约束优化的空间变迹算法的旁瓣抑制应用

doi:10.12305/j.issn.1001-506X.2022.11.02

Abstract

Abstract:

Synthetic aperture radar (SAR) echo signals have a high dynamic range, it will cause the sidelobe of the strong target to cover the main lobe of the weak target and cause miss detection. Although the traditional windowing method can eliminate the sidelobe, it can result in the decrease of the resolution and the energy of the main lobe. The spatial variant apodization algorithm (SVA) has been proposed to effectively solve this problem. However, while the existing improved SVA algorithms can effectively suppress the sidelobe, but at the same time, it leads to the reduction of the main lobe energy. Therefore, this paper proposes an improved SVA algorithm based on constrained optimization, which can effectively solve the problem of the main lobe energy reduction by strictly constraining the monotonicity of the filter and the selection of effective points. It can effectively suppress the sidelobes while retaining the details of the image, which is beneficial to the image target further detection and identification.

Key words: synthetic aperture radar (SAR), sidelobe suppression, spatial variant apodization (SVA) algorithm, constrained optimization

CLC Number:

TN951

Zheng XU, Guangzhong GONG, Yunhua LUO, Guangde LI. Application of improved spatial variant apodization algorithm through constrained optimization in sidelobe suppression[J]. Systems Engineering and Electronics, 2022, 44(11): 3298-3304.

Figures/Tables 9

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References 30

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目标间距/m	原始回波	MSVA	本文算法	相对于MSVA能量提升比例/%
0.35	1	0.307 0	0.911 0	196.74
0.5	1	0.653 5	0.778 1	19.07
0.8	1	0.811 0	0.900 7	11.06
1.0	1	0.920 7	0.972 7	5.64
1.5	1	0.948 0	0.977 9	3.15
3.0	1	0.976 2	0.991 8	1.60

指标	原始回波	MSVA	本文算法
PSLR/dB	-14.732 6	-21.686 6	-47.707 4
ISLR/dB	-16.812 3	-43.116 1	-49.038 8
主瓣宽度	1	0.793 3	0.886 7

指标	原始图像	MSVA	本文算法
归一能量	1	0.290 5	0.437 7

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Application of improved spatial variant apodization algorithm through constrained optimization in sidelobe suppression

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