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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.10352 |
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| _version_ | 1866916452985995264 |
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| author | Saad-Falcon, Alex Ancelin, Brighton Romberg, Justin |
| author_facet | Saad-Falcon, Alex Ancelin, Brighton Romberg, Justin |
| contents | Tracking signals in dynamic environments presents difficulties in both analysis and implementation. In this work, we expand on a class of subspace tracking algorithms which utilize the Grassmann manifold -- the set of linear subspaces of a high-dimensional vector space. We design regularized least squares algorithms based on common manifold operations and intuitive dynamical models. We demonstrate the efficacy of the approach for a narrowband beamforming scenario, where the dynamics of multiple signals of interest are captured by motion on the Grassmannian. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_10352 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Subspace Tracking with Dynamical Models on the Grassmannian Saad-Falcon, Alex Ancelin, Brighton Romberg, Justin Signal Processing Tracking signals in dynamic environments presents difficulties in both analysis and implementation. In this work, we expand on a class of subspace tracking algorithms which utilize the Grassmann manifold -- the set of linear subspaces of a high-dimensional vector space. We design regularized least squares algorithms based on common manifold operations and intuitive dynamical models. We demonstrate the efficacy of the approach for a narrowband beamforming scenario, where the dynamics of multiple signals of interest are captured by motion on the Grassmannian. |
| title | Subspace Tracking with Dynamical Models on the Grassmannian |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2402.10352 |