地基观测数据估计空间目标特性研究进展
doi: 10.11728/cjss2025.06.2024-0181 cstr: 32142.14.cjss.2024-0181
-
李徽 男, 1998年6月出生于安徽省淮北市, 现为中国科学院大学天文与空间科学学院硕士研究生, 主要研究方向为空间目标特性分析建模. E-mail: lihui@ynao.ac.cn -
李荣旺 男, 1985年1月出生于云南省大理白族自治州, 现为中国科学院云南天文台应用天文研究团组研究员, 硕士生导师, 中国科学院青促会会员, 云南省兴滇英才青年人才, 主要研究方向为人造天体动力学、空间碎片旋转特性等. E-mail: lirw@ynao.ac.cn
作者简介:
通讯作者:
Research Progress on Estimating Space Objects Characteristics Using Ground-based Observation Data
-
摘要: 空间活动日益频繁, 目标解体和碰撞生成大量空间碎片可能引发灾难性后果, 因此对空间目标进行监测与表征变得尤为重要. 空间目标的姿态、形状、材质等特性信息对于目标识别、碰撞规避和主动清除具有重要意义. 对空间态势感知领域的重要学术会议AMOS (Advanced Maui Optical and Space Surveillance Technologies)近年来文集中的相关技术论文进行系统分析, 涵盖地基观测数据在空间目标表征中的应用, 从姿态估计、形状估计到姿态演化以及机器学习辅助决策等, 研究结果可为空间目标综合分析提供丰富的技术手段和估计方法, 并为未来空间目标表征技术发展提供了有价值的参考. 此外, 针对特性估计相关数据日益丰富、反演算法愈发成熟的现状和趋势, 提出中国应该建立体系化的空间目标特性估计机制新思路.Abstract: With the rapid increase in space activities, the proliferation of space debris from space objects’ breakup and collisions poses catastrophic risks to orbital operations. Consequently, the monitoring and characterization of space objects—including their attitude, shape, and material properties—have become critical for target identification, collision avoidance, and active debris removal. This study systematically reviews relevant technical papers from recent proceedings of the AMOS Conference, a key academic forum in space situational awareness. The analysis encompasses ground-based observational data applications in space object characterization, attitude estimation, shape reconstruction, attitude evolution, and machine learning-assisted decision-making. These methodologies provide a comprehensive toolkit for the integrated analysis of space objects, offering valuable insights for future advancements in characterization technologies. Against the current situation and trend of increasingly abundant data related to characteristic estimation and increasingly mature propagation algorithms, this paper proposes a new idea that China should establish a systematic space target characteristic estimation mechanism.
-
Key words:
- Astrometry /
- Space objects /
- Light curves /
- Space situational awareness /
- Feature characterization /
- Machine learning
-
图 1 J2000历元赤道坐标下长征三号乙(CZ-3B)运载火箭上面级可能的翻滚轴方向
Figure 1. Possible tumble axis directions of CZ-3B upper stage in equatorial coordinates at J2000 epoch
图 2 各参数后验分布的最终估计
Figure 2. Final estimates of the posterior distributions of each parameter
图 3 航天飞机RGB图像第1, 5, 10, 100帧
Figure 3. The 1st, 5th, 10th, and 100th frame of the RGB shuttle sequence
图 4 在测试集上评估多分类模型得到的混淆矩阵
Figure 4. Confusion matrix of the multiclassification model evaluated on the test subset
图 6 空间目标特性估计体系
Figure 6. Schematic diagram of the space object characteristics estimation system
表 1 不同类型数据对17种特性描述的支持情况
Table 1. Different types of data Support for 17 properties description
目标特性 光学 雷达 红外 遥测信号 目标测量特性 位置 是 是 是 是 速度 是 是 是 是 目标物理特性 尺寸 ― 是 ― ― 质量 ― 支持 ― ― 平台类型 是 支持 ― ― 目标旋转特性 旋转速度 是 是 是 ― 旋转轴 是 是 是 ― 目标推进特性 推进类型 生命模式 生命模式 生命模式 ― 可用燃料 支持 ― ― ― 速度变化 生命模式 生命模式 生命模式 ― 目标电量特性 电能产生 ― ― 支持 ― 电能消耗 ― ― 支持 支持 目标其他特性 线框简图 是 是 ― ― 材料成分 是 ― ― ― 热辐射 ― ― 是 ― 任务状态 支持 支持 支持 是 气体排放 ― ― 是 ― 
下载: 导出CSV
-
[1] FURFARO R, LINARES R, REDDY V. Shape identification of space objects via light curve inversion using deep learning models[C]//2019 Advanced Maui Optical and Space Surveillance Technologies Conference. Wailea, Maui, Hawaii: Maui Economic Development Board, 2019 [2] ZHANG H L, WANG J, ZHANG Y Z, et al. Review of artificial intelligence applications in astronomical data processing[J]. Astronomical Techniques and Instruments, 2024, 1(1): 1-15 doi: 10.61977/ati2024001 [3] GOU Ruixin, DU Xiaoping, LIU Hao. Advances in attitude inversion of space object based on photometric data[J]. Laser :Times New Roman;">& Optoelectronics Progress, 2016, 53(10): 9-18 (苟瑞新, 杜小平, 刘浩. 光度数据反演空间目标姿态的研究进展[J]. 激光与光电子学进展, 2016, 53(10): 9-18GOU Ruixin, DU Xiaoping, LIU Hao. Advances in attitude inversion of space object based on photometric data[J]. Laser & Optoelectronics Progress, 2016, 53(10): 9-18 [4] WANG Yang, DU Xiaoping, FAN Chunlin. Progress of light curve inversion technology for resident space object characteristics[J]. Chinese Science Bulletin, 2017, 62(15): 1578-1590 (王阳, 杜小平, 范椿林. 地基光度曲线反演空间目标特征技术研究进展[J]. 科学通报, 2017, 62(15): 1578-1590 doi: 10.1360/N972016-01082WANG Yang, DU Xiaoping, FAN Chunlin. Progress of light curve inversion technology for resident space object characteristics[J]. Chinese Science Bulletin, 2017, 62(15): 1578-1590 doi: 10.1360/N972016-01082 [5] MA Baolin, ZHU Xuyu, XIONG Chengkang. Development overview of foreign space situation awareness system[J]. Tactical Missile Technology, 2025(1): 60-66,74 (马宝林, 朱旭宇, 熊承康. 国外太空态势感知系统发展综述[J]. 