天基分布式雷达海面目标跟踪应用总体技术研究

doi:10.12305/j.issn.1001-506X.2024.08.14

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (8): 2667-2675.doi: 10.12305/j.issn.1001-506X.2024.08.14

• 传感器与信号处理 • 上一篇

天基分布式雷达海面目标跟踪应用总体技术研究

高飞¹^,*, 吴疆¹, 马俊², 刘佳², 张选民¹, 李彬¹, 蒙继东¹, 牛文博¹, 党红杏¹

1. 西安空间无线电技术研究所, 陕西西安 710100
2. 航天东方红卫星有限公司, 北京 100094

收稿日期:2023-02-20 出版日期:2024-07-25 发布日期:2024-08-07
通讯作者: 高飞
作者简介:高飞(1979—), 男, 工程师, 博士, 主要研究方向为雷达系统仿真与设计、机载/星载雷达信号处理、阵列信号处理
吴疆(1987—), 男, 工程师, 硕士, 主要研究方向为雷达系统集成设计
马俊(1987—), 男, 高级工程师, 硕士, 主要研究方向为小卫星及星座总体设计
刘佳(1983—), 女, 高级工程师, 博士, 主要研究方向为小卫星及星座任务设计与仿真
张选民(1988—), 男, 高级工程师, 硕士, 主要研究方向为星载合成孔径雷达系统设计、目标成像与检测信号处理
李彬(1981—), 男, 高级工程师, 硕士, 主要研究方向为雷达系统设计、微波系统设计
蒙继东(1989—), 男, 工程师, 硕士, 主要研究方向为雷达系统设计、高速目标雷达信号检测
牛文博(1984—), 男, 高级工程师, 硕士, 主要研究方向为雷达系统仿真与设计
党红杏(1974—), 女, 研究员, 硕士, 主要研究方向为高分辨率机载/星载雷达系统设计、信号处理
基金资助:
2022年度中国空间研究院CAST基金重点项目;卫星信息智能处理与应用技术重点实验室基金(2022-ZZKY-JJ-09-01)

Research on the overall technology of space-based distributed radar sea surface target tracking application

Fei GAO¹^,*, Jiang WU¹, Jun MA², Jia LIU², Xuanmin ZHANG¹, Bin LI¹, Jidong MENG¹, Wenbo NIU¹, Hongxing DANG¹

1. Xi'an Space Radio Technology Research Institute, Xi'an 710100, China
2. DFH Satellite Co., Ltd, Beijing 100094, China

Received:2023-02-20 Online:2024-07-25 Published:2024-08-07
Contact: Fei GAO

摘要/Abstract

摘要：

天基雷达在广域目标监视方面具有独特优势, 利用天基雷达实现广域海面目标跟踪具有重大现实意义和特殊难度。针对天基分布式雷达体制, 在分析其用于海面多目标跟踪场景所存在的区域非均衡覆盖、低/超低回访周期、实时处理等特殊问题影响基础上, 提出了星间接力跟踪处理方式和栅格化跟踪处理框架, 并给出了相应的多目标跟踪性能评估指标体系。仿真评估结果表明了所提栅格化跟踪处理框架相对常规全域处理框架的优越性以及评估指标的合理性。

关键词: 天基雷达, 分布式雷达, 海面目标, 目标跟踪, 性能评估

Abstract:

Space-based radar (SBR) has unique advantages in wide-area target surveillance, and it is of great practical significance and special difficulty to realize wide-area sea surface target tracking using SBR. Based on analyzing the effects of special problems such as regional unbalanced coverage, low/ultra-low return visit period and real-time processing in application to sea surface multi-target tracking scene for space-based distributed radar system, the tracking processing mode of inter-satellite relay and the tracking processing framework of rasterization pertinently are put forward, and the corresponding multi-target tracking performance evaluation indicator system is presented. The simulation evaluation results show the superiority of the proposed tracking processing framework of rasterization relative to conventional global processing framework and the rationality of the evaluation index.

Key words: space-based radar (SBR), distributed radar, sea surface target, target tracking, performance evaluation

中图分类号:

TN959.74

高飞, 吴疆, 马俊, 刘佳, 张选民, 李彬, 蒙继东, 牛文博, 党红杏. 天基分布式雷达海面目标跟踪应用总体技术研究[J]. 系统工程与电子技术, 2024, 46(8): 2667-2675.

Fei GAO, Jiang WU, Jun MA, Jia LIU, Xuanmin ZHANG, Bin LI, Jidong MENG, Wenbo NIU, Hongxing DANG. Research on the overall technology of space-based distributed radar sea surface target tracking application[J]. Systems Engineering and Electronics, 2024, 46(8): 2667-2675.

