Modified rank sum nonparametric CFAR to combat clutter edge

• Published in: EURASIP journal on advances in signal processing Vol. 2023; no. 1; pp. 75 - 17
• Main Authors: Xiangwei, Meng, Yuan, Meng
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2023; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Analysis; CFAR; Clutter; Constant false alarm rate; Detectors; Engineering; False alarms; Mathematical analysis; Nonhomogeneous background; Nonparametric detection; Nonparametric statistics; Quantum Information Technology; Radar detection; Radar systems; Radar targets; Sensors; Signal,Image and Speech Processing; Spintronics; Target detection; Nonparametric detection; CFAR; Nonhomogeneous background; Radar detection
• ISSN: 1687-6180; 1687-6172; 1687-6180
• DOI: 10.1186/s13634-023-01032-z

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.