Adaptive cell-averaging CFAR detection in distributed sensor networks

Barkat, M.; Varshney, Pramod K.

doi:10.1109/7.81424

Cited by 35 publications

(11 citation statements)

References 19 publications

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“…Mezache · F. Soltani (B) Département d'Electronique Faculté des Sciences de l'Ingénieur, Université de Constantine, Route d'Ain El Bey, Constantine 25000, Algeria e-mail: f.soltani@caramail.com A. Mezache e-mail: mezache_a@yahoo.fr ber of clutter environments. In recent years, there has been a growing interest in distributed detection network of radar sensors with CFAR behaviour [5][6][7][8][9]. Barkat and Varshney [5] developed the theory of cell-averaging CFAR detection for Rayleigh clutter and interferences, using multiple sensors and data fusion.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, there has been a growing interest in distributed detection network of radar sensors with CFAR behaviour [5][6][7][8][9]. Barkat and Varshney [5] developed the theory of cell-averaging CFAR detection for Rayleigh clutter and interferences, using multiple sensors and data fusion. Blum and Qiao [7] analysed the case where the signal observations are assumed to be dependent from sensor to sensor and weak narrowband random signal are observed in additive Gaussian noise-plus-clutter of unknown power.…”

Section: Introductionmentioning

confidence: 99%

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Threshold optimization of decentralized CFAR detection in weibull clutter using genetic algorithms

Mezache

Soltani

2007

SIViP

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The use of genetic algorithms (GAs) tool for the solution of distributed constant false alarm rate (CFAR) detection for Weibull clutter statistics is considered. An approximate expression of the probability of detection (P D ) of the ordered statistics CFAR (OS-CFAR) detector in Weibull clutter is derived. Optimal threshold values of distributed maximum likelihood CFAR (ML-CFAR) detectors and distributed OS-CFAR detectors with a known shape parameter of the background statistics are obtained using GA tool. For the distributed ML-CFAR detection, we consider also the case when the shape parameter is unknown of the Weibull distribution. A performance assessment is carried out, and the results are compared and given as a function of the shape parameter and of system parameters.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Threshold optimization of decentralized CFAR detection in weibull clutter using genetic algorithms

Mezache

Soltani

2007

SIViP

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“…In their approach, each CA-CFAR detector transmits a binary decision to the fusion center where a final decision based on the AND or the OR counting rule is obtained. They have also addressed the adaptive CA-CFAR detector problem for parallel and tandem distributed networks [13]. Distributed OS-CFAR detectors with the AND or the OR fusion rule is considered by Uner and Varshney [14].…”

Section: Introductionmentioning

confidence: 99%

A new distributed constant false alarm rate detector

Amirmehrabi

Viswanathan

1997

IEEE Trans. Aerosp. Electron. Syst.

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“…In their approach, each CA-CFAR detector transmits a binary decision to the fusion center where a final decision based on the AND or the OR counting rule is obtained. They have also addressed the adaptive CA-CFAR detector problem for parallel and tandem distributed networks [6]. Distributed OS-CFAR detectors with the AND or the OR fusion rule are considered in [7][8][9].…”

Section: Introductionmentioning

confidence: 99%