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Self-calibration and collaborative localization for UWB positioning systems : a survey and future research directions

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Abstract
Ultra-Wideband (UWB) is a Radio Frequency technology that is currently used for accurate indoor localization. However, the cost of deploying such a system is large, mainly due to the need for manually measuring the exact location of the installed infrastructure devices ("anchor nodes"). Self-calibration of UWB reduces deployment costs, because it allows for automatic updating of the coordinates of fixed nodes when they are installed or moved. Additionally, installation costs can also be reduced by using collaborative localization approaches where mobile nodes act as anchors. This article surveys the most significant research that has been done on self-calibration and collaborative localization. First, we find that often these terms are improperly used, leading to confusion for the readers. Furthermore, we find that in most of the cases, UWB-specific characteristics are not exploited, so crucial opportunities to improve performance are lost. Our classification and analysis provide the basis for further research on self-calibration and collaborative localization in the deployment of UWB indoor localization systems. Finally, we identify several research tracks that are open for investigation and can lead to better performance, e.g., machine learning and optimized physical settings.
Keywords
WIRELESS SENSOR NETWORKS, COOPERATIVE LOCALIZATION, INDOOR LOCALIZATION, TECHNOLOGIES, PROPAGATION, PERFORMANCE, ALGORITHMS, PROTOCOLS, TRACKING, Survey, indoor localization, ultra-wideband, self-calibration, collaborative localization

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Citation

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MLA
Ridolfi, Matteo, et al. “Self-Calibration and Collaborative Localization for UWB Positioning Systems : A Survey and Future Research Directions.” ACM COMPUTING SURVEYS, vol. 54, no. 4, 2021, doi:10.1145/3448303.
APA
Ridolfi, M., Kaya, A., Berkvens, R., Weyn, M., Joseph, W., & De Poorter, E. (2021). Self-calibration and collaborative localization for UWB positioning systems : a survey and future research directions. ACM COMPUTING SURVEYS, 54(4). https://doi.org/10.1145/3448303
Chicago author-date
Ridolfi, Matteo, Abdil Kaya, Rafael Berkvens, Maarten Weyn, Wout Joseph, and Eli De Poorter. 2021. “Self-Calibration and Collaborative Localization for UWB Positioning Systems : A Survey and Future Research Directions.” ACM COMPUTING SURVEYS 54 (4). https://doi.org/10.1145/3448303.
Chicago author-date (all authors)
Ridolfi, Matteo, Abdil Kaya, Rafael Berkvens, Maarten Weyn, Wout Joseph, and Eli De Poorter. 2021. “Self-Calibration and Collaborative Localization for UWB Positioning Systems : A Survey and Future Research Directions.” ACM COMPUTING SURVEYS 54 (4). doi:10.1145/3448303.
Vancouver
1.
Ridolfi M, Kaya A, Berkvens R, Weyn M, Joseph W, De Poorter E. Self-calibration and collaborative localization for UWB positioning systems : a survey and future research directions. ACM COMPUTING SURVEYS. 2021;54(4).
IEEE
[1]
M. Ridolfi, A. Kaya, R. Berkvens, M. Weyn, W. Joseph, and E. De Poorter, “Self-calibration and collaborative localization for UWB positioning systems : a survey and future research directions,” ACM COMPUTING SURVEYS, vol. 54, no. 4, 2021.
@article{8716730,
  abstract     = {{Ultra-Wideband (UWB) is a Radio Frequency technology that is currently used for accurate indoor localization. However, the cost of deploying such a system is large, mainly due to the need for manually measuring the exact location of the installed infrastructure devices ("anchor nodes"). Self-calibration of UWB reduces deployment costs, because it allows for automatic updating of the coordinates of fixed nodes when they are installed or moved. Additionally, installation costs can also be reduced by using collaborative localization approaches where mobile nodes act as anchors. This article surveys the most significant research that has been done on self-calibration and collaborative localization. First, we find that often these terms are improperly used, leading to confusion for the readers. Furthermore, we find that in most of the cases, UWB-specific characteristics are not exploited, so crucial opportunities to improve performance are lost. Our classification and analysis provide the basis for further research on self-calibration and collaborative localization in the deployment of UWB indoor localization systems. Finally, we identify several research tracks that are open for investigation and can lead to better performance, e.g., machine learning and optimized physical settings.}},
  articleno    = {{88}},
  author       = {{Ridolfi, Matteo and Kaya, Abdil and Berkvens, Rafael and Weyn, Maarten and Joseph, Wout and De Poorter, Eli}},
  issn         = {{0360-0300}},
  journal      = {{ACM COMPUTING SURVEYS}},
  keywords     = {{WIRELESS SENSOR NETWORKS,COOPERATIVE LOCALIZATION,INDOOR LOCALIZATION,TECHNOLOGIES,PROPAGATION,PERFORMANCE,ALGORITHMS,PROTOCOLS,TRACKING,Survey,indoor localization,ultra-wideband,self-calibration,collaborative localization}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{27}},
  title        = {{Self-calibration and collaborative localization for UWB positioning systems : a survey and future research directions}},
  url          = {{http://doi.org/10.1145/3448303}},
  volume       = {{54}},
  year         = {{2021}},
}

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