Automatic censoring switching-CFAR detector based on sorting

LIU Gui-ru; WANG Lu-lin; ZOU Shan

doi:10.3969/j.issn.1000-5641.2017.03.014

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May 2017

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LIU Gui-ru, WANG Lu-lin, ZOU Shan. Automatic censoring switching-CFAR detector based on sorting[J]. Journal of East China Normal University (Natural Sciences), 2017, (3): 120-132. doi: 10.3969/j.issn.1000-5641.2017.03.014

Citation:

LIU Gui-ru, WANG Lu-lin, ZOU Shan. Automatic censoring switching-CFAR detector based on sorting[J]. Journal of East China Normal University (Natural Sciences), 2017, (3): 120-132. doi: 10.3969/j.issn.1000-5641.2017.03.014

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Automatic censoring switching-CFAR detector based on sorting

doi: 10.3969/j.issn.1000-5641.2017.03.014

1.
College of Computer and Information Science, Anhui Polytechnic University, Wuhu Anhui 241000, China
2.
Prospective Technology Research Institute, Chery Automobile Co., Ltd, Wuhu Anhui 241006, China

Received Date: 2016-09-14
Publish Date: 2017-05-25

Abstract

Abstract

Because the conventional CFAR (Constant False-Alarm Rate) detectors have poor detection performance in non-homogeneous environments, an automatic censoring switching-CFAR detector based on sorting (ACS-CFAR) is proposed. The middle cell of the reference window acts as a cell under test; other cells are sorted into the ranked reference cells by ascending order according to their magnitudes. According to the location parameters of the two boundary points which can effectively discriminate between thermal noise, clutter edge or interferences plus thermal noise and interferences immersed in the clutter plus thermal noise region, the detection algorithm can effectively select a suitable cell set from the ranked reference cells to estimate the unknown background level. Combined with the number of the selecting reference cells and the desired probability of false alarm, the corresponding scaling factor can be calculated. Finally, the adaptive detection threshold will be obtained according to background noise level estimated value and the calculated scaling factor. The performances of the ACS-CFAR detector is simulated and evaluated in different simulation environments and compared to the performance of the CA-CFAR, VI-CFAR and ACCA-CFAR detectors, the detection probability of ACS-CFAR detector is up to 98.73%, 98.16% in homogeneous and non-homogeneous environments, respectively. The ACS-CFAR detector performs like the CA-CFAR detector in homogeneous environments and better than the VI-CFAR and ACCA-CFAR detector in non-homogeneous environments, false alarm rate errors are controlled within $\pm $ 0.10%. The simulation results show that the proposed ACS-CFAR detector has better detection performance in homogenous and the presence of interfering targets and clutter edge environments.
- target detection,
- constant false-alarm rate (CFAR),
- automatic censoring,
- Switching-CFAR,
- non-homogenous noise

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References(22)

References

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