Terrain aided navigation for underwater vehicles using maximum likelihood method

Abstract

Terrain matching navigation provides a capability for estimating position by matching real-time measurement of terrain to a terrain database. Since this process is without errors accumulating with time, it is very attractive as compared to limit the drift errors inherent in dead-reckoning or inertial navigation for underwater vehicles. The geometric description of an undulating terrain surface as a mathematical function or look-up table is generally nonlinear, which leads to a nonlinear state estimation problem. However, the maximum likelihood estimation algorithm uses probability criterion directly and has a theoretical advantage in solving nonlinear state estimation problems. The detail of terrain matching aided navigation based on maximum likelihood estimation is presented in this paper. In the method, a multi-beam echo sounder is used to acquire bathymetry data, and a maximum likelihood estimation algorithm is used for matching the analysis between real-time bathymetry and the reference digital map. Terrain statistical information is also introduced in order to select the most suitable terrain matching field. The results of simulation demonstrate that the proposed approach is feasible, accurate, and robust.