ArticleSensors (Basel, Switzerland)2019
Three-Dimensional Empirical AoA Localization Technique for Indoor Applications.
Article in Sensors (Basel, Switzerland), 2019. 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.
- FPGA-Based Particle Swarm Collaborative Target Localization Algorithm for UAV Swarms.Sensors (Basel, Switzerland) · 2025Article
- A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2023Article
- Radar Position Estimation by Sequential Irradiation of ESM Receivers.Sensors (Basel, Switzerland) · 2021Article
- The Power Gain Difference Method Analysis.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small and pervasive devices have been increasingly used to identify and track objects automatically. Consequently, several low-cost localization schemes have been proposed in the literature based on angle of arrival (AoA), time difference of arrival (TDoA), received signal strength indicator (RSSI) or their combinations. In this paper, we propose a three-dimensional empirical AoA localization (TDEAL) technique for battery-powered devices. The proposed technique processes the AoA measurements at fixed reader nodes to estimate the locations of the tags. The proposed technique provides localization accuracy that mitigates non-linear empirical errors in AoA measurements. We utilize two omni-directional antenna arrays at each fixed reader node to estimate the location vector. With multiple location estimations from different fixed reader nodes, each estimated location is assigned a weight that is inversely proportional to the AoA phase-difference error. Furthermore, the actual AoA parabolic formula of the location is approximated to a cone to simplify the location calculation process. The proposed localization technique has a low hardware cost, low computational requirements, and precise location estimates. Based on the performance evaluation, significant location accuracy is achieved by TDEAL; where, for instance, an average error margin of less than 13 cm is achieved using 10 readers in an area of 10 × 10 m2. TDEAL can be utilized to provide reference points when integrated with a relative (e.g., inertial navigation systems) localization systems.
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