Single-anchor UWB Localization using Channel Impulse Response Distributions
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866909494163800064 |
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| author | Li, Sitian Balatsoukas-Stimming, Alexios Burg, Andreas |
| author_facet | Li, Sitian Balatsoukas-Stimming, Alexios Burg, Andreas |
| contents | Ultra-wideband (UWB) devices are widely used in indoor localization scenarios. Single-anchor UWB localization shows advantages because of its simple system setup compared to conventional two-way ranging (TWR) and trilateration localization methods. In this work, we focus on single-anchor UWB localization methods that learn statistical features of the channel impulse response (CIR) in different location areas using a Gaussian mixture model (GMM). We show that by learning the joint distributions of the amplitudes of different delay components, we achieve a more accurate location estimate compared to considering each delay bin independently. Moreover, we develop a similarity metric between sets of CIRs. With this set-based similarity metric, we can further improve the estimation performance, compared to treating each snapshot separately. We showcase the advantages of the proposed methods in multiple application scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2211_04246 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Single-anchor UWB Localization using Channel Impulse Response Distributions Li, Sitian Balatsoukas-Stimming, Alexios Burg, Andreas Signal Processing Ultra-wideband (UWB) devices are widely used in indoor localization scenarios. Single-anchor UWB localization shows advantages because of its simple system setup compared to conventional two-way ranging (TWR) and trilateration localization methods. In this work, we focus on single-anchor UWB localization methods that learn statistical features of the channel impulse response (CIR) in different location areas using a Gaussian mixture model (GMM). We show that by learning the joint distributions of the amplitudes of different delay components, we achieve a more accurate location estimate compared to considering each delay bin independently. Moreover, we develop a similarity metric between sets of CIRs. With this set-based similarity metric, we can further improve the estimation performance, compared to treating each snapshot separately. We showcase the advantages of the proposed methods in multiple application scenarios. |
| title | Single-anchor UWB Localization using Channel Impulse Response Distributions |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2211.04246 |