Real-time stochastic model for precise underwater positioning

Abstract

There are two important aspects in optimally processing the acoustic measurements: the establishment of the functional model and the refinement of the associated stochastic model. In most cases the functional model may be sufficiently well-established, but the stochastic model error has not received considerable attention and it still remains a challenging research topic in real-time positioning. The equal weight stochastic model (EWSM) commonly used at present is under the assumption of equal-precision observation, which is imprecise and not coincident with reality. The purpose of this paper is to develop an approach to obtaining more accurate weights of observables by real-time estimating the variance of observations. The inaccurate stochastic model effect is analyzed and the real time stochastic model (RTSM) estimated by using the least squares residual of observations is presented to improve the positioning accuracy. Simulation results have shown that the underwater positioning accuracy goes from 0.173 m to 0.157 m based on GPS Intelligent Buoy (GIB) by employing the real time stochastic model, while that can be improved from 0.426 m to 0.306 m based on surveying vessel (SV) when adopting RTSM. Both simulations based on GIB and SV indicate that real-time stochastic model can perform better than conventional equal weight stochastic model in positioning accuracy.