基于SAS算法的起飞一发失效应急路径规划方法

doi:10.7527/S1000-6893.2016.0051

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基于SAS算法的起飞一发失效应急路径规划方法

焦卫东¹, 程颖¹, 柯然²

1. 中国民航大学天津市智能信号与图像处理重点实验室, 天津 300300;
2. 中国农业银行科技部, 上海 200000

收稿日期:2015-11-13 修回日期:2015-12-17 出版日期:2016-10-15 发布日期:2016-04-13
通讯作者: 焦卫东,Tel.:020-24092444 E-mail:nxjiaowd@sina.com E-mail:nxjiaowd@sina.com
作者简介:焦卫东男,博士,副教授,硕士生导师。主要研究方向:虚拟现实技术在民航中的应用及图像/视频处理与编码。Tel:022-24092444 E-mail:nxjiaowd@sina.com
基金资助:
国家自然科学基金委员会-中国民航局民航联合研究基金（U1533115）；天津市应用基础与前沿技术研究计划（14JCYBJC16000）；中央高校基本科研业务费专项资金（3122013C016，3122013Z001）

A path planning method for EOSID based on SAS algorithm

JIAO Weidong¹, CHENG Ying¹, KE Ran²

1. Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;
2. Sci-tech Department, Agricultural Bank of China, Shanghai 200000, China

Received:2015-11-13 Revised:2015-12-17 Online:2016-10-15 Published:2016-04-13
Supported by:
Civil Aviation Joint Funds of the National Natural Science Foundation of China and Civil Aviation Administration of China (U1533115); Tianjin Research Program of Application Foundation and Advanced Technology (14JCYBJC16000); The Fundamental Research Funds for the Central Universities (3122013C016, 3122013Z001)

摘要/Abstract

摘要：

为解决起飞一发失效应急程序（EOSID）手动设计的不足，提出一种基于SRTM数据的稀疏A*搜索（SAS）算法的EOSID路径规划方法。首先采用航天飞机雷达地形测绘使命（SRTM）的网格地形数据，结合起飞一发失效相关规章，考虑爬升梯度与保护区限制确定可行搜索空间；然后基于可行搜索空间运用稀疏A*搜索算法搜索应急离场路径，在传统A*算法寻找扩展节点时加入起飞性能约束条件，同时利用地形高程数据进行地形和威胁回避，生成一条三维应急离场航迹；最后利用三次样条曲线对规划的应急离场航迹进行平滑处理。实验结果表明该方法能自动搜索出有效的EOSID三维航迹。

关键词: EOSID, 航迹规划, 稀疏A*算法, 起飞性能, 三次样条曲线

Abstract:

To resolve the problem that engine out standard instrument departure (EOSID) is only designed manually by engineers, a sparse A* search (SAS) algorithm based on shuttle radar topography mission (SRTM) data is proposed to optimize three-dimensional engine failure takeoff paths. The path planning is divided into two stages: planning space determination and path search. In planning space, SRTM grid terrain data is used, and relevant regulations of EOSID are considered to deal with search space. In path search, SAS algorithm is used to search the departure path. The takeoff performance constraints are added into traditional A* algorithm. Meanwhile, terrain and threat avoidance is finished by using terrain elevation data to produce a three-dimensional instead of a two-dimensional trajectory. The planned departure trajectory is then smoothed by the cubic B-spline curve, and obstacle clearance verification is being conducted. Simulation result shows that the proposed algorithm can be used to optimize a viable EOSID three-dimensional tracking automatically.

Key words: engine out standard instrument departure (EOSID), path planning, sparse A* search (SAS), takeoff perfor-mance, cubic B-spline curve

中图分类号:

V328.3

焦卫东, 程颖, 柯然. 基于SAS算法的起飞一发失效应急路径规划方法[J]. 航空学报, 2016, 37(10): 3140-3148.

JIAO Weidong, CHENG Ying, KE Ran. A path planning method for EOSID based on SAS algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(10): 3140-3148.

