Open AccessTest Results of the Long Baseline Navigation Solutions under a Large a Priori Position Uncertainty
Author(s) -
V.V. Bogomolov
Publication year - 2022
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1215/1/012006
Subject(s) - a priori and a posteriori , position (finance) , baseline (sea) , beacon , weighting , kalman filter , linearization , extended kalman filter , computer science , iterated function , control theory (sociology) , cluster analysis , a priori estimate , underwater , mathematics , artificial intelligence , geography , real time computing , acoustics , control (management) , philosophy , mathematical analysis , oceanography , epistemology , quantum mechanics , physics , finance , nonlinear system , geology , economics , archaeology
A method is proposed for long baseline navigation of autonomous underwater vehicles (AUV) to be used in the case of a large a priori position uncertainty. The new modified method is based on the iterated Kalman filter (IKF) working with different initial linearization points. The final solution is calculated by clustering and weighting the IKF results. This approach allows position estimates to be determined in accordance with the global maximum of posteriori probability density of coordinates. The test results obtained with the use of three beacons and an underwater vehicle are presented.