Sensor-Target Geometry for Hybrid Bearing/Range Underwater Localization

Abstract

In this paper, the influence of sensor-target relative geometry on the potential performance of underwater target localization with hybrid bearing/range sensors is investigated. The optimality criterion function is built on the knowledge of Fisher information matrix (FIM), and another analysis on the mean squared error (MSE) is also presented. For a fixed distance between the sensors to the underwater target, the MSE is minimized if and only if the determinant of the FIM is maximized. The main contribution in this paper is the dependence of the range measurement error on the acoustic propagation distance because of the complex underwater environment, which result in a different FIM expression compared to the ideal assumption case. Simulation results are provided to show the effectiveness of the algorithms presented.