天空中的RFEye
RFEye in the Sky
摘要：
我们介绍RFEye，一种通用的技术来定位信号的波形无关，使用一个单一的无人机（UAV）配备只有一个全向天线。这是通过在两个附近位置从半径为1米的球体内的不协调位置获取信号，并在UAV处制定异步分布式接收器波束形成以计算来自未知发射器的波达方向（DoA）来实现的。该方法包括四个步骤：1）盲检测和提取待定位信号中的唯一特征; 2）异步信号采集和调节; 3）通过在无人机上创建虚拟分布式天线阵列来计算DoA; 4）使用来自两个位置的DoA来获得辐射源的位置定位。这些步骤进行了分析的各种来源的错误，计算复杂度和广泛使用的信号子空间为基础的DOA估计算法进行比较。RFEye使用英特尔航空无人机实现，配备USRP B205软件定义无线电，以获取来自地面发射器的信号。实际户外实验表明，RFEye在Wi-Fi的2D和3D中的中值精度分别为1.03米和2.5米，在LoRa（长距离）波形的2D和3D中的中值精度分别为1.15米和2.7米，并且对风和无人机位置误差等外部因素具有鲁棒性。
英文摘要：
We introduce RFEye, a generalized technique to locate signals independent of the waveform, using a single Unmanned Aerial Vehicle (UAV) equipped with only one omnidirectional antenna. This is achieved by acquiring signals from uncoordinated positions within a sphere of 1-meter radius at two nearby locations and formulating an asynchronous, distributed receiver beamforming at the UAV to compute the Direction of Arrival (DoA) from the unknown transmitter. The proposed method includes four steps: 1) Blind detection and extraction of unique signature in the signal to be localized, 2) Asynchronous signal acquisition and conditioning, 3) DoA calculation by creating a virtual distributed antenna array at UAV and 4) Obtaining position fix of emitter using DoA from two locations. These steps are analyzed for various sources of error, computational complexity and compared with widely used signal subspace-based DoA estimation algorithms. RFEye is implemented using an Intel-Aero UAV, equipped with a USRP B205 software-defined radio to acquire signals from a ground emitter. Practical outdoor experiments show that RFEye achieves a median accuracy of 1.03m in 2D and 2.5m in 3D for Wi-Fi, and 1.15m in 2D and 2.7m in 3D for LoRa (Long Range) waveforms, and is robust to external factors like wind and UAV position errors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
