【作者】 黄文娟；

【导师】 杨淑莹；

【作者基本信息】 天津理工大学 ， 计算机应用技术， 2010， 硕士

【摘要】 粒子滤波方法是近年提出的一种适用于目标跟踪的有效算法,但存在粒子的退化现象,导致许多状态更新的估计对目标跟踪轨迹不起任何作用,在浪费大量计算资源的同时降低了粒子滤波器的性能。因此研究一种实时性,准确性和鲁棒性好的寻优方法是目标跟踪的关键问题。人工鱼群算法具有快速跟踪极值点漂移的能力,及较强的跳出局部极值点的能力,因此在运动目标跟踪领域具有重要的应用价值。本文对基于人工鱼群算法的目标跟踪系统进行研究。本文在分析了人工鱼群算法和粒子滤波算法理论基础上,构建人工鱼群目标跟踪模式,该模式采用人工鱼的觅食、聚群、追尾三种行为策略,不同的行为模式定义粒子不同的状态转移方程,根据试探行为接近目标程度而选不同的状态转移模型,避免了粒子滤波算法相同的状态转移模式,使粒子具有智能群体的行为。仿真实验表明,人工鱼群算法在动态目标速度和方向骤变,以及存在遮挡物情况下,避免目标丢失现象,为解决动态目标跟踪提供了新方法。本文利用进化规划的变异算子,增加人工鱼的多样性,扩大鱼群的分布搜索范围,加快获得全局最优解的速度。采用协同控制技术,构建多个子人工鱼群的分布体系,对每一个子群体进行三种行为试探,将最优子群体的状态指导其它群体的移动,实现了个体与群体的信息交互与相互协作机制,消除人工鱼漫无日的随机游动。仿真实验表明该方法能够适应目标运动的随机性和动态性,扩大了搜索范围,提高跟踪性能。更多还原

【Abstract】 The particle filter method is an effective algorithm which is put forward for target tracking. Due to the degeneration phenomenon in the algorithm of particle filter, state estimate to a trajectory may be invalid, resource is wasted, and performance is reduced. Therefore, the method with real-time, accuracy and robustness is a key for the target tracking. The abilities of the maximum drifting and jumping out of a local extreme value are possessed by the algorithm of artificial fish swarm. So, the algorithm of artificial fish swarm has an important application value in the area of target tracking. Target tracking using the algorithm of artificial fish swarm is studied in the paper.Based on the analysis of the algorithms of artificial fish and particle filter, the target tracking model by artificial fish swarm is proposed in the paper. The behaviors of preying, clustering, tailgating in artificial fish swarm are adopted. Different behavior is defined as different state transition formula which is selected to use according to the distance near a target. Thus, the same transition formula in classical particle filter is avoided and this makes particles more intelligent. Simulation results show that the algorithm can be used to solve the losing target phenomenon when a motion target speeding and changing direction suddenly or being blocked. A new method is proposed in target tracking model.In order to expand distribution scope and quickly get a global optimal state, the evolution of mutation operator is used to increase the diversity of artificial fish in the paper. Based on the technology of synergistic control, artificial fish is divided into different groups in distribution system. In different groups three behaviors are tested and the better value is gained which is used to guide the motion of other groups. The cooperation and mutual information between any individual and groups are realized. At the same time, the aimless random swimming of artificial fish is eliminated. Simulation results show that the target moving randomly and dynamically can be tracked, the search scope expanded, and tracking performance improved by the proposed method.更多还原