Intention Recognition of Non-Cooperative Space Targets Based on GMM-HMM

Intention recognition of non-cooperative space target is a crucial problem for space situational awareness. This paper proposes a method for intention recognition of long-distance space non-cooperative targets based on the Gaussian mixture-hidden Markov network (GMM-HMM). Typical target intention set are defined and a multi-layer nonlinear optimization method is adopted to generate realistic target trajectories and construct the dataset. Subsequently, the proposed model is trained and tested on the dataset. The results demonstrate the effectiveness of the proposed method in recognizing the intentions of long-distance space non-cooperative targets and verify the robustness and generalization ability of the model.