Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search

This paper proposes a time difference of arrival (TDOA) passive positioning sensor selection method based on tabu search to balance the relationship between the positioning accuracy of the sensor network and system consumption. First, the passive time difference positioning model, taking into accoun...

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Main Authors: Qian Li, Baixiao Chen, Minglei Yang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/22/6547
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spelling doaj-fb4686a6a3de4ab9835481bf9007f0522020-11-25T04:05:31ZengMDPI AGSensors1424-82202020-11-01206547654710.3390/s20226547Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu SearchQian Li0Baixiao Chen1Minglei Yang2National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaThis paper proposes a time difference of arrival (TDOA) passive positioning sensor selection method based on tabu search to balance the relationship between the positioning accuracy of the sensor network and system consumption. First, the passive time difference positioning model, taking into account the sensor position errors, is considered. Then, an approximate closed-form constrained total least-squares (CTLS) solution and a covariance matrix of the positioning error are provided. By introducing a Boolean selection vector, the sensor selection problem is transformed into an optimization problem that minimizes the trace of the positioning error covariance matrix. Thereafter, the tabu search method is employed to solve the transformed sensor selection problem. The simulation results show that the performance of the proposed sensor optimization method considerably approximates that of the exhaustive search method. Moreover, it can significantly reduce the running time and improve the timeliness of the algorithm.https://www.mdpi.com/1424-8220/20/22/6547passive localizationtime difference of arrival (TDOA)sensor selection optimizationconstrained total least-squares (CTLS)tabu search
collection DOAJ
language English
format Article
sources DOAJ
author Qian Li
Baixiao Chen
Minglei Yang
spellingShingle Qian Li
Baixiao Chen
Minglei Yang
Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
Sensors
passive localization
time difference of arrival (TDOA)
sensor selection optimization
constrained total least-squares (CTLS)
tabu search
author_facet Qian Li
Baixiao Chen
Minglei Yang
author_sort Qian Li
title Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
title_short Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
title_full Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
title_fullStr Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
title_full_unstemmed Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
title_sort time difference of arrival passive localization sensor selection method based on tabu search
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-11-01
description This paper proposes a time difference of arrival (TDOA) passive positioning sensor selection method based on tabu search to balance the relationship between the positioning accuracy of the sensor network and system consumption. First, the passive time difference positioning model, taking into account the sensor position errors, is considered. Then, an approximate closed-form constrained total least-squares (CTLS) solution and a covariance matrix of the positioning error are provided. By introducing a Boolean selection vector, the sensor selection problem is transformed into an optimization problem that minimizes the trace of the positioning error covariance matrix. Thereafter, the tabu search method is employed to solve the transformed sensor selection problem. The simulation results show that the performance of the proposed sensor optimization method considerably approximates that of the exhaustive search method. Moreover, it can significantly reduce the running time and improve the timeliness of the algorithm.
topic passive localization
time difference of arrival (TDOA)
sensor selection optimization
constrained total least-squares (CTLS)
tabu search
url https://www.mdpi.com/1424-8220/20/22/6547
work_keys_str_mv AT qianli timedifferenceofarrivalpassivelocalizationsensorselectionmethodbasedontabusearch
AT baixiaochen timedifferenceofarrivalpassivelocalizationsensorselectionmethodbasedontabusearch
AT mingleiyang timedifferenceofarrivalpassivelocalizationsensorselectionmethodbasedontabusearch
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