LAUSR

Ultra-short baseline (USBL) is a mature navigation method for underwater applications. Acoustic outliers and the slant distance calculation error are the main challenges for improving positioning accuracy. The latter, in particular, is often overlooked. In this paper, the slant distance calculation errors due to the motion effect and acoustic outliers will be mainly investigated. To address the problem, the influence of the motion effect on localization in dynamic environments is analyzed first. Aiming at the two challenges, a new measurement model based on the round trip time delay and bearing angles is derived, which can avoid the influence of the motion effect. Besides, to improve the robustness against outliers, a novel robust Kalman filter is designed based on the mixture distribution model. Simulation tests prove that the designed Kalman filter can improve the positioning accuracy in a dynamic environment and overcome the influence of motion effect on slant distance calculation. The proposed method also plays superior performance than the traditional ones under the influence of outliers. The algorithm has also been verified by the river test, and it has better robustness and higher positioning accuracy under dynamic conditions.