Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866909206547791872 |
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| author | Rastorgueva-Foi, Elizaveta Kaltiokallio, Ossi Ge, Yu Turunen, Matias Talvitie, Jukka Tan, Bo Keskin, Musa Furkan Wymeersch, Henk Valkama, Mikko |
| author_facet | Rastorgueva-Foi, Elizaveta Kaltiokallio, Ossi Ge, Yu Turunen, Matias Talvitie, Jukka Tan, Bo Keskin, Musa Furkan Wymeersch, Henk Valkama, Mikko |
| contents | In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment (UE) and landmark location information in millimeter-wave (mmWave) networks, with minimal prior knowledge. Firstly, we propose a new multipath channel parameter estimation solution that operates directly with beam reference signal received power (BRSRP) measurements, alleviating the need to know the true antenna beam-patterns or the underlying beamforming weights. Additionally, the method has built-in robustness against unavoidable antenna sidelobes. Secondly, we propose new snapshot SLAM algorithms that have increased robustness and identifiability compared to prior art, in practical built environments with complex clutter and multi-bounce propagation scenarios, and do not rely on any a priori motion model. The performance of the proposed methods is assessed at the 60 GHz mmWave band, via both realistic ray-tracing evaluations as well as true experimental measurements, in an indoor environment. A wide set of offered results demonstrate the improved performance, compared to the relevant prior art, in terms of the channel parameter estimation as well as the end-to-end SLAM performance. Finally, the article provides the measured 60 GHz data openly available for the research community, facilitating results reproducibility as well as further algorithm development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_13741 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation Rastorgueva-Foi, Elizaveta Kaltiokallio, Ossi Ge, Yu Turunen, Matias Talvitie, Jukka Tan, Bo Keskin, Musa Furkan Wymeersch, Henk Valkama, Mikko Signal Processing In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment (UE) and landmark location information in millimeter-wave (mmWave) networks, with minimal prior knowledge. Firstly, we propose a new multipath channel parameter estimation solution that operates directly with beam reference signal received power (BRSRP) measurements, alleviating the need to know the true antenna beam-patterns or the underlying beamforming weights. Additionally, the method has built-in robustness against unavoidable antenna sidelobes. Secondly, we propose new snapshot SLAM algorithms that have increased robustness and identifiability compared to prior art, in practical built environments with complex clutter and multi-bounce propagation scenarios, and do not rely on any a priori motion model. The performance of the proposed methods is assessed at the 60 GHz mmWave band, via both realistic ray-tracing evaluations as well as true experimental measurements, in an indoor environment. A wide set of offered results demonstrate the improved performance, compared to the relevant prior art, in terms of the channel parameter estimation as well as the end-to-end SLAM performance. Finally, the article provides the measured 60 GHz data openly available for the research community, facilitating results reproducibility as well as further algorithm development. |
| title | Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2312.13741 |