面向预警监视任务的天基雷达研究进展

doi:10.12305/j.issn.1001-506X.2025.10.08

摘要/Abstract

摘要：

随着空间技术的快速发展，天基雷达系统已成为全球监视和战略预警的重要技术手段，然而天基雷达系统在遂行太空环境下的空间目标预警监视任务需解决诸多技术难题。近年来，针对天基雷达的系统设计与关键技术开展广泛研究，在大型可展开天线技术、空间环境下的检测跟踪技术、数据处理与信息传输链路、天基传感器调度等技术方向已经形成诸多研究成果。本文介绍天基雷达关键技术的发展脉络，从最初的导弹预警卫星演化到目前的多功能综合监测系统，并递进地梳理天基动平台场景面向检测、跟踪、逆合成孔径雷达成像、雷达组网与资源调度5类任务需求的研究内容和研究进展，为面向空间预警监视任务的天基雷达关键技术研究提供纵向和横向的对比视角。在目前研究的基础上，分析天基雷达系统的优势与面临的挑战，进一步给出天基雷达预警监视任务中潜在的研究方向和未来的发展趋势。

关键词: 天基雷达, 空间目标监视, 预警监视任务, 雷达任务需求

Abstract:

With the rapid advancement of space technology, space-based radar （SBR） system becomes a important technology for global surveillance and strategic early warning. However, SBR system still face many technical challenges in the early warning and surveillance （EWS） task of space targets in the space environment. In recent years, extensive research has been conducted on the system design and key technologies of space-based radar, resulting in numerous research achievements in areas such as large-scale deployable antenna technology, detection and tracking technology in space environments, data processing and information transmission links, and space-based sensor scheduling. This paper introduces the development trajectory of key SBR technologies, from the earliest missile early warning satellites to the current multifunctional integrated surveillance systems, and systematically reviews the main research content and progress in tasks oriented towards detection, tracking, inverse synthetic aperture radar （ISAR） imaging, radar networking and resource allocation, providing a vertical and horizontal comparative perspective for the study of key technologies of SBR for space EWS tasks. On the basis of current research, the advantages and challenges of SBR system is further analyzed, and potential research directions and future development trends in the EWS tasks of space-based radar are proposed.

Key words: space-based radar (SBR), space target surveillance, early warning and surveillance (EWS) task, radar mission requirement

中图分类号:

TN 957

郑舒予, 杨庆伟, 蒋李兵, 王壮. 面向预警监视任务的天基雷达研究进展[J]. 系统工程与电子技术, 2025, 47(10): 3199-3217.

Shuyu ZHENG, Qingwei YANG, Libing JIANG, Zhuang WANG. Research progress on space-based radar for early warning and surveillance task[J]. Systems Engineering and Electronics, 2025, 47(10): 3199-3217.

