基于低轨星网的多目标协同跟踪滤波技术

doi:10.12305/j.issn.1001-506X.2022.06.23

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (6): 1957-1967.doi: 10.12305/j.issn.1001-506X.2022.06.23

基于低轨星网的多目标协同跟踪滤波技术

翟光, 王妍欣, 孙一勇*

北京理工大学宇航学院, 北京 100081

收稿日期:2021-07-29 出版日期:2022-05-30 发布日期:2022-05-30
通讯作者: 孙一勇
作者简介:翟光(1979—), 男, 教授, 博士, 主要研究方向为航天器导航、制导与控制|王妍欣(1996—), 女, 硕士研究生, 主要研究方向为分布式滤波、多目标数据关联|孙一勇(1987—), 男, 讲师, 博士, 主要研究方向为智能控制、机器人系统、飞行器

Cooperative tracking filtering technology of multi-target based on low orbit satellite constellation

Guang ZHAI, Yanxin WANG, Yiyong SUN*

School of Aerospace Engineering, Beijing Institution of Technology, Beijing 100081, China

Received:2021-07-29 Online:2022-05-30 Published:2022-05-30
Contact: Yiyong SUN

摘要/Abstract

摘要：

低轨高密度星网因其覆盖范围广、能够对弹道目标进行全程跟踪而受到广泛的重视。针对低轨星网对多弹道目标协同跟踪问题, 提出一种基于卡方分布和无迹卡尔曼滤波(unscented Kalman filter, UKF)的多目标协同跟踪滤波算法。该方法首先在卡方分布的假设下, 设计了一种基于测量平面的数据关联指标函数, 实现量测值的分配; 在此基础上采用变结构滤波框架对多弹道目标进行状态更新; 最后给出了多目标状态估计性能的评估指标。数值仿真实验证明, 所提算法可以有效地实现多目标在测量平面上的数据关联, 并以较少的计算量对多目标进行准确估计。

关键词: 机动多目标跟踪, 数据关联, 无迹卡尔曼滤波, 卡方分布

Abstract:

The low orbit and high density satellite constellation attracts increasing attention due to its wide coverage and its capability of tracking ballistic targets throughout their traces. To cope with the problem of multiple ballistic targets cooperative tracking, this paper proposes a multi-target cooperative tracking filter based on Chi-square distribution and unscented Kalman filter (UKF). Under the assumption of a Chi-square distribution, this paper develops an indicator function of data association on the measurement plane to assign measurements. And based on the assignment, the variable filter structure is adopted to update the states of multi-target. Finally, the evaluation index of multi-target state estimation performance is given. The numerical simulations show that the algorithm proposed in this paper can effectively realize data association on measurement plane and estimate the state of multiple maneuvering targets (MTT) accurately with less computational load.

Key words: multiple maneuvering targets tracking (MTT), data association, unscented Kalman filter (UKF), Chi-square distribution

中图分类号:

TN96

翟光, 王妍欣, 孙一勇. 基于低轨星网的多目标协同跟踪滤波技术[J]. 系统工程与电子技术, 2022, 44(6): 1957-1967.

Guang ZHAI, Yanxin WANG, Yiyong SUN. Cooperative tracking filtering technology of multi-target based on low orbit satellite constellation[J]. Systems Engineering and Electronics, 2022, 44(6): 1957-1967.

