The Global Navigation Satellite System combined with acoustic technique has achieved great economic benefits in positioning of ocean bottom seismometers, with hundreds of underwater transponders attached to seismometers typically being deployed during oil exploration. The previous single transponder positioning method ignored the similar underwater environments between the transponders. Due to the refraction effect of sound, the technique usually showed poor positioning accuracy in shallow water when the incidence angles are large. In this paper, the effect of sound ray bending is analyzed based on the sound ray tracing method in shallow water, and a new piecewise incidence angle model is proposed to improve the positioning accuracy of multiple objects in order to estimate the sound ray bending correction. The parameters of the new model are divided into groups and estimated by sequential least squares method, together with all of the transponders. The observability analysis is discussed in simulation and testing experiments in the South China Sea. The results show that the newly proposed method is able to make full use of the acoustic observation data of hundreds of transponders to accurately estimate the SRB correction, which could also significantly improve the positioning accuracy of multiple transponders.

Autonomous and Remotely-operated Vehicles (ARVs) rely on precise underwater navigation via integrated Ultra-Short Baseline (USBL) acoustic positioning system and Strap-down Inertial Navigation System (SINS). However, spatiotemporal variations in underwater Sound Speed Profile (SSP) degrade USBL performance, reducing overall navigation accuracy. This study proposes a novel in-situ SSP correction scheme for SINS/USBL integration. We analyze SSP temporal variation with the USBL positioning scheme to build a Two Dimensional (2D) temporal SSP model; then derive partial derivatives (based on equal-gradient ray-tracing) to quantify the displacements from azimuth, incident angle, and propagation time errors; and finally develop an adaptive two-stage information filter to estimate sound speed perturbation and detect USBL outliers. Simulations and South China Sea trials are conducted to verify its effectiveness. Compared with the traditional tight-coupling method, root mean square errors are reduced from 0.45m and 0.23 m with the traditional tightly-coupled method to 0.08 m and 0.07 m with the in-situ SSP correction scheme, representing improvements of 82.2% in the north and 69.6% in the east directions, respectively. Experimental results demonstrate that the proposed method effectively estimates the sound speed disturbance in real time, thereby significantly improving the performance of tightly integrated inertial-acoustic navigation systems.

Global navigation satellite system-acoustic (GNSS-A) combined underwater positioning technique is widely applied in seafloor displacement monitoring and offshore exploration. The conventional GNSS-A positioning strategy is under the assumption of equal-precision sea-surface transducer’s positions determined by GNSS positioning, which weakens the positioning accuracy of single seafloor transponder-equipped station. In this article, the extended joint adjustment (JA) of the measurements of the sea surface transducers to seafloor transponders and measurements of the transponder to transponder ranging is proposed. First, we refine the transducer-to-transponder timing observation equation system by acoustic ray-tracing strategy to reduce the sound-speed-related errors. Second, we establish the mathematical model for extended JA with inter-station ranging measurements for seafloor geodetic network (SGN) positioning. Finally, the efficacy of the proposed method is demonstrated both in simulations and in real measurement datasets. Experimental results show that the proposed method outperforms the traditional positioning methods, especially in the horizontal components.

More accurate and realistic stochastic model is required for high-precision underwater positioning. The common stochastic modeling procedure, assuming that the measurements are statistically independent in space and time and have same accuracy, is certainly not realistic. Any misspecification in the stochastic model may have a significant effect on underwater acoustic data processing. Taking the heteroscedastic space and time correlation into consideration, a novel stochastic modeling procedure based on an iterative minimum norm quadratic unbiased estimator method has been developed to improve underwater positioning accuracy. Testing results by experiment data show that the positioning accuracy can be superiorly improved from 1.226, 1.434, and 1.018 m based on a traditional stochastic model estimation scheme to 0.935, 0.336, and 0.190 m for three transponders when adopting the new method.