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参考文献 123

1	袁浩轩. 基于复数域深度学习的ISAR机动空间目标识别方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2024.
	YUAN H X. Research on recognition method of maneuvering space target in ISAR image based on complex-valued deep learning[D]. Harbin: Harbin Institute of Technology, 2024.
2	李青, 林幼权, 武楠. 美国天基预警雷达发展历程及现状分析[J]. 现代雷达, 2018, 40 (1): 7- 10.
	LI Q, LIN Y Q, WU N. Analysis of development history and status for American space-base early warning radar[J]. Modern Radar, 2018, 40 (1): 7- 10.
3	CANTAFIO L J. Space-based radar handbook[M]. Norwood: Artech House, 1989.
4	贲德, 林幼权. 天基监视雷达[J]. 现代雷达, 2005, 27 (4): 1- 4. doi: 10.3969/j.issn.1004-7859.2005.04.001
	BEN D, LIN Y Q. Space-base surveillance radar[J]. Modern Radar, 2005, 27 (4): 1- 4. doi: 10.3969/j.issn.1004-7859.2005.04.001
5	贲德, 龙伟军. 天基雷达的关键技术[J]. 数据采集与处理, 2013, 28 (4): 391- 396. doi: 10.3969/j.issn.1004-9037.2013.04.001
	BEN D, LONG W J. Key technology of space-based radar[J]. Journal of Data Acquisition and Processing, 2013, 28 (4): 391- 396. doi: 10.3969/j.issn.1004-9037.2013.04.001
6	宋万均, 马志昊, 刁华飞. 美国空间态势感知力量研究[J]. 中国航天, 2019, 48 (4): 48- 51. doi: 10.3969/j.issn.1002-7742.2019.04.012
	SUN W J, MA Z H, DIAO H F. Study on the ability of U. S. space situation awareness[J]. Aerospace China, 2019, 48 (4): 48- 51. doi: 10.3969/j.issn.1002-7742.2019.04.012
7	林幼权, 武楠. 天基预警雷达[M]. 北京: 国防工业出版社, 2017.
	LIN Y Q, WU N. Space based early warning radar[M]. Beijing: National Defense Industry Press, 2017.
8	潘洁. 稀疏阵列天基雷达系统分析和运动目标成像探测技术研究[D]. 北京: 中国科学院大学, 2019.
	PAN J. Study on sparse array space-based radar system analysis and moving target imaging detection technology[D]. Beijing: Chinese Academy of Sciences, 2019.
9	李道京, 刘波, 尹建凤, 等. 高分辨率雷运动目标成像探测技术[M]. 北京: 国防工业出版社, 2014.
	LI D J, LIU B, YIN J F, et al. High resolution radar moving target imaging detection technology[M]. Beijing: National Defense Industry Press, 2014.
10	张泽. 空间目标的SAR/ISAR成像方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2019.
	ZHANG Z. Research on SAR/ISAR imaging method for space target[D]. Harbin: Harbin Institute of Technology, 2019.
11	杜玉晗. 地基/星载逆合成孔径雷达空间目标成像研究[D]. 哈尔滨: 哈尔滨工业大学, 2020.
	DU Y H. Research on ground-based/spaceborne inverse synthetic aperture radar imaging for space targets[D]. Harbin: Harbin Institute of Technology, 2020.
12	潘洁, 李道京, 周建卫, 等. 大型稀疏阵列天基雷达系统分析[J]. 电子与信息学报, 2016, 38 (12): 3269- 3274.
	PAN J, LI D J, ZHOU J W, et al. Space-based radar system analysis based on large scale sparse array[J]. Journal of Electronics & Information Technology, 2016, 38 (12): 3269- 3274.
13	张野. 空间目标太赫兹雷达三维成像技术研究[D]. 长沙: 国防科技大学, 2020.
	ZHANG Y. Research on Terahertz radar-based space targets 3D imaging techniques[D]. Changsha: National University of Defence Technology, 2020.
14	郭俊川. 基于太赫兹雷达的空间碎片高分辨三维成像技术研究[D]. 成都: 电子科技大学, 2022.
	GUO J C. Research on three-dimensional imaging technology of space debris based on Terahertz radar[D]. Chengdu: University of Electronic Science and Technology of China, 2020.
15	王海涛, 朱根才, 贲德, 等. 基于先前CPI 多维数据的天基雷达信号处理算法[J]. 宇航学报, 2008, 29 (2): 665- 669. doi: 10.3873/j.issn.1000-1328.2008.02.051
	WANG H T, ZHU G C, BEN D. Space-based radar signal processing algorithm based on previous CPI multidimensional data[J]. Journal of Astronautics, 2008, 29 (2): 665- 669. doi: 10.3873/j.issn.1000-1328.2008.02.051
16	王海涛, 朱根才, 贲德, 等. 基于有色载入技术的天基雷达信号处理算法[J]. 南京航空航天大学学报, 2008, 40 (5): 651- 654.
	WANG H T, ZHU G C, BEN D, et al. Signal process algorithm for space-based radar based on color loading[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2008, 40 (5): 651- 654.
17	王海涛, 朱根才, 贲德, 等. 自然图景的天基监视雷达地杂波仿真[J]. 应用科学学报, 2008, 26 (5): 526- 530.
	WANG H T, ZHU G C, BEN D, et al. Land clutter simulation of space-based surveillance radar for natural scene[J]. Journal of Applied Sciences electronics and Information Engineering, 2008, 26 (5): 526- 530.
18	王海涛, 叶琦, 刘爱芳, 等. 基于自适应波形设计的天基雷达目标检测方法[J]. 宇航学报, 2013, 34 (8): 1130- 1136.
	WANG H T, YE Q, LIU A F, et al. Target detection based on adaptive waveform design for space based radar[J]. Journal of Astronautics, 2013, 34 (8): 1130- 1136.
19	汤春林. 天基AMTI雷达信号处理若干关键技术研究[D]. 成都: 电子科技大学, 2013.
	TANG C L. Research on the key techniques of signal processing in space-based AMTI radar[D]. Chengdu: University of Electronic Science and Technology of China, 2013.
20	王微. 天基预警雷达信号处理关键技术研究[D]. 成都: 电子科技大学, 2019.
