Modified cell averaging CFAR detector based on Grubbs criterion in non‐homogeneous background

Zhou, Wei; Xie, Junhao; Xi, Kun; Du, Yuhan

doi:10.1049/iet-rsn.2018.5160

Cited by 25 publications

(10 citation statements)

References 28 publications

(37 reference statements)

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“…Some researchers pointed out that the Grubbs criterion can achieve fewer misjudgements [33]. The reason is that Grubbs criterion is based on normal distribution theory and two important indicators of normal distribution theory, i.e.…”

Section: Principle Of Lof and Grubbs Criterionmentioning

confidence: 99%

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Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor

Ding

Zhang

Ding

et al. 2020

IET Renewable Power Generation

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Aiming at improving the effectiveness and real-time performance of the fault detection of the photovoltaic (PV) array under different outdoor conditions, a novel method based on Grubbs criterion and local outlier factor (G-LOF) method is proposed in this study. The simulation model of the PV array is built to obtain the reference current of each PV string. The local outlier factor (LOF) is a ratio of the average local reachability density of sample neighbourhoods relative to its local reachability density. In this study, the LOF is used to quantify the abnormality by comparing the measured current and the simulated reference current. To reduce the false alarm probability of LOF, the Grubbs criterion is utilised as the test criterion to detect the abnormality of PV strings and it is merged with the LOF to derivate the G-LOF. The experiments of partial shading, open-circuit fault and short-circuit fault of PV modules are implemented in sunny and cloudy days. Experimental results verify that the proposed G-LOF method can sensitively detect above abnormalities, especially can detect the slight performance reduction caused by the partial shading or faults.

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Section: Principle Of Lof and Grubbs Criterionmentioning

confidence: 99%

“…In statistics, Grubbs criterion is usually used to detect the abnormal data and eliminate the coarse error. Some researchers pointed out that the Grubbs criterion can make less erroneous judgement [33]. However, this method cannot evaluate the fault degree.…”

Section: Introductionmentioning

confidence: 99%

Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor

Ding

Zhang

Ding

et al. 2020

IET Renewable Power Generation

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“…In recent years, to improve detection performance in multiple target situations and the clutter edge, many CFAR detectors have been studied based on weighted iteration [14], [15], machine learning [16], [17], variability index [18], and outlier rejection based on the Grubbs criterion [19]. These studies have improved detection performances in multiple target situations and the clutter edge.…”

Section: Introductionmentioning

confidence: 99%

Robust CFAR Detector With Ordered Statistic of Sub-Reference Cells in Multiple Target Situations

et al. 2022

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Herein, a robust constant false alarm rate (CFAR) detector with ordered statistic of subreference cells (OSS-CFAR) is proposed in multiple target situations. This detector can improve background level estimation and reduce computational complexity using sub-reference cells. The detection performance of the OSS-CFAR detector and of conventional CFAR detectors in multiple target situations are investigated and compared using computer simulations and experimental data with sea clutter. The simulations and experimental results show that the OSS-CFAR detector achieves robust detection performance with low computational complexity, whereas conventional CFAR detectors suffer performance degradation in multiple target situations. At the clutter edge, the OSS-CFAR detector with appropriate parameters achieves an acceptable false alarm rate compared to conventional CFAR detectors.INDEX TERMS Constant false alarm rate detector, clutter edge, multiple target situations, ordered statistic of sub-reference cells.

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“…This reveals the fact that the traditional CFAR schemes still own a powerful vitality in practise. In recent 2 years, there are also many published works [10–16] focused on the new proposal or the theoretical research on CFAR detection schemes.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of RQ non‐parametric CFAR detector in multiple target and non‐uniform clutter

Meng

2020

IET Radar, Sonar & Navigation

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Modified cell averaging CFAR detector based on Grubbs criterion in non‐homogeneous background

Cited by 25 publications

References 28 publications

Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor

Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor

Robust CFAR Detector With Ordered Statistic of Sub-Reference Cells in Multiple Target Situations

Performance evaluation of RQ non‐parametric CFAR detector in multiple target and non‐uniform clutter

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