Xiang, Lin ; Zhang, Mengshuai ; Klein, Anja (2023)
Robust Dynamic Trajectory Optimization for UAV-Aided Localization of Ground Target.
2023 IEEE Global Communications Conference. Kuala Lumpur, Malaysia (04.12.2023-08.12.2023)
doi: 10.1109/GLOBECOM54140.2023.10437337
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In this paper, we consider employing an unmanned aerial vehicle (UAV) equipped with an onboard radar transceiver to localize a ground target at an unknown position. Exploiting the UAV’s mobility, we aim to gather line-of-sight (LoS) range measurements from favorable waypoints and improve the ensuing multi-lateration process while estimating the target’s location. To this end, we introduce a novel localization error metric, characterized geometrically by the radius of a defined confidence region where the target resides at a predetermined confidence level. Additionally, we investigate robust dynamic optimization of the UAV’s trajectory to minimize the defined localization error metric online, utilizing sequentially available but delayed range estimates. The formulated optimization problem belongs to a convex-nonconcave minimax problem, which is generally intractable. To solve this problem, we further propose two iterative online algorithms based on semidefinite programming (SDP) relaxation and alternating/sequential convex optimization techniques. Simulation results show that the proposed online schemes outperform several benchmarks, either in the final localization accuracy or in the rate of decreasing the localization error.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Xiang, Lin ; Zhang, Mengshuai ; Klein, Anja |
| Art des Eintrags: | Bibliographie |
| Titel: | Robust Dynamic Trajectory Optimization for UAV-Aided Localization of Ground Target |
| Sprache: | Englisch |
| Publikationsjahr: | 4 Dezember 2023 |
| Veranstaltungstitel: | 2023 IEEE Global Communications Conference |
| Veranstaltungsort: | Kuala Lumpur, Malaysia |
| Veranstaltungsdatum: | 04.12.2023-08.12.2023 |
| DOI: | 10.1109/GLOBECOM54140.2023.10437337 |
| URL / URN: | https://ieeexplore.ieee.org/document/10437337 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | In this paper, we consider employing an unmanned aerial vehicle (UAV) equipped with an onboard radar transceiver to localize a ground target at an unknown position. Exploiting the UAV’s mobility, we aim to gather line-of-sight (LoS) range measurements from favorable waypoints and improve the ensuing multi-lateration process while estimating the target’s location. To this end, we introduce a novel localization error metric, characterized geometrically by the radius of a defined confidence region where the target resides at a predetermined confidence level. Additionally, we investigate robust dynamic optimization of the UAV’s trajectory to minimize the defined localization error metric online, utilizing sequentially available but delayed range estimates. The formulated optimization problem belongs to a convex-nonconcave minimax problem, which is generally intractable. To solve this problem, we further propose two iterative online algorithms based on semidefinite programming (SDP) relaxation and alternating/sequential convex optimization techniques. Simulation results show that the proposed online schemes outperform several benchmarks, either in the final localization accuracy or in the rate of decreasing the localization error. |
| Freie Schlagworte: | Open6GHUB, DAAD, emergenCITY, emergenCITY_KOM |
| Zusätzliche Informationen: | Signal Processing for Communications |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Kommunikationstechnik LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY |
| Hinterlegungsdatum: | 25 Jan 2024 10:43 |
| Letzte Änderung: | 25 Apr 2024 08:06 |
| PPN: | 517481111 |
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