	WANG W. Research on the key techniques of signal processing for spaceborne early warning radar[D]. Chengdu: University of Electronic Science and Technology of China, 2019.
21	江朝抒, 汪学刚, 陈祝明. 一种分布式星载单脉冲雷达GMTI方法[J]. 电子学报, 2010, 38 (4): 949- 953.
	JIANG C S, WANG X G, CHEN Z M. GMTI for distributed space-based monopulse radar[J]. Acta Electronica Sinica, 2010, 38 (4): 949- 953.
22	冯晶晶, 陈祝明, 江朝抒. 非均匀分布式星载雷达栅瓣抑制技术研究[J]. 现代雷达, 2010, 4, 50- 53. doi: 10.3969/j.issn.1004-7859.2010.04.013
	FENG J J, CHEN Z M, JIANG C S. Grating lobes suppression for non-uniform distributed space-based radar[J]. Modern Radar, 2010, 4, 50- 53. doi: 10.3969/j.issn.1004-7859.2010.04.013
23	邢孟道, 李真芳, 保铮, 等. 分布式小卫星雷达空时频成像方法研究[J]. 宇航学报, 2005, 26, 70- 77. doi: 10.3321/j.issn:1000-1328.2005.z1.014
	XING M D, LI Z F, BAO Z, et al. Study of distributed micro-satellites radar space-time-frequency imaging method[J]. Journal of Astronautics, 2005, 26, 70- 77. doi: 10.3321/j.issn:1000-1328.2005.z1.014
24	李真芳, 王洪洋, 保铮, 等. 分布式小卫星雷达阵列误差估计与校正方法[J]. 系统工程与电子技术, 2004, 26 (9): 1159- 1162. doi: 10.3321/j.issn:1001-506X.2004.09.002
	LI Z F, WANG H Y, BAO Z, et al. Approach to array error estimation for distributed micro-satellite SAR systems[J]. Systems Engineering and Electronics, 2004, 26 (9): 1159- 1162. doi: 10.3321/j.issn:1001-506X.2004.09.002
25	王彤, 保铮, 廖桂生. 天基分布式雷达GMTI方法[J]. 电子学报, 2006, 34 (3): 399- 403. doi: 10.3321/j.issn:0372-2112.2006.03.004
	WANG T, BAO Z, LIAO G S. A new GMTI method of space-based distributed radar[J]. Acta Electronica Sinica, 2006, 34 (3): 399- 403. doi: 10.3321/j.issn:0372-2112.2006.03.004
26	陆必应, 梁甸农. 天基稀疏阵杂波自由度分析[J]. 电子学报, 2006, 34 (6): 1134- 1137. doi: 10.3321/j.issn:0372-2112.2006.06.033
	LU B Y, LIANG D N. Estimation of the clutter rank of space-based sparse array[J]. Acta Electronica Sinica, 2006, 34 (6): 1134- 1137. doi: 10.3321/j.issn:0372-2112.2006.06.033
27	陆必应. 天基GMTI与解模糊方法研究[D]. 长沙: 国防科技大学, 2006.
	LU B Y. Research on space-based GMTI and ambiguity mitigation method[D]. Changsha: National University of Defence Technology, 2006.
28	张增辉. 天基雷达空时自适应杂波抑制技术[D]. 长沙: 国防科学技术大学, 2008.
	ZHANG Z H. Space-time adaptive processing for clutter mitigation of space based radar[D]. Changsha: National University of Defence Technology, 2008.
29	伍勇, 汤俊, 彭应宁. 正交模式分布式小卫星雷达杂波抑制性能研究[J]. 系统工程与电子技术, 2009, 31 (7): 1529- 1533. doi: 10.3321/j.issn:1001-506X.2009.07.001
	WU Y, TANG J, PENG Y N. Study on clutter suppression performance of distributed aperture radar using orthogonal waveforms[J]. Systems Engineering and Electronics, 2009, 31 (7): 1529- 1533. doi: 10.3321/j.issn:1001-506X.2009.07.001
30	李道京, 刘波, 尹建风, 等. 天基毫米波空间碎片观测雷达系统分析与设计[J]. 宇航学报, 2010, 31 (12): 2746- 2753. doi: 10.3873/j.issn.1000-1328.2010.12.019
	LI D J, LIU B, YIN J F, et al. Analysis and design of spaceborne MMW radar for space debris observation system[J]. Journal of Astronautics, 2010, 31 (12): 2746- 2753. doi: 10.3873/j.issn.1000-1328.2010.12.019
31	刘波, 李道京, 尹建风, 等. 基于天基雷达的空间目标轨道预测[J]. 空间科学学报, 2010, 30 (6): 532- 536. doi: 10.11728/cjss2010.06.532
	LIU B, LI D J, YIN J F, et al. Space object orbit prediction based on spaceborne radar[J]. Chinese Journal of Space Science, 2010, 30 (6): 532- 536. doi: 10.11728/cjss2010.06.532
32	康雪艳, 江碧涛, 张云华, 等. 天基多载频稀疏阵STAP方法的幅相误差影响[J]. 测试技术学报, 2009, 23 (3): 221- 225. doi: 10.3969/j.issn.1671-7449.2009.03.008
	KANG X Y, JIANG B T, ZHANG Y H, et al. Analysis of amplitude and phase errors on STAP for multi-carrier-frequency space based sparse array[J]. Journal of Test and Measurement technology, 2009, 23 (3): 221- 225. doi: 10.3969/j.issn.1671-7449.2009.03.008
33	PERRY R P, DIPIETRO R C, FANTE R L. SAR imaging of moving targets[J]. IEEE Trans. on Aerospace and Electronic Systems, 1999, 35 (1): 188- 200. doi: 10.1109/7.745691
34	张顺生, 曾涛. 基于keystone变换的微弱目标检测[J]. 电子学报, 2005, 9, 1675- 1678. doi: 10.3321/j.issn:0372-2112.2005.09.033
	ZHANG S S, ZENG T. Weak target detection based on keystone transform[J]. Acta Electronica Sinica, 2005, 9, 1675- 1678. doi: 10.3321/j.issn:0372-2112.2005.09.033
35	XU J, YU J, PENG Y N, et. al. Radon-Fourier transform （RFT） for radar target detection （III）: optimality and fast implementations[J]. IEEE Trans. on Aerospace and Electronic Systems, 2012, 48 (2): 991- 1004. doi: 10.1109/TAES.2012.6178044
36	SUN Z, LI X L, CUI G L, et al. Hypersonic target detection and velocity estimation in coherent radar system based on scaled Radon Fourier transform[J]. IEEE Trans. on Vehicular Technology, 2020, 69 (6): 6525- 6540. doi: 10.1109/TVT.2020.2988990
