Analysis of the clutter map CFAR in Weibull clutter

Hamadouche, M.; Barakat, M.; Khodja, Mohammed-El-Amine

doi:10.1016/s0165-1684(99)00115-2

Cited by 17 publications

(8 citation statements)

References 14 publications

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“…This will be discussed subsequently in terms of practical implementation of the test in Eq. (10). The next section discusses the application of Eq.…”

Section: Decision Rulementioning

confidence: 99%

“…Due to this, there are three choices available for j, corresponding to a minimum (denoted MIN, when j = 1), median (MED, j = 2), and maximum (MAX, j = 3). Figure 2 compares the performance of these decision rules, where the detection process (10) coupled with binary integration is denoted as the nonlinear mapping (NLM). In this case, the CUT SCR is 5 dB, representing a small target.…”

Section: Receiver Operating Characteristic Curvesmentioning

confidence: 99%

“…These investigations have been extended to account for different clutter models and to address issues with earlier detector design in a number of subsequent analyses [7][8][9][10][11][12][13][14][15]. Such decision rules can be formulated as follows.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear Transformations and Radar Detector Design

Weinberg¹

2017

Advances in Statistical Methodologies and Their Application to Real Problems

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A nonlinear transformation is introduced, which can be used to compress a series of random variables. For a certain class of random variables, the compression results in the removal of unknown distributional parameters from the resultant series. Hence, the application of this transformation is investigated from a radar target detection perspective. It will be shown that it is possible to achieve the constant false alarm rate property through a simple manipulation of this transformation. Due to the effect the transformation has on the cell under test, it is necessary to couple the approach with binary integration to achieve reasonable results. This is demonstrated in an X-band maritime surveillance radar detection context.

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“…This will be discussed subsequently in terms of practical implementation of the test in Eq. (10). The next section discusses the application of Eq.…”

Section: Decision Rulementioning

confidence: 99%

Section: Receiver Operating Characteristic Curvesmentioning

confidence: 99%

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Nonlinear Transformations and Radar Detector Design

Weinberg¹

2017

Advances in Statistical Methodologies and Their Application to Real Problems

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“…For example we can reach to the Rayleigh distribution by setting 2 for the shape parameter in the Weibull distribution. This distribution is expressed by the following equation [4], [5]:…”

Section: Clutter Modelingmentioning

confidence: 99%

“…Similarly, the clutter map method requires storage of the environment data in a number of different scans [4]. After these scans, the clutter map is prepared and thresholding is performed through comparison of signal and the noise with the clutter map [5].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of Adaptive Thresholding in Marine RADARs

Alaee

Amiri

Firoozmand

et al. 2010

2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation

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In order to detect targets upon sea surface or near it, marine radars should be capable of distinguishing target reflections from the sea clutter. Our proposed method in this paper relates to detection of dissimilar marine targets in an inhomogeneous environment with clutter and non-stationary noises, and is based on adaptive thresholding determination methods. Variation and mean vales of the noise have been estimated in this paper, based on non-stationary, statistical methods and thresholding has been carried out using the suggested two-pole recursive filter. Fixating the rate of false alarm, the concerned threshold resolves the assumption problem of existence or absence of the signal. Performance of the mentioned algorithm has been compared with method known as CA-CFAR in terms of decreasing the losses and increasing calculation speed. The algorithm provided for detection of signal has been implemented at the end of signalprocessing algorithms of sea marine radars. The results obtained from the algorithm performance in a real environment indicate appropriate workability of this method in heterogeneous environment and non-stationary interference.

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Clutter map CFAR detector based on maximal resolution cell

Zhang

Sheng

et al. 2013

SIViP

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Analysis of the clutter map CFAR in Weibull clutter

Cited by 17 publications

References 14 publications

Nonlinear Transformations and Radar Detector Design

Nonlinear Transformations and Radar Detector Design

Modeling and Simulation of Adaptive Thresholding in Marine RADARs

Clutter map CFAR detector based on maximal resolution cell

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