论文部分内容阅读
为提高移动目标跟踪的精度,提出一种基于阶段化捕食空间自适应尺度策略蝙蝠算法(APRBA)的粒子滤波移动目标跟踪算法。首先,给出蝙蝠算法基本步骤,同时为提高蝙蝠算法的优化性能,利用阶段化捕食空间自适应尺度策略对蝙蝠算法进行改进,提高算法的优化性能;其次,利用提出的APRBA算法的超声波食物源定位和下一目标预测,对粒子滤波算法进行改进实现目标跟踪精度的有效提升;最后,通过在移动目标模型跟踪实验中,验证了所提目标跟踪算法的有效性。
In order to improve the accuracy of moving target tracking, a moving target tracking algorithm based on particle swarm optimization algorithm based on phased adaptive predator-scale bat algorithm (APRBA) is proposed. First of all, the basic steps of the bat algorithm are given. At the same time, to improve the performance of the bat algorithm, bat algorithm is improved by using the adaptive scale strategy of phased predator space to improve the performance of the algorithm. Secondly, using the proposed APRBA algorithm, Positioning and next target prediction, the particle filter algorithm is improved to achieve the target tracking accuracy improvement. Finally, the effectiveness of the proposed target tracking algorithm is verified by tracking experiments in the moving target model.