37	SUN J, XING M D. High-speed multi-target detection with narrowband radar[J]. IET Radar Sonar and Navigation, 2010, 4(4): 595603.
38	CHEN X L, JIAN G, LIU N B, et al. Maneuvering target detection via radon-fractional Fourier transform-based long-time coherent integration[J]. IEEE Trans. on Signal Processing, 2014, 62(4): 939953.
39	CHEN X L, CAI F Q, YU C, et al. Radon-fractional Fourier transform and its application to radar maneuvering target detection[C]//Proc. of the International Conference on Radar, 2013: 346−350.
40	JIN K, LI G Q, LAI T, et al. A novel long-time coherent integration algorithm for Doppler-ambiguous radar maneuvering target detection[J]. IEEE Sensors Journal, 2020, 20 (16): 9394- 9407. doi: 10.1109/JSEN.2020.2988583
41	JIN K, ZHANG H M, QI Y L, et al. Radar coherent detection and parameter estimation for maneuvering target based on KT-CICPF[C]//Proc. of the IEEE Advanced Information Technology, Electronic and Automation Control Conference, 2019: 166−170.
42	LI X L, SUN Z, YI W, et al. Radar detection and parameter estimation of high-speed target based on MART-LVT[J]. IEEE Sensors Journal, 2019, 19 (4): 1478- 1486. doi: 10.1109/JSEN.2018.2882198
43	ZHANG J, DING T, ZHANG L R. Longtime coherent integration algorithm for high-speed maneuvering target detection using space-based bistatic radar[J]. IEEE Trans. on Geoscience and Remote Sensing, 2020, 60, 5100216.
44	DING T, ZHANG J, TANG S Y. A novel iterative inner-pulse integration target detection method for bistatic radar[J]. IEEE Trans. on Geoscience and Remote Sensing, 2022, 60, 5114915.
45	ZHENG S Y, JIANG L B, YANG Q W, et al. GS-orthogonalization OMP method for space target detection via bistatic space-based radar[J]. Chinese Journal of Aeronautics, 2024, 37(7): 333−351.
46	李小龙. 高速机动目标长时间相参积累算法研究[D]. 成都: 电子科技大学, 2017.
	LI X L. Research on long time coherent integration algorithm for high speed maneuvering target[D]. Chengdu: University of Electronic Science and Technology of China, 2017.
47	FANG X, CAO Z J, MIN R, et al. Radar maneuvering target detection based on two steps scaling and fractional Fourier transform[J]. Signal Processing, 2018, 155, 1- 13.
48	HUANG P H, LIAO G S. An approach for refocusing of ground moving target without target motion parameter estimation[J]. IEEE Trans. on Geoscience and Remote Sensing, 2017, 55 (1): 336- 350. doi: 10.1109/TGRS.2016.2606437
49	ZHENG J B, ZHANG J C, XU S W, et al. Radar detection and motion parameters estimation of maneuvering target based on the extended keystone transform[J]. IEEE Access, 2018, 6 (2): 76060- 76074.
50	HUANG P H, LIAO G S, YANG Z, et al. A fast SAR imaging method for ground moving target using a second-order WVD transform[J]. IEEE Trans. on Geoscience and Remote Sensing, 2016, 54 (4): 1940- 1956. doi: 10.1109/TGRS.2015.2490582
51	黄鹏辉. 复杂运动目标长时间相参积累方法研究[D]. 西安: 西安电子科技大学, 2017.
	HUANNG P H. Research on long-time coherent integration method for complex moving target detection[D]. Xi’an: Xidian University, 2017.
52	柳超, 王月基. 对海探测雷达多目标跟踪技术综述[J]. 雷达学报, 2021, 10 (1): 100- 115. doi: 10.12000/JR20081
	LIU C, WANG Y J. Review of multi-target tracking technology for marine radar[J]. Journal of Radars, 2021, 10 (1): 100- 115. doi: 10.12000/JR20081
53	BARSHALOM Y, FORTMANN T E. Multitarget-multisensor tracking: principles and techniques[J]. IEEE Aerospace and Electronics Systems Magzine, 1996, 11 (2): 41- 44.
54	BARSHALOM Y. Tracking methods in a multitarget environment[J]. IEEE Trans. on Automatic Control, 1975, 20 (4): 439- 449.
55	FORTMANN T E, BAR-SHALOM Y, SCHEFFLER J D. Sonar tracking with a mobile robot[J]. IEEE Journal of Oceanic Engineering, 1988, 13 (2): 87- 95.
56	BLOM H A P, BAR-SHALOM Y. The interacting multiple model algorithm for systems with Markovian switching coefficients[J]. IEEE Trans. on Automatic Control, 1988, 33 (8): 780- 783. doi: 10.1109/9.1299
57	KROLIK J S, KAILATH T. New results in recursive identification and tracking[J]. IEEE Trans. on Automatic Control, 1982, 27 (1): 126- 131.
58	BLACKMAN S. Multiple hypothesis tracking for multiple target tracking[J]. IEEE Aerospace and Electronic Systems Magazine, 1995, 10 (1): 15- 21.
59	盛涛, 夏海宝, 杨永建, 等. 密集杂波环境下的简化JPDA多目标跟踪算法[J]. 信号处理, 2020, 36 (8): 1280- 1287.
	SHENG T, XIA H B, YANG Y J, et al. A simplified JPDA multi-target tracking algorithm for dense clutter environment[J]. Journal of Signal processing, 2020, 36 (8): 1280- 1287.