参考文献 24

1	赵秋艳, 胡朝斌, 陈川, 等. 低轨大规模星座的机遇与挑战[J]. 空间碎片研究, 2020, 20 (1): 1- 9.
	ZHAO Q Y , HU Z B , CHEN C , et al. Opportunities and challenges of large-scale LEO constellation[J]. Space Debris Research, 2020, 20 (1): 1- 9.
2	谢恺, 薛模根, 周一宇, 等. 天基红外低轨星座对目标的跟踪算法研究[J]. 宇航学报, 2007, (3): 186- 193.
	XIE K , XUE M G , ZHOU Y Y , et al. Research on target tracking algorithm of space-based infrared low orbit constellation[J]. Journal of Astronautics, 2007, (3): 186- 193.
3	YU Y H . Distributed target tracking in wireless sensor networks with data association uncertainty[J]. IEEE Communications Letters, 2017, 21 (6): 1281- 1284. doi: 10.1109/LCOMM.2017.2673824
4	SHI Y F , ULLAH I , SONG T L , et al. Multisensor distributed out-of-sequence-tracks fusion with track origin uncertainty[J]. Aerospace Science and Technology, 2020, 106, 106226. doi: 10.1016/j.ast.2020.106226
5	罗玉文, 柳丹, 范雄华, 等. 空地概率数据关联转换量测滤波算法[J]. 北京理工大学学报, 2019, 39 (12): 1268- 1276.
	LUO Y W , LIU D , FAN X H , et al. Study on air-ground probability data association converted measurement filter algorithm[J]. Transactions of Beijing Institution of Technology, 2019, 39 (12): 1268- 1276.
6	龚轩, 乐孜纯, 王慧, 等. 多目标跟踪中的数据关联技术综述[J]. 计算机科学, 2020, 47 (10): 136- 144.
	GONG X , LE Z C , WANG H , et al. Survey of data association technology in multi-target tracking[J]. Computer Science, 2020, 47 (10): 136- 144.
7	YOON K , SONG Y , JEON M . Multiple hypothesis tracking algorithm for multi-target multi-camera tracking with disjoint views[J]. IET Image Processing, 2018, 12 (7): 1175- 1184. doi: 10.1049/iet-ipr.2017.1244
8	SUN L , CAO Y H , WU W H , et al. A multi-target tracking algorithm based on Gaussian mixture model[J]. Journal of Systems Engineering and Electronics, 2020, 31 (3): 482- 487. doi: 10.23919/JSEE.2020.000020
9	TIAN K S , ZHANG F . Multi-target tracking algorithm of boost-phase ballistic missile defense[J]. Journal of Systems Engineering and Electronics, 2013, 24 (1): 90- 100. doi: 10.1109/JSEE.2013.00012
10	BATTISTELLI G, CHISCI L, FANTACCI C, et al. Distributed peer-to-peer multitarget tracking with association-based track fusion[C]//Proc. of the IEEE 17th International Confe-rence on Information Fusion, 2014.
11	ROECKER J A , PHILLIS G L . Suboptimal joint probabilistic data association[J]. IEEE Trans.on Aerospace Electronic Systems, 1993, 29 (2): 510- 517. doi: 10.1109/7.210087
12	POORE A B, RIJAVEC N. Multitarget tracking and multidimensional assignment problems[C]//Proc. of the Signal and Data Processing of Small Targets, 1991.
13	KOLITZ S E. Passive-sensor data fusion[C]//Proc. of the Signal and Data Processing of Small Targets, 1991, 1481: 329-340.
14	ROECKER J A . Track monitoring when tracking with multiple 2D passive sensors[J]. IEEE Trans.on Aerospace and Electronic Systems, 1991, 27 (6): 872- 876. doi: 10.1109/7.104247
15	LIM J , KIM H S , PARK H M . Interactive-multiple-model algorithm based on minimax particle filtering[J]. IEEE Signal Processing Letters, 2020, 27, 36- 40. doi: 10.1109/LSP.2019.2954000
16	KALMAN R E . A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering, 1960, 82 (1): 35. doi: 10.1115/1.3662552
17	HE S M , SHIN H S , TSOURDOS A . Distributed multiple model joint probabilistic data association with gibbs sampling-aided implementation[J]. Information Fusion, 2020, 64, 20- 31. doi: 10.1016/j.inffus.2020.04.007
18	LI X H , LI Y A , YU J , et al. PMHT approach for multi-target multi-sensor sonar tracking in clutter[J]. Sensors, 2015, 15 (11): 28177- 28192. doi: 10.3390/s151128177
19	DAHMANI M , MECHE A , KECHE M , et al. An improved fuzzy alpha-beta filter for tracking a highly maneuvering target[J]. Aerospace Science and Technology, 2016, 58, 298- 305. doi: 10.1016/j.ast.2016.08.029
20	ZHAI G , BI X Z , ZHAO H Y , et al. Non-cooperative maneuvering spacecraft tracking via a variable structure estimator[J]. Aerospace Science and Technology, 2018, 79, 352- 363. doi: 10.1016/j.ast.2018.05.052
21	AMIRZADEH A , KARIMPOUR A . An interacting fuzzy-fading-memory-based augmented Kalman filtering method for maneuvering target tracking[J]. Digital Signal Processing, 2013, 23 (5): 1678- 1685. doi: 10.1016/j.dsp.2013.05.002
22	SACKS J , SORENSON H . Nonlinear extensions of the fading memory filter[J]. IEEE Trans.on Automatic Control, 1971, 16 (5): 506- 507. doi: 10.1109/TAC.1971.1099796
23	LIU M , LAI J Z , LI Z M , et al. An adaptive cubature Kalman filter algorithm for inertial and land-based navigation system[J]. Aerospace Science and Technology, 2016, 51, 52- 60. doi: 10.1016/j.ast.2016.01.010
24	SINGER R A . Estimating optimal tracking filter performance for manned maneuvering targets[J]. IEEE Trans.on Aerospace and Electronic Systems, 1970, AES-6 (4): 473- 483. doi: 10.1109/TAES.1970.310128

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基于低轨星网的多目标协同跟踪滤波技术

Cooperative tracking filtering technology of multi-target based on low orbit satellite constellation

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