AN accurate-evaluator based multi-pursuer multi-target assignment by maximizing interception probability

To address the issue of intercepting target unmanned aerial vehicle(UAV) swarms with UAV swarms (SIS), this paper proposes an accurate evaluator to solve the multi-pursuer multi-target assignment(MPMTA)problem, also known as the traditional Weapon Target Assignment (WTA) method, aiming to achieve high-probability interceptions. Firstly, the covariance analysis technique is introduced to calculate the mean and variance of the miss distance, which are combined with the damage radius of airborne warheads to accurately evaluate the probability of interceptions. Then, this accurate index is utilized to formulate the MPMTA model with the consideration of the target’s threat. Additionally, the improved Column Enumeration (ICE) method is introduced to solve the accurate model rapidly and exactly. The ICE method employs the marginal return optimization approach to determine the initial values for the column enumeration problem and effectively combines the advantages of heuristic algorithms in terms of computational speed and the optimality of exact algorithms. Numerical simulations validate the effectiveness of this method based on an accurate evaluator, demonstrating that the accurate interception probability model and precise algorithm enhance the accuracy of the MPMTA assignment problem.