60	REID D B. An algorithm for tracking multiple targets[J]. IEEE Trans. on Automatic Control, 1979, 24 (6): 843- 854. doi: 10.1109/TAC.1979.1102177
61	BLACKMAN S, POPOLI R. Design and analysis of modern tracking systems[M]. Norwood: Artech House, 1999.
62	JEFFREY K U. Algorithms for multiple target tracking[J]. American Scientist, 1992, 80 (2): 128- 134.
63	BLACKMAN S S, POPOLI R. Design and analysis of modern tracking systems[M]. Boston: Artech House, 1999.
64	KURIEN T. Issues in the design of practical multitarget tracking algorithms[M]//BAR-SHALOM Y. Multitarget multisensor tracking: advanced applications. Norwood: Artech House, 1990: 43−83.
65	SATHYAN T, SINHA A, KIRUBARAJAN T, et al. MDA-based data association with prior track information for passive multitarget tracking[J]. IEEE Trans. on Aerospace and Electronic Systems, 2011, 47 (1): 539- 556. doi: 10.1109/TAES.2011.5705690
66	余若峰, 杨威, 付耀文, 等. 面向不同雷达任务的认知波形优化综述[J]. 电子学报, 2022, 50 (3): 726- 752. doi: 10.12263/DZXB.20211068
	YU R F, YANG W, FU Y W, et al. A review on cognitive waveform optimization for different radar missions[J]. Acta Electronica Sinica, 2022, 50 (3): 726- 752. doi: 10.12263/DZXB.20211068
67	MAHLER R P S. Multitarget Bayes filtering via first-order multitarget moments[J]. IEEE Trans. on Aerospace and Electronic Systems, 2003, 39 (4): 1152- 1178. doi: 10.1109/TAES.2003.1261119
68	VO B N, MAHLER R P S. The Gaussian mixture probability hypothesis density filter[J]. IEEE Trans. on Signal Processing, 2006, 54 (10): 3873- 3888. doi: 10.1109/TSP.2006.879267
69	VO B N, MAHLER R P S. Sequential Monte Carlo methods for multitarget filtering with random finite sets[J]. IEEE Trans. on Aerospace and Electronic Systems, 2009, 45 (2): 454- 471.
70	MAHLER R P S. PHD ﬁlters of higher order in target number[J]. IEEE Trans. on Aerospace and Electronic Systems, 2007, 43 (3): 1523- 1543.
71	VO B T, VO B N, CANTONI A. Analytic implementations of the cardinalized probability hypothesis density filter[J]. IEEE Trans. on Signal Processing, 2007, 55 (7): 3553- 3567. doi: 10.1109/TSP.2007.894241
72	MAHLER R P S. Statistical multisource multitarget information fusion[M]. Norwood: Artech House, 2007.
73	VO B N, MAHLER R P S. The cardinalized probability hypothesis density filter[J]. IEEE Trans. on Signal Processing, 2009, 57 (8): 3053- 3067. doi: 10.1109/TSP.2009.2020002
74	MAHLER R P S. A unifying perspective on multitarget filters based on cardinalized random finite sets[J]. IEEE Trans. on Aerospace and Electronic Systems, 2014, 50 (1): 40- 55.
75	VO B N, MAHLER R P S. The labelled multi-Bernoulli filter[J]. IEEE Trans. on Signal Processing, 2013, 61 (13): 3460- 3474. doi: 10.1109/TSP.2013.2259822
76	李春霞. 宽带雷达空间目标及目标群跟踪方法研究[D]. 北京: 北京理工大学, 2015.
	LI C X. Research on space target and targets group tracking methods of wideband radar[D]. Beijing: Beijing Institute of Technology, 2015.
77	龚阳, 崔琛. 基于GM-PHD滤波的空间邻近多目标跟踪算法[J]. 系统工程与电子技术, 2022, 44 (1): 76- 85. doi: 10.12305/j.issn.1001-506X.2022.01.11
	GONG Y, CUI C. Multi-target tracking algorithm based on GM-PHD filter for spatially close targets[J]. Systems Engineering and Electronics, 2022, 44 (1): 76- 85. doi: 10.12305/j.issn.1001-506X.2022.01.11
78	ZHENG S Y, JIANG L B, YANG Q W, et al. Adaptive PHD filter with RCS and Doppler feature for space targets tracking via space-based radar[J]. IEEE Trans. on Aerospace and Electronic Systems, 2024, 60 (4): 3750- 3765. doi: 10.1109/TAES.2023.3327692
79	宋慧波, 高梅国, 田黎育, 等. 一种基于动态规划法的雷达微弱多目标检测方法[J]. 电子学报, 2006, 34 (12): 2142- 2145. doi: 10.3321/j.issn:0372-2112.2006.12.004
	SONG H B, GAO M G, TIAN L Y, et al. An algorithm based on DP for radar dim multi-target detection[J]. Acta Electronica Sinica, 2006, 34 (12): 2142- 2145. doi: 10.3321/j.issn:0372-2112.2006.12.004
80	宋慧波, 高梅国, 田黎育. 一种有效的雷达微弱目标检测法[J]. 仪器仪表学报, 2006, 1326- 1327. doi: 10.3321/j.issn:0254-3087.2006.10.034
	SONG H B, GAO M G, TIAN L Y. Effective algorithm for radar dim target detection[J]. Chinese Journal of Scientific Instrument, 2006, 1326- 1327. doi: 10.3321/j.issn:0254-3087.2006.10.034
81	胡琳, 王首勇, 万洋. 基于动态规划的TBD改进算法[J]. 空军雷达学院学报, 2010, 24 (2): 79- 82.
	HU L, WANG S Y, WAN Y. Improvement on track-before-detection algorithm based on dynamic programming[J]. Journal of Air Force Radar Academy, 2010, 24 (2): 79- 82.
82	方梓成. 多帧联合检测与跟踪技术研究[D]. 成都: 电子科技大学, 2016.
	FANG Z C. Research on multi-frame detection and tracking technique[D]. Chengdu: University of Electronic Science and Technology of China, 2016.
