Abstract
Autonomous navigation has meant a challenge for traditional positioning systems. As a consequence, ad-hoc deployments of sensors for addressing particular environment characteristics have emerged known as Local Positioning Systems (LPS). Among LPS, those based on temporal measurements present an excellent trade-off among accuracy, availability, robustness and costs. However, the existence of different Time-Based Positioning architectures - Time of Arrival (TOA), Time Difference of Arrival (TDOA) and Asynchronous Time Difference of Arrival (A-TDOA)- with different characteristics in clock and signal path noise uncertainties has supposed that it does not exist any preferred a priori architecture for urban NLOS complex scenarios. As a consequence, in this paper, we propose a general framework for the optimization of the node deployments of each architecture in urban scenarios based on accuracy, availability and robustness. This framework allows us to compare the performance of the TBS architectures in the urban scenario proposed as a novel methodology for the deployment of LPS time architectures in urban environments. Results in the proposed scenario have shown the preeminence of the A-TDOA architecture in primary and emergency conditions which supposes and outstanding remark for future high-demanded accuracy applications in urban environments.
Highlights
Localization accuracy has become a crucial task for high-demanded autonomous navigation
The development of autonomous navigation with high accuracy needs has supposed a challenge in NLOS urban scenarios
We propose a methodology for the deployment of Time-Based Positioning Systems (TBS) in urban environments
Summary
Localization accuracy has become a crucial task for high-demanded autonomous navigation. Asynchronous TDOA configurations avoid the synchronism errors but increase the signal travel paths by retransmitting the positioning signals to the CS nodes [26], being the availability of a CS in each possible target location under coverage mandatory for computing the time measurements, making the system dependent on these processing sensors. In [39] a novel methodology distinguishing the region for the location of the system nodes and the region for the navigation of the vehicles in LPS is introduced, in [40] a multi-objective methodology for optimizing the parameters which reduce the localization uncertainties of LPS is proposed, in [41] a multi-objective approach to the node location problem allows the joint optimization for system accuracy and the avoidance of disruptive phenomena on signals such as the multipath or in [42] the localization of the unknown anchors is optimized preserving the network connectivity These wide range of applications of the node location problem in WSN must be particularized for localization schemes.
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