Abstract
An asynchronous time difference of arrival (ATDOA) positioning system requires no time synchronization among all the anchor and target nodes, which makes it highly practical and can be easily deployed. This paper first presents an ATDOA localization model, and then primarily focuses on two new localization algorithms for the system. The first algorithm is a two-step positioning algorithm that combines semidefinite programming (SDP) with a Taylor series method to achieve global convergence as well as superior estimation accuracy, and the second algorithm is a constrained least-squares method that has the advantage of low complexity and fast convergence while maintaining good performance. In addition, a novel receiver re-selection method is presented to significantly improve estimation accuracy. In this paper, we also derive the Cramer-Rao lower bound (CRLB) of the ATDOA positioning system using a distance-dependent noise variance model, which describes a realistic indoor propagation channel.
Highlights
Position information brings enormous benefits to many real-life applications ranging from cargo tracking, tourist guiding, emergency evacuation, to countless usage scenarios
This is largely due to the extra signal transmission scheme involved in the localization process, that is, it requires both direct path and re-transmitted path signal for localization, and the compound noise power is significantly higher than time of arrival (TOA) and time difference of arrival (TDOA) systems
4 A high accuracy two-step localization algorithm we propose a two-step localization algorithm that combines a semidefinite programming (SDP) technique and a Taylor series method to achieve high estimation accuracy
Summary
Position information brings enormous benefits to many real-life applications ranging from cargo tracking, tourist guiding, emergency evacuation, to countless usage scenarios. The time-based localization method, including oneway time of arrival (TOA) and time difference of arrival (TDOA), exploits the fine delay resolution property of wideband signals and has great potential for providing high accuracy location estimation. We first develop a two-step algorithm that takes advantage of the SDP’s global convergence property to provide a solution, that is used as an initial estimate for a Taylor series method to achieve superior accuracy. We present a constrained least-squares (CLS) estimator that provides good solution accuracy with reduced complexity for ATDOA positioning systems. The localization algorithm’s performance is thoroughly studied based on practical achievable ranging accuracy This unique analysis method allows us to fully understand the advantages and disadvantages of different algorithms. Symmetric matrices A and B, A B means that A − B is The time difference measured at anchor Rx can be positive semidefinite
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