Maneuvering Vehicle Localization with an Acoustic Long Baseline System - Li, Zhao (Canadian Acoustics, 2015)
This paper describes a localization approach which compensates for vehicle motion during the interrogation-reception time interval between the vehicle and transponders in an acoustic long baseline (LBL) system lake trial. In the lake trial, a maneuvering vehicle was localized by both GPS and the LBL system. When localizing the vehicle with the static-vehicle localization model, where the vehicle is assumed to be static during the interrogation-reception time interval, the averaged localization error was found as 19±14 cm by comparing acoustic localization results with GPS data. This error was significant larger than the expected 4 cm posterior uncertainties and the vehicle motion was thought as the main cause of this error. To address this problem, a motion-compensated inversion approach is developed base on Bayesian inversion algorithm which includes travel-time corrections as additional unknown parameters with prior determined by interpolating the vehicle location at interrogation time instants using static-vehicle localization model results. After processing the trial data with the motion-compensated inversion approach, the averaged localization error was decreased to 3.4±1.4 cm, much accurate than the error for the static inversion.