ2 targets. A thorough performance assessment by several numerical examples, which has considered the role that each parameter can play in the processor performance, is also given. The results show that the processor performance improves, for weak SNR of the primary target, as the correlation coefficient ρs increases and this occurs either in the absence or in the presence of outlying targets. As the strength of the target return increases, the processor tends to invert this behavior. The SWI & SWII and SWIII & SWIV models enclose the correlated target cases when the target correlation follows χ2 fluctuation models with two and four degrees of freedom, respectively, and this behavior is common for all GTM based detectors.

Cite This Paper

Mohamed B. El Mashade,"Partially-Correlated χ2 Targets Detection Analysis of GTM-Adaptive Processor in the Presence of Outliers", IJIGSP, vol.6, no.12, pp. 70-90, 2014. DOI: 10.5815/ijigsp.2014.12.10

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