分布式MIMO-ISAR子图像融合方法

谷文堃; 王党卫; 马晓岩

doi:10.12000/JR16042

分布式MIMO-ISAR子图像融合方法

DOI: 10.12000/JR16042

空军预警学院武汉 430019

基金项目:

国家自然科学基金 61179015

详细信息

作者简介:
谷文堃 (1984-), 男, 籍贯山东济南, 工作单位为94326部队, 助理工程师。现为空军预警学院信息与通信工程专业在读博士研究生。研究方向为MIMO雷达信号处理。E-mail:guwenkun@hotmail.com

王党卫 (1976-), 男, 籍贯陕西杨凌, 于2006年在国防科技大学取得博士学位。现为空军预警学院副教授。主要研究方向为MIMO雷达系统及信号处理、雷达目标成像与识别。E-mail:wdwjane@tom.com

马晓岩 (1961-), 男, 籍贯湖北蒲圻, 于2002年在清华大学获得博士学位。现为空军预警学院教授。主要研究方向为雷达系统设计及目标检测与识别。E-mail:lyma_xiaoyan@126.com

通讯作者:
谷文堃guwenkun@hotmail.com

中图分类号: TN958
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- 被引次数: 0
出版历程
- 收稿日期: 2016-02-22
- 修回日期: 2016-03-22
- 网络出版日期: 2017-02-28

Distributed MIMO-ISAR Sub-image Fusion Method

Air Force Early Warning Academy, Wuhan 430019, China

Funds:

The National Natural Science Foundation of China 61179015

摘要

摘要: 高机动目标雷达截面积（Radar Cross Section，RCS）的快速起伏，容易对常规单站逆合成孔径雷达（Inverse Synthetic Aperture Radar，ISAR）成像性能的稳定性造成影响。针对这一问题，该文提出了一种基于频率分集分布式多输入多输出逆合成孔径雷达（Multiple Input Multiple Output-Inverse Synthetic Aperture Radar，MIMO-ISAR）子图像融合的成像方法。首先建立了分布式MIMO-ISAR不同通道所获取的2维ISAR图像解析表达式，导出了距离和方位畸变因子，通过对不同通道所获取ISAR图像畸变的补偿，实现了频率分集分布式MIMOISAR融合成像。仿真实验结果证实了提出方法的有效性。
- 多输入多输出雷达 /
- 分布式雷达 /
- 逆合成孔径雷达 /
- 图像融合 /
- 正交频分复用
Abstract: The fast fluctuation associated with maneuvering a target's radar cross-section often affects the imaging performance stability of traditional monostatic Inverse Synthetic Aperture Radar (ISAR). To address this problem, in this study, we propose an imaging method based on the fusion of sub-images of frequencydiversity-distributed multiple Input-Multiple Output-Inverse Synthetic Aperture Radar (MIMO-ISAR). First, we establish the analytic expression of a two-dimensional ISAR sub-image acquired by different channels of distributed MIMO-ISAR. Then, we derive the distance and azimuth distortion factors of the image acquired by the different channels. By compensating for the distortion of the ISAR image, we ultimately realize distributed MIMO-ISAR fusion imaging. Simulations verify the validity of this imaging method using distributed MIMOISAR.
- Multiple Input Multiple Output (MIMO) radar /
- Distributed radar /
- Inverse Synthetic Aperture Radar (ISAR) /
- Image fusion /
- Orthogonal Frequency Division Multiplexing (OFDM)

HTML全文

图 1 分布式MIMO-ISAR观测模型

Figure 1. Distributed MIMO-ISAR measurement model

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图 2 接收机结构

Figure 2. Receiver configuration

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图 3 成像流程

Figure 3. Imaging process

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图 4 飞机几何模型

Figure 4. Plane geometry model

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图 5 各通道子图像 (M²=25, SNR=10 dB)

Figure 5. Sub-image of each channel (M²=25, SNR=10 dB)

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图 6 最终成像结果 (SNR=10 dB)

Figure 6. Final image (SNR=10 dB)

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图 7 不同SNR下的成像结果

Figure 7. Images in different SNR values

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