Uncertainty Analysis of Multiple Target Tracking in Distributed Sensor Networks
En Fan, Shigen Shen, Hu Ke-li, Yuan Chang-Hong, Pin Wang · International Journal of Control and Automation · 2016
The related theories and technologies on sensor networks are a hot research field. Due to great uncertainties existed in its data processing, multiple target tracking (MTT) has become a difficult problem in distributed sensor networks (DNWs). Hence, this paper mainly studies the uncertainty problems on MTT in the framework of DNW systems by using the fuzzy theory. According to its model structure, a DNW system can be divided into three layers according to its model structure: the data capture layer, data processing layer and data analysis layer. Based on data processing in different layers, the MTT process can be classified as three phrases: data association/fusion of measurementmeasurement/sensor track, sensor track-local track, and local track-global track. It presents a complete procedure of data processing on MTT in a real tracking system. Then, the uncertainty problems on MTT are classified. After analyzing data characteristics, one can utilize the fuzzy information processing technology to solve these problems. Finally, the difficulties on MTT in real tracking systems are summarized.