Prediction-Based Distance Weighted Algorithm for Target Tracking in Binary Sensor Network  

作　　者：SUN Xiaoyan LI Jiandong CHEN Yanhui HUANG Pengyu 

机构地区：[1]Broadband qgireless Communications Laboratory, Information Science Institute State Key Laboratory of Integrated Service Networks,Xidian University, Xi＇an, 710071, China [2]College of Information Engineering, Xi＇an International University, Xi＇an, 710077, China

出　　处：《China Communications》2010年第4期41-50,共10页中国通信（英文版）

基　　金：This work is supported by The National Science Fund for Distinguished Young Scholars （60725105）; National Basic Research Program of China （973 Program） （2009CB320404）; Program for Changjiang Scholars and Innovative Research Team in University （IRT0852）; The National Natural Science Foundation of China （60972048, 61072068）; The Special Fund of State Key Laboratory （ISN01080301）; The Major program of National Science and Technology （2009ZX03007- 004）; Supported by the 111 Project （B08038）; The Key Project of Chinese Ministry of Education （107103）.

摘　　要：Binary sensor network(BSN) are becoming more attractive due to the low cost deployment,small size,low energy consumption and simple operation.There are two different ways for target tracking in BSN,the weighted algorithms and particle filtering algorithm.The weighted algorithms have good realtime property,however have poor estimation property and some of them does not suit for target’s variable velocity model.The particle filtering algorithm can estimate target's position more accurately with poor realtime property and is not suitable for target’s constant velocity model.In this paper distance weight is adopted to estimate the target’s position,which is different from the existing distance weight in other papers.On the analysis of principle of distance weight (DW),prediction-based distance weighted(PDW) algorithm for target tracking in BSN is proposed.Simulation results proved PDW fits for target's constant and variable velocity models with accurate estimation and good realtime property.Binary sensor network（BSN） are becoming more attractive due to the low cost deployment, small size, low energy consumption and simple operation. There are two different ways for target tracking in BSN, the weighted algorithms and particle filtering algorithm. The weighted algorithms have good realtime property, however have poor estimation property and some of them does not suit for target＇s variable velocity model. The particle filtering algorithm can estimate target＇s position more accurately with poor realtime property and is not suitable for target＇s constant velocity model. In this paper distance weight is adopted to estimate the target＇s position, which is different from the existing distance weight in other papers. On the analysis of principle of distance weight （DW）, prediction-based distance weighted（PDW） algorithm for target tracking in BSN is proposed. Simulation results proved PDW fits for target＇s constant and variable velocity models with accurate estimation and good realtime property.

关 键 词：Binary Sensor Network Weighted Algorithm Particle Filter Distance Weight Recursive Least Squre（RLS） 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置] TP13[自动化与计算机技术—控制科学与工程]