A Study on a Multi-sensor Cooperative Scheduling Method for Mid-course Guidance of Air-to-air Missiles

To address the challenge of balancing tracking accuracy, guidance performance, and emission stealth in multi-sensor scheduling during the mid-course phase of air-to-air missile guidance, this paper proposes a guidance-quality-integrated scheduling method. A radar-infrared multi-platform model is built, where a Causal Attention LSTM predicts and filters target states, and an emission interception-probability factor quantifies sensor exposure. A guidance-quality factor based on radar activation timing is introduced to assess its impact on terminal intercept probability. These metrics-emission risk, tracking accuracy, and guidance quality-are formulated as a multi-objective optimization problem, and an opposition-based learning war strategy optimization algorithm is used to derive the optimal scheduling sequence. Simulation results show that the proposed method improves intercept probability while maintaining a balanced trade-off between stealth and tracking performance.