| 基于改进粒子滤波算法的水下目标跟踪 |
| |
| 引用本文： | 周伟江,董博,许伟杰.基于改进粒子滤波算法的水下目标跟踪[J].声学技术,2018,37(2):187-191. |
| |
| 作者姓名： | 周伟江 董博 许伟杰 |
| |
| 作者单位： | 中国人民解放军92493部队;中国科学院声学研究所东海研究站 |
| |
| 摘 要： | 针对常规粒子滤波算法粒子数目保持不变的问题,提出了一种可以自适应调整粒子数目的改进算法。该算法将KL距离(Kullback-Leibler Divergence,KLD)引入粒子滤波重采样过程,保证在一定的滤波精度下,可以有效地调整滤波过程中使用的粒子数目,从而实现了滤波过程中粒子数目的自适应。将该算法应用于纯方位水下目标跟踪,仿真结果表明,该方法有效地改善了滤波效果,计算量低,适合于实际应用。
|
| 关 键 词： | 目标跟踪 粒子滤波 KL距离 |
| 收稿时间： | 2017/5/21 0:00:00 |
| 修稿时间： | 2017/7/17 0:00:00 |
Underwater target tracking based on improved particle filter |
| |
| ZHOU Wei-jiang,DONG Bo and XU Wei-jie.Underwater target tracking based on improved particle filter[J].Technical Acoustics,2018,37(2):187-191. |
| |
| Authors: | ZHOU Wei-jiang DONG Bo and XU Wei-jie |
| |
| Affiliation: | PAL 92493, Huludao 125000, Liaoning, China,Shanghai Acoustics Laboratory, Institute of Acoustics, Chinese Academy of Sciences, Shanghai 200032, China and Shanghai Acoustics Laboratory, Institute of Acoustics, Chinese Academy of Sciences, Shanghai 200032, China |
| |
| Abstract: | An improved adaptive particle number method is presented to solve the problem of huge computation complexity.The algorithm is proposed via introducing the KLD (Kullback-Leibler Divergence) into the process of resampling so as to control the effective particle number.Numerical simulations demonstrate that the modified method can improve tracking performance and suit for practical applications. |
| |
| Keywords: | target tracking particle filter Kullback-Leibler Divergence (KLD) |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《声学技术》浏览原始摘要信息 |
|
点击此处可从《声学技术》下载全文 |
|
