An Adaptive Joint Alignment Method of Angle Misalignment and Seafloor Transponder for Ultrashort Baseline Underwater Positioning

Ultrashort baseline (USBL) underwater positioning techniques are widely used to provide location-based services for unmanned underwater vehicles. Angle misalignment is a primary source of error that reduces the accuracy of USBL positioning. The conventional least squares (LS) alignment method assumes that the position of the seafloor transponder, which is derived from global navigation satellite system/acoustic (GNSS/A) underwater positioning, can be determined without error and that the alignment observations are independent. However, errors inevitably occur in the estimation of the transponder position by GNSS/A positioning, and the precision varies in three dimensions. Owing to geometric constraints, the observations are statistically correlated rather than independent. Ignoring these assumptions significantly reduces the precision of angle misalignment estimation. In this contribution, we propose an adaptive joint alignment (AJA) method, where both angle misalignment and the position of the seafloor transponder are treated as unknown parameters. The raw USBL data, including the acoustic range and bearing angle, are treated as observations, whereas the position of the seafloor transponder is treated as a virtual observation. An adaptive weighting factor derived from the maximum likelihood estimator is introduced to balance the contributions of the real and virtual observations to parameter estimation. Simulation results show that the proposed method improves angle misalignment estimation accuracy by 61.61% and 48.06% relative to the LS and two-step nonlinear Gauss–Markov (TSNGM) methods, respectively. Sea-trial results, evaluated in terms of USBL positioning accuracy, show that the AJA method achieves improvements of 66.02%–68.15% over the uncalibrated USBL system and 8.07%–10.08% over the LS method.