Performance avalysis of generalized smallest option of CFAR algorithm

Meng Xiangwei; Guan Jian; He You

Volume 25 Issue 1

Jan. 2003

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Jinwei XIE, Zhiyong SUO, Zhenfang LI, Yuekun WANG. High-precision Digital Surface Model Inversion Approach in Forest Region Based on PolInSAR[J]. Journal of Electronics & Information Technology, 2019, 41(2): 293-301. doi: 10.11999/JEIT180387

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Meng Xiangwei, Guan Jian, He You. Performance avalysis of generalized smallest option of CFAR algorithm[J]. Journal of Electronics & Information Technology, 2003, 25(1): 17-23.

Citation:

Meng Xiangwei, Guan Jian, He You. Performance avalysis of generalized smallest option of CFAR algorithm[J]. Journal of Electronics & Information Technology, 2003, 25(1): 17-23.

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Performance avalysis of generalized smallest option of CFAR algorithm

Received Date: 2001-05-28
Rev Recd Date: 2002-02-22
Publish Date: 2003-01-19

Abstract

Abstract

In order to enhance the performance of OSSO, the Generalized Smallest Op-tion(GSO) of logic CFAR algorithm is proposed in this paper. For this CFAR. algorithms, it splits the reference window into two sub-windows and uses the linear combined order statis-tics to create two local noise power estimations, the smallest of them is used to set an adaptive threshold. How to select the weighted coefficient of the linear combined order statistics in the practical situation, several suggestions are given. In the special cases of GSO, QBWSO, TMSO, CMSO, OSSO and SO methods are deduced. The analytic results show that the detection per-formance of QBWSO and TMSO is superior to that of OSSO both in homogeneous background and in multiple target situation, the CFAR loss of QBWSO is slightly lower than that of TMSO in homogeneous background. In homogeneous background, the detection performance of SO is the best.

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References(1)

References

G.V. Trunk, Range resolution of targets using automatic detectors, IEEE Trans. on AES, 1978,14(5), 750-755.[2]A.R. Elias-Fuste, M. G. De Mercado, E. R. Davo, Analysis of some modified order statistic CFAR: OSGO and OSSO CFAR, IEEE Trans. on AES, 1990, 26(1), 197-202.[3]H. Rohling, Radar CFAR thresholding in clutter and multiple-target situations, IEEE Trans. on AES, 1983, 19(4), 608-621.[4]He You, Performance of some generalised modified order statistics CFAR detectors with automatic censoring technique in multiple target situations, IEE Proc.-F, 1994, 141(4), 205-212.[5]孟祥伟,何友,基于准最佳加权有序统计的最大选择CFAR检测算法,电子学报,1997,25(12),74-78.[6]P.P. Gandhi, S. A. Kassam, Analysis of CFAR processors in nonhomogeneous background, IEEE Trans. on AES, 1988, 24(4), 427-445.[7]M. Weiss, Analysis of some modified cell-averaging CFAR processors in multiple-target situations,IEEE Trans. on AES, 1982, 18(1), 102-114.

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