Adaptive Control Bat Algorithm Intelligent Optimization Particle Filter for Maneuvering Target Tracking

被引：0

作者：

Chen Z.-M. ^{[1
]}

Wu P.-L. ^{[2
]}

Bo Y.-M. ^{[2
]}

Tian M.-C. ^{[2
]}

Yue C. ^{[2
]}

Gu F.-F. ^{[1
]}

机构：

[1] China Satellite Maritime Tracking and Controlling Department, Jiangyin, 214431, Jiangsu

[2] School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2018年 / 46卷 / 04期

关键词：

Bat algorithm; Closed-loop control; Particle diversity; Particle filter; Target tracking;

D O I：

10.3969/j.issn.0372-2112.2018.04.017

中图分类号：

学科分类号：

摘要：

Resampling of particle filters will cause particle depletion and the comprehensive performance is low, which can hardly meet the requirement of high frequency accurate radar. To address to the problem, a novel adaptive control bat algorithm optimized particle filter for maneuvering target tracking was proposed in this paper. It introduced bat algorithm into particle filter and took particle as bat individual to simulate the process of hunting and made particles move to high likelihood area. Meanwhile, by taking proportion of accepting as feedback, the improved algorithm designed closed-loop control strategy and controlled the balance between ability of global optimization and local optimization and improved rationality of particles distribution and accuracy of filter. Finally, the improved algorithm was tested in basic nonlinear filter model and strong maneuvering-jamming target tracking model. The experimental results prove that the new algorithm conduces to enhancement of the precision for target tracking. © 2018, Chinese Institute of Electronics. All right reserved.

引用

页码：886 / 894

页数：8

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