Modeling of underwater vehicle positioning accuracy assessment based on ultrashort baseline

Abstract

Considering the effects of complexity and uncertainty in underwater environments, solving the lower bound of the underwater vehicle positioning error variance is crucial for assessing positioning accuracy. To address the problem of nonlinear measurement equations for underwater acoustic sensors with ultrashort baseline measurements of underwater vehicles, this paper designs a method for recursively deriving an improved posterior Cramer-Rao lower bound for underwater vehicles using Taylor expansion linearization and then conducts simulation experiments. The results show that the improved posterior Cramer-Rao lower bound has good results and can be used as an evaluation standard for the positional results of underwater vehicle filter estimates.