空间目标T/R-R型雷达多视角融合成像算法

doi:10.12305/j.issn.1001-506X.2024.09.14

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (9): 3019-3030.doi: 10.12305/j.issn.1001-506X.2024.09.14

空间目标T/R-R型雷达多视角融合成像算法

郭宝锋¹, 焦丽婷¹, 李胜², 朱晓秀³^,*, 薛东方¹, 孙慧贤¹

1. 中国人民解放军陆军工程大学石家庄校区, 河北石家庄 050003
2. 中国人民解放军63963部队, 北京 100072
3. 中国人民解放军32398部队, 北京 100192

收稿日期:2023-05-08 出版日期:2024-08-30 发布日期:2024-09-12
通讯作者: 朱晓秀
作者简介:郭宝锋(1987—), 男, 讲师, 博士, 主要研究方向为信号与信息处理、雷达成像技术
焦丽婷(1995—), 女, 硕士研究生, 主要研究方向为雷达信号处理、雷达图像融合
李胜(1987—), 男, 工程师, 博士, 主要研究方向为装备运用与论证
朱晓秀(1993—), 女, 工程师, 博士, 主要研究方向为雷达信号处理、雷达成像技术
薛东方(1983—), 男, 讲师, 硕士, 主要研究方向为雷达信号处理
孙慧贤(1980—), 男, 副教授, 博士, 主要研究方向为信息系统与通信工程
基金资助:
国家自然科学基金(61601496);河北省自然科学基金(F2019506031)

Multi-view fusion imaging algorithm for T/R-R radar of space targets

Baofeng GUO¹, Liting JIAO¹, Sheng LI², Xiaoxiu ZHU³^,*, Dongfang XUE¹, Huixian SUN¹

1. Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China
2. Unit 63963 of the PLA, Beijing 100072, China
3. Unit 32398 of the PLA, Beijing 100192, China

Received:2023-05-08 Online:2024-08-30 Published:2024-09-12
Contact: Xiaoxiu ZHU

摘要/Abstract

摘要：

针对T/R-R(transmitting receiving-receiving)构型雷达成像实际, 结合空间目标的轨道先验和双基地逆合成孔径雷达(inverse synthetic aperture radar, ISAR)成像的体制优势, 提出了一种基于复贝叶斯压缩感知(Bayesian compressed sensing, BCS)算法的T/R-R型雷达稀疏孔径多视角融合成像方法。所提方法在建立双站雷达融合成像模型的基础上, 利用Laplace先验在复数域建立目标的稀疏模型, 提高了算法的稀疏促进作用, 获得了高分辨目标图像。仿真实验结果表明, 所提方法不仅可实现双站雷达多视角的融合成像, 还可实现双站雷达各自存在稀疏孔径条件下的多视角融合成像, 进一步拓展了应用场景, 可有效提高方位分辨率和成像质量。

关键词: T/R-R型雷达, 空间目标, 多视角融合成像

Abstract:

A T/R-R (transmitting receiving-receiving) radar sparse aperture multi-view fusion imaging method based on the complex Bayesian compressed sensing (BCS) algorithm is proposed for the practical imaging of T/R-R configuration radar, taking into account the orbital priors of space targets and the advantages of the dual-station inverse synthetic aperture radar (ISAR) imaging system. On the basis of establishing a dual station radar fusion imaging model, the proposed method utilizes Laplace priors to establish a sparse model of the target in the complex domain, improving the sparsity promotion effect of the algorithm and obtaining high-resolution target images. The simulation experiment results show that the proposed method can not only achieve multi-view fusion imaging of dual station radar, but also achieve multi-view fusion imaging of dual-station radar with sparse aperture respectively, further expanding the application scenarios and effectively improving azimuth resolution and imaging quality.

Key words: T/R-R (transmitting receiving-receiving) radar, space target, multi-view fusion imaging

中图分类号:

TN958

郭宝锋, 焦丽婷, 李胜, 朱晓秀, 薛东方, 孙慧贤. 空间目标T/R-R型雷达多视角融合成像算法[J]. 系统工程与电子技术, 2024, 46(9): 3019-3030.

Baofeng GUO, Liting JIAO, Sheng LI, Xiaoxiu ZHU, Dongfang XUE, Huixian SUN. Multi-view fusion imaging algorithm for T/R-R radar of space targets[J]. Systems Engineering and Electronics, 2024, 46(9): 3019-3030.

图/表 16

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参数名称	参数值	参数名称	参数值
载频/GHz	10	脉冲重复频率/Hz	100
带宽/MHz	800	累积脉冲个数/个	100
采样率/GHz	1	旋转角速度/(rad/s)	0.026 5
脉冲宽度/μs	20	累积转角/(°)	1.5

算法	指标	SNR/dB
算法	指标	20	10	0
稀疏约束最优化算法	IC	51.35	46.49	39.38
稀疏约束最优化算法	TBR	29.54	25.47	20.16
本文算法	IC	54.98	51.14	46.28
本文算法	TBR	32.56	28.73	25.17

算法	指标	SNR/dB
算法	指标	20	10	0
稀疏约束最优化算法	IC	43.35	34.49	21.38
稀疏约束最优化算法	TBR	25.13	19.47	12.32
本文算法	IC	51.51	47.13	44.25
本文算法	TBR	30.17	26.85	23.35

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空间目标T/R-R型雷达多视角融合成像算法

Multi-view fusion imaging algorithm for T/R-R radar of space targets

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