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首页> 外文期刊>Journal of aerospace engineering >Dynamic Perceptive Bat Algorithm Used to Optimize Particle Filter for Tracking Multiple Targets
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Dynamic Perceptive Bat Algorithm Used to Optimize Particle Filter for Tracking Multiple Targets

机译：动态感知蝙蝠算法用于优化跟踪多个目标的粒子滤波

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摘要

Resampling of standard particle filters will cause particle depletion and require abundant particles in the state estimation, which can hardly meet the accuracy and velocity requirements of a modern radar tracking system. This paper proposes an improved multiple-maneuvering-target tracking algorithm based on a novel intelligent particle filter. The improved algorithm combines the bat algorithm and particle filters and takes particles as bats to simulate behavior of bats in pursuit of prey. By adjusting frequency, volume, and pulse rate, particle groups search for the optimal value and move to high likelihood areas intelligently under the guidance of the optimal particle. Meanwhile, it improves the optimization mechanism of the bat algorithm; dynamic control of searching velocity and perception range are proposed. It makes the algorithm seek optimization within a self-adaptive cognition range, and the optimizing rate can be adjusted dynamically to control the balance of global and local optimizing abilities. Furthermore, the improved algorithm combines interacting multiple model and joint probabilistic data association, which enables improved accuracy in target tracking and robustness in a complex environment by iterative optimization. Simulation results show that the improved algorithm enhances the performance of a multiple-maneuvering-target tracking system. (c) 2018 American Society of Civil Engineers.
机译：对标准粒子滤波器的重采样将导致粒子耗竭，并且在状态估计中需要大量粒子，这几乎无法满足现代雷达跟踪系统的精度和速度要求。提出了一种基于新型智能粒子滤波的改进的多目标跟踪算法。改进的算法结合了蝙蝠算法和粒子过滤器，并以粒子作为蝙蝠来模拟蝙蝠的行为，以追踪猎物。通过调整频率，音量和脉冲率，粒子组搜索最佳值，并在最佳粒子的指导下智能地移动到高可能性区域。同时，改进了bat算法的优化机制。提出了搜索速度和感知范围的动态控制。它使算法在自适应认知范围内寻求优化，并且可以动态调整优化速率以控制全局和局部优化能力的平衡。此外，改进的算法结合了相互作用的多个模型和联合概率数据关联，从而可以通过迭代优化提高目标跟踪的准确性和复杂环境中的鲁棒性。仿真结果表明，改进算法提高了多目标跟踪系统的性能。 （c）2018年美国土木工程师学会。

著录项

  • 来源
    《Journal of aerospace engineering》 |2018年第3期|04018015.1-04018015.17|共17页
  • 作者

    Chen Zhimin; Bo Yuming; Tian Mengchu; Wu Panlong; Ling Xiaodong;

  • 作者单位

    China Satellite Maritime Tracking & Controlling D, Jiangyin 214431, Peoples R China;

    Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China;

    Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China;

    Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China;

    China Satellite Maritime Tracking & Controlling D, Jiangyin 214431, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Particle filter; Bat algorithm; Dynamic perceptive; Multiple targets;

    机译：粒子滤波;蝙蝠算法;动态感知;多个目标;

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