DocumentCode :
2699167
Title :
A generalized smallest of selection CFAR algorithm [radar signal processing]
Author :
Xiangwei, Meng ; Jian, Guan ; You, He
Author_Institution :
Dept. of Electron. Eng., Naval Aeronaut. Eng. Acad., Shandong, China
fYear :
2003
fDate :
3-5 Sept. 2003
Firstpage :
130
Lastpage :
132
Abstract :
A generalized smallest of selection CFAR (constant false alarm rate detection) algorithm (TMSO), based on the trimmed mean (TM) method, is proposed in this paper. It takes the smallest local estimation of either the leading or lagging window, which applies the trimmed mean method as a noise power estimation to set an adaptive threshold. Thus, the smallest of selection (SO), the generalized ordered statistic smallest of (GOSSO), or the ordered statistic smallest of (OSSO), is the special case of TMSO. It is shown that the performance of TMSO in homogeneous background and in multiple target situations is improved over that of GOSSO or OSSO.
Keywords :
adaptive signal processing; radar detection; radar signal processing; GOSSO; OSSO; TMSO; adaptive threshold; constant false alarm rate detection; generalized ordered statistic smallest of method; generalized smallest of selection CFAR algorithm; homogeneous background; lagging window local estimation; leading window local estimation; multiple targets; noise power estimation; radar detection environment; trimmed mean method; Aerospace engineering; Cities and towns; Degradation; Envelope detectors; Erbium; Helium; Radar detection; Roads; Statistics; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference, 2003. Proceedings of the International
Print_ISBN :
0-7803-7870-9
Type :
conf
DOI :
10.1109/RADAR.2003.1278724
Filename :
1278724
Link To Document :
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