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Modified rank sum nonparametric CFAR to combat clutter edge

Authors :
Meng Xiangwei
Meng Yuan
Source :
EURASIP Journal on Advances in Signal Processing, Vol 2023, Iss 1, Pp 1-17 (2023)
Publication Year :
2023
Publisher :
SpringerOpen, 2023.

Abstract

Abstract The classical rank sum (RS) nonparametric constant false alarm rate (CFAR) detector plays an important role in the theoretical study and practical application of radar target detection. In order to improve the ability of the classical RS nonparametric detector to control the false alarm rate at clutter edges, a modified rank sum (MRS) nonparametric CFAR based on the mean ratio of the samples in the leading and lagging windows is proposed. The analytical expressions of the detection probability and false alarm rate of the MRS nonparametric CFAR in homogeneous background and at clutter edges are derived, and a comparison to the performance of the classical RS nonparametric detector along with some conventional parametric CFAR schemes in homogeneous background, multiple targets situation and clutter edges is made. The numerical results show that the detection performance of the MRS nonparametric CFAR in homogeneous background and in a moderate number of interfering targets situation is close to that of the classical RS nonparametric detector, and its ability to control the rise of the false alarm rate at clutter edges is evidently improved.

Details

Language :
English
ISSN :
16876180
Volume :
2023
Issue :
1
Database :
Directory of Open Access Journals
Journal :
EURASIP Journal on Advances in Signal Processing
Publication Type :
Academic Journal
Accession number :
edsdoj.0b0735b3e9d94f9ca52207e8b67233d9
Document Type :
article
Full Text :
https://doi.org/10.1186/s13634-023-01032-z