Orientation Analysis Based on EKF Algorithm and Simulated Annealing Algorithm

The aim of this study is to investigate the azimuthal orientation analysis based on the Extended Kalman Filter (EKF) algorithm and simulated annealing algorithm to ensure safe positioning in deep-sea environments. In this paper, a temporal orientation model is first constructed, and the EKF algorithm is used to accurately estimate the submarine's motion trajectory under normal communication conditions; in case of communication failure, the kinematic and kinetic equations are applied to establish an ideal trajectory model, and the model is corrected by introducing the stochasticity of the sea current velocity through Monte Carlo simulation. In addition, the effects of salinity and temperature on density are taken into account in the Z-axis direction to create a physical model of depth variation. In order to assess the effectiveness of SAR equipment, this study used the hierarchical analysis method (AHP) to determine the weights of each index and combined with the TOPSIS method to score each type of equipment. In the single-objective SAR model, the probability distribution of the fault location is rasterised and the paths between the grids are optimised using a directed graph model as well as a greedy algorithm, which translates into the problem of finding the shortest Hamiltonian path. And then, the optimal solution is found with the help of simulated annealing algorithm. These methods enable efficient analysis of positioning and search and rescue tasks and enhance operational safety in complex marine environments.