基于SAS算法的起飞一发失效应急路径规划方法
收稿日期: 2015-11-13
修回日期: 2015-12-17
网络出版日期: 2016-04-13
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
Received date: 2015-11-13
Revised date: 2015-12-17
Online 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)
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。
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 . DOI: 10.7527/S1000-6893.2016.0051
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.
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