Heterogeneous Data Fusion Model for Passive Object Localization

The passive object localization problemPOLPaims to detect the location of the target. This task requires the target does not have any device to receive signal or transfer. The sensor fusion model for localization is more popular, such as the Kalman Filter(KF). In this paper, an novel fusion model based on the KF is used in fusing some parameters, like the RSSI(Receive Signal Strength Index), infrared data and ultrasound data, which are come from the measurements. The proposed fusion model can promote the accuracy of localization, and provides the higher available of localization. The simulation result have proved that the proposed methods is adequate to the passive localization, compared with other traditional methods, the localization accuracy is greatly improved.