To enhance the missile early warning radar's capacity for rapid and precise target detection, a novel dynamic search area matching (DSAM) model guided by target information is introduced. This model leverages a comprehensive analysis of target state estimation and error data obtained from geosynchronous orbit early warning satellites and radar systems. The trajectory prediction error is derived using elliptical trajectory theory, informing the target guidance information. Additionally, an error ellipse-based search area model is established for the early warning radar, integrated with a dynamic search area matching strategy that accounts for both the radar's search frame period and the target's motion state. This approach ensures continuous and stable target tracking. Simulation experiments demonstrate the superiority of this model in terms of search probability, search data rate, and time resource utilization efficiency, positioning it as a valuable search optimization method for missile early warning radar.