ID 原文 译文
5574 该算法使得每架无人机在任意时刻都能直接或间接地获取虚拟长机信息。 The algorithm makes every drone can directly or indirectly, in any time for the virtual flight information.
5575 引入集群对虚拟长机的反馈机制,与传统反馈算法不同的是,本文中反馈无人机的数量和组成成员都是变化的,从而提高了系统的收敛速度和鲁棒性。 Introduction of cluster on the feedback mechanism of virtual flight, unlike traditional feedback algorithm, this article feedback of unmanned aerial vehicle (uav) and the number of members are changing, so as to improve the convergence speed and robustness of the system.
5576 在此基础上进一步讨论编队的损伤问题,设计了一种基于分层的分布式递归自修复算法,解决了网络分裂状态下的自修复及修复后队形变化过大的问题。 On this basis to further discuss the damage of formation, we design a distributed recursive self-healing algorithm based on hierarchical, solve the network under the split of the repair and after repair formation change too much.
5577 仿真结果表明了所建模型的合理性和求解方法的有效性。 The simulation results show the rationality of the model and the effectiveness of the method.
5578 由于人工势场法中障碍物的影响距离通常为一个固定值,不可避免地导致无谓避碰行为的出现,极大影响航路规划的效率。 Due to obstacles in the artificial potential field method is usually a fixed value, the influence of the distance, inevitably lead to the emergence of meaningless collision avoidance behavior, greatly affect the efficiency of route planning.
5579 本文在动态环境下,针对无谓避碰行为,提出碰撞危险度评估模型和障碍物影响距离确定模型; Under the dynamic environment, this paper aimed at meaningless collision avoidance behavior, distance to determine the influence of collision risk evaluation model and obstacles proposed model;
5580 针对障碍物在目标附近目标不可及问题(goals nonreachable with obstacles nearby,GNRON),提出能够区别评估障碍物的时间碰撞危险度模型; For barrier near the target goals and problems (goals nonreachable with obstacles basis, GNRON), is put forward to the difference between evaluation time collision risk model of the obstacles;
5581 针对陷阱问题,提出虚拟障碍物法,以此构成基于碰撞危险度的无陷阱动态航路规划法。 According to trap problem, put forward the method of virtual obstacles to constitute no trap dynamic route planning method based on risk of collision.
5582 仿真结果表明该方法能够有效避免无谓避碰行为和陷阱问题的发生,且无GNRON问题,所得路径也较短且平滑。 The simulation results show that this method can effectively avoid meaningless collision avoidance behavior and trap the happening of the problem, and no GNRON problem, the path is short and smooth.
5583 针对分布式相参雷达(distributed coherent aperture radar,DCAR)精确的目标参数估计问题,首先建立了以多普勒分复用(Doppler division multiple access,DDMA)波形作为发射波形、存在滤波器网格失配的DCAR信号模型,接着分析并验证了滤波器网格失配严重影响目标参数估计进而降低DCAR信号相参合成性能,最后提出了联合全局-局域搜索和基于稀疏傅里叶变换(sparse Fourier transform,SFT)的两种DCAR目标参数估计方法来降低滤波器网格失配,联合全局-局域搜索的方法通过对滤波器局域加密的方式降低网格失配。 For distributed coherent radar (distributed coherent aperture radar, DCAR) precise target parameter estimation problem, first established by Doppler division multiplexing (Doppler division multiple access, DDMA) waveform as the transmitting waveform, filter mesh DCAR signal model mismatch, then analyze and validate the filter mesh mismatch seriously affect the target parameter estimation and thus DCAR signal phase circuit performance, and finally puts forward the joint - local search and global based on sparse Fourier transform (sparse Fourier transform, the SFT) of two kinds of DCAR target parameter estimation method to reduce mismatch filter mesh, united global - local search method to filter through local encrypted way lower grid mismatch.