Intention Recognition of Close-Range Space Objects Based on GRU-SA

Intention recognition of non-cooperative space objects is a crucial problem for space situational awareness. This paper proposes a method for intention recognition of close-range space non-cooperative objects before intention realization based on the GRU-self-attention network (GRU-SA). Typical intention set is defined and the comprehensive learning particle swarm optimization (CLPSO) algorithm is adopted to construct the dataset. The proposed network is trained and tested on the dataset. The results demonstrate the effectiveness of the proposed method in recognizing the intentions of close-range space non-cooperative objects and verify the robustness of the model.