Location Prediction for Tracking Moving Objects Based on Grey Theory
Yingyuan Xiao, Hua Zhang, Hongya Wang · 2007
The traditional predictive methods for tracking moving objects usually assume that moving objects have linear motion patterns. This severely limits their applicability, since in practice movement is usually free and uncertain. In this paper, a novel location prediction model based on grey theory is presented. The proposed location prediction model adopts the grey modeling method to predict the future location of uncertain moving objects. Comparing with the linear prediction model, the proposed prediction model relaxes the limitation to motion pattern of moving objects and the requirement for accuracy of sampling data. The experiment results show the proposed prediction model can provide the more exact prediction than the linear prediction model.