journal article·2020-05-27Open access

Cooperative Standoff Tracking of Moving Targets Using Modified Lyapunov Vector Field Guidance

Fei Che, Yifeng Niu, Jie Li, Lizhen Wu

Applied Sciences· Volume 10· Issue 11

Abstract

Cooperative standoff tracking of moving targets is an important application of fixed-wing unmanned aerial vehicles (UAVs). To cope with the problem of long convergence time and unstable tracking in cooperative target tracking, traditional Lyapunov vector field guidance (LVFG) is modified. The guidance parameter c is discussed, and the gradient descent method is utilized to develop the optimal guidance parameter search algorithm. As for tracking moving targets, an interacting multiple model-based unscented Kalman filter (IMM-UKF) estimator is built for predicting the target state, and the result is used for correcting the guidance law. Meanwhile, a speed-based controller is developed for faster convergence to the desired intervehicle phase, and the stability of the controller is proved using the Lyapunov stability theory. Numerical simulation results indicate the proposed guidance converges faster to the standoff circle without intersecting the orbit. The state estimator reduces the estimate error and the intervehicle phase converges faster to the desired phase than the traditional control method. Furthermore, extensive hardware-in-the-loop simulations are carried out to verify the feasibility of the algorithm.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Guidance and Control Systems · Spacecraft Dynamics and Control · Adaptive Control of Nonlinear Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China

Funding

National Natural Science Foundation of China

References (25)

Show source-provided references
1. Rysdyk, R., Lum, C., and Vagners, J. (2002, January 5–8). Autonomous orbit coordination for two unmanned aerial vehicles. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, CA, USA.
2. Nonlinear model predictive coordinated standoff tracking of a moving ground vehicle10.2514/1.56254 ↗
3. Road-map–assisted standoff tracking of moving ground vehicle using nonlinear model predictive control10.1109/TAES.2014.130688 ↗
4. Wang, S., Wei, R., and Lv, M. (2014, January 8–10). Unmanned aerial vehicle standoff target tracking using modified reference point guidance. Proceedings of the 2014 IEEE Chinese Guidance, Navigation and Control Conference, Yantai, China.10.1109/CGNCC.2014.7007541 ↗
5. Coordinated Standoff Target Tracking Guidance Method for UAVs10.1109/ACCESS.2018.2875787 ↗
6. Dale, L. (2003, January 15–18). Lyapunov vector fields for UAV flock coordination. Proceedings of the Presented at the 2nd AIAA “Unmanned Unlimited” Conf, and Workshop & Exhibit, San Diego, CA, USA.
7. Coordinated standoff tracking of moving targets using Lyapunov guidance vector fields10.2514/1.30507 ↗
8. UAV path planning with tangent-plus-Lyapunov vector field guidance and obstacle avoidance10.1109/TAES.2013.6494384 ↗
9. Decentralised standoff tracking of moving targets using adaptive sliding mode control for UAVs10.1007/s10846-013-9864-0 ↗
10. Standoff target tracking using a vector field for multiple unmanned aircrafts10.1007/s10846-012-9765-7 ↗
11. Curvature-constrained Lyapunov vector field for standoff target tracking10.2514/1.G002281 ↗
12. Fast Lyapunov Vector Field Guidance for Standoff Target Tracking Based on Offline Search10.1109/ACCESS.2019.2932998 ↗
13. A modified guidance law for ground moving target tracking with a class of the fast adaptive second-order sliding mode10.1177/0142331215589807 ↗
14. Guidance law for standoff tracking of a moving object10.2514/1.G002707 ↗
15. Coordinated standoff tracking of moving targets: Control laws and information architectures10.2514/1.37212 ↗
16. Qian, Z., Rui, Z., and Jie, Z. (2016, January 16–18). Coordinated standoff tracking of moving targets with optimal measurement configuration. Proceedings of the 2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), Chengdu, China.10.1109/ICCWAMTIP.2016.8079896 ↗
17. Decentralized real-time estimation and tracking for unknown ground moving target using UAVs10.1109/ACCESS.2018.2885776 ↗
18. Kingston, D., and Beard, R. (2007). UAV splay state configuration for moving targets in wind. Advances in Cooperative Control and Optimization, Springer.10.1007/978-3-540-74356-9_7 ↗
19. Coordinated standoff tracking of moving targets using differential geometry10.1631/jzus.C1300287 ↗
20. Kokolakis, N.-M.T., and Koussoulas, N.T. (2018, January 12–15). Coordinated standoff tracking of a ground moving target and the phase separation problem. Proceedings of the 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas, TX, USA.10.1109/ICUAS.2018.8453292 ↗
21. Unknown ground moving target tracking using multiple unmanned aerial vehicles10.1177/0954410017744812 ↗
22. Wang, C., Yan, C., Xiang, X., and Zhou, H. (2019, January 17–19). A Continuous Actor-Critic Reinforcement Learning Approach to Flocking with Fixed-Wing UAVs. Proceedings of the Asian Conference on Machine Learning, Nagoya, Japan.
23. An optimized image-based visual servo control for fixed-wing unmanned aerial vehicle target tracking with fixed camera10.1109/ACCESS.2019.2918686 ↗
24. Petritoli, E., Giagnacovo, T., and Leccese, F. (2014, January 29–30). Lightweight GNSS/IRS integrated navigation system for UAV vehicles. Proceedings of the 2014 IEEE Metrology for Aerospace (MetroAeroSpace), Benevento, Italy.10.1109/MetroAeroSpace.2014.6865894 ↗
25. Yuan, G., Yuan, K., and Zhang, H. (2013, January 12–15). A variable proportion adaptive federal kalman filter for INS/ESGM/GPS/DVL integrated navigation system. Proceedings of the 2011 Fourth International Joint Conference on Computational Sciences and Optimization, Harbin, China.10.1109/CSO.2011.63 ↗