83	YI W, FANG Z C, WEN M. An efficient coherent multi-frame track-before-detect algorithm in radar systems[C]//Proc. of the IEEE Radar Conference, 2017: 1521−1526.
84	YI W, JIANG H C, KIRUBARAJAN T, et al. Track-before-detect strategies for radar detection in G0-distributed clutter[J]. IEEE Trans. on Aerospace and Electronic Systems, 2017, 53 (5): 2516- 2533.
85	TIAN Y L, LI W J, YI W, et al. Environment constraint force enhanced on-road multi-vehicle tracking using millimeter-wave radar[C]// Proc. of the IEEE Intelligent Vehicles Symposium, 2024: 703−708.
86	ZHOU G J, WANG L. Pseudo-spectrum based speed square filter for track-before-detect in range-Doppler domain[J]. IEEE Trans. on Signal Processing, 2019, 67 (21): 5596- 5610. doi: 10.1109/TSP.2019.2943256
87	BERGMANN P, MEINHARDT T, LEAL L. Tracking without bells and whistles[C]//Proc. of the International Conference on Computer Vision, 2019.
88	张袁鹏, 郑岱堃, 李昕哲, 等. 基于隐马尔可夫模型的动态规划检测前跟踪算法[J]. 系统工程与电子技术, 2019, 41 (11): 2479- 2487.
	ZHANG Y P, ZHENG D K, LI X Z, et al. Dynamic programming track-before-detect algorithm based on hidden Markov model[J]. Systems Engineering and Electronics, 2019, 41 (11): 2479- 2487.
89	薄钧天, 王国宏, 于洪波, 等. 临近空间高超声速多目标检测前跟踪算法[J]. 航空学报, 2022, 43 (5): 507- 519.
	BO J T, WANG G H, YU H B, et al. Track before detection algorithm for multiple hypersonic targets in near space[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43 (5): 507- 519.
90	李东升. 随机有限集框架下多幅度起伏目标的检测前跟踪算法研究[D]. 桂林: 桂林电子科技大学, 2022.
	LI D S. Research on track-before-detect algorithm for multiple amplitude fluctuation targets in the random finite set framework[D]. Guilin: Guilin University of Electronic Technology, 2022.
91	陆晓莹. 基于动态规划的雷达弱目标检测前跟踪算法研究[J]. 成都: 电子科技大学, 2023.
	LU X Y. Research on track-before-detect algorithm based on dynamic programming for weak target with radar[J]. Chengdu: University of Electronic Science and Technology of China, 2023.
92	李武军. 机载雷达多帧检测前跟踪方法研究[D]. 成都: 电子科技大学, 2023.
	LI W J. Research on multi-frame track-before-detect methods in airborne radar systems[D]. Chengdu: University of Electronic Science and Technology of China, 2023.
93	Available: http://www.topisme.com/article/2010/03/space_201003_045.html[EB/OL].
94	Available: http://innogst.whu.edu.cn/newsnoticedetail.jspid=y0jhlmzwmx[EB/OL].
95	MARCHETTI E, STOVE A, HOARE E, et al. Images of satellite elements with a spaceborne sub-THz ISAR system[C]//Proc. of the 18th European Radar Conference, 2022: 425−428.
96	MARCHETTI E, STOVE A, HOARE E, et al. Space-based sub-THz ISAR for space situational awareness-concept and design[J]. IEEE Trans. on Aerospace and Electronic Systems, 2022, 58 (3): 1558- 1573. doi: 10.1109/TAES.2021.3126375
97	YANG X B, PI Y M, LIU T, et al. Three-dimensional imaging of space debris with spacebased Terahertz radar[J]. IEEE Sensors Journal, 2017, 18 (3): 1063- 1072.
98	冯夕冉. 基于天基雷达的空间目标成像参数设计与算法研究[D]. 北京: 中国科学院空天信息创新研究院, 2020.
	FENG X R. Design of space target imaging parameters and research on imaging algorithm based on space-based radar[D]. Beijing: Aerospace Information Research Institute, Chinese Academy of Sciences, 2020.
99	潘洁, 李道京, 姜文. 基于三维成像处理的稀疏阵列天基雷达运动目标探测方法[J]. 现代雷达, 2022, 44 (5): 6- 11.
	PAN J, LI D J, JIANG W. Moving target detection approach of sparse array space-based radar based on 3D imaging processing[J]. Modern Radar, 2022, 44 (5): 6- 11.
100	ZHOU Y J, XIE P, LI C, et al. Automatic dynamic estimation of on-orbit satellites through spaceborne ISAR imaging[J]. IEEE Trans. on Radar Systems, 2023.
101	CHEN R, JIANG Y. Hybrid SAR-ISAR imaging for space target via 2D spectrum and SIHR with spaceborne radar[J]. IEEE Trans. on Aerospace and Electronic Systems, 2024, 60(2): 1−22.
102	DU Y H, JIANG Y C. Parametric translational motion compensation of spaceborne ISAR imagery for earth-orbit targets based on parabola detection and entropy minimization[J]. Remote Sensing Letters, 2021, 12 (2): 160- 168. doi: 10.1080/2150704X.2020.1837986
103	DAVIS M E. Space based radar technology challenges [C]//Proc. of the IEEE Aerospace Conference, 2005: 2154−2161.
104	张春红, 宋光磊, 苗慧. 双基地天基雷达功率孔径积分析[J]. 遥测遥控, 2011, 32 (1): 39- 42. doi: 10.3969/j.issn.2095-1000.2011.01.009
	ZHANG C H, SONG G L, MIAO H. Analysis of power-aperture product in bistatic space based radar system[J]. Journal of Telemetry, Tracking and Command, 2011, 32 (1): 39- 42. doi: 10.3969/j.issn.2095-1000.2011.01.009
105	TAN X, YANG Z, LI X L , et al. Modeling and characteristic analysis for air-space based bistatic radar[C]//Proc. of the CIE International Conference on Radar, 2021: 1719−1722.
