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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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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1724433489502142464 |