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Guidance law for intercepting target with multiple no-fly zone constraints

Published online by Cambridge University Press:  24 August 2017

P. Zhao ,
W. Chen  and
W. Yu
P. Zhao
Affiliation:
School of Astronautics, Beihang University, Beijing, 100191, China
W. Chen
Affiliation:
School of Astronautics, Beihang University, Beijing, 100191, China
W. Yu*
Affiliation:
School of Astronautics, Beihang University, Beijing, 100191, China
*
yuwenbin_buaa@163.com
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Abstract

A composite guidance law is proposed for intercepting moving target while strictly satisfying the constraints on multiple No-Fly Zones (NFZs) distributed arbitrarily. The research has two major steps. In the first step, by considering only one NFZ, a guidance law is developed with three parts: Orientation Adjustment Scheme (OAS), Boundary-Constraint Handling Scheme (BCHS), and Proportional Navigation (PN). OAS determines the major flight direction by predicting the collision point of the missile and target. BCHS controls the missile to approach and then fly along the boundary of the NFZ smoothly so as to bypass the NFZ through a short path. PN is used to intercept the target in the endgame phase. In the second step, we use the multi-step decision process to set up a series of appropriate waypoints in order to avoid multiple NFZs. The superior performance of the proposed guidance law has been demonstrated by trajectory simulations.

Keywords

Guidance lawMultiple No-fly zonesAvoidanceBoundary-constraint handling schemeMulti-step decision process
Type
Research Article
Information
The Aeronautical Journal , Volume 121 , Issue 1244 , October 2017 , pp. 1479 - 1501
Copyright
Copyright © Royal Aeronautical Society 2017 

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References

REFERENCES

1. Tang, Y. Overview of development of world's air defense and antimissile weapon systems, Aerospace Manufacturing Technology, February 2010, (1), pp 2-6 (In Chinese).Google Scholar
2. Wu, F., Luo, F., Chen, X. and Liu, S. The development trend of foreign anti-aircraft gun missile system, Aerodynamic Missile J, 2012, (9), pp 62-65 (In Chinese).Google Scholar
3. Hewitt, M.A. Time Sensitive Targeting: Overcoming the Intelligence Gap in Interagency Operations, 2003, Naval War College, US.Google Scholar
4. Gu, B., Yan, R. and Xu, J. Time-sensitive target and striking decision, Command Information System and Technology, June 2011, 2, (3), pp 26-29 (In Chinese).Google Scholar
5. Zardashti, R. and Bagherian, M. A new model for optimal TF/TA flight path design problem, Aeronautical J, May 2009, 13, (1143), pp 301-308.CrossRefGoogle Scholar
6. Zardashti, R., Nikkhah, A.A. and Yazdanpanah, M.J. Constrained optimal terrain following/threat avoidance trajectory planning using network flow, Aeronautical J, May 2014, 118, (1203), pp 523-539.CrossRefGoogle Scholar
7. Xu, C., Duan, H. and Liu, F. Chaotic artificial bee colony approach to Uninhabited Combat Air Vehicle (UCAV) path planning, Aerospace Science and Technology, April 2010, 14, (8), pp 535-541.CrossRefGoogle Scholar
8. Wang, G., Chu, H.E. and Mirjalili, S. Three-dimensional path planning for UCAV using an improved bat algorithm, Aerospace Science and Technology, February 2016, 49, pp 231—238.CrossRefGoogle Scholar
9. Bagherian, M. and Alos, A. 3D UAV trajectory planning using evolutionary algorithms: A comparison study, Aeronautical J, October 2015, 119, (1220), pp 1271-1285.CrossRefGoogle Scholar
10. Mattei, M. and Blasi, L. Smooth flight trajectory planning in the presence of no-fly zones and obstacles, J Guidance Control and Dynamics, March-April 2010, 33, (2), pp 454-462.CrossRefGoogle Scholar
11. Yu, X., Liu, L., Liu, J., Tang, G. and Zheng, W. Rapid generation of entry trajectories with waypoint and no-fly zone constraints, Acta Astronautica, August 2012, 77, (8), pp 167-181.Google Scholar
12. Shen, L., Liu, L., Tang, G. and Zhu, J. An online planning algorithm for hypersonic aircraft with multiple no-fly zones, 2015 Annual Conference of China Flight Dynamics, Beijing, China, 2015, pp 188–196 (In Chinese).Google Scholar
13. Menon, P.K.A., Kim, E. and Cheng, V.H.L. Optimal trajectory synthesis for terrain-following flight, J Guidance Control and Dynamics, July-August 1991, 14, (4), pp 807-813.CrossRefGoogle Scholar
14. Stryk, O.V. and Bulirsch, R. Direct and indirect methods for trajectory optimization, Annals of Operations Research, September 1992, 37, (1), pp 357-373.CrossRefGoogle Scholar
15. Mao, Y., Zhang, D. and Wang, L. Reentry trajectory optimization for hypersonic vehicle based on improved Gauss pseudospectral method, Soft Computing, June 2016, pp 1-10.Google Scholar
16. Jun, M. and Andrea, R. Path planning for unmanned aerial vehicles in uncertain and adversarial environments, Cooperative Control Models Applications and Algorithms, Springer US, September 2003, 1, pp 95-110.CrossRefGoogle Scholar
17. Yang, H.I. and Zhao, Y.J. Trajectory planning for autonomous aerospace vehicles amid known obstacles and conflicts, J Guidance Control and Dynamics, November-December 2004, 27, (6), pp 997-1008.CrossRefGoogle Scholar
18. Jorris, T.R. and Cobb, R.G. Three-dimensional trajectory optimization satisfying waypoint and no-fly zone constraints, J Guidance Control and Dynamics, March-April 2009, 32, (2), pp 551-572.CrossRefGoogle Scholar
19. Shi, E., Cai, T. and He, C. Study of the new method for improving artificial potential field in mobile robot obstacle avoidance, Proceedings of the IEEE International Conference on Automation and Logistics, Jinan, China, August 2007, pp 282-286.Google Scholar
20. Masoud, A.A. Decentralized self-organizing potential field-based control for individually motivated mobile agents in a cluttered environment, IEEE Transactions on Systems, Man, and Cybernetics, May 2007, 37, (3), pp 372-390.CrossRefGoogle Scholar
21. Jing, R., Kenneth, A., Rajni, V.P. and Terry, M.P. A potential field model using generalized sigmoid functions, IEEE Transactions on Systems, Man, and Cybernetics, April 2007, 37, (2), pp 477-484.Google Scholar
22. Hwang, Y.K. and Ahuja, N. A potential field approach to path planning, IEEE Transactions on Robotics and Automation, February 1992, 8, (1), pp 23-32.CrossRefGoogle Scholar
23. Peng, J., Sun, X., Dong, W. and Li, X. Research on guidance law design integrating threat avoidance tactic for fighter, Acta Armamentraii, January 2010, 31, (1), pp 48-53 (In Chinese).Google Scholar
24. Ruiter, A.H.J. and de Owlia, S. Autonomous obstacle avoidance for fixed-wing unmanned aerial vehicles, Aeronautical J, November 2015, 119, (1221), pp 1415-1436.CrossRefGoogle Scholar
25. Yu, W. and Chen, W. Guidance law with circular no-fly zone constraint, Nonlinear Dynamics, July 2014, 78, (3), pp 1953-1971.CrossRefGoogle Scholar
26. Sniedovich, M. Dynamic Programming: Foundations and Principles, 2010, CRC Press, UK.Google Scholar