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参考文献 37

1	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.
	LIU C , WANG Y J . Review of multi-target tracking technology for marine radar[J]. Journal of Radars, 2021, 10 (1): 100- 115.
2	FORTMANN T E , BAR-SHALOM Y , SCHEFFE M . Sonar tracking of multiple targets using joint probabilistic data association[J]. IEEE Journal of Oceanic Engineering, 1983, 8 (3): 173- 184. doi: 10.1109/JOE.1983.1145560
3	REID D . An algorithm for tracking multiple targets[J]. IEEE Trans. on Automatic Control, 1979, 24 (6): 843- 854. doi: 10.1109/TAC.1979.1102177
4	MAHLER R P S . Multitarget Bayes filtering via first-order multi-target moments[J]. IEEE Trans. on Aerospace and Electronic Systems, 2003, 39 (4): 1152- 1178. doi: 10.1109/TAES.2003.1261119
5	MUSICKI D , EVANS R . Joint integrated probabilistic data association: JIPDA[J]. IEEE Trans. on Aerospace and Electronic Systems, 2004, 40 (3): 1093- 1099. doi: 10.1109/TAES.2004.1337482
6	BLACKMAN S S , POPOLI R . Design and analysis of modern tracking systems[M]. Boston: Artech House, 1999: 1- 24.
7	VO B N , SINGH S , DOUCET A . Sequential Monte Carlo methods for multitarget filtering with random finite sets[J]. IEEE Trans. on Aerospace and Electronic Systems, 2005, 41 (4): 1224- 1245. doi: 10.1109/TAES.2005.1561884
8	WHITELEY N , SINGH S , GODSILL S . Auxiliary particle implementation of probability hypothesis density filter[J]. IEEE Trans. on Aerospace and Electronic Systems, 2010, 46 (3): 1437- 1454. doi: 10.1109/TAES.2010.5545199
9	RISTIC B , CLARK D , VO B N , et al. Adaptive target birth intensity for PHD and CPHD filters[J]. IEEE Trans. on Aerospace and Electronic Systems, 2012, 48 (2): 1656- 1668. doi: 10.1109/TAES.2012.6178085
10	MAHLER R . PHD filters of higher order in target number[J]. IEEE Trans. on Aerospace and Electronic Systems, 2007, 43 (4): 1523- 1543. doi: 10.1109/TAES.2007.4441756
11	VO B N , VO B T , PHUNG D . Labeled random finite sets and the Bayes multi-target tracking filter[J]. IEEE Trans. on Signal Processing, 2014, 62 (24): 6554- 6567. doi: 10.1109/TSP.2014.2364014
12	REUTER S , VO B T , VO B N , et al. The labeled multi-Bernoulli filter[J]. IEEE Trans. on Signal Processing, 2014, 62 (12): 3246- 3260. doi: 10.1109/TSP.2014.2323064
13	LERRO D, BAR-SHALOM Y. Automated tracking with target amplitude information[C]//Proc. of the American Control Conference, 1990: 2875-2880.
14	EHRMAN L M, BLAIR W D. Comparison of methods for using target amplitude to improve measurement-to-track associa-tion in multi-target tracking[C]//Proc. of the 9th International Conference on Information Fusion, 2006.
15	LERRO D , BAR-SHALOM Y . Interacting multiple model tracking with target amplitude feature[J]. IEEE Trans. on Aerospace and Electronic Systems, 1993, 29 (2): 494- 509. doi: 10.1109/7.210086
16	KIRUBARAJAN T , BAR-SHALOM Y . Low observable target motion analysis using amplitude information[J]. IEEE Trans. on Aerospace and Electronic Systems, 1996, 32 (2): 1367- 1384.
17	EHRMAN L M, BLAIR W D. RCS-aided tracking: does it always improve data association?[C]//Proc. of the IEEE National Radar Conference, 2007.
18	EHRMAN L M, BURTON C, BLAIR W D. Using target RCS to aid measurement-to-track association in multi-target tracking[C]//Proc. of the 38th Southeastern Symposium on System Theory, 2006: 89-93.
19	EHRMAN L M , BLAIR W D . Using target RCS when tracking multiple Rayleigh targets[J]. IEEE Trans. on Aerospace and Electronic Systems, 1996, 46 (2): 701- 716.
20	BUZZI S , LOPS M , VENTURINO L , et al. Track-before-detect procedures in a multi-target environment[J]. IEEE Trans. on Aerospace and Electronic Systems, 2008, 44 (3): 1135- 1150. doi: 10.1109/TAES.2008.4655369