参考文献

[1] TALGORN B, LAPORTE S, BES C, et al. One engine out trajectory optimization:AIAA-2010-9013[R]. Reston:AIAA, 2010.
[2] MASSON B, BAIN M, PAGE J. Engine-Out takeoff path optimization out of terrain challenging airports:AIAA-2011-6313[R]. Reston:AIAA, 2011.
[3] MALAEK S M, ABASSI A. Near-Optimal terrain collision avoidance trajectories using elevation maps[C]//IEEE Aerospace Conference.Piscataway, NJ:IEEE Press, 2006.
[4] BARRAQUAND J, LANGLOIS B, LATOMBE J C. Numerical potential field techniques for robot path planning[J]. IEEE Journals & Magazines, 1992, 22(2):224-241.
[5] 王治国. 飞机起飞一发失效应急程序设计研究[D]. 大连:大连理工大学, 2008:1-22. WANG Z G. A study on engine out standard instrument departures design[D]. Dalian:Dalian University of Technology, 2008:1-22(in Chinese).
[6] 骆昕. 起飞一发失效应急程序设计难点的研究分析[J]. 四川:中国民航飞行学院学报, 2014, 25(1):57-63. LUO X. Research and analysis on key problems of engine out standard instrument departures design[J]. Beijing:Journal of Civil Aviation Flight University of China, 2014, 25(1):57-63(in Chinese).
[7] 杨新涅, 丁松滨, 赵磊, 等. 宁波栎社机场进离场程序的优化[J]. 中国民航大学学报, 2007, 25(3):8-12. YANG X S, DING S B, ZHAO L, et al. Optimization of departure and arrival procedures of Ningbo Lishe aerodrome[J]. Journal of Civil Aviation University of China, 2007, 25(3):8-12(in Chinese).
[8] Australian Government Civil Aviation Safety Authority. Civil aviation order 20.7.1B[S]. Canberra:Civil Aviation Safety Authority, 2005.
[9] Australian Government Civil Aviation Safety Authority. Civil guidelines for the consideration and design of engine out SID (EOSID) and engine out missed approach procedures[S]. Canberra:Civil Aviation Safety Authority, 2006.
[10] ICAO. Annex 6, International standards and recommended practices[S]. Montreal:ICAO, 1990.
[11] NILSSON N. Problem-solving methods in artificial intelligence[M]. New York:McGraw-Hill, 1971.
[12] 郑昌文, 严平, 丁明跃, 等. 飞行器航迹规划[M]. 北京:国防工业出版社, 2008:3-49. ZHENG C W, YAN P, DING M Y, et al. Route planning for air vehicles[M]. Beijing:National Defense Industry Press, 2008:3-49(in Chinese).
[13] SZCZERBA R J, GALKOWSKI P, GLICKTEIN I S, et al.Robust algorithm for real-time route planning[J]. Aerospace and Electronic Systems, 2000, 36(3):869-878.
[14] 刘希, 朱凡, 蔡满意, 等. 一种改进的快速航路规划方法[J]. 飞行力学, 2011, 29(1):89-92. LIU X, ZHU F, CAI M Y, et al. Improved method for fast path planning[J]. Flight Dynamics, 2011, 29(1):89-92(in Chinese).
[15] 王奎民. 基于SAS算法的三维多UAV协同航迹规划方法[J]. 电子科技, 2013, 26(11):14-16. WANG K M. Three-dimensional multi-UAV cooperative path planning based on improved SAS algorithm[J]. Electronic Science & Technology 2013, 26(11):14-16(in Chinese).
[16] 马培军, 毛云云, 张洪涛, 等. 基于3DSAS的多约束航迹协同规划与搜索方法[J]. 系统工程与电子技术, 2011, 33(7):1527-1533. MA P J, MAO Y Y, ZHANG H T, et al. Cooperative planning for multiple trajectories with multiple constraints based on 3DSAS[J]. Systems Engineering and Electronics, 2011, 33(7):1527-1533(in Chinese).
[17] 孟中杰, 黄攀峰, 闫杰. 基于改进稀疏A*算法的高超声速飞行器航迹规划技术[J]. 西北工业大学学报, 2010, 28(2):182-186. MENG Z J, HUANG P F, YAN J. Exploring trajectory planning for hypersonic vehicle using improved sparse A* algorithm[J]. Journal of Northwestern Polytechnical University, 2010, 28(2):182-186(in Chinese).
[18] 黄文刚, 张怡, 姜文毅, 等. 变步长稀疏A*算法的无人机航路规划[J]. 计算机工程与应用, 2012, 48(29):206-209. HUANG W G, ZHANG Y, JIANG W Y, et al. SAS algorithm with changeable steps for route planning of UAVs[J]. Computer Engineering and Applications, 2012, 48(29):206-209(in Chinese).
[19] 王金敏, 崔奇, 初楠. 运用三次样条曲线拟合机器人运动路径[J]. 机械设计, 2005, 22(7):44-46. WANG J M, CUI Q, CHU N. Fitting robot motion path based on cubic spline curve[J]. Journal of Machine Design, 2005, 22(7):44-46(in Chinese).
[20] 张玲. 基于三次样条曲线拟合公路平面线形方法研究[D]. 武汉:武汉理工大学, 2007:24-31. ZHANG L. Analysis of fitting method on plan curve based on cubic spline[D]. Wuhan:Wuhan University of Technology, 2007:24-31(in Chinese).

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于SAS算法的起飞一发失效应急路径规划方法

A path planning method for EOSID based on SAS algorithm

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