基于尺度变换原理的SAR波数域成像算法

韦维; 朱岱寅; 吴迪

doi:10.12000/JR19112

基于尺度变换原理的SAR波数域成像算法

DOI: 10.12000/JR19112

南京航空航天大学电子信息工程学院雷达成像与微波光子技术教育部重点实验室南京 211106

基金项目: 国家重点研发计划(2017YFB0502700)，国家自然科学基金(61671240)，航空科学基金(20182052013)

详细信息

作者简介:
韦　维(1996–)，男，江苏人，硕士生。研究方向为超高分辨率合成孔径雷达成像技术。E-mail: weiw@nuaa.edu.cn

朱岱寅(1974–)，男，江苏人，教授，博士生导师。研究方向为合成孔径雷达/逆合成孔径雷达(SAR/ISAR)成像以及自聚焦算法，干涉SAR成像，SAR地面动目标指示，以及机载雷达动目标指示技术。自2018年开始担任《雷达学报》编委。E-mail: zhudy@nuaa.edu.cn

吴　迪(1982–)，男，河南人，副教授，硕士生导师。研究方向为雷达信号处理、地面动目标指示技术。E-mail: wudi82@nuaa.edu.cn

通讯作者:
朱岱寅 zhudy@nuaa.edu.cn

责任主编：林赟 Corresponding Editor: LIN Yun
中图分类号: TN957.5
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出版历程
- 收稿日期: 2019-12-16
- 修回日期: 2020-02-13
- 网络出版日期: 2020-04-01

Wavenumber Domain Algorithm Based on the Principle of Chirp Scaling for SAR Imaging

Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Funds: The National Key Research and Development Program of China (2017YFB0502700), The National Natural Science Foundation of China (61671240), The Aeronautical Science Foundation of China (20182052013)

More Information

Corresponding author: ZHU Daiyin, zhudy@nuaa.edu.cn

摘要

摘要: 距离徙动算法(RMA)作为一种合成孔径雷达(SAR)频域成像算法，理论上能够达到最优性能。然而，该算法采用逐像素点卷积运算实现Stolt映射，其计算效率无法满足SAR大数据量处理需求。据此，该文提出基于尺度变换原理(PCS)的RMA成像算法。首先，将SAR回波数据沿距离向进行划分，利用子带参考距离处2阶距离方位耦合项与高阶项对子带信号进行补偿；然后，转化非线性Stolt映射为线性形式；最后，利用PCS原理实现Stolt插值，以实现高效率的数据重采样。所提PCS-RMA算法仅利用快速傅里叶变换和复矢量相乘操作即可实现改进型Stolt映射，兼具良好的聚焦性能与较高的计算效率。基于多组仿真数据与X波段1.2 GHz带宽的机载SAR实测数据处理结果，验证了所提算法的有效性，同时该算法可进一步应用于弹载/星载/无人机载SAR数据的快速成像处理。
- 合成孔径雷达 /
- 改进型距离徙动算法 /
- 尺度变换原理 /
- 高分辨成像 /
- 子带划分
Abstract: As a frequency-domain algorithm for Synthetic Aperture Radar (SAR) imaging, the Range Migration Algorithm (RMA) can theoretically achieve optimal performance. However, because its Stolt mapping is performed using pixel-by-pixel convolution, the computational efficiency of RMA is inadequate for massive SAR data processing requirements. In this paper, we propose a modified RMA based on the Principle of Chirp Scaling (PCS). First, SAR echo data is divided along the range direction, and the subswath signal is compensated by the second-order range-azimuth coupling term and high-order terms at the reference distance. Then, the nonlinear Stolt mapping is modified to become linear. Finally, Stolt interpolation is realized using PCS to efficiently resample the processed data. Demonstrating both well-focused performance and high computational efficiency, the proposed PCS-RMA employs only fast Fourier transforms and complex vector multiplication operations to achieve modified Stolt mapping. The processing results of several simulation data and X-band-measured airborne SAR data with a pulse bandwidth of 1.2 GHz verify the effectiveness of the proposed algorithm. The proposed algorithm can also be employed for the rapid processing of missile-borne, spaceborne, and drone-borne SAR data.
- Synthetic Aperture Radar(SAR) /
- Modified Range Migration Algorithm(RMA) /
- Principle of Chirp Scaling(PCS) /
- High-resolution imaging /
- Subswath division

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图 1 聚束模式几何模型

Figure 1. Geometric model of spotlight mode

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图 2 残余相位误差

Figure 2. Residual phase error

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图 3 改进型Stolt插值处理流程

Figure 3. Processing flow of modified Stolt interpolation

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图 4 PCS-RMA算法处理流程

Figure 4. Processing flow of PCS-RMA

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图 5 点目标分布几何关系

Figure 5. Geometric relationship of point target distribution

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图 6 点目标IRF等高线

Figure 6. Contours of point target IRF

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图 7 点目标IRF距离向剖面

Figure 7. Range profiles of point target IRF

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图 8 点目标IRF方位向剖面

Figure 8. Azimuth profiles of point target IRF

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图 9 数据处理时间对比

Figure 9. Comparisons of data processing time

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图 10 RMA处理结果

Figure 10. Processing results of the traditional RMA

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图 11 PCS-RMA处理结果

Figure 11. Processing results of the proposed PCS-RMA

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表 1 点目标仿真参数

Table 1. Point target simulation parameters

参数	数值
载频	9.65 GHz
信号带宽	1.5 GHz
脉冲重复频率	1500 Hz
载机速度	100 m/s
中心斜距	10 km
方位向分辨率	0.1 m

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表 2 点目标IRF聚焦性能参数

Table 2. Focusing performance parameters of point target IRF

点目标	距离向			方位向
点目标	PSLR(dB)	ISLR(dB)	IRW(m)	PSLR(dB)	ISLR(dB)	IRW(m)
A	–13.3728	–11.5636	0.0990	–13.2710	–11.1409	0.1017
B	–13.4564	–11.5881	0.1001	–13.3030	–11.2275	0.1000
C	–13.5875	–9.8772	0.1001	–13.5265	–10.7503	0.1033

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