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2017, 06, No.186 37-43+49
Research on Penetration Route Planning Based on Hierarchical Sparse A* Search
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DOI: 10.16358/j.issn.1009-1300.2017.06.07
摘要:

针对小型集群飞行器三维突防航迹规划面临的精确度、实时性、任务适应性和可实现性综合匹配问题,在稀疏A*算法基础上,提出了基于分层策略的突防航迹规划算法,建立了三维航迹规划问题数学模型,给出了分层策略和突防航迹规划步骤。在算法扩展节点过程中采用支配检测方法,进一步提高了算法效率。在45 km×60 km规划区域内,典型想定下单机、四机和八机三维突防航迹规划长度分别为54.24 km、198.96 km和387.13 km,对应规划算法耗时分别为0.67 s、4.15s和11.04 s,同一任务场景下分层稀疏A*算法规划用时是标准A*算法的24.7%、14.2%和10.5%。仿真结果表明,该算法可在确保航迹规划精确度的前提下,大幅缩短航迹规划时间,具有较高的理论价值和工程适用性。

Abstract:

Aiming at the problem of accuracy,real-time,task adaptability and achievable matching of three-dimensional penetrating route planning of small-scale cluster aircraft,on the basis of Sparse A* Search( SAS) algorithm,a penetration planning algorithm based on hierarchical strategy is proposed. The mathematical model of planning arithmetic is established,and the steps of stratification and penetration planning are given. The method of dominating detection is used in the process of expanding the nodes,which further improves the efficiency of the algorithm. In the planning area of 45 km × 60 km,the planning length of three-dimensional penetrating route of one,four and eight small-scale cluster aircrafts are54. 24 km,198. 96 km and 387. 13 km,and the corresponding planning algorithm time are 0. 67 s,4. 15 s and 11. 04 s,respectively. In the same task scenario,the hierarchical sparse A* search algorithm is planned to be 24. 7%,14. 2%,and 10. 5% of the standard sparse A* search algorithm. Simulation results show that the algorithm can greatly shorten the time of track planning,and has high theoretical value and engineering applicability,under the precondition of ensuring the accuracy of penetrating route planning.

References

[1]郑昌文,严平,丁明跃,等.飞行器航迹规划研究现状与趋势[J].宇航学报,2007,28(6):1441-1446.

[2]Bortoff S.Path planning for UAVs[C].Proceedings of the American Control Conference,IEEE Press,Piscataway,NJ,2000,1:364-368.

[3]胡中华,赵敏.无人机航迹规划技术研究及发展趋势[J].航空电子技术,2009,40(2):24-25.

[4]张斌,钱正祥.基于蚁群算法的无人机航迹规划技术及研究现状[J].战术导弹技术,2012,(4):58-62.

[5]唐汇禹,彭世蕤,孙经蛟,等.基于SAPSO算法的无人机三维航迹规划[J].战术导弹技术,2017,(2):62-68.

[6]刘莉,于成龙,王祝,等.小型无人机快速三维航迹规划方法[J].系统工程与电子技,2013,35(12):2521-2526.

[7]孙静,吴碧,许玉堂,等.复杂环境下无人机三维航迹规划方法研究[J].弹箭与制导学报,2014,34(3):170-174.

[8]周其忠,闫利,魏军强,等.复杂环境下分层递阶多航迹协同规划研究[J].战术导弹技术,2014,34,(3):170-174.

[9]宋绍梅,张克,关世义.基于层次分解策略的无人机多机协同航线规划方法研究[J].战术导弹技术,2004,(1):44-48.

[10]Zheng C,Ding M,Zhou C,et al.Coevolving and cooperating path planner for multiple unmanned air vehicles[J].Engineering Application of Artifi cial Intelligence,2004,17(8):887-896.

[11]丁明跃,郑昌文,周成平,等.无人飞行器航迹规划[M].北京:电子工业出版社,2009.

[12]Szczerba R J,Galkowski P,Glicktein I S,et al.Robust algorithm for real-time route planning[J].IEEE Trans.on Aerospance and Electronic Systerms,2000,36(3):869-878.

Basic Information:

DOI:10.16358/j.issn.1009-1300.2017.06.07

China Classification Code:TJ765;V271.4

Citation Information:

[1]刘大卫,孙静,龙腾等.基于分层稀疏A~*算法的突防航迹规划研究[J].战术导弹技术,2017,No.186(06):37-43+49.DOI:10.16358/j.issn.1009-1300.2017.06.07.

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