基于投影空间下奇异值分解的海面小目标CFAR检测

doi:10.12305/j.issn.1001-506X.2022.02.20

Abstract

Abstract:

A method of clutter suppression based on singular value decomposition (SVD) in projection space is proposed. In the radar echo data, the clutter space is constructed directly by using the data vectors of neighboring range cells of cell under test (CUT). The SVD of the clutter space in the projection space is carried out to achieve clutter suppression. Therefore, a new detector is designed which combines orthogonal projection(OP), SVD and the traditional constant false alarm rate (CFAR) detector, called OP-SVD-CFAR. The detection performance of the proposed OP-SVD-CFAR detector is compared with that of the OP-CFAR, the maximum eigenvalue matrix CFAR detector, the SVD fractional Fourier transform (SVD-FRFT) detector and the CA-CFAR detector respectively. The experimental results show that the detection performance of the proposed OP-SVD-CFAR detector is obviously superior to the compared ones.

Key words: sea clutter, clutter suppression, radar detection, projection space, singular value decomposition

CLC Number:

TN911.23

Yanling SHI, Lei WANG, Junhao LI. CFAR detection for small targets on sea surface based on singular value decomposition in projection space[J]. Systems Engineering and Electronics, 2022, 44(2): 512-519.

Figures/Tables 9

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Table 1

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References 27

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#data1算法	SCR损失/dB
	VV		HH
	SIR=0	SIR=5	SIR=0	SIR=5
CA-CFAR	0.6	1.5	1.5	3.7
SVD-FRFT	2.4	5.6	11.5	16
MEMD	0.3	1.1	0.4	1.2
OP-CFAR	6.7	10.7	6	18.4
OP-SVD-CFAR	0.1	0.2	0.2	0.3

#data2算法	SCR损失/dB
	VV		HH
	SIR=0	SIR=5	SIR=0	SIR=5
CA-CFAR	0.2	0.4	0.4	0.6
SVD-FRFT	0.3	0.7	0.2	0.5
MEMD	0.3	0.8	0.6	1
OP-CFAR	1.6	4.2	6.7	14.5
OP-SVD-CFAR	0.1	0.2	0.1	0.3

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CFAR detection for small targets on sea surface based on singular value decomposition in projection space

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