21	BOERS Y , DRIESSEN J N . Multitarget particle filter track before detect application[J]. IEE Proceedings-Radar, Sonar & Navigation, 2004, 151 (6): 351- 357.
22	STREIT R L , GRAHAM M L , WALSH M J . Multitarget tracking of distributed targets using histogram-PMHT[J]. Di-gital Signal Processing, 2002, 12 (2/3): 394- 404.
23	PUNITHAKUMAR K, KIRUBARAJAN T. A sequential Monte Carlo probability hypothesis density algorithm for multitarget track-before-detect[C]//Proc. of the Conference on Signal and Data Processing of Small Targets, 2005: 59131S.
24	LIN L , BAR-SHALOM Y , KIRUBARAJAN T . Track labeling and PHD filter for multitarget tracking[J]. IEEE Trans. on Aerospace and Electronic Systems, 2006, 42 (3): 778- 795. doi: 10.1109/TAES.2006.248213
25	KOCH W, SAUL R. A Bayesian approach to extended object tracking and tracking of loosely structured target groups[C]//Proc. of the 7th International Conference on Information Fusion, 2005: 827-834.
26	BAUM M, HANEBECK U D. Random hypersurface models for extended object tracking[C]//Proc. of the IEEE International Symposium on Signal Processing and Information Technology, 2009: 178-183.
27	BAUM M , HANEBECK U D . Extended object tracking with random hypersurface models[J]. IEEE Trans. on Aerospace and Electronic Systems, 2014, 50 (1): 149- 159. doi: 10.1109/TAES.2013.120107
28	WILLIAMS J . Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA, and association-based member[J]. IEEE Trans. on Aerospace and Electronic Systems, 2015, 51 (1664): 1687.
29	GARCÍA-FERNÁNDEZÁF , WILLIAMS J L , GRANSTRÖM K , et al. Poisson multi-Bernoulli mixture filter: direct derivation and implementation[J]. IEEE Trans. on Aerospace and Electronic Systems, 2018, 54 (4): 1883- 1901. doi: 10.1109/TAES.2018.2805153
30	GRAZIANO M , RENGA A , MOCCIA A . Integration of automatic identification system (AIS) data and single-channel synthetic aperture radar (SAR) images by SAR-based ship velocity estimation for maritime situational awareness[J]. Remote. Sens., 2019, 11, 2196. doi: 10.3390/rs11192196
31	GAGLIONE D, BRACA P, SOLDI G. Belief propagation based AIS/radar data fusion for multi-target tracking[C]//Proc. of the 21st International Conference on Information Fusion, 2018.
32	HABTEMARIAM B , THARMARASA R , MCDONALD M , et al. Measurement level AIS/radar fusion[J]. Signal Processing, 2015, 106, 348- 357. doi: 10.1016/j.sigpro.2014.07.029
33	HABTEMARIAM B K, THARMARASA R, MEGER E, et al. Measurement level AIS/radar fusion for maritime surveil-lance[C]//Proc. of the SPIE-the International Society for Optical Engineering, 2012.
34	GUERRIERO M, WILLETT P, CORALUPPI S, et al. Radar/AIS data fusion and SAR tasking for maritime surveillance[C]//Proc. of the 11th International Conference on Information Fusion, 2008.
35	郁文贤, 计科峰, 柳彬. 星载SAR与AIS综合的海洋目标信息处理技术[M]. 北京: 科学出版社, 2017.
	YU W X , JI K F , LIU B . Marine target information processing technology integrated with spaceborne SAR and AIS[M]. Beijing: Science Press, 2017.
36	何友, 修建娟, 关欣, 等. 雷达数据处理及应用[M]. 北京: 电子工业出版社, 2013.
	HE Y , XIU J J , GUAN X , et al. Radar data processing with applications[M]. Beijing: Publishing House of Electronics Industry, 2013.
37	朱自谦, 胡士强. 机载雷达多目标跟踪技术[M]. 北京: 国防工业出版社, 2013.
	ZHU Z Q , HU S Q . Airborne radar multi-target tracking technology[M]. Beijing: National Defense Industry Press, 2013.

参数	取值
观测区域经纬度范围	经度: 122°~130°, 纬度: 23°~28°
经纬度栅格数量	16×10
星座	75星Walker星座
单星单轨覆盖面积/km	1 000×400
蒙特卡罗实验次数	50
目标运动模型	匀速模型
目标分布密度(个/10 000 km²)	30
目标个数	30
发现概率	0.9
虚警概率	10^-6
回访周期/min	5~15
跟踪时长/min	720
跟踪滤波器	卡尔曼滤波器

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天基分布式雷达海面目标跟踪应用总体技术研究

Research on the overall technology of space-based distributed radar sea surface target tracking application

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