An improved particle filter algorithm based on neural network for target tracking

被引：0
|
作者：
Wen, Qin [1 ]
Peng Qicong [1 ]
机构：
[1] Univ Elect Sci & Technol, Inst Commun & Informat Engn, Chengdu, Peoples R China
来源：
INTELLIGENT INFORMATION PROCESSING III | 2006年 / 228卷
关键词：
particle filter; target tracking; general regression neural network;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To the shortcoming of general particle filter, an improved algorithm based on neural network is proposed and is shown to be more efficient than the general algorithm in the same sample size. The improved algorithm has mainly optimized the choice of importance density. After receiving the samples drawn from prior density, and then adjust the samples with general regression neural network (GRNN), make them approximate the importance density. Apply the new method to target tracking problem, has made the result more precise than the general particle filter,
引用
收藏
页码：297 / +
页数：2
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