Estimation of Coordinates and Motion Parameters of an Accompanied Vessel Based on Factor-Graph Optimization

Abstract

The signal from a noise-emitting source propagates due to the phenomenon of sound refraction in the marine environment along various trajectories (rays) and is received by the antenna array of an autonomous underwater vehicle from a certain direction (bearing) at different elevation angles. To reduce the uncertainty region of the target coordinates, the paper uses the values of signal correlation across elevation angles, which are compared with reference data computed on a grid of distances and formed based on a ray representation model of the marine environment field. Information on hydroacoustic conditions in the observation area, including measurements of the vertical sound speed distribution, is used as input data for the field model. The proposed solution is based on a combined approach, the essence of which is that the problem of estimating the coordinates and motion parameters of an accompanied vessel from bearing measurements and correlation values of received signals is formulated within a Bayesian framework, and factor-graph optimization methods are used to construct suboptimal algorithms. To evaluate the effectiveness of the proposed algorithm, a simulation program was developed and used to conduct predictive simulation modeling of the considered problem on various episodes and under different hydroacoustic conditions. The results obtained were compared with a non-recursive algorithm constructed within the Bayesian approach. An analysis of the algorithms' consistency was conducted. It is shown that the algorithm based on factor-graph optimization has a significant advantage in computational cost. The results obtained were compared with a non-recursive algorithm. An analysis of the algorithms' consistency was performed. It is shown that the algorithm based on factor-graph optimization has a significant advantage in computational costs.