A data fusion technique for continuous wave radar sensor using Kalman filter

A data fusion technique for continuous wave radar sensor using Kalman filter

A novel high precision displacement sensor was developed using phase-based continuous wave radar. This new sensor promises non-contact, high accuracy, high bandwidth, and capability of operating in harsh environments. In this type of radar, minimum two channels are required to uniquely determine pha...

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Main Author: Ittichote Chuckpaiwong
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
Subjects:
Engineering
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/21310
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Institution: Mahidol University
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spelling th-mahidol.213102018-07-24T10:41:12Z A data fusion technique for continuous wave radar sensor using Kalman filter Ittichote Chuckpaiwong Mahidol University Engineering A novel high precision displacement sensor was developed using phase-based continuous wave radar. This new sensor promises non-contact, high accuracy, high bandwidth, and capability of operating in harsh environments. In this type of radar, minimum two channels are required to uniquely determine phase, which linearly corresponds to displacement. However, extra channels can be used to reduce measurement noise and thus increase the sensor repeatability if used properly. This paper introduces the benefit of a multi-channel over a traditional two-channel system by providing an optimal method to combine data. A Kalman filter is used as a means of data fusion providing an optimal estimation of phase with improved signal quality. Experimental results are provided to verify the validity and effectiveness of the multi-channel algorithm compared with the two-channel. 2018-07-24T03:41:12Z 2018-07-24T03:41:12Z 2004-12-27 Conference Paper Sixth IASTED International Conference on Signal and Image Processing. (2004), 363-368 2-s2.0-10444231856 https://repository.li.mahidol.ac.th/handle/123456789/21310 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=10444231856&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Engineering
spellingShingle Engineering
Ittichote Chuckpaiwong
A data fusion technique for continuous wave radar sensor using Kalman filter
description A novel high precision displacement sensor was developed using phase-based continuous wave radar. This new sensor promises non-contact, high accuracy, high bandwidth, and capability of operating in harsh environments. In this type of radar, minimum two channels are required to uniquely determine phase, which linearly corresponds to displacement. However, extra channels can be used to reduce measurement noise and thus increase the sensor repeatability if used properly. This paper introduces the benefit of a multi-channel over a traditional two-channel system by providing an optimal method to combine data. A Kalman filter is used as a means of data fusion providing an optimal estimation of phase with improved signal quality. Experimental results are provided to verify the validity and effectiveness of the multi-channel algorithm compared with the two-channel.
author2 Mahidol University
author_facet Mahidol University
Ittichote Chuckpaiwong
format Conference or Workshop Item
author Ittichote Chuckpaiwong
author_sort Ittichote Chuckpaiwong
title A data fusion technique for continuous wave radar sensor using Kalman filter
title_short A data fusion technique for continuous wave radar sensor using Kalman filter
title_full A data fusion technique for continuous wave radar sensor using Kalman filter
title_fullStr A data fusion technique for continuous wave radar sensor using Kalman filter
title_full_unstemmed A data fusion technique for continuous wave radar sensor using Kalman filter
title_sort data fusion technique for continuous wave radar sensor using kalman filter
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/21310
_version_ 1763494442581360640

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