Research on the Optimization Method of Collaborative Air Search of Radar Guidance

To counter the degradation of detection range and probability caused by stealth targets, this paper investigates optimization methods for collaborative air search. An information-level cooperative strategy is adopted. Prior target information is first obtained through wide-beam coarse search. The search space is then divided according to the detection performance differences among platforms, and the acquired information is utilized to guide the search of other collaborative platforms, thereby optimizing the illumination times for each beam position. By establishing monopulse detection models and non-cooperative search models, the performance limitations of single-platform and dual-platform non-cooperative search are analyzed. Based on this, a collaborative search method incorporating airspace division and prior-information guidance is proposed and extended to multi‑platform scenarios. Simulation results demonstrate that the proposed collaborative method significantly improves the average detection probability while effectively reducing the actual search time, validating the effectiveness of information-level cooperation in enhancing seeker search performance. This study may provide a reference for the development of inter-missile cooperative detection technologies.