基于图Laplacian的多机编队目标跟踪方法

doi:10.12305/j.issn.1001-506X.2021.03.25

摘要/Abstract

摘要：

针对多无人机目标跟踪问题中存在的相位协同时间长和跟踪目标速度受限问题, 基于图Laplacian方法提出一种分布式多机编队目标跟踪算法。首先, 将无人机编队队形控制问题转换为基于旋转、缩放和平移的运动参数组设计问题, 并通过设计编队控制律, 实现动态编队队形的精准生成与变换。其次, 将此编队队形控制方法应用到目标跟踪问题上, 通过分析不同目标速度下的跟踪情况建立相应的跟踪模型, 实现无人机编队对目标进行快速协同跟踪, 并克服跟踪目标速度限制问题。最后, 仿真结果验证了所提方法的有效性和优势。

关键词: 多无人机, 目标跟踪, 编队控制, 图Laplacian

Abstract:

Aiming at the problem of long phase coordination time and limited target speed in multiple unmanned aerial vehicles (UAVs) target tracking, this paper presents a distributed UAV formation target tracking algorithm based on the graph Laplacian method. Firstly, the UAV formation control problem is transformed into the design problem of moving parameter group based on rotation, scaling and translation. And through the design of formation control law, the accurate generation of dynamic formation is realized. Secondly, the formation control method is applied to the target tracking problem. By analyzing the tracking situation under different target speeds and establishing the corresponding tracking model, the problem of tracking target speed limit is overcome, and the UAV formation can co-track the target quickly. Finally, the simulation results verify the effectiveness and advantages of the designed method.

Key words: multiple unmanned aerial vehicle (UAV), target tracking, formation control, graphical Laplacian

中图分类号:

张毅, 方国伟, 杨秀霞. 基于图Laplacian的多机编队目标跟踪方法[J]. 系统工程与电子技术, 2021, 43(3): 796-805.

Yi ZHANG, Guowei FANG, Xiuxia YANG. Target tracking method for UAVs formation based on graph Laplacian[J]. Systems Engineering and Electronics, 2021, 43(3): 796-805.

