An Axial Attention-Based UUV Non-Cooperative Target State Estimation Method
To improve the accuracy of unmanned underwater vehicle(UUV)state estimation of non-cooperative targets,an axial attention-based target state estima-tion method is proposed in this paper.The state estimation mechanism of the UUV non-cooperative target based on sonar observation is analyzed.The non-Markov state-space model of the problem is transformed into a first-order Markov state-space model with memory,and a recursive filtering model is constructed.Aiming at the unreliability of forward-looking sonar observation and the unpredictability of target motion,a multi-step prediction network based on transformer is proposed to describe the complex motion process of non-cooperative target relative to sonar under nonlin-ear observation.Aiming at the instability of observation and the unpredictability of posterior distribution,based on the Monte Carlo approximate inference principle,the multi-step prediction network is used to map the particles in the target measurement state space to the target prediction state space,and a non-cooperative target state estimation algorithm based on the axial attention is constructed.The simulation re-sults show that the adaptability and robustness of the proposed method to uncertain inputs.
Target state estimationaxial attentionunmanned underwater vehicleforward-looking sonarnon-cooperative targets
万方数据