106	杨晓丹, 马志昊. 分布式天基空间监视雷达编队构形[J]. 兵工自动化, 2009, 28 (7): 28- 30. doi: 10.3969/j.issn.1006-1576.2009.07.010
	YANG X D, MA Z H. Formation configuration of distributed space-based surveillance radar[J]. Ordnance Industry Automation, 2009, 28 (7): 28- 30. doi: 10.3969/j.issn.1006-1576.2009.07.010
107	韩蕾, 马志昊, 陈磊, 等. 天基低轨空间监视雷达密集短弧观测数据的定轨应用研究[J]. 飞行器测控学报, 2008, 27 (3): 85- 89.
	HAN L, MA Z H, CHEN L, et al. Short-arc dense observations in low earth orbit determination from space-based radar[J]. Journal of Spacecraft TT&C Technology, 2008, 27 (3): 85- 89.
108	马志昊, 韩蕾, 陈磊. 天基近地轨道空间监视雷达卫星重访效能分析[J]. 飞行器测控学报, 2007, 26 (6): 40- 44.
	MA Z H, HAN L, CHEN L. Recovery analysis of space-based radar for LEO surveillance[J]. Journal of Spacecraft TT&C Technology, 2007, 26 (6): 40- 44.
109	ZHANG J, DING T, ZHANG L R. Longtime coherent integration algorithm for high-speed maneuvering target detection using space-based bistatic radar[J]. IEEE Trans. on Geoscience and Remote Sensing, 2022, 60
110	CHEN J. Approach for along-track baseline distribution design in a multi-satellite distributed space-based radar system[C]//Proc. of the IEEE International Geoscience and Remote Sensing Symposium, 2023: 6125−6128.
111	ZHNAG T F, WANG Z H, QIAO N, et al. A novel working model for distributed space-based early warning radar[C]//Proc. of the CIE International Conference on Radar, 2021: 2604−2607.
112	常家云. 天基雷达组网探测近地轨道目标[D]. 北京: 北京理工大学, 2016.
	CHANG J Y. Low-earth orbit (LEO) object detection by spaceborne netted radar[D]. Beijing: Beijing Institute of Technology, 2016.
113	王久龙, 王潇逸, 胡海飞, 等. 美国“下一代过顶持续红外”（OPIR）预警卫星研究进展[J]. 现代防御技术, 2022, 50 (2): 18- 25. doi: 10.3969/j.issn.1009-086x.2022.02.003
	WANG J L, WANG X Y, HU H F, et al. Research progress of the US “next generation overhead persistent infrared” （OPIR） early warning satellite[J]. Modern Defence Technology, 2022, 50 (2): 18- 25. doi: 10.3969/j.issn.1009-086x.2022.02.003
114	HAYKIN S. Cognitive radar: a way of the future[J]. IEEE Signal Processing Magazine, 2006, 23 (1): 30- 40. doi: 10.1109/MSP.2006.1593335
115	易伟, 袁野, 刘光宏, 等. 多雷达协同探测技术研究进展: 认知跟踪与资源调度算法[J]. 雷达学报, 2023, 12 (3): 471- 499. doi: 10.12000/JR23036
	YI W, YUAN Y, LIU G H, et al. Recent advances in multi-radar collaborative surveillance: cognitive tracking and resource scheduling algorithms[J]. Journal of Radars, 2023, 12 (3): 471- 499. doi: 10.12000/JR23036
116	DAI J H, PU W, LIU H, et al. Target capacity based resource optimization for multiple target tracking in radar network[J]. IEEE Trans. on Signal Processing, 2021, 69, 2410- 2421. doi: 10.1109/TSP.2021.3071173
117	YI W, YUAN Y, HOSEINNEZHAD R, et al. Resource scheduling for distributed multi-target tracking in netted colocated MIMO radar systems[J]. IEEE Trans. on Signal Processing, 2020, 68, 1602- 1617. doi: 10.1109/TSP.2020.2976587
118	周琳, 刁伟峰, 王祎. 基于可观性分析的高精度空间目标跟踪方法[J]. 雷达科学与技术, 2021, 19 (5): 485- 490. doi: 10.3969/j.issn.1672-2337.2021.05.003
	ZHOU L, DIAO W F, WANG F. Novel observability-based high precision space target tracking methodology[J]. Radar Science and Technology, 2021, 19 (5): 485- 490. doi: 10.3969/j.issn.1672-2337.2021.05.003
119	王增福, 杨广宇, 金术玲. 考虑综合性能最优的非短视快速天基雷达多目标跟踪资源调度算法[J]. 雷达学报, 2024, 13 (1): 253- 269. doi: 10.12000/JR23162
	WANG Z F, YANG G Y, JIN S L. A non-myopic and fast resource scheduling algorithm for multi-target tracking of space-based radar considering optimal integrated performance[J]. Journal of Radars, 2024, 13 (1): 253- 269. doi: 10.12000/JR23162
120	YANG Q W, JIANG L B, ZHENG S Y, et al. Joint power and bandwidth allocation with RCS fluctuation characteristic for space target tracking[J]. Remote Sensing, 2023, 15 (16): 3971.
121	杨媛媛. 中低轨预警系统传感器资源调度方法研究[D]. 长沙: 国防科学技术大学, 2019.
	YANG Y Y. Research on sensor scheduling method in LEO warning system[D]. Changsha: National University of Defence Technology, 2019.
122	WANG Y C, HUANG Y, SHENG W D, et al. Space-based optical system sensor scheduling based on joint optimization of tracking performance and detection probability[C]//Proc. of the International Conference on Information Science, Parallel and Distributed Systems, 2020: 59−64.
123	张晟宇. 敏捷卫星多目标在轨协同观测技术研究[D]. 北京: 中国科学院大学(中国科学院微小卫星创新研究院), 2021.
	ZHANG Y Y. Research on multi-target on-board cooperative observation technology for agile satellite[D]. Beijing: Innovation Academy for Micro-satellites Chinese Academy of Sciences, 2021.

