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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/2405.09245 |
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| _version_ | 1866917672586838016 |
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| author | Fang, Zexin Han, Bin Schotten, Hans D. |
| author_facet | Fang, Zexin Han, Bin Schotten, Hans D. |
| contents | Unmanned aerial vehicles (UAVs) are well-suited to localize jammers, particularly when jammers are at non-terrestrial locations, where conventional detection methods face challenges. In this work we propose a novel localization method, sample pruning gradient descend (SPGD), which offers robust performance against multiple power-modulated jammers with low computational complexity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_09245 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Robust UAV-Based Approach for Power-Modulated Jammer Localization Using DoA Fang, Zexin Han, Bin Schotten, Hans D. Signal Processing Unmanned aerial vehicles (UAVs) are well-suited to localize jammers, particularly when jammers are at non-terrestrial locations, where conventional detection methods face challenges. In this work we propose a novel localization method, sample pruning gradient descend (SPGD), which offers robust performance against multiple power-modulated jammers with low computational complexity. |
| title | A Robust UAV-Based Approach for Power-Modulated Jammer Localization Using DoA |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2405.09245 |