提出了基于矢量数据的三维航迹规划方法。
A three-dimensional path planning method based on vector data is presented.
航迹规划算法改进。
Smoothing algorithm is integrated into dynamic trajectory programming.
为此本文研究了低可观测飞行器的航迹规划方法。
Therefore, this thesis makes a research on the route planning method of low observable aircraft.
该方法能够在具有预先未知威胁的飞行环境中在线实时航迹规划。
This approach can be used for on line route re planning in flying environment with unknown threat.
而决定突防成功与否的一个关键因素又在于航迹规划的正确性和有效性。
The correctness and validity of route planning is the main factor that determines the result of low-altitude penetration.
本文首先对基于栅格法和人工势场法思想的离线航迹规划算法进行了研究。
Firstly, the research of this paper is focus on preflight global planning algorithm based on cell decomposition methods and artificial potential field methods.
覆盖航迹规划技术对于提高无人机的侦察能力和目标搜索能力具有重要的意义。
The coverage flight path planning is very important to enhance the UAV's abilities of reconnaissance and target searching.
在分析多峰值函数优化问题的基础上，提出了一种基于进化计算的飞行器多航迹规划方法。
Based on the analysis of multi-modal function optimization using evolutionary computation, a new multiple routes planner for unmanned air vehicles is proposed.
航迹规划的目的是要利用地形和敌情等信息，规划出生存概率最大的无人飞行器突防轨迹。
Path planning is designed to make use of terrain and enemy and other information to plan out the largest survival probability penetration trajectory of Unmanned Aerial Vehicle (UAV).
论述了航迹规划的基本要求，如导航要求、突防要求、飞行器性能要求及战略和战术要求。
The basic requirements such as navigation requirement, penetration requirement, characteristics requirement for the aircraft, and the strategic and tactic requirements are also introduced.
提出了一种在已知静态环境下利用进化计算实现多无人飞行器的分层离线协同航迹规划方法。
An evolutionary computation method is utilized to design a hierarchical and off-line path planner for multiple Unmanned Aerial Vehicles (UAV) coordinated navigation in known static environments.
为解决作战环境中的多无人机协同航迹规划问题，提出一种基于层次分解策略的航迹规划方法。
A path planning method based on the hierarchical decomposition strategy was proposed for multi-UAV cooperative path planning in the battle field.
针对多飞行器的协调航迹规划展开研究，提出了一种基于协同进化的多飞行器协调航迹规划算法。
The cooperative route planning problem of multiple air vehicles is studied with the proposal of a novel coevolutionary coordinative route planner.
遗传算法的最大特点是其并行性和全局寻优性，特别适用于航迹规划这类多目标规划问题的求解。
The biggest feature of GA is the parallelism and the global searching, so it's very suitable for the multi-goals problems like flight path planning.
航迹规划是飞行任务规划的重要组成部分，对行就规划算法进行研究具有重要的理论和实用价值。
Flight path planning is a very important part of the mission planning system, so the research on the flight path planning algorithms is well worth both on theoretic and practical.
目前在飞行器航迹规划和航迹控制这一研究领域中，寻找飞行器最优航迹成为一个重要的研究方向。
Currently how to search for an optimal trajectory becomes an important aspect in trajectory planning and control's fields.
提出采用一种结合三角网格退化、变域动态规划以及航迹优化的方法来解决突发威胁下的航迹规划问题。
This method combined the ameliorated grid degenerate and dynamic programming, it can solve the problem of time delay in path planning with sudden appearing threats.
TA最优航迹规划技术可以在很大程度上提高突防飞行器的突防概率，是实现飞行器低空突防飞行的关键技术。
The probability of low altitude penetration can be highly improved by the TF/TA optimal trajectory planning. Trajectory planning is a key technique in realizing low-altitude-penetration.
适当地结合规划-跟踪算法和航迹角控制器可给再入制导带来极大的灵活性和适应性。
Proper combination of planning-tracking algorithm and FPA controller can bring great flexibility and adaptability to reentry guidance.
通常所使用的动态规划算法得到的规划航迹有时达不到目标点。
The planning track that is gotten from dynamic programming algorithm sometimes can not achieve the aimed target.
航迹角修正法的采用，进一步修正了规划出的飞行轨迹，从而获得了理想的飞行参考轨迹。
After adopting the correcting method of flight path Angle, flight path planned is further modified and ideal reference flight path is obtained.
解决了无人机在飞行过程中遇到突然出现的威胁时的航迹重规划难题，给出了应用该算法的具体步骤。
It mainly resolves the pop-up threats in route replanning, and the particular applying approach for this algorithm is presented.
然后建立协同模型，为各无人机规划出既能满足时间协同要求，又能满足整体代价最优的可行航迹。
Then a cooperative planning model was established, which could plan a feasible path for each UAV, which meeted both the requirements of time-coordination and the minimum cost.
航迹的规划采用曲线拟合的方式。
The approach of curve fitting is used to mark out of the flight path.
该算法采用分层思想，将局部规划与全局规划相结合，并对代价函数进行了改进，在保证航迹优化的基础上，提高了搜索效率。
The algorithm uses the thought of delamination, makes local planning and global planning combination, and improves cost function, finally with ensuring optimal trajectory increases search efficiency.
该算法采用分层思想，将局部规划与全局规划相结合，并对代价函数进行了改进，在保证航迹优化的基础上，提高了搜索效率。
The algorithm uses the thought of delamination, makes local planning and global planning combination, and improves cost function, finally with ensuring optimal trajectory increases search efficiency.
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