Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866916658149326848 |
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| author | Kitchen, Astrid Holm Filtenborg Brøndt, Mikkel Sebastian Lundsgaard Jensen, Marie Saugstrup Pedersen, Troels Westerkam, Anders Malthe |
| author_facet | Kitchen, Astrid Holm Filtenborg Brøndt, Mikkel Sebastian Lundsgaard Jensen, Marie Saugstrup Pedersen, Troels Westerkam, Anders Malthe |
| contents | We propose a distributed joint localization and tracking algorithm using a message passing framework, for multiple-input multiple-output radars. We employ the mean field approach to derive an iterative algorithm. The obtained algorithm features a small communication overhead that scales linearly with the number of radars in the system. The proposed algorithm shows good estimation accuracy in two simulated scenarios even below 0 dB signal to noise ratio. In both cases the ground truth falls within the 95 % confidence interval of the estimated posterior for the majority of the track. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16236 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars Kitchen, Astrid Holm Filtenborg Brøndt, Mikkel Sebastian Lundsgaard Jensen, Marie Saugstrup Pedersen, Troels Westerkam, Anders Malthe Signal Processing We propose a distributed joint localization and tracking algorithm using a message passing framework, for multiple-input multiple-output radars. We employ the mean field approach to derive an iterative algorithm. The obtained algorithm features a small communication overhead that scales linearly with the number of radars in the system. The proposed algorithm shows good estimation accuracy in two simulated scenarios even below 0 dB signal to noise ratio. In both cases the ground truth falls within the 95 % confidence interval of the estimated posterior for the majority of the track. |
| title | Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2503.16236 |