Performance Bounds of Near-Field Sensing with Circular Arrays
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910585316179968 |
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| author | Wang, Zhaolin Mu, Xidong Liu, Yuanwei |
| author_facet | Wang, Zhaolin Mu, Xidong Liu, Yuanwei |
| contents | The performance bounds of near-field sensing are studied for circular arrays, focusing on the impact of bandwidth and array size. The closed-form Cramer-Rao bound (CRBs) for angle and distance estimation are derived, revealing the scaling laws of the CRBs with bandwidth and array size. Contrary to expectations, enlarging array size does not always enhance sensing performance. Furthermore, the asymptotic CRBs are analyzed under different conditions, unveiling that the derived expressions include the existing results as special cases. Finally, the derived expressions are validated through numerical results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_17318 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Performance Bounds of Near-Field Sensing with Circular Arrays Wang, Zhaolin Mu, Xidong Liu, Yuanwei Information Theory Signal Processing The performance bounds of near-field sensing are studied for circular arrays, focusing on the impact of bandwidth and array size. The closed-form Cramer-Rao bound (CRBs) for angle and distance estimation are derived, revealing the scaling laws of the CRBs with bandwidth and array size. Contrary to expectations, enlarging array size does not always enhance sensing performance. Furthermore, the asymptotic CRBs are analyzed under different conditions, unveiling that the derived expressions include the existing results as special cases. Finally, the derived expressions are validated through numerical results. |
| title | Performance Bounds of Near-Field Sensing with Circular Arrays |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2404.17318 |