Autonomous Sensing UAV for Accurate Multi-User Identification and Localization in LAWN
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908859801534464 |
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| author | Paglierani, Niccolò Linsalata, Francesco Teeda, Vineeth Scazzoli, Davide Magarini, Maurizio |
| author_facet | Paglierani, Niccolò Linsalata, Francesco Teeda, Vineeth Scazzoli, Davide Magarini, Maurizio |
| contents | This paper presents an autonomous sensing framework for identifying and localizing multiple users in Fifth Generation (5G) cooperative networks using an Unmanned Aerial Vehicle (UAV) that is not part of the serving access network. Unlike conventional aerial serving nodes, the proposed UAV operates passively and is dedicated solely to sensing. Passively receiving Uplink (UL) Sounding Reference Signals (SRS), the UAV requires only minimal initial coordination with the network infrastructure during the mission. A complete signal processing chain is proposed and developed, encompassing synchronization, user identification, and localization, all executed onboard UAV during flight. The system autonomously plans and adapts its mission workflow to estimate multiple user positions within a single deployment, integrating flight control with real-time sensing. The approach is validated through extensive simulations and a full-scale low-altitude experimental campaign. Urban simulation scenarios show localization errors below 8 m, while rural field tests achieve errors below 3 m, with reliable synchronization and user identification ensured in both cases. The results confirm the feasibility of infrastructure-independent sensing UAVs as a core element of the emerging Low Altitude Economy (LAE), supporting situational awareness and rapid deployment in emergency or connectivity-limited environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13171 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Autonomous Sensing UAV for Accurate Multi-User Identification and Localization in LAWN Paglierani, Niccolò Linsalata, Francesco Teeda, Vineeth Scazzoli, Davide Magarini, Maurizio Signal Processing This paper presents an autonomous sensing framework for identifying and localizing multiple users in Fifth Generation (5G) cooperative networks using an Unmanned Aerial Vehicle (UAV) that is not part of the serving access network. Unlike conventional aerial serving nodes, the proposed UAV operates passively and is dedicated solely to sensing. Passively receiving Uplink (UL) Sounding Reference Signals (SRS), the UAV requires only minimal initial coordination with the network infrastructure during the mission. A complete signal processing chain is proposed and developed, encompassing synchronization, user identification, and localization, all executed onboard UAV during flight. The system autonomously plans and adapts its mission workflow to estimate multiple user positions within a single deployment, integrating flight control with real-time sensing. The approach is validated through extensive simulations and a full-scale low-altitude experimental campaign. Urban simulation scenarios show localization errors below 8 m, while rural field tests achieve errors below 3 m, with reliable synchronization and user identification ensured in both cases. The results confirm the feasibility of infrastructure-independent sensing UAVs as a core element of the emerging Low Altitude Economy (LAE), supporting situational awareness and rapid deployment in emergency or connectivity-limited environments. |
| title | Autonomous Sensing UAV for Accurate Multi-User Identification and Localization in LAWN |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2511.13171 |