| 摘要: | 近年來無人機（UAV）的發展與應用正迅速擴展，從民用到軍事領域都有廣泛應用。在民用領域，無人機被應用於航空攝影、農業、物流配送、災害應急等各個方面。例如，農業無人機可用於作物監測、噴灑農藥，提高了農業生產效率；物流配送無人機則可以快速送達包裹，解決了最後一公里配送難題。在軍事方面，無人機被用於偵察、目標定位、空中攻擊等任務，大大提高了戰場情報的即時性和準確性，降低了人員傷亡風險。然而，當無人機被當作軍事武器，往往會造成極大的危險與損害，因此防治無人機便是一個重要的問題，本篇論文使用了輔助波束對演算法，它可以估計無人機的接收角度(AOA)，且相對於以往的數位波束成型的演算法，它的計算複雜度較低，且實現成本也相對不高，因此是個極高性價比的角度估計演算法。為了持續追蹤無人機，我們還結合了擴展卡爾曼濾波器，能讓追蹤無人機的誤差更低。除了完整的系統模擬，也會使用軟體定義無線電平台（SDR）及馬達來實現角度估計及持續追蹤無人機，最後用模擬及實作結果進行分析與討論。;In recent years, the development and application of Unmanned
Aerial Vehicles (UAVs) have been rapidly expanding, with widespread use in both civilian and military sectors. In civilian applications, UAVs are utilized for aerial photography, agriculture, logistics delivery, disaster response, and more. For instance, agricultural UAVs are employed for crop monitoring and pesticide spraying, improving agricultural productivity; while logistics delivery UAVs facilitate rapid parcel delivery, addressing last-mile delivery challenges. In the military realm, UAVs are used for reconnaissance, target location, and aerial strikes, significantly enhancing the real-time and accuracy of battlefield intelligence while reducing the risk of casualties. However, when employed as military weapons, UAVs can pose significant dangers and damages. Therefore, UAV countermeasures have become an important issue. This paper introduces the Auxiliary Beam Pair (ABP) algorithm for UAV angle estimation, which offers lower computational complexity and cost compared to conventional Digital Beamforming (DBF) algorithms, making it a highly cost-effective angle estimation approach. To maintain continiuous UAV tracking, an Extended Kalman Filter (EKF) is integrated to minimize tracking errors. In addition to comprehensive system simulations, software-defined radio (SDR) platforms and motors are utilized for angle estimation and continuous UAV tracking. Finally, both simulation and implementation results are analyzed and discussed. |