图/表 8

图1

图2

图3

图4

图5

图6

图7

图8

参考文献 31

1	韩亮, 任章, 董希旺. 多无人机协同控制方法及应用研究[J]. 导航定位与授时, 2018, 4 (1): 1- 7.
	HAN L , REN Z , DONG X W . Research on multi-UAV cooperative control methods and applications[J]. Navigation Positioning and Timing, 2018, 4 (1): 1- 7.
2	HE S M , WANG J , LIN D F . Unknown ground moving target tracking using multiple unmanned aerial vehicles[J]. Procee-dings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2019, 233 (3): 1021- 1032. doi: 10.1177/0954410017744812
3	XU Z F , WEI R X , ZHAO X L , et al. Coordinated Standoff target tracking guidance method for UAVs[J]. IEEE Access, 2018, 6, 59853- 59859. doi: 10.1109/ACCESS.2018.2875787
4	SAKAMAKI J Y, BEARD R W, RICE M D. Cooperative estimation for a vision-based target tracking system[C]//Proc.of the International Conference on Unmanned Aircraft Systems, 2016: 878-885.
5	FREW E W , LAWRENCE D A , MORRIS S . Coordinated standoff tracking of moving targets using Lyapunov guidance vector fields[J]. Journal of guidance, control, and dynamics, 2008, 31 (2): 290- 306. doi: 10.2514/1.30507
6	SUMMERS T H , AKELLA M R , MEARS M J . Coordinated Standoff tracking of moving targets: control laws and information architectures[J]. Journal of Guidance, Control, and Dynamics, 2009, 32 (1): 56- 69. doi: 10.2514/1.37212
7	杨祖强, 方舟, 李平. 基于TAU矢量场制导的多无人机协同Standoff跟踪方法[J]. 浙江大学学报(工学版), 2017, 50 (5): 984- 992.
	YANG Z Q , FANG Z , LI P . Cooperative Standoff tracking for multi-UAVs based on TAU vector field guidance[J]. Journal of Zhejiang University (Engineering Science), 2017, 50 (5): 984- 992.
8	ZHAO Y Y , WANG X K , WANG C , et al. Systemic design of distributed multi-UAV cooperative decision-making for multi-target tracking[J]. Autonomous Agents and Multi-Agent Systems, 2019, 33 (1/2): 132- 158.
9	GU J J , SU T , WANG Q H , et al. Multiple moving targets surveillance based on a cooperative network for multi-UAV[J]. IEEE Communications Magazine, 2018, 56 (4): 82- 89. doi: 10.1109/MCOM.2018.1700422
10	DONG X W , LI Y F , LU C , et al. Time-varying formation tracking for UAV swarm systems with switching directed topologies[J]. IEEE Trans.on Neural Networks and Learning Systems, 2018, 30 (12): 3674- 3685.
11	YOO S J . Distributed consensus tracking of a class of asynchronously switched nonlinear multi-agent systems[J]. Automatica, 2018, 87 (1): 421- 427.
12	DEHGHANI M A , MENHAJ M B . Communication free leader-follower formation control of unmanned aircraft systems[J]. Robotics and Autonomous Systems, 2016, 80 (1): 69- 75.
13	PAN Y J , WERNER H , HUANG Z , et al. Distributed coo-perative control of leader-follower multi-agent systems under packet dropouts for quadcopters[J]. Systems & Control Letters, 2017, 106 (1): 47- 57.
14	邵壮, 祝小平, 周洲. 无人机编队机动飞行时的队形保持反馈控制[J]. 西北工业大学学报, 2015, 33 (1): 26- 32. doi: 10.3969/j.issn.1000-2758.2015.01.005
	SHAO Z , ZHU X P , ZHOU Z . A formation keeping feedback control for formation flight of UAVs[J]. Journal of Northwes-tern Polytechnical University, 2015, 33 (1): 26- 32. doi: 10.3969/j.issn.1000-2758.2015.01.005
15	邵壮, 祝小平, 周洲. 三维动态环境下多无人机编队分布式保持控制[J]. 控制与决策, 2016, 31 (6): 1068- 1079.
	SHAO Z , ZHU X P , ZHOU Z . Distributed formation keeping control of UAVs in 3-D dynamic environment[J]. Control and Decision, 2016, 31 (6): 1068- 1079.
16	YIN H , CAM L L , ROY U . Formation control for multiple unmanned aerial vehicles in constrained space using modified artificial potential field[J]. Mathematical Modelling Enginee-ring Problems, 2017, 4 (2): 100- 105. doi: 10.18280/mmep.040207
17	FU X W, WANG H X, PAN J, et al. A distributed formation control method of swarm UAVs based on artificial potential field and consensus strategy[C]//Proc.of the Australian & New Zealand Control Conference, 2019.
18	邱华鑫, 段海滨, 范彦铭. 基于鸽群行为机制的多无人机自主编队[J]. 控制理论与应用, 2015, 32 (10): 1298- 304. doi: 10.7641/CTA.2015.50314
	XIU H X , DUAN H B , FAN Y M . Multiple unmanned aerial vehicle autonomous formation based on the behavior mechanism in pigeon flocks[J]. Control Theory and Application, 2015, 32 (10): 1298- 1304. doi: 10.7641/CTA.2015.50314
19	XUE R B , SONG J M , CAI G H . Distributed formation flight control of multi-UAV system with nonuniform time-delays and jointly connected topologies[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2016, 230 (10): 1871- 81. doi: 10.1177/0954410015619446
20	COPP D A , VAMVOUDAKIS K G , HESPANHA J P . Distributed output-feedback model predictive control for multi-agent consensus[J]. Systems & Control Letters, 2019, 127 (1): 52- 59.
21	REN W , ATKINS E . Distributed multi-vehicle coordinated control via local information exchange[J]. International Journal of Robust and Nonlinear Control: IFAC-Affiliated Journal, 2007, 17 (10/11): 1002- 1033.
22	YOU K Y , XIE L H . Network topology and communication data rate for consensusability of discrete-time multi-agent systems[J]. IEEE Trans.on Automatic Control, 2011, 56 (10): 2262- 2275. doi: 10.1109/TAC.2011.2164017
23	OH K K , AHN H S . Distance-based undirected formations of single-integrator and double-integrator modeled agents in n-dimensional space[J]. International Journal of Robust and Nonlinear Control, 2014, 24 (12): 1809- 1820. doi: 10.1002/rnc.2967
24	ZHAO S , ZELAZO D . Bearing rigidity and almost global bea-ring-only formation stabilization[J]. IEEE Trans.on Automatic Control, 2015, 61 (5): 1255- 1268.
25	张民, 夏卫政, 黄坤. 基于Leader-Follower编队的无人机协同跟踪地面目标制导律设计[J]. 航空学报, 2018, 39 (2): 225- 237.
	ZHANG M , XIA W Z , HUANG K . Guidance law for cooperative tracking of a ground target based on leader-follower formation of UAVs[J]. Acta Aeronautica Et Astroautical Sinica, 2018, 39 (2): 225- 237.
26	MENG Z Y , LIN Z L , REN W . Robust cooperative tracking for multiple non-identical second-order nonlinear systems[J]. Automatica, 2013, 49 (8): 2363- 2372. doi: 10.1016/j.automatica.2013.04.040
27	ZAHREDDINE Z , ELSHEHAWEY E . On the stability of a system of differential equations with complex coefficients[J]. Indian Joumal Pure and Applied Mathematics, 1988, 19 (10): 963- 972.
28	CALLIER F M , DESOER C A . Linear system theory[M]. New York: Springer, 1991.
29	PARK S . Guidance law for standoff tracking of a moving object[J]. Journal of Guidance, Control, and Dynamics, 2017, 40 (11): 2948- 2955. doi: 10.2514/1.G002707
30	PELAPUR R, CANDEMIR S, BUNYAK F, et al. Persistent target tracking using likelihood fusion in wide-area and full motion video sequences[C]//Proc.of the 15th International Conference on Information Fusion, 2012.
31	ZHOU Y, TANG D Q, ZHOU H, et al. Vision-based online localization and trajectory smoothing for fixed-wing UAV tracking a moving target[C]//Proc.of the International Conference on Computer Vision Workshops, 2019.

