Algorithm of long baseline navigation of an autonomous underwater vehicle in the absence of a priori data on its location under conditions of sparse beacon placement

A recursive algorithm is developed to determine coordinates of an autonomous underwater vehicle (AUV) using measurements of ranges to acoustic beacons, taken at different times, together with relative lag and course indicator data. It is assumed that a priori coordinates of the AUV are unknown, and the unambiguous navigation solution cannot be obtained from one-shot measurements due to a sparse beacon location. The algorithm is started upon the first receipt of simultaneous measurements from two beacons. Joint processing of current and saved measurements before the algorithm launch is provided using the Kalman filter. The ambiguity of the AUV location is resolved according to the ratio of a posteriori probabilities of alternatives. The results of modeling and processing of field data, as well as performance assessments, confirming the efficiency of the developed algorithm are presented.