A Study of Observability Analysis and Data Fusion for Bias Estimation in a Multi-Radar System
Gun-Hee Won, Taek-Lyul Song, Dasol Kim, Il-Hwan Seo, Gyu-Hwan Hwang · Journal of Institute of Control Robotics and Systems · 2011
Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.