二进制传感器网络基于预测的距离加权目标跟踪算法

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

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.