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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/110801


    題名: 無人機的射頻及光學追蹤系統整合與多目標融合;Integrated RF and Optical Tracking System with Multi-Target Association for Unmanned Aerial Vehicles
    作者: 陳浩文;WEN, CHEN HAO
    貢獻者: 通訊工程學系
    關鍵詞: 無人機;射頻方向估測;多目標關聯;多基站定位;射頻與光學系統整合;Unmanned Aerial Vehicle (UAV);Direction-of-Arrival (DOA) Estimation;Multi-Target Association;Multi-Base-Station Localization;RF–Optical System Integration
    日期: 2026-08-25
    上傳時間: 2026-10-20 16:26:34 (UTC+8)
    出版者: 國立中央大學
    摘要: 隨著無人機(Unmanned Aerial Vehicle, UAV)技術快速發展,非法無人機入侵對空域安全、公共管理與重要場域監控造成潛在威脅,因此即時且穩定的多目標 UAV 定位與追蹤系統具有重要需求。本文提出一套多目標 UAV 射頻與光學追蹤整合系統,以 Fusion Center 作為核心,整合多站 RF DOA 量測模組、PTZ 光學追蹤模組與 Web GUI 監控介面,實現多目標定位、追蹤、光學導引與即時顯示。

    在多目標情境下,不同基站會輸出多組未標記之 DOA 量測結果,Fusion Center 無法直接判斷不同基站量測是否來自同一台 UAV。為解決此問題,本文利用多基站 AoA 射線產生候選定位點,並以 MAP 觀點建立多目標量測關聯方法。系統根據 Kalman Filter 預測結果建立追蹤關聯成本,並可結合 RSSI 輔助成本選取最佳量測配對。完成關聯後,再透過 EKF 對 UAV 狀態進行預測與更新,以降低原始 triangulation 定位結果之波動並維持目標軌跡連續性。

    在系統實作方面,本文完成 RF 基站資料傳輸、Fusion Center 定位追蹤、PTZ 相機導引控制與 Web GUI 即時監控之整合。整體而言,本文所提出之系統具備多目標 UAV 量測關聯、定位追蹤、光學導引與即時監控能力,並具有實際部署與模組化擴充之應用潛力。;With the rapid development of Unmanned Aerial Vehicle (UAV) technology, unauthorized UAV intrusions have become a potential threat to airspace security, public management, and critical-site monitoring. Therefore, a real-time and stable multi-target UAV localization and tracking system is highly required. This thesis proposes an integrated RF and optical tracking system for multi-target UAV monitoring. The system adopts a Fusion Center as the core module and integrates multi-station RF DOA measurement modules, a Pan-Tilt-Zoom (PTZ) optical tracking module, and a Web GUI monitoring interface to achieve multi-target localization, tracking, optical guidance, and real-time visualization.

    In multi-target scenarios, different base stations output multiple unlabeled DOA measurements, making it difficult for the Fusion Center to determine which measurements correspond to the same UAV. To address this issue, candidate localization points are generated using multi-base-station AoA rays, and a MAP-based multi-target measurement association method is developed. The system constructs a tracking association cost based on Kalman Filter prediction results and can further incorporate an RSSI-assisted cost to select the optimal measurement pairing. After association, an Extended Kalman Filter (EKF) is applied to predict and update UAV states, reducing the fluctuation of raw triangulation results and maintaining trajectory continuity.

    For system implementation, this thesis completes the integration of RF base-station data transmission, Fusion Center localization and tracking, PTZ camera guidance control, and Web GUI real-time monitoring. Field experiment results show that applying the EKF reduces triangulation-based localization errors. For example, in a dual-target flight experiment, the Position RMSE of UAV1 is reduced from 39.60 m to 28.86 m, while that of UAV2 is reduced from 46.17 m to 32.57 m. Overall, the proposed system demonstrates integrated capabilities in multi-target UAV measurement association, localization and tracking, optical guidance, and real-time monitoring, showing its potential for practical deployment and modular expansion.
    顯示於類別:[通訊工程研究所] 博碩士論文

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