Research on underwater location algorithm based on probability graph model

Abstract

With the rapid development of acoustic technology, underwater localization plays a more and more important role in the field of Marine resource exploitation and Marine military. In order to accurately obtain the underwater target location, the long baseline positioning method is often used. However, in the long baseline positioning process, sparse beacon or missing beacon communication information will lead to insufficient measurement information, so that the effective position of the target can not be obtained. Therefore, for a moving target, it is necessary to combine the measurement information of other positions and adopt the multi-parameter fusion estimation method to solve the problem, but it is difficult to obtain the analytical solution by multi-parameter fusion. Aiming at the above two problems, this paper uses the probability graph model to estimate the target. In this method, the distance between the target and the node is taken as the input to represent the spatial interconnection, and the target speed is taken as the input to represent the interconnection between the positions of two adjacent moments. After the probability graph is established, the sum product algorithm is adopted to obtain the expression of the edge function of the variable through message passing and updating. Finally, the validity of the probabilistic graph method is proved by lake experiment. In the process of multi-beacon and single beacon positioning and tracking, the target position can be estimated at every moment and the trajectory of the target can be described.