Coherent multilook detection for targets in Pareto distributed clutter

Weinberg, Graham V.

doi:10.1049/el.2011.0963

Cited by 26 publications

(45 citation statements)

References 7 publications

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“…Using the theory of SIRPs, it can be shown that the corresponding clutter intensity model is Pareto, with shape parameter α and scale parameter β [16]. We now specify the whitened version of the statistical test (1).…”

Section: Detection Frameworkmentioning

confidence: 99%

“…Using the formulation above and by applying SIRP theory to construct appropriate densities, the GLRT is shown in [2,16,18] to take the form L(r r r) = W (r r r) u u u 2 r r r 2 + β…”

Section: Detection Frameworkmentioning

confidence: 99%

“…This result demonstrates that it is important to not choose n too close to zero; otherwise, the performance of (9) may be similar to the WMF. In the case of horizontally polarised returns, the WMF has been shown to experience a significant detection loss because the clutter is very heavy tailed [16]. Hence, in such cases, it is prudent to select an n further away from zero.…”

Section: General Detectormentioning

confidence: 99%

“…The analysis of relevant detection schemes Correspondence: Graham.Weinberg@dsto.defence.gov.au Electronic Warfare and Radar Division, Defence Science and Technology Organisation, P.O. Box 1500, Edinburgh, South Australia 5111, Australia can be found in [2,[15][16][17][18]. Much work has been devoted to examining the Neyman-Pearson optimal detector [19] and its suboptimal variants, such as the generalised likelihood ratio test (GLRT) detector [2,18].…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Detection Frameworkmentioning

confidence: 99%

“…Using the formulation above and by applying SIRP theory to construct appropriate densities, the GLRT is shown in [2,16,18] to take the form L(r r r) = W (r r r) u u u 2 r r r 2 + β…”

Section: Detection Frameworkmentioning

confidence: 99%

Section: General Detectormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coherent CFAR detection in compound Gaussian clutter with inverse gamma texture

Weinberg

2013

EURASIP J. Adv. Signal Process.

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“…Some heavy-tailed radar clutter models, such as K distribution [16][17][18], Pareto distribution [19,20], KK distribution [21,22], are utilized in the target detection scheme design. In [16], the K-distribution is expressed as spherically invariant random process and then two CFAR detectors, i.e., scatterer density dependent GLRT (SDD-GLRT) and non-scatterer density dependent GLRT (NSDD-GLRT), are proposed.…”

Section: Introductionmentioning

confidence: 99%

Range-Spread Target Detection in Compound Gaussian Clutter With Reciprocal of the Square Root of Gamma Texture

Gao¹,

Zhan²,

Wan³

2014

PIER

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Abstract-In this paper, the range-spread target detection in compound Gaussian clutter with reciprocal of the square root of gamma (RSRG) texture is investigated. The RSRG distribution has been proved to be a good model for texture component of extremely heterogeneous radar clutter. Taking this compound Gaussian model as a spherically invariant random process (SIRP), the Neyman-Pearson optimal detector for the range-spread target detection with known target amplitude is derived firstly. By replacing the ideal target amplitude with its maximum likelihood estimate (MLE), the generalized likelihood ratio test (GLRT) is then obtained. The statistical property of the texture component is taken into account in both of these two detectors, which makes the detectors computationally complicated. A suboptimal generalized likelihood ratio test based on order statistics (OS-GLRT) is finally proposed by substituting the texture component with its MLE. The OS-GLRT makes use of some largest observations from the range cells occupied by the most likely target scatters. The performance assessment conducted by Monte Carlo simulation validates the effectiveness of the proposed detectors.

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A hybrid STAP approach to target detection for heterogeneous scenarios in radar seekers

Zhao

Sun

2012

Multidim Syst Sign Process

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Coherent multilook detection for targets in Pareto distributed clutter

Cited by 26 publications

References 7 publications

Coherent CFAR detection in compound Gaussian clutter with inverse gamma texture

Coherent CFAR detection in compound Gaussian clutter with inverse gamma texture

Range-Spread Target Detection in Compound Gaussian Clutter With Reciprocal of the Square Root of Gamma Texture

A hybrid STAP approach to target detection for heterogeneous scenarios in radar seekers

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