联合距离方位二维NCS的星弹双基前视SAR成像算法

刘裕洲; 蔡天倚; 李亚超; 宋炫; 王选琪; 安培赟

doi:10.12000/JR23144

联合距离方位二维NCS的星弹双基前视SAR成像算法

doi: 10.12000/JR23144

1.
西安电子科技大学雷达信号处理全国重点实验室西安 710071
2.
北京遥感设备研究所北京 100039

基金项目: 国家重点研发计划(2018YFB2202500)，国家自然科学基金(62171337, 62101396)，陕西省重点研发计划(2017KW-ZD-12)，陕西省杰出青年基金(S2020-JC-JQ-0056)，中央高校基本科研基金(XJS212205)，西安电子科技大学研究生创新基金(YJSJ23016)

详细信息

作者简介:
刘裕洲，博士生，研究方向为双基地合成孔径雷达(BiSAR)前视成像和地面动目标成像(GMTI)技术

蔡天倚，硕士，研究方向为软件工程、雷达信号处理等

李亚超，教授，博士生导师，研究方向为合成孔径雷达(SAR)/逆SAR (ISAR)成像、弹载SAR成像、地面运动目标检测(GMTI)、SAR图像的匹配和定向、基于现场可编程门阵列(FPGA)和数字信号处理(DSP)技术的实时信号处理以及分布式雷达

宋　炫，博士，研究方向为双基地合成孔径雷达(SAR)前视成像技术

王选琪，博士生，研究方向为双基地合成孔径雷达前视成像与协同探测技术

安培赟，硕士生，研究方向为双基地合成孔径雷达前视成像与运动补偿技术

通讯作者:
李亚超 ycli@mail.xidian.edu.cn

责任主编：李悦丽 Corresponding Editor: LI Yueli
中图分类号: TN957.52
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出版历程
- 收稿日期: 2023-08-29
- 修回日期: 2023-11-11
- 网络出版日期: 2023-12-11
- 刊出日期: 2023-12-28

A Range and Azimuth Combined Two-dimensional NCS Algorithm for Spaceborne-missile Bistatic Forward-looking SAR

1.
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
2.
Beijing Institute of Remote-Sensing Equipment, Beijing 100039, China

Funds: The National Key R&D Program of China (2018YFB2202500), The National Natural Science Foundation of China (62171337, 62101396), The Key R&D program of Shaanxi Province (2017KW-ZD-12), The Shaanxi Province Funds for Distinguished Young Youths (S2020-JC-JQ-0056), The Fundamental Research Funds for the Central Universities (XJS212205), The Innovation Fund of Xidian University (YJSJ23016)

More Information

Corresponding author: LI Yachao, ycli@mail.xidian.edu.cn

摘要

摘要: 星弹双基前视SAR能够全天时全天候获取导弹前方区域高分辨图像，是一种极具潜力的成像制导技术。然而，距离和方位参数的耦合与空变，阻碍着星弹双基前视SAR向高分辨成像发展。该文首先基于低轨星载照射源与高速前视的弹载接收平台构型，推导了回波信号的精确距离多普勒域解析式。然后，在距离向上，提出距离非线性变标(NCS)算法来均衡距离徙动和距离调频率，并在二维频域一致补偿；在方位向上，该文所提算法将收发机的方位调频率进行分解，利用方位NCS消除方位调频率在方位向上的高阶空变。最后，进行二维匹配滤波，得到全局聚焦良好的SAR图像。点目标和场景仿真验证了所提算法的有效性。
- 星弹双基前视SAR /
- 距离徙动 /
- 方位调频率 /
- 非线性变标 /
- 空变性
Abstract: The spaceborne-missile bistatic forward-looking Synthetic Aperture Radar (SAR) is a promising imaging guidance technology that can obtain high-resolution images of the area in front of the missile all day and in all weather types. However, the coupling and spatial variations in range and azimuth parameters hinder the development of high-resolution spaceborne-missile bistatic forward-looking SAR imaging. In this study, the accurate-range Doppler domain analytical formula for echo signals was derived based on the low-orbit spaceborne illuminator and high-speed forward-looking missile-borne receiving platform configuration. Subsequently, in range processing, a range Nonlinear Chirp Scaling (NCS) was proposed to equalize the range cell migration and range Frequency Modulation (FM) rate, and both can be uniformly compensated in the two-dimensional frequency domain. In azimuth processing, the proposed method decomposed the azimuth FM rates of the transmitter and receiver. Then, the azimuth NCS was used to eliminate the high-order spatial variation of the azimuth FM rate. Finally, a two-dimensional matched filtering was performed to obtain a SAR image with a good global focus. The point and scene simulation verify the effectiveness of the proposed algorithm.
- Spaceborne-missile bistatic forward-looking SAR /
- Range Cell Migration (RCM) /
- Azimuth FM rate /
- Nonlinear Chirp Scaling (NCS) /
- Spatial variation