[1]	仇祝令, 查宇飞, 李振宇, 李禹铭, 张鹏, 朱川. 基于多模型蒸馏的时间正则化相关滤波跟踪算法[J]. 系统工程与电子技术, 2022, 44(8): 2448-2456.
[2]	侯子林, 程婷, 彭瀚. 基于量测转换序贯滤波的GMPHD机动目标跟踪[J]. 系统工程与电子技术, 2022, 44(8): 2474-2482.
[3]	史浩然, 卢发兴, 祁江鑫, 杨光. 基于辅助信标的无人机协同目标跟踪[J]. 系统工程与电子技术, 2022, 44(7): 2302-2310.
[4]	金国栋, 薛远亮, 谭力宁, 许剑锟. 基于孪生神经网络的目标跟踪算法进展研究[J]. 系统工程与电子技术, 2022, 44(6): 1805-1822.
[5]	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.
[6]	王帅, 向建军, 彭芳, 唐书娟. 基于新最速下降法的目标跟踪算法[J]. 系统工程与电子技术, 2022, 44(5): 1512-1519.
[7]	辛怀声, 曹晨. 基于交互多模型的分组δ-广义标签多伯努利算法[J]. 系统工程与电子技术, 2022, 44(4): 1128-1138.
[8]	李洪瑶, 李小强, 韩心中, 谢学立, 席建祥. 基于决策融合的多无人机协同目标检测识别算法[J]. 系统工程与电子技术, 2022, 44(3): 746-754.
[9]	谢家豪, 黄树彩, 韦道知, 张曌宇, 王文豪. 基于P_EV准则的不确定混合多传感器联盟求解[J]. 系统工程与电子技术, 2022, 44(3): 819-826.
[10]	宋子壮, 杨嘉伟, 张东方, 王诗强, 张硕. 基于无锚框的红外多类别多目标实时跟踪网络[J]. 系统工程与电子技术, 2022, 44(2): 401-409.
[11]	姚云翔, 陈莹. 注意力机制下双模态交互融合的目标跟踪网络[J]. 系统工程与电子技术, 2022, 44(2): 410-419.
[12]	辛怀声, 宋鹏汉, 曹晨. 多模型广义标签多伯努利滤波器[J]. 系统工程与电子技术, 2022, 44(12): 3603-3613.
[13]	刘浩楠, 宋骊平. 基于核Fisher判别的群结构更新模型及群目标跟踪算法[J]. 系统工程与电子技术, 2022, 44(10): 3012-3019.
[14]	方澄, 路稳, 姬菁颖, 宋玉蒙, 梁斐菲, 罗志伟. 基于外观相似性更新的相关滤波跟踪算法[J]. 系统工程与电子技术, 2022, 44(1): 117-126.
[15]	韩统, 汤安迪, 周欢, 徐登武, 谢磊. 基于LASSA算法的多无人机协同航迹规划方法[J]. 系统工程与电子技术, 2022, 44(1): 233-241.