Optimal CFAR detection in Weibull clutter

Anastassopoulos, V.; Λαμπρόπουλος, Γεώργιος

doi:10.1109/7.366292

Cited by 112 publications

(57 citation statements)

References 17 publications

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“…There are numerous papers regarding CFAR detection, however most of them rely on a precise assumption of distribution of a noise signal in the time domain and are performed in the time domain [1,[10][11][12]7,17]. The CFAR detection based on the Gabor transform was addressed in [4,5], however in this paper the extended, discrete detectionrecognition methodology is discussed.…”

Section: Introductionmentioning

confidence: 99%

Detection-recognition algorithm based on the Gabor transform for unknown signals embedded in unknown noise

Swiercz

Pieniezny

2009

Mathematics and Computers in Simulation

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Section: Introductionmentioning

confidence: 99%

Detection-recognition algorithm based on the Gabor transform for unknown signals embedded in unknown noise

Swiercz

Pieniezny

2009

Mathematics and Computers in Simulation

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“…In realistic radar applications, the clutter distribution quite often deviates from Rayleigh, particularly when high-resolution radars operate at low grazing angles [1][2][3][4]. The Weibull probability density function (pdf) fits well the data acquired from a num-A.…”

Section: Introductionmentioning

confidence: 99%

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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“…The literature contains many examples of CFAR detectors produced from ones not possessing the CFAR property [8,23,24]. As an example, the LTD detector (5) has been constructed with the assumption that β is known.…”

Section: General Detectormentioning

confidence: 99%

Coherent CFAR detection in compound Gaussian clutter with inverse gamma texture

Weinberg

2013

EURASIP J. Adv. Signal Process.

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Recent publications have explored coherent radar detection in a compound Gaussian clutter environment with inverse gamma texture, since the latter clutter model has been validated for X-band high-resolution maritime surveillance radar clutter returns. This paper explores the development of coherent constant false alarm rate (CFAR) detectors for this scenario. In the first instance, a detector is constructed with explicit knowledge of the clutter parameters. It is then shown that the probability of false alarm/threshold relationship does not vary with the clutter power. To achieve a CFAR detector, clutter parameter approximations are then introduced, and the cost associated with this is then analysed.

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Optimal CFAR detection in Weibull clutter

Cited by 112 publications

References 17 publications

Detection-recognition algorithm based on the Gabor transform for unknown signals embedded in unknown noise

Detection-recognition algorithm based on the Gabor transform for unknown signals embedded in unknown noise

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

Coherent CFAR detection in compound Gaussian clutter with inverse gamma texture

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