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图 1 星弹双基前视SAR几何构型

Figure 1. Geometry configuration of spaceborne-missile bistatic forward-looking SAR

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图 2 所提距离模型误差

Figure 2. The error of proposed range history model

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图 3 距离预处理效果对比

Figure 3. Comparison of range preprocessing effect

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图 4 NCS原理示意图

Figure 4. Principle diagram of NCS

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图 5 所提成像算法流程图

Figure 5. Flowchart of the proposed imaging algorithm

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图 6 仿真点目标分布

Figure 6. Distribution of simulation point targets

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图 7 距离预处理前后信号的二维频谱对比

Figure 7. Comparison of the signal in two-dimensional spectrum before and after range preprocessing

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图 8 所提算法的点仿真成像结果

Figure 8. The point simulation imaging results of the proposed algorithm

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图 9 不同算法的P₁点二维等高线图

Figure 9. Two-dimensional contour maps of the point P₁ using different algorithms

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图 10 不同算法的P₁点方位剖面图

Figure 10. Azimuth profile of the point P₁ using different algorithms

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图 11 不同算法的P₁点距离剖面图

Figure 11. Range profile of the point P₁ using different algorithms

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图 12 不同算法的P₂点二维等高线图

Figure 12. Two-dimensional contour maps of the point P₂ using different algorithms

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图 13 不同算法的P₂点方位剖面图

Figure 13. Azimuth profile of the point P₂ using different algorithms

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图 14 不同算法的P₂点距离剖面图

Figure 14. Range profile of the point P₂ using different algorithms

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图 15 所提算法的场景仿真成像结果

Figure 15. Scene simulation imaging results of the proposed algorithm

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图 16 不同算法的场景成像结果放大

Figure 16. The amplified scene imaging results of different algorithms

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图 17 不同算法的场景仿真孤立点分析

Figure 17. Isolated point analysis in scene simulation of different algorithms

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表 1 雷达系统仿真参数

Table 1. Simulation parameters of radar system

参数	数值
载波波长(m)	0.05
系统带宽(MHz)	180
合成孔径时间(s)	3
卫星高度(km)	755
卫星速度(m/s)	6800
导弹作用距离(km)	46
导弹沿速度方向加速度(m/s²)	80
导弹垂直速度方向加速度(m/s²)	10
导弹速度(m/s)	1020
场景中心点位置(km)	(0,45,0)

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表 2 点目标成像性能评估

Table 2. Point target imaging performance evaluation

点目标	成像算法	方位向			距离向
点目标	成像算法	分辨率(m)	PSLR (dB)	ISLR (dB)	分辨率(m)	PSLR (dB)	ISLR (dB)
${P_1}$	TNCS算法	2.17	N/A	N/A	1.63	N/A	N/A
	FNCS算法	1.85	–10.54	–8.06	1.13	–11.69	–9.39
	所提算法	1.82	–13.28	–10.06	1.08	–13.27	–10.14
${P_2}$	TNCS算法	2.23	N/A	N/A	1.78	N/A	N/A
	FNCS算法	1.88	–10.47	–7.81	1.19	–10.23	–8.52
	所提算法	1.83	–13.26	–10.02	1.09	–13.26	–10.12

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