Positioning technologies for wireless communications

Conventionally, wireless localization schemes work based on the assumption that the sensors/receivers (Rx) are always in Line-of-Sight (LOS) with the transmitter (Tx) to locate Tx. However, this assumption may not be realistic due to multipath, Non-Line-of-Sight (NLOS) propagation and multiple acces...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Jii, Ay Wei
مؤلفون آخرون: Lim Chin Heng
التنسيق: Final Year Project
اللغة:English
منشور في: 2010
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10356/40856
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
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spelling sg-ntu-dr.10356-408562023-07-07T16:51:30Z Positioning technologies for wireless communications Jii, Ay Wei Lim Chin Heng Pina Marziliano School of Electrical and Electronic Engineering Temasek Laboratories @ NTU DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems Conventionally, wireless localization schemes work based on the assumption that the sensors/receivers (Rx) are always in Line-of-Sight (LOS) with the transmitter (Tx) to locate Tx. However, this assumption may not be realistic due to multipath, Non-Line-of-Sight (NLOS) propagation and multiple access interference. Under such conditions, the accuracy of localization schemes will be affected. Among these error sources, NLOS is perhaps the most crucial one. In this thesis, we focus on the development and implementation of a robust NLOS mitigation scheme that can improve the accuracy of Time of Arrival (TOA) geo-location in a simulated single moving sensor environment. Our proposed algorithm development can be simplified as 3 structures: Robust adaptive trimming method (basic), Reconstruction of trimmed TOA profile, and Non-parametric (NP) noise density estimator. Note that NLOS errors are modeled as Ɛ-contaminated Gaussian noise with impulsive behaviour and the trimming method is based on a statistical approach to minimize the impulsive noise effect. For further improvement, geometry information between Rx and Tx or polynomial curve fit is suggested to perform reconstruction of trimmed TOA profile. Follow on this; a NP detector which makes minimal a priori assumptions on the noise model, a symmetry density is proposed to integrate with the basic trimming and reconstruction algorithms. Numerical simulations of the above algorithms are done by MATLAB and its results illustrate the promising performance in a mixed LOS and NLOS environment. Bachelor of Engineering 2010-06-23T01:33:03Z 2010-06-23T01:33:03Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/40856 en Nanyang Technological University 67 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
Jii, Ay Wei
Positioning technologies for wireless communications
description Conventionally, wireless localization schemes work based on the assumption that the sensors/receivers (Rx) are always in Line-of-Sight (LOS) with the transmitter (Tx) to locate Tx. However, this assumption may not be realistic due to multipath, Non-Line-of-Sight (NLOS) propagation and multiple access interference. Under such conditions, the accuracy of localization schemes will be affected. Among these error sources, NLOS is perhaps the most crucial one. In this thesis, we focus on the development and implementation of a robust NLOS mitigation scheme that can improve the accuracy of Time of Arrival (TOA) geo-location in a simulated single moving sensor environment. Our proposed algorithm development can be simplified as 3 structures: Robust adaptive trimming method (basic), Reconstruction of trimmed TOA profile, and Non-parametric (NP) noise density estimator. Note that NLOS errors are modeled as Ɛ-contaminated Gaussian noise with impulsive behaviour and the trimming method is based on a statistical approach to minimize the impulsive noise effect. For further improvement, geometry information between Rx and Tx or polynomial curve fit is suggested to perform reconstruction of trimmed TOA profile. Follow on this; a NP detector which makes minimal a priori assumptions on the noise model, a symmetry density is proposed to integrate with the basic trimming and reconstruction algorithms. Numerical simulations of the above algorithms are done by MATLAB and its results illustrate the promising performance in a mixed LOS and NLOS environment.
author2 Lim Chin Heng
author_facet Lim Chin Heng
Jii, Ay Wei
format Final Year Project
author Jii, Ay Wei
author_sort Jii, Ay Wei
title Positioning technologies for wireless communications
title_short Positioning technologies for wireless communications
title_full Positioning technologies for wireless communications
title_fullStr Positioning technologies for wireless communications
title_full_unstemmed Positioning technologies for wireless communications
title_sort positioning technologies for wireless communications
publishDate 2010
url http://hdl.handle.net/10356/40856
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