Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form
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...
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doaj-a3e3b7b28fef44f9afb5111b30ea7a6b2020-11-25T02:20:24ZengMDPI AGSensors1424-82202020-01-0120239010.3390/s20020390s20020390Refinement of TOA Localization with Sensor Position Uncertainty in Closed-FormYi Gan0Xunchao Cong1Yimao Sun2The 10th Research Institute of CETC, Chengdu 610036, ChinaThe 10th Research Institute of CETC, Chengdu 610036, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaThe 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.https://www.mdpi.com/1424-8220/20/2/390source localizationtime of arrival (toa)small sensor networksensor position uncertaintyclosed-formerror refined |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi Gan Xunchao Cong Yimao Sun |
spellingShingle |
Yi Gan Xunchao Cong Yimao Sun Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form Sensors source localization time of arrival (toa) small sensor network sensor position uncertainty closed-form error refined |
author_facet |
Yi Gan Xunchao Cong Yimao Sun |
author_sort |
Yi Gan |
title |
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form |
title_short |
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form |
title_full |
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form |
title_fullStr |
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form |
title_full_unstemmed |
Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form |
title_sort |
refinement of toa localization with sensor position uncertainty in closed-form |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-01-01 |
description |
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. |
topic |
source localization time of arrival (toa) small sensor network sensor position uncertainty closed-form error refined |
url |
https://www.mdpi.com/1424-8220/20/2/390 |
work_keys_str_mv |
AT yigan refinementoftoalocalizationwithsensorpositionuncertaintyinclosedform AT xunchaocong refinementoftoalocalizationwithsensorpositionuncertaintyinclosedform AT yimaosun refinementoftoalocalizationwithsensorpositionuncertaintyinclosedform |
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