基于单频时变阈值的1-bit SAR成像方法研究

赵博; 黄磊; 周汉飞; 张亮; 李强; 黄敏

doi:10.12000/JR18036

基于单频时变阈值的1-bit SAR成像方法研究

DOI: 10.12000/JR18036

深圳大学信息工程学院深圳 518060

基金项目: 国家自然科学基金（U1713217，61501485，61501300，61601300，61601304），中国博士后科学基金（2015M582413，2017M610547），广东省自然科学基金（2015A030311030），深圳市基础研究项目（ZDSYS201507081625213，JCYJ20160520165659418，JCYJ20170302142545828，JCYJ20150324140036835），深圳大学科研启动项目（201557，2016057）

详细信息

作者简介:
赵　博(1986–)，男，河南南阳人，博士，博士后。2015年在西安电子科技大学获得博士学位，现在深圳大学从事博士后研究工作。主要研究方向为雷达信号处理与电子对抗。E-mail: b_zhao@126.com

黄　磊(1975–)，男，广东湛江人，博士，特聘教授。主要研究方向为阵列信号处理、雷达信号处理

周汉飞(1981–)，男，博士，博士后。主要研究方向为雷达信号处理

通讯作者:
黄磊　 dr.lei.huang@ieee.org

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出版历程
- 收稿日期: 2018-04-28
- 修回日期: 2018-06-25
- 网络出版日期: 2018-08-28

1-bit SAR Imaging Method Based on Single-frequency Time-varying Threshold

College of Information Engineering, Shenzhen University, Shenzhen 518060, China

Funds: The National Natural Science Foundation of China (U1713217, 61501485, 61501300, 61601300, 61601304), The China Postdoctoral Science Foundation (2015M582413, 2017M610547), The Natural Science foundation of Guangdong Province, China (2015A030311030), The Foundation of Shenzhen City (ZDSYS201507081625213, JCYJ20160520165659418, JCYJ20170302142545828, JCYJ20150324140036835), The Shenzhen University (201557, 2016057)

摘要

摘要: 该文提出一种基于单频时变阈值的1-bit合成孔径雷达(SAR)成像方法，通过将回波数据与时变阈值比较，将其量化为1-bit采样数据，从而降低SAR回波数据的位宽，达到简化系统、提升效率的目的。传统的1-bit采样将信号与0阈值比较，这将造成信号相对幅度的非线性失真，影响成像质量。而随机时变阈值虽然能够保留幅度信息，却会引入额外的类噪声干扰。单频时变阈值将能够有效地保留1-bit采样量化中丢失的相对幅度信息，同时避免引入类噪声干扰，有效地提高了1-bit采样量化下的SAR成像质量。通过仿真实验定量分析了算法的成像聚焦质量、幅度信息保持能力，并通过对场景目标的成像验证了算法的有效性。
- 合成孔径雷达 /
- 1-bit采样 /
- 时变阈值
Abstract: This paper proposes a 1-bit Synthetic Aperture Radar (SAR) imaging method based on a single-frequency time-varying threshold. Synthetic aperture radar echoes are quantized to 1-bit sampling data by comparing the data with the threshold; this reduces the data-width of the SAR echoes, consequently simplifying the system and improving efficiency. The conventional 1-bit sampling compares the signal to a zero threshold, bringing nonlinear distortion to the relative amplitude and degrading the imaging quality. The random threshold can keep the amplitude information, but it introduces additional noise-like interferences. In contrary, the single-frequency time-varying threshold can maintain the amplitude information lost during the 1-bit sampling and quantization, and at the same time, eliminate noise-like interferences; thus, the imaging quality of SAR using 1-bit sampling and quantization can be improved. The focusing quality and the amplitude-maintaining ability of the proposed approach is quantitatively analyzed, and the effectiveness of the approach is verified by an imaging experiment on a scene.
- Synthetic Aperture Radar (SAR) /
- 1-bit sampling /
- Time-varying threshold

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图 1 乘法运算实现框图

Figure 1. Realization block of multiplication

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图 2 单散射点高分辨距离像

Figure 2. High resolution range profile of the single scatterer

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图 3 多散射点高分辨距离像

Figure 3. High resolution range profile of multiple scatterers

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图 4 2维SAR成像结果

Figure 4. 2-Dimension SAR imaging results

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图 5 2维SAR成像结果(局部)

Figure 5. 2-Dimension SAR imaging results (Local)

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表 1 SAR参数

Table 1. SAR parameters

参数名称	参数值
信号带宽(MHz)	300
脉冲宽度(μs)	1
采样率(GHz)	6.9
载频(GHz)	37.6
单频阈值频率(GHz)	16.2
信号阈值比(dB)	0
场景中心斜距(km)	10
天线孔径(m)	1
载机速度(m/s)	50
脉冲重复频率(Hz)	400

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表 2 单散射点聚焦质量指标

Table 2. Focusing quality indexes of the single scatterer

采样方法	PSLR (dB)		ISLR (dB)		IRW (m)
采样方法	均值	方差	均值	方差	均值	方差
传统采样	–13.7217	–	–10.1301	–	0.4435	–
传统1-bit采样	–13.4556	–	–9.3684	–	0.4435	–
Gaussian 1-bit采样	–13.4054	0.0059	–8.0347	0.0007	0.4435	0.2163×10^–5
Sinusoid 1-bit采样	–13.8106	0.0016	–9.3048	0.0005	0.4474	0.1621×10^–5

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表 3 多散射点幅度质量指标

Table 3. Amplitude quality indexes of multiple scatterers

采样方法	幅度1			幅度2			幅度3
采样方法	均值	误差	方差	均值	误差	方差	均值	误差	方差
传统采样	0.9729	2.71%	–	1.9683	1.58%	–	2.9775	0.75%	–
传统1-bit采样	0.1818	–	–	0.3185	–	–	0.5067	–	–
传统1-bit采样(缩放)	1.1311	13.11%	–	1.7710	11.45%	–	3.0834	2.78%	–
Gaussian 1-bit采样	1.0477	4.77%	0.0633	1.9870	0.65%	0.0629	2.9920	0.27%	0.0617
Sinusoid 1-bit采样	1.0181	1.81%	0.0377	2.0186	0.93%	0.0189	2.9812	0.63%	0.0108

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