Joint localization algorithm of TDOA and FDOA considering the position error of underwater sensors

Abstract

The joint localization method of TDOA and FDOA is widely used because it can estimate the underwater moving source well. Usually, a two-step weighted least squares (TSWLS) algorithm is used to estimate the source. However, the noise square term is always neglected in the TSWLS algorithm. In order to improve this situation, an improved TSWLS algorithm is proposed under the circumstance of sensor position inaccuracy. First, a new localization equation is constructed by the time difference equation, and the source position and velocity are initially estimated. The intermediate variables are then Taylor expanded and inserted into the localization equation of the algorithm's first step to modify the initial estimate value. Finally, the source's precise position and velocity are determined, and the proposed method was demonstrated to achieve the Cramer-Rao lower bound (CRLB) accuracy through simulations.

Performance Analysis and Sensor-Target Geometry Optimization for TOA and TDOA-Based Hybrid Source Localization Method

“…The explosive growth of fifth-generation (5G) wireless communications will introduce a large number of new technological scenarios with higher requirements for location-based services [1], precise target localization techniques are becoming increasingly important in the application of radar [2], sonar [3], and wireless sensor networks [4] in 5G. At the same time, in order to improve the utility of mobile navigation scenarios, there is a need not only to provide continuous and comprehensive area coverage for users and seamless and stable indoor and outdoor LBS, but also to provide new ideas by organically synchronizing multiple technologies through public mobile communication systems using convergent positioning [4].…”