There are today some proposed techniques where, e.g. bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques , most often relying on high accuracy maps, with the accuracy of the navigational sensors being less important.
Instead of relying on high accuracy maps and low accuracy navigation sensors, this paper presents an idea of the opposite, namely using low accuracy maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements.
Keywords: Particle filter, Autonomous Navigation, Recursive Bayesian Estimation, Sea Navigation
30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2017, May 15–16, 2017, Karlskrona, Sweden
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