Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization
Ultra-Wide Bandwidth (UWB) and mm-wave radio systems can resolve specular multipath components (SMCs) from estimated channel impulse response measurements. A geometric model can describe the delays, angles-of-arrival, and angles-of-departure of these SMCs, allowing for a prediction of these channel...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/2/462 |
| _version_ | 1797490539892834304 |
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| author | Hong Anh Nguyen Van Khang Nguyen Klaus Witrisal |
| author_facet | Hong Anh Nguyen Van Khang Nguyen Klaus Witrisal |
| author_sort | Hong Anh Nguyen |
| collection | DOAJ |
| description | Ultra-Wide Bandwidth (UWB) and mm-wave radio systems can resolve specular multipath components (SMCs) from estimated channel impulse response measurements. A geometric model can describe the delays, angles-of-arrival, and angles-of-departure of these SMCs, allowing for a prediction of these channel features. For the modeling of the amplitudes of the SMCs, a data-driven approach has been proposed recently, using Gaussian Process Regression (GPR) to map and predict the SMC amplitudes. In this paper, the applicability of the proposed multipath-resolved, GPR-based channel model is analyzed by studying features of the propagation channel from a set of channel measurements. The features analyzed include the energy capture of the modeled SMCs, the number of resolvable SMCs, and the ranging information that could be extracted from the SMCs. The second contribution of the paper concerns the potential applicability of the channel model for a multipath-resolved, single-anchor positioning system. The predicted channel knowledge is used to evaluate the measurement likelihood function at candidate positions throughout the environment. It is shown that the environmental awareness created by the multipath-resolved, GPR-based channel model yields higher robustness against position estimation outliers. |
| first_indexed | 2024-03-10T00:34:26Z |
| format | Article |
| id | doaj.art-6865d9c655264ab499dc0401589515ab |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T00:34:26Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6865d9c655264ab499dc0401589515ab2023-11-23T15:19:02ZengMDPI AGSensors1424-82202022-01-0122246210.3390/s22020462Amplitude Modeling of Specular Multipath Components for Robust Indoor LocalizationHong Anh Nguyen0Van Khang Nguyen1Klaus Witrisal2School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi 11615, VietnamSchool of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi 11615, VietnamSignal Processing and Speech Communication Lab, Graz University of Technology, 8010 Graz, AustriaUltra-Wide Bandwidth (UWB) and mm-wave radio systems can resolve specular multipath components (SMCs) from estimated channel impulse response measurements. A geometric model can describe the delays, angles-of-arrival, and angles-of-departure of these SMCs, allowing for a prediction of these channel features. For the modeling of the amplitudes of the SMCs, a data-driven approach has been proposed recently, using Gaussian Process Regression (GPR) to map and predict the SMC amplitudes. In this paper, the applicability of the proposed multipath-resolved, GPR-based channel model is analyzed by studying features of the propagation channel from a set of channel measurements. The features analyzed include the energy capture of the modeled SMCs, the number of resolvable SMCs, and the ranging information that could be extracted from the SMCs. The second contribution of the paper concerns the potential applicability of the channel model for a multipath-resolved, single-anchor positioning system. The predicted channel knowledge is used to evaluate the measurement likelihood function at candidate positions throughout the environment. It is shown that the environmental awareness created by the multipath-resolved, GPR-based channel model yields higher robustness against position estimation outliers.https://www.mdpi.com/1424-8220/22/2/462situational awarenessenvironmental awarenesslocation awarenessgeometry-based channel modelinggaussian process regressionsingle-anchor positioning |
| spellingShingle | Hong Anh Nguyen Van Khang Nguyen Klaus Witrisal Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization Sensors situational awareness environmental awareness location awareness geometry-based channel modeling gaussian process regression single-anchor positioning |
| title | Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization |
| title_full | Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization |
| title_fullStr | Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization |
| title_full_unstemmed | Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization |
| title_short | Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization |
| title_sort | amplitude modeling of specular multipath components for robust indoor localization |
| topic | situational awareness environmental awareness location awareness geometry-based channel modeling gaussian process regression single-anchor positioning |
| url | https://www.mdpi.com/1424-8220/22/2/462 |
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