ArticleSensors (Basel, Switzerland)2020
Local Wireless Sensor Networks Positioning Reliability Under Sensor Failure.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 33 citations in OpenAlex.
- An Innovative Linear Wireless Sensor Network Reliability Evaluation Algorithm.Sensors (Basel, Switzerland) · 2025Article
- Deep Learning-Based Transmitter Localization in Sparse Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2024Article
- Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios.Sensors (Basel, Switzerland) · 2021Article
- Hybrid Memetic Algorithm for the Node Location Problem in Local Positioning Systems.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Local Positioning Systems are collecting high research interest over the last few years. Its accurate application in high-demanded difficult scenarios has revealed its stability and robustness for autonomous navigation. In this paper, we develop a new sensor deployment methodology to guarantee the system availability in case of a sensor failure of a five-node Time Difference of Arrival (TDOA) localization method. We solve the ambiguity of two possible solutions in the four-sensor TDOA problem in each combination of four nodes of the system by maximizing the distance between the two possible solutions in every target possible location. In addition, we perform a Genetic Algorithm Optimization in order to find an optimized node location with a trade-off between the system behavior under failure and its normal operating condition by means of the Cramer Rao Lower Bound derivation in each possible target location. Results show that the optimization considering sensor failure enhances the average values of the convergence region size and the location accuracy by 31% and 22%, respectively, in case of some malfunction sensors regarding to the non-failure optimization, only suffering a reduction in accuracy of less than 5% under normal operating conditions.
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Registered trials
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