Multi-target assignment method for collaborative interception based on reachable domain coverage
Abstract
For multi-target interception tasks in near-space scenarios where the overload capability is balanced, employing multiple interceptors for collaborative interception is a critical approach to enhance the interception success rates. This paper investigates multi-target assignment method for “multi-to-multi” collaborative interception based on reachable domain coverage. Initially, we rapidly predict the reachable domains of maneuvering targets using filtering estimation and error propagation theory. Subsequently, by integrating trajectory optimization with machine learning techniques, we swiftly determine the reachable domains of interceptor missiles. Further, we construct an optimization model for multi-target assignment based on the positional coverage of reachable domains and solve it using the differential evolution algorithm. Finally, through a numerical example involving 12 interceptors collaboratively intercepting 4 hypersonic gliding vehicles, we validate the accuracy and efficiency of our proposed methods for rapid prediction of reachable domains for maneuvering targets and rapid determination of reachable domains for interceptor missiles, as well as the effectiveness of the multi-target assignment method.
