ArticleSensors (Basel, Switzerland)2020
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form.
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 3 papers.
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Who cites it
3 citing papers in PubMed.
- Novel Solutions to the Three-Anchor ToA-Based Three-Dimensional Positioning Problem.Sensors (Basel, Switzerland) · 2021Article
- Method for Remote Determination of Object Coordinates in Space Based on Exact Analytical Solution of Hyperbolic Equations.Sensors (Basel, Switzerland) · 2020Article
- A Novel Experiment-free Site-specific TDoA Localization Performance-Evaluation Approach.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
3 authors.
Funding
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Abstract
The subject of localization has received great deal attention in the past decades. Although it is perhaps a well-studied problem, there is still room for improvement. Traditional localization methods usually assume the number of sensors is sufficient for providing desired performance. However, this assumption is not always satisfied in practice. This paper studies the time of arrival (TOA)-based source positioning in the presence of sensor position errors. An error refined solution is developed for reducing the mean-squared-error (MSE) and bias in small sensor network (the number of sensors is fewer) when the noise or error level is relatively large. The MSE performance is analyzed theoretically and validated by simulations. Analytical and numerical results show the proposed method attains the Cramér-Rao lower bound (CRLB). It outperforms the existing closed-form methods with slightly raising computation complexity, especially in the larger noise/error case.
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