Highly Dynamic Doppler Space Target Situation Awareness Algorithm for Spaceborne ISAR
-
摘要: 在轨目标天基逆合成孔径雷达(ISAR)成像技术的发展为空间态势感知提供了关键技术支撑。针对天基ISAR空间目标成像中复杂相对运动导致的高阶三维空变距离徙动与相位误差问题，该文提出一种联合高分辨成像与姿态反演的态势感知算法，从而实现更为全面的空间目标状态评估过程。该文首先对卫星目标的成像特性进行分析，建立了目标多普勒参数与图像域散射点间的映射模型，并对空变多普勒参数的空间分布进行估计与重建；进而设计自适应区域分割机制实现三维空时误差的区域化一致性补偿，显著提升成像分辨率，同时基于卫星平面部件成像特性推导多普勒参数与卫星姿态间的显式关联，采用主成分分析法直接拟合平面系数反演目标姿态，避免依赖于传统的矩形状部件分割方法；最后，该文通过不同成像条件下的仿真结果验证了文中算法的有效性。Abstract:
Objective With the growing number of operational satellites in orbit, Space Situation Awareness (SSA) has become a critical capability for ensuring the safety of space operations. Traditional ground-based radar and optical systems face inherent limitations in tracking deep-space objects due to atmospheric interference and orbital obscuration. Therefore, spaceborne Inverse Synthetic Aperture Radar (ISAR) has emerged as a pivotal technology for on-orbit target characterization, offering all-weather, long-duration observation. However, higher-order Three-Dimensional (3D) spatial-variant range migration and phase errors, caused by the complex relative motion between a spaceborne ISAR platform and its target, can seriously degrade imaging quality. Meanwhile, conventional Two-Dimensional (2D) Range–Doppler (RD) imaging provides valuable intensity distributions of scattering points but remains a projection of the target’s 3D structure. The absence of geometric information limits accurate attitude estimation and collision risk assessment. To address these challenges and achieve more comprehensive SSA, this paper proposes a joint space target imaging and attitude estimation algorithm. Methods This paper proposes a joint space target imaging and attitude estimation algorithm composed of three main components: space target imaging characterization, high-resolution imaging, and attitude estimation. First, the imaging characteristics of satellite targets are analyzed to establish the mapping relationship between the image domain and the Doppler parameters of individual scattering points. Second, adaptive segmentation in the two-dimensional (2D) image domain combined with high-precision regional compensation is applied to obtain high-resolution imaging results. Finally, the spatial distribution characteristics of the Doppler parameters are exploited to derive an explicit expression for the second-order Doppler parameters and to estimate the planar component attitude of the target, such as that of the solar wing. Results and Discussions The proposed SSA method achieves high-resolution imaging even in the presence of orbital error and complex 3D spatial-variant Doppler error. Moreover, target attitude estimation can be performed without the need for rectangular component extraction. The effectiveness of the algorithm is verified through three simulation experiments. When the target adopts different attitudes, the method successfully produces both high-resolution imaging results and accurate target attitude estimation ( Fig. 7 ,Fig. 8 ). To further evaluate performance, comparative simulations are conducted (Fig. 9 ,Fig. 10 ). In addition, a method for estimating the long- and short-edge pointing of the satellite solar wing is presented in Section 3.3. The effectiveness of the proposed high-precision imaging algorithm for spinning targets is analyzed in Section 3.4, where the third simulation demonstrates the extended SSA capability of the algorithm (Fig. 11 ,Fig. 12 ).Conclusions This paper proposes a joint high-resolution imaging and attitude estimation algorithm to address the situational awareness requirements of highly dynamic Doppler space targets. First, the imaging characteristics of satellite targets and the mapping relationship between scattering points and higher-order Doppler parameters are derived. Second, an adaptive region segmentation algorithm is developed to compensate for 3D spatial-variant errors, thereby significantly enhancing imaging resolution. Meanwhile, an explicit correlation between Doppler parameters and satellite attitude is established based on the characteristics of planar components. Simulation results under different imaging conditions confirm the validity and reliability of the algorithm. Compared with conventional approaches, the proposed method achieves joint compensation of orbital and rotational errors. Furthermore, the attitude estimation process does not require rectangular component segmentation and remains effective even when rectangular components are partially obscured. -
