scholarly journals Robust Centralized CFAR Detection for Multistatic Sonar Systems

2021 ◽  
Vol 30 (2) ◽  
pp. 322-330
Author(s):  
Lu Shuping ◽  
Ding Feng ◽  
Li Ranwei
Keyword(s):  
1980 ◽  
Vol 25 (11) ◽  
pp. 942-943
Author(s):  
DONALD A. DEWSBURY
Keyword(s):  

1975 ◽  
Author(s):  
R. J. Hornick ◽  
G. Yamashita ◽  
J. E. Robinson ◽  
H. J. Winkler

1980 ◽  
Vol 127 (2) ◽  
pp. 125 ◽  
Author(s):  
J.F. Dix ◽  
N. Dean ◽  
J. Widdowson ◽  
J. Mavor
Keyword(s):  

2012 ◽  
Vol 38 (12) ◽  
pp. 1885 ◽  
Author(s):  
Ming-Bo ZHAO ◽  
Jun HE ◽  
Qiang FU

2010 ◽  
Author(s):  
Jon La Follett ◽  
John Stroud ◽  
Pat Malvoso ◽  
Joseph Lopes ◽  
Raymond Lim ◽  
...  

2019 ◽  
Vol 11 (12) ◽  
pp. 1428 ◽  
Author(s):  
Yong Jia ◽  
Yong Guo ◽  
Chao Yan ◽  
Haoxuan Sheng ◽  
Guolong Cui ◽  
...  

This paper demonstrates the feasibility of detection and localization of multiple stationary human targets based on cross-correlation of the dual-station stepped-frequency continuous-wave (SFCW) radars. Firstly, a cross-correlation operation is performed on the preprocessed pulse signals of two SFCW radars at different locations to obtain the correlation coefficient matrix. Then, the constant false alarm rate (CFAR) detection is applied to extract the ranges between each target and the two radars, respectively, from the correlation matrix. Finally, the locations of human targets is calculated with the triangulation localization algorithm. This cross-correlation operation mainly brings about two advantages. On the one hand, the cross-correlation explores the correlation feature of target respiratory signals, which can effectively detect all targets with different signal intensities, avoiding the missed detection of weak targets. On the other hand, the pairing of two ranges between each target and two radars is implemented simultaneously with the cross-correlation. Experimental results verify the effectiveness of this algorithm.


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