Abstract
Asynchronous Time Local Positioning Systems are emerging as a decisive tool for high-demanded accuracy applications. Its relevance relies on the unnecessary synchronism of the system devices and the ad-hoc node deployment for fitting the design requirements in irregular scenarios. In this paper, we provide a new methodology for obtaining optimized cost-effective asynchronous node deployments based on system accuracy, enhanced primary and emergency operating conditions and security robustness. In addition, we perform a deep analysis of the NP-Hard node location problem and we propose a new Cramér-Rao Bound (CRB) error characterization considering Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) system connections and clock instabilities for evaluating the quality of a node deployment. We apply a Genetic Algorithm optimization in an irregular scenario of simulations to display this innovative methodology with a trade-off between resolution in the search in the space of solutions and the achievement of time-effective results. Results show that deployments with 4 and 5 coordinator sensors fulfill the design requirements in the proposed scenario in both primary and emergency conditions (1.14 and 1.70 meters and 0.89 and 1.47 meters of mean errors respectively) while 5 coordinator sensor configurations outperform 4 coordinator sensor configurations in system security robustness proving their preeminence in this study.
Highlights
Global Navigation Satellite Systems (GNSS) provide global coverage with a constellation of satellites in the space
The remainder of the paper is organized as follows: we introduce a detailed description of the A-Time Difference of Arrival (TDOA) architecture, the definition of the node distribution problem and the methodology to reach a cost-effective node deployment in asynchronous architectures in Section 2, the combined noise and clock Cramér-Rao Bound (CRB) model for the optimization is presented in Section 3, the Genetic Algorithm settings for this combined optimization and the results of the optimization are introduced in Section 4 while Section 5 discuss and conclude the paper
Asynchronous time local positioning systems have emerged over the last few years
Summary
Global Navigation Satellite Systems (GNSS) provide global coverage with a constellation of satellites in the space. We propose a methodology to deploy an optimized cost-effective distribution of coordinator and worker sensors in large-scale asynchronous LPS applications (e.g. coverage of more than 1 km or required combinations of more than the minimum architecture sensors to cover the entire TLE with the accuracy bounds desired) by considering CS availability and accuracy in each target position under coverage This includes the optimization for nominal and eventual failure operating conditions of the system CS in each possible target location and the finding of the optimized location and the appropriate combination of WS for maximizing accuracy in the space of coverage of the system. The remainder of the paper is organized as follows: we introduce a detailed description of the A-TDOA architecture, the definition of the node distribution problem and the methodology to reach a cost-effective node deployment in asynchronous architectures in Section 2, the combined noise and clock CRB model for the optimization is presented in Section 3, the Genetic Algorithm settings for this combined optimization and the results of the optimization are introduced in Section 4 while Section 5 discuss and conclude the paper
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