战术导弹技术, 2025(1): 60-66,74MA Baolin, ZHU Xuyu, XIONG Chengkang. Development overview of foreign space situation awareness system[J]. Tactical Missile Technology, 2025(1): 60-66,74 [6] LAMBERT J V, KISSELL K E. The early development of satellite characterization capabilities at the air force laboratories[C]//Advanced Maui Optical and Space Surveillance Technologies Conference. Wailea, Maui, Hawaii: Maui Economic Development Board, 2006 [7] RUSH K A, YOST M, SMITH L, et al. An application of the unscented Kalman filter for spacecraft attitude estimation on real and simulated light curve data[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [8] BLACKETER L D J. Angular velocity vector determination of spacecraft in flat-spin attitude states[C]//23rd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2022 [9] GALLEGO Á, DE ANDRÉS A, PAULETE C, et al. RSO characterization and attitude estimation with data fusion and advanced data simulation[C]//24th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [10] CLARK R, DAVE S, WAWROW J, et al. Performance of parameterization algorithms for resident space Object (RSO) attitude estimates[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [11] BURTON A, FRUEH C. Fast light curve inversion for regular and tumbling attitude motion[C]//24th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [12] BADURA G P, VALENTA C R. Physics-guided machine learning for satellite spin property estimation from light curves[C]//24th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [13] HROBÁR T, ŠILHA J, ZIGO M, et al. Attitude determination of cylindrical rocket bodies by using simultaneous bistatic photometric measurements[C]//2023 Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [14] CAMPBELL T, FURFARO R, REDDY V, et al. Bayesian approach to light curve inversion of 2020 SO[J]. The Journal of the Astronautical Sciences, 2022, 69(1): 95-119 doi: 10.1007/s40295-021-00301-z [15] Campbell T, Battle A, Gray B, et al. Spin axis and physical property inversion of moon-impactor Chang’e 5-t1 rocket body[C]//24th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [16] ŠILHA J, SCHILDKNECHT T, PITTET J N, et al. Comparison of ENVISAT’s attitude simulation and real optical and SLR observations in order to refine the satellite attitude model[C]//17th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [17] LIPS T, KANZLER R, BRESLAU A, et al. Debris attitude motion measurements and modeling - observation vs. simulation[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [18] POLO M C, ABAY R, GEHLY S, et al. Attitude detection of buccaneer RMM cubesat through experimental and simulated light curves in combination with telemetry data[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [19] BENSON C J, NAUDET C J, SCHEERES D J, et al. Radar and optical study of defunct GEO satellites[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [20] BENSON C J, NAUDET C J, SCHEERES D J, et al. Radar-derived spin states of defunct GEO satellites and rocket bodies[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference, 2021. Maui, Hawaii: Maui Economic Development Board, 2021 [21] BENSON C J, NAUDET C J, SCHEERES D J, et al. Radar and optical study of defunct geosynchronous satellites[J]. The Journal of the Astronautical Sciences, 2021, 68(3): 728-749 doi: 10.1007/s40295-021-00266-z [22] WATANABE K, HANADA T, FUJITA K. Dynamics observation of space objects using adaptive optics simulation and light curve analysis[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [23] SEITZER P, SCHACHTER J H, SZCZERBA M, et al. Optical tracking and attitude determination of LEO CubeSats with LEDs: a balloon demonstration[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [24] SANTONI F, SEITZER P, CARDONA T, et al. Optical tracking and orbit determination performance of self-illuminated small spacecraft: LEDSAT (LED-based SATellite)[J]. Advances in Space Research, 2018, 62(12): 3318-3334 doi: 10.1016/j.asr.2018.08.018 [25] BAZIK M, FLEWELLING B, MAJJI M, et al. Bayesian inference of spacecraft pose using particle filtering[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, Inc. , 2018 [26] ARAKAWA R, MATSUSHITA Y, HANADA T, et al. Attitude estimation of space objects using imaging observations and deep learning[C]//20th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2019 [27] LUCAS J, KYONO T, WERTH M, et al. Estimating satellite orientation through turbulence with deep learning[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [28] OKKELBERG K, LUCAS J, KYONO T, et al. Self-supervised auxiliary task learning for estimating satellite orientation[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2021 [29] KOBAYASHI D, BURTON A, FRUEH C. AI-assisted near-field monocular monostatic pose estimation of spacecraft[C]//24th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2023 [30] AMATO D, FURFARO R, ROSENGREN A J, et al. Attitude propagation of resident space objects with recurrent neural networks[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [31] PHELPS M, GAZAK J Z, SWINDLE T, et al. Inferring space object