任务类型	任务内涵和要求
预警探测	在广阔空间范围内对潜在目标进行搜寻、侦测与追踪。在此任务中，雷达需具备广阔的搜索视野和较长的作用距离。尽管如此，对于目标精确定位和运动参数的测定，其精度要求并不会过于严苛。换言之，预警探测更侧重于雷达搜索覆盖范围和远程探测能力，而非对测量精度的极端追求。
精密测量	对雷达系统的精度要求较高，需要其能够精确捕捉并记录目标的运动路径和具体坐标。这类应用常见于武器试验靶场的性能评估，或是为空间目标提供精细的轨道数据。由于测量任务的特定性，雷达搜索区域通常是预设的，具有明确界限，因此相较于广域搜索，其覆盖范围较为有限。
武器制导	在此任务中，雷达扮演着向武器系统输送目标定位信息的角色，确保武器能够精确地锁定并攻击预定目标。首要目标是确保所提供的目标位置和运动参数达到武器系统所需的攻击精度。至于雷达作用距离，则需与武器的有效射程相匹配，以覆盖必要的攻击范围。简而言之，雷达在武器制导中的作用是提供精确的目标参数，而其探测距离应与武器的攻击范围相适应。
目标识别	涉及对已被雷达系统追踪的目标进行深入分析，以识别其独有的特性或行为模式，其中包括对目标内部运动特征的细致刻画，或是在特定区域内对目标进行区分。在此类任务中，分辨力是衡量雷达性能的关键标准。简而言之，目标识别的关键在于雷达区分目标特征的能力，其核心指标是分辨力。

多目标跟踪类型	跟踪方法	跟踪精度	运算量
数据关联类	GNN	低	低
	JPDA	中等	中等
	JIPDA	中等	中等
	MHT	高	高
RFS类	PHD	低	低
	CPHD	中等	中等
	TCPHD	中等	低
	MeMBer	中等	中等
	PMBM	高	中等
	GLMB	高	高
	LMB	高	中等