[1] 黎吉顺, 尹灿斌, 徐灿, 等. 空间目标ISAR姿态估计技术综述[J/OL]. 电波科学学报, 2025: 1–12. http://www.cjors.cn/cn/article/doi/10.12265/j.cjors.2024236, 2025.LI Jishun, YIN Canbin, XU Can, et al. Review of ISAR-based attitude estimation techniques for space targets[J/OL]. Chinese Journal of Radio Science, 2025: 1–12. http://www.cjors.cn/cn/article/doi/10.12265/j.cjors.2024236, 2025. [2] 宫蕊, 汪玲, 徐楚, 等. 一种联合InISAR成像和微多普勒特征提取的空间目标转动矢量估计方法[J]. 电子与信息学报, 2021, 43(3): 640–649. doi: 10.11999/JEIT200648.GONG Rui, WANG Ling, XU Chu, et al. Total rotation vector estimation of space target combining InISAR imaging and micro-Doppler feature extraction[J]. Journal of Electronics & Information Technology, 2021, 43(3): 640–649. doi: 10.11999/JEIT200648. [3] ZHOU Yejian, XIE Pengfei, LI Chenwei, et al. Automatic dynamic estimation of on-orbit satellites through spaceborne ISAR imaging[J]. IEEE Transactions on Radar Systems, 2023, 1: 34–47. doi: 10.1109/TRS.2023.3267739. [4] CHEN Ruida, JIANG Yicheng, NI He, et al. Spaceborne ISAR imaging of space target with intrapulse motion compensation based on modified phase difference[J]. IEEE Geoscience and Remote Sensing Letters, 2025, 22: 4000305. doi: 10.1109/LGRS.2024.3505855. [5] 杨利超, 邢孟道, 孙光才, 等. 一种微波光子雷达ISAR成像新方法[J]. 电子与信息学报, 2019, 41(6): 1271–1279. doi: 10.11999/JEIT180661.YANG Lichao, XING Mengdao, SUN Guangcai, et al. A novel ISAR imaging algorithm for microwave photonics radar[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1271–1279. doi: 10.11999/JEIT180661. [6] LIU Yifei, YU Weidong, YANG Shenghui, et al. An effective space-borne ISAR high-resolution imaging approach for satellite on-orbit based on minimum entropy optimization[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17: 4523–4537. doi: 10.1109/JSTARS.2024.3359264. [7] WANG Yong and JIANG Yicheng. ISAR imaging of maneuvering target based on the L-class of fourth-order complex-lag PWVD[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3): 1518–1527. doi: 10.1109/TGRS.2009.2032296. [8] 杨利超, 高悦欣, 邢孟道, 等. 基于广义keystone和频率变标的微波光子ISAR高分辨实时成像算法[J]. 雷达学报, 2019, 8(2): 215–223. doi: 10.12000/JR18120.YANG Lichao, GAO Yuexin, XING Mengdao, et al. High resolution microwave photonics radar real-time imaging based on generalized keystone and frequency scaling[J]. Journal of Radars, 2019, 8(2): 215–223. doi: 10.12000/JR18120. [9] 李俊颜, 杨青, 李中余, 等. 基于空变多普勒参数聚类的微波光子ISAR高精度成像方法[J]. 电子学报, 2024, 52(12): 3941–3956. doi: 10.12263/DZXB.20240442.LI Junyan, YANG Qing, LI Zhongyu, et al. High-precision microwave photonic ISAR imaging method based on spatially variant doppler parameter clustering[J]. Acta Electronica Sinica, 2024, 52(12): 3941–3956. doi: 10.12263/DZXB.20240442. [10] 周叶剑, 张磊, 王虹现, 等. 多站ISAR空间目标姿态估计方法[J]. 电子与信息学报, 2016, 38(12): 3182–3188. doi: 10.11999/JEIT160603.ZHOU Yejian, ZHANG Lei, WANG Hongxian, et al. Attitude estimation for space satellite targets with multistatic ISAR systems[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3182–3188. doi: 10.11999/JEIT160603. [11] DU Rongzhen, ZHOU Zuobang, LIU Lei, et al. A new attitude estimation method of space target utilizing ISAR image sequence under low SNR[C]. 2021 CIE International Conference on Radar, Haikou, China, 2021: 57–61. doi: 10.1109/Radar53847.2021.10027965. [12] ZHOU Yejian, ZHANG Lei, and CAO Yunhe. Attitude estimation for space targets by exploiting the quadratic phase coefficients of inverse synthetic aperture radar imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(6): 3858–3872. doi: 10.1109/TGRS.2018.2888631. [13] WANG Jiadong, LI Yachao, SONG Ming, et al. Joint estimation of absolute attitude and size for satellite targets based on multi-feature fusion of single ISAR image[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5111720. doi: 10.1109/TGRS.2022.3159345. [14] SHAO Shuai, LIU Hongwei, and YAN Junkun. Integration of imaging and recognition for marine targets in fast-changing attitudes with multistation wideband radars[J]. IEEE Transactions on Aerospace and Electronic Systems, 2024, 60(2): 1692–1710. doi: 10.1109/TAES.2023.3339406. [15] DU Yuhan, JIANG Yicheng, and ZHOU Wei. An accurate two-step ISAR cross-range scaling method for Earth-orbit target[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(11): 1893–1897. doi: 10.1109/LGRS.2017.2725986. [16] 浮丹丹, 周绍光, 徐洋, 等. 基于主成分分析的点云平面拟合技术研究[J]. 测绘工程, 2014, 23(4): 20–23. doi: 10.3969/j.issn.1006-7949.2014.04.005.FU Dandan, ZHOU Shaoguang, XU Yang, et al. Point cloud plane fitting technology based on principal component analysis[J]. Engineering of Surveying and Mapping, 2014, 23(4): 20–23. doi: 10.3969/j.issn.1006-7949.2014.04.005. -
下载:
图(13)
计量
- 文章访问数: 24
- HTML全文浏览量: 8
- PDF下载量: 3
- 被引次数: 0
下载:
