1.哈尔滨工业大学电子与信息工程学院,黑龙江哈尔滨 150001
2.中国空间技术研究院遥感卫星总体部,北京 100094
3.华北水利水电大学电子工程学院,河南郑州 450046
[ "任航 男,2000年3月出生于河南省新乡市.现为哈尔滨工业大学博士研究生.主要研究方向为星载照射源下双基地SAR成像算法及其运动补偿.中国电子学会会员编号:E190185699A. E-mail: hangren@stu.hit.edu.cn" ]
[ "张云 女,1975年出生于黑龙江省虎林市.现为哈尔滨工业大学教授、博士生导师.主要研究方向为雷达信号处理、SAR成像、机器学习和遥感模式分析. E-mail: zhangyunhit@hit.edu.cn" ]
[ "吕争 男,1985年10月出生于辽宁省阜新市.现为中国空间技术研究院遥感卫星总体部高级工程师.主要研究方向为微波遥感卫星总体设计和遥感图像应用.E-mail: lvzheng_irss@spacechina.com" ]
[ "李高鹏 男,1976年11月出生于湖北省荆州市.现为哈尔滨工业大学研究员、硕士生导师.主要研究方向为新体制雷达、阵列信号处理、智能信息融合与识别等. E-mail: ligaopeng@hit.edu.cn" ]
[ "杨雪莹 女,2001年7月出生于黑龙江省齐齐哈尔市.现为哈尔滨工业大学硕士研究生.主要研究方向为星载/机载SAR成像与三维重构.E-mail: xueyingyang@stu.hit.edu.cn" ]
[ "任瑗 女,2005年9月出生于河南省新乡市.现为华北水利水电大学电子工程学院本科生.主要研究方向为信号处理和SAR成像.E-mail: 16638192761@163.com" ]
[ "化青龙 男,1995年出生于安徽省阜阳市.现为哈尔滨工业大学副研究员.主要研究方向为雷达图像处理和深度学习网络框架.中国电子学会会员编号:E190031354M.E-mail: huaqinglong@hit.edu.cn" ]
收稿:2025-03-16,
修回:2025-06-30,
纸质出版:2025-07-25
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任航, 张云, 吕争, 等. 基于改进等效单基的MEO星机BiSAR成像算法[J]. 电子学报, 2025, 53(07): 2513-2531.
REN Hang, ZHANG Yun, LÜ Zheng, et al. An Improved Monostatic Equivalent Imaging Algorithm for MEO-Airborne Bistatic SAR[J]. Acta Electronica Sinica, 2025, 53(07): 2513-2531.
任航, 张云, 吕争, 等. 基于改进等效单基的MEO星机BiSAR成像算法[J]. 电子学报, 2025, 53(07): 2513-2531. DOI:10.12263/DZXB.20250194
REN Hang, ZHANG Yun, LÜ Zheng, et al. An Improved Monostatic Equivalent Imaging Algorithm for MEO-Airborne Bistatic SAR[J]. Acta Electronica Sinica, 2025, 53(07): 2513-2531. DOI:10.12263/DZXB.20250194
中轨(Medium Earth Orbit,MEO)合成孔径雷达(Synthetic Aperture Radar,SAR)具有中等分辨率、宽幅观测、短重访周期等优势,结合机载SAR接收机构成双基系统,可突破传统低轨(Low Earth Orbit,LEO)星机双基地SAR的覆盖限制,具有广阔的应用前景.然而,MEO SAR因轨道曲率显著、回波传播时延较长,其成像几何构型更为复杂,导致传统LEO星机双基地SAR成像算法失效;相比之下,尽管地球同步轨道(Geosynchronous Earth Orbit,GEO)SAR也面临“走停”假设和轨迹曲率引起的偏差,但由于其平台高度高、运行速度缓慢、加速度极小,引起的非线性误差通常可通过二阶多项式近似模型予以补偿.MEO SAR平台运动速度与加速度均大得多,引发的高阶非线性相位误差更为严重,使得GEO斜距模型在MEO场景下难以满足精度要求.针对这些挑战,本文提出了一种基于改进等效单基的频域成像算法.首先结合MEO的轨道特性,创新性地引入轨道弯曲补偿因子,提出改进的非“走停”等效单基斜距模型,突破传统等效单基方法对高机动非线性轨迹的建模局限.在此基础上,本文利用级数反演的方法推导信号精确的频域形式,并考虑了场景的方位空变效应,精确补偿了MEO曲线轨迹及长传播时延引起的相位误差,且具有低计算复杂度.实验表明:相比传统方法,所提算法的点目标峰值旁瓣比、积分旁瓣比和分辨率均接近理论值,在扩展面目标仿真中,图像熵降低约30%,对比度提升约20%,可有效抑制MEO SAR复杂轨迹导致的散焦现象.
Medium Earth orbit synthetic aperture radar (MEO SAR) can achieve medium spatial resolution with a wide observable swath and short revisit time. The combination of MEO SAR illuminator and airborne SAR receiver could overcome the coverage limitations of traditional low Earth orbit (LEO) airborne BiSAR systems
demonstrating broad application prospects. However
due to the high orbital altitude
long propagation delay
and significant trajectory curvature of the MEO platform
the imaging geometry becomes more complex
and the conventional LEO-airborne bistatic SAR imaging algorithms become invalid. Although Geosynchronous Orbit (GEO) SAR systems also suffer from the phase errors induced by the “stop-go” assumption and trajectory curvature
their high altitude
low speed
and minimal acceleration allow the slant range variation to be approximated by second-order models. In contrast
MEO SAR has much higher velocity and acceleration
which aggravates high-order nonlinear phase errors
making conventional GEO slant range models inadequate for MEO scenarios. To address these challenges
this paper proposes an improved monostatic equivalent imaging algorithm for MEO-airborne bistatic SAR. This method establishes an MEO-airborne bistatic geometric model based on the orbit characteristics of MEO SAR
innovatively introduces an orbital curvature compensation factor
and proposes an improved “non-stop-go” equivalent slant range model. It overcomes the modelling limitations of traditional equivalent monostatic methods for high-maneuverability and curved trajectories. Furthermore
this paper employs series inversion to derive two-dimensional spectra while considering azimuth space-variant effects in the scene
ultimately developing an imaging algorithm suitable for MEO-airborne bistatic SAR. Experimental results demonstrate that compared with traditional methods
the proposed algorithm achieves peak sidelobe ratio
integrated sidelobe ratio
and resolution close to theoretical values for point targets. In extended target imaging of the proposed algorithm
the image entropy is reduced by 30% and contrast improved by 20% than the traditional equivalent monostatic method
effectively suppressing defocusing caused by MEO SAR’s complex orbital characteristics.
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