Spyglass: Directional Spectrum Sensing with Single-shot AoA Estimation and Virtual Arrays

TL;DR

This paper introduces Spyglass, a spectrum sensor designed to address the challenges of effective spectrum usage in dense wireless environments, and develops Searchlite, a protocol-agnostic signal detection and separation algorithm and SSFP, a signal processing technique using Fourier transforms that is synchronized to switching boundaries.

Abstract

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.

Figures (14)

• Figure 1: Spyglass can estimate the angular locations of any wireless transmitter in the environment. It uses time-frequency energy detection, synchronized DSP and switching arrays to achieve its function in real-time with efficient hardware use.
• Figure 2: 100 MHz RF spectrum centered at 2450 MHz captured with an SDR visualized using a spectrogram inspectrum. Regions of brighter color correspond to time-frequency instants where energy is high. Different devices operate using different protocols and share the spectrum. The white annotations on the image are automatically performed using Searchlite.
• Figure 3: End-to-end architecture of the Spyglass system, showcasing the signal processing pipeline from input to output. The diagram illustrates the integration of multi-antenna detection, switched antenna array, and angle-of-arrival measurements. Each component and interface is labeled to highlight the data flow and processing stages, providing a comprehensive view of the system's functionality. Below the block diagram, a view of the time-frequency plane is shown, where energy detection, and subsequent relative channel estimation is highlighted.
• Figure 4: Architecture of the Searchlite algorithm illustrating the signal processing pipeline. The process begins with performing STFT on each input signal channel, followed by ensemble averaging, noise estimation, and energy detection on the reference channel. Ultimately, specific areas of energy are extracted synchronously on all channels, providing multi-channel signal agnostic detection.
• Figure 5: Full Spyglass hardware system featuring the switched antenna array, SDR, and the control PCB