orientation with spectroscopy and convolutional networks[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2021 [32] PHELPS M, SWINDLE T, GAZAK J Z, et al. Improving spectral-based estimation of space object orientation[C]//23rd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2022 [33] ANTOLIN J, YU Z X, PRASAD S. Optical estimation of the 3d shape of a solar illuminated, reflecting satellite surface[C]//17th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [34] MCMAHON J W, SCHEERES D J. Shape estimation from lightcurves including constraints from orbit determination[C]//17th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [35] FAN S, FRIEDMAN A, FRUEH C. Satellite shape recovery from light curves with noise[C]//20th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2019 [36] CABRERA D V, UTZMANN J, FÖRSTNER R. Inversion of the shape of space debris from non-resolved optical measurements within SPOOK[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2021 [37] IKEDA N, NISHIMURA T, IWAHORI T, et al. Shape and orbit estimation techniques for space debris observation using the middle and upper atmosphere radar (MU radar)[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [38] JIA B, PHAM K D, BLASCH E, et al. Space object classification using fused features of time series data[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [39] MCQUAID I, MERKLE L D, BORGHETTI B, et al. Space object identification using deep neural networks[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [40] FURFARO R, LINARES R, REDDY V. Space objects classification via light-curve measurements: deep convolutional neural networks and model-based transfer learning[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [41] LINARES R, FURFARO R, REDDY V. Space objects classification via light-curve measurements using deep convolutional neural networks[J]. The Journal of the Astronautical Sciences, 2020, 67(3): 1063-1091 doi: 10.1007/s40295-019-00208-w [42] BADURA G, VALENTA C R, GUNTER B. Convolutional neural networks for inference of space object attitude status[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [43] BADURA G P, VALENTA C R, GUNTER B. Convolutional neural networks for inference of space object attitude status[J]. The Journal of the Astronautical Sciences, 2022, 69(2): 593-626 doi: 10.1007/s40295-022-00309-z [44] ABERCROMBIE M D, CALEF B, NADERI S. Light curve analysis of deep space objects in complex rotation states[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2021 [45] KERR E, PETERSEN E G, TALON P, et al. Using AI to analyse light curves for GEO object characterisation[C]//22nd Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2021 [46] POLO M C, ALENIN A, VAUGHN I, et al. GEO satellite characterization through polarimetry using simultaneous observations from nearby optical sensors[C]//17th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [47] PEARCE E C, FORD H A, SCHILDKNECHT T, et al. Rapid characterization of geosynchronous space debris with 5-color near-IR photometry[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [48] PEARCE E C, KRANTZ H, BLOCK A, et al. Multicolor and spectral characterization of space objects in the near-IR[C]//21st Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2020 [49] CORDELLI E, SCHLATTER P, SCHILDKNECHT T. Simultaneous multi-filter photometric characterization of space debris at the Swiss optical ground station and geodynamics observatory zimmerwald[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [50] BENSON C J, SCHEERES D J, RYAN W H, et al. Rotation state evolution of retired geosynchronous satellites[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [51] SAKAMOTO R, SCHEERES D J. Modeling energy dissipation and deformation in a tumbling defunct satellite using a finite element method[C]//20th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2019 [52] SPURBECK J, JAH M K, KUCHARSKI D, et al. Satellite characterization, classification, and operational assessment via the exploitation of remote photoacoustic signatures[C]//19th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2018 [53] FURFARO R, LINARES R, GAYLOR D, et al. Resident space object characterization and behavior understanding via machine learning and ontology-based Bayesian networks[C]//17th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [54] KELLY K G. Integrating machine learning into space operations[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 [55] RICHMOND D, SPOTO G. Comparison of phenomenology for satellite characterization[C]//16th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2016 [56] RICHMOND D, BRENNAN J. Satellite characterization data collection and analysis[C]//18th Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: Maui Economic Development Board, 2017 -
-
下载:
图(6) / 表(1)
计量
- 文章访问数: 477
- HTML全文浏览量: 174
- PDF下载量: 18
-
被引次数:
0(来源:Crossref)
0(来源:其他)
