In this paper, we introduce Spyglass, a spectrum sensor designed to address the challenges of effective spectrum usage in dense wireless environments. Spyglass is capable of observing a frequency band and accurately estimating the Angle of Arrival (AoA) of any signal during a single transmission. This includes additional signal context such as center frequency, bandwidth, and I/Q samples. We overcome challenges such as the clutter of fleeting transmissions in common bands, the high cost of array processing for AoA estimation, and the difficulty of detecting and estimating channels for unknown signals. Our first contribution is the development of Searchlite, a protocol-agnostic signal detection and separation algorithm. We use a switched array to reduce cost and processing complexity, and we develop SSFP, a signal processing technique using Fourier transforms that is synchronized to switching boundaries. Spyglass performs multi-channel blind AoA estimation synchronized with the array. Implemented using commercially available hardware, Spyglass demonstrates a median AoA accuracy of 1.4$^\circ$ and the ability to separate simultaneous signals from multiple devices in an unconstrained RF environment, providing valuable tools for large-scale RF data collection and analysis.

翻译：本文提出Spyglass频谱传感器，旨在解决密集无线环境中频谱有效利用的挑战。Spyglass能够观测频段并在单次传输期间精确估计任意信号的到达角，同时获取中心频率、带宽及I/Q采样等附加信号上下文信息。我们攻克了常见频段中瞬态传输干扰密集、阵列处理实现到达角估计成本高昂、以及未知信号检测与信道估计困难等难题。首要贡献是开发了Searchlite——一种与协议无关的信号检测与分离算法。通过采用开关阵列降低硬件成本与处理复杂度，并开发了SSFP信号处理技术，该技术利用与切换边界同步的傅里叶变换方法。Spyglass实现了与阵列同步的多通道盲到达角估计。基于商用硬件实现的系统在无约束射频环境中展现出1.4$^\circ$的中值到达角精度，并能分离多设备并发信号，为大规模射频数据采集与分析提供了有力工具。