Extensive Monte Carlo simulations for performance comparison of three non-coherent integrations using Log-t-CFAR detection against Weibull clutter

Detouche, Nedjma; Laroussi, Toufik

doi:10.1109/setit.2012.6482004

Cited by 11 publications

(8 citation statements)

References 11 publications

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“…For non-Rayleigh distributions, many studies have confirmed that the log-t detector can maintain constant false alarm characteristics in Weibull and Log-normal distributions with unknown parameters, as well as K distribution [12,32,33]. The proposed architecture will be configured as an ML detector when the blue paths work, whereas it will be a log-t detector when the magenta paths work.…”

Section: Cfar Detectormentioning

confidence: 96%

Reconfigurable hardware architecture for Mean Level and log-t CFAR detectors in FPGA implementations

Jiafei

Jiang

Yang

et al. 2019

IEICE Electron. Express

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For radar target detection, the selection of the optimal constant false alarm rate (CFAR) detector usually relies on clutter distribution types. By integrating two types of Mean Level and log-t CFAR detectors, a reconfigurable hardware architecture is proposed and implemented on field programmable gate array (FPGA). It allows to switch a suitable detector for specific clutter distribution and configure the parameters including the number of reference and guard cells, the threshold factor, and the desired false alarm probability. Synthesis results reveal its advantages of occupying 18% less hardware resources than the architecture that naively integrates two types of detectors. According to the experimental results, the proposed architecture can perform a processing speed of 100 MHz and require only 83 microseconds for a clutter of 8192 samples.

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Section: Cfar Detectormentioning

confidence: 96%

Reconfigurable hardware architecture for Mean Level and log-t CFAR detectors in FPGA implementations

Jiafei

Jiang

Yang

et al. 2019

IEICE Electron. Express

View full text Add to dashboard Cite

show abstract

“…The statistical distribution characteristics of the radar clutter can be expressed by the composite K distribution probability density function (PDF) with different scale parameters and shape parameters. In the PDF expression of K distribution, because there are the Gamma function and Bessel function, so this leads to difficulties in analysis, and it is very difficult to express the detect probability and false alarm probability explicitly [21]. However, K distribution clearly represents the correlation characteristics of clutter.…”

Section: Signal Model and Statistical Analysismentioning

confidence: 99%

“…Literature [21] extended the log-t CFAR detector to non-coherent multi-pulse processing and established three kinds of detecting processors: the conventional integration detector (CI-CFARD), the non-conventional integration detector (NCI-CFARD) and the binary integration detector (BI-CFARD). The detection methods of three detectors were compared and analyzed in the background of Weibull clutter.…”

Section: Introductionmentioning

confidence: 99%

Research on a New Comprehensive CFAR (Comp-CFAR) Processing Method

et al. 2019

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Since the clutter statistics of marine radar are non-stationary and difficult to ascertain, the constant false-alarm rate (CFAR) processor based on some clutter statistical characteristics is hard to obtain the CFAR performance. Especially, for clutter with long smearing effect characteristics, such as lognormal distribution, Pareto distribution, and K distribution, it is difficult to obtain CFAR characteristics using conventional CFAR processing techniques. The main consideration of this paper is to improve the robustness of CFAR, and the Comp-CFAR method is proposed according to the central limit theorem and the logarithmic compression principle of the signal. This method mainly includes clutter two-parameter logarithmic compression processing and accumulation of the magnitudes' average comprehensive CFAR processing. The experimental verification of CFAR characteristics and target detection performance with CFAR in four typical clutter environments shows that this method has better detection ability compared with the NCI-CFAR.INDEX TERMS Adaptive CFAR, clutter suppression, accumulation of the magnitudes, target detection.

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“…Using a logarithmic amplifier to convert the random variable with Weibull distribution into another one with Gumbel distribution [3], the skewness does not change with the value of the clutter parameter [15]. Therefore, we study a SK‐CFAR detector that combining skewness with Log‐t CFAR detector [16]. The workflow of the SK‐CFAR detector is shown in Fig.…”

Section: Sk‐cfar Detector Based On the Local Spectrum Refinementmentioning

confidence: 99%

UAV target detection and parameter estimation in non‐homogeneous clutter

Huang

2019

J. eng.

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Extensive Monte Carlo simulations for performance comparison of three non-coherent integrations using Log-t-CFAR detection against Weibull clutter

Cited by 11 publications

References 11 publications

Reconfigurable hardware architecture for Mean Level and log-t CFAR detectors in FPGA implementations

Reconfigurable hardware architecture for Mean Level and log-t CFAR detectors in FPGA implementations

Research on a New Comprehensive CFAR (Comp-CFAR) Processing Method

UAV target detection and parameter estimation in non‐homogeneous clutter

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