Simulation tool for the analysis of cooperative localization algorithms for wireless sensor networks

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • University of Cordoba

Abstract

Within the context of the Internet of Things (IoT) and the Location of Things (LoT) service, this paper presents an interactive tool to quantitatively analyze the performance of cooperative localization techniques for wireless sensor networks (WSNs). In these types of algorithms, nodes help each other determine their location based on some signal metrics such as time of arrival (TOA), received signal strength (RSS), or a fusion of them. The developed tool is intended to provide researchers and designers a fast way to measure the performance of localization algorithms considering specific network topologies. Using TOA or RSS models, the Crámer-Rao lower bound (CRLB) has been implemented within the tool. This lower bound can be used as a benchmark for testing a particular algorithm for specific channel characteristics and WSN topology, which allows determination if the necessary accuracy for a specific application is possible. Furthermore, the tool allows us to consider independent characteristics for each node in the WSN. This feature allows the avoidance of the typical “disk graph model,” which is usually applied to test cooperative localization algorithms. The tool allows us to run Monte-Carlo simulations and generate statistical reports. A set of basic illustrative examples are described comparing the performance of different localization algorithms and showing the capabilities of the presented tool.

Details

Original languageEnglish
Article number2866
JournalSensors (Switzerland)
Volume19
Issue number13
Publication statusPublished - 1 Jul 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Algorithms, Cooperative localization, Indoor localization, Industrial safety, IoT, LoT

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