An Adaptive WSN Node Tracking Algorithm Based on Rough-set Neural Network

被引：4
|
作者：
Wang, Haobo [1 ]
Ren, Weizheng [1 ]
Cui, Yansong [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
来源：
2012 INTERNATIONAL WORKSHOP ON INFORMATION AND ELECTRONICS ENGINEERING | 2012年 / 29卷
关键词：
WSN; rough-set; neural network; tracking;
D O I：
10.1016/j.proeng.2012.01.207
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In order to overcome effects of complex environment and movement on node tracking, and improve tracking precision further, a rough-set neural network-based adaptive tracking algorithm named rough-set adaptive interactive multi-modulus (RSAIMM) was proposed in which tracking filter based on neural network was employed. When target moved between maneuvering and non-maneuvering, rough-set neural network output adaptive feature value automatically online, to adapt to the movement with adequately accurate system variance and maintain high precision tracking of target state. Simulation results showed that compared with traditional interactive multi-modulus (IMM) tracking algorithm, tracking precision of RSAIMM algorithm was improved by 23.15%. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology
引用
收藏
页码：1750 / 1754
页数：5
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