Distributed cooperative multi-missile maneuvering target tracking via approximate Chernoff fusion of Gaussian mixtures

To address the challenge that traditional single-missile observation modes cannot achieve high-accuracy acceleration estimation for highly maneuvering targets, thereby affecting terminal guidance precision, this paper proposes a distributed fusion algorithm based on multi-missile cooperative measurement and the interactive multiple model framework. First, a cooperative measurement scheme is designed, and observability analysis is conducted to derive the constraints under which cooperative measurement enhances the observability of target motion states. Second, an approximate Chernoff fusion strategy is introduced to solve the problem of local estimation fusion among multiple missile nodes based on Gaussian mixture models. Finally, simulation experiments are carried out in representative highly maneuvering target scenarios. The results demonstrate that, compared with conventional methods, the proposed algorithm improves the estimation accuracy of position, velocity, and acceleration by approximately 90%, 95%, and 52%, respectively, and its stability is further verified through Monte Carlo simulations.