Research on general ground target tracking based on terrain information

By introducing terrain information, the ground target tracking performance may be further improved because the constraints of the terrain information are helpful to decrease the target modeling uncertainties resulting from unexpected maneuvers. A general ground target tracking scheme is proposed that adaptively determines a reduced model set, so that the 'excessive competition' of multiple models is avoided and the computation burden is reduced. Furthermore, the extended map tuned variance (EMTV) method is presented based on the above scheme. In the EMTV, the strategy of adaptively obtaining the reduced model set and adjusting model-conditional variance is also presented. The results of simulation show that EMTV is the best compared with the traditional Kalman filter and the map-tuned variance (MTV) method.