Penetrating Barriers: Microwave-Based Remote Sensing and Reconstruction of Audio Signals Through Walls

This study investigate the remote detection and reconstruction of audio signals using Radio Frequency (RF) emissions, focusing on the implications for eavesdropping detection and prevention. Utilizing the widely used 2.4 GHz continuous wave microwave radiation directed at a speaker membrane, we successfully reassembled human speech and music signals, demonstrating the feasibility of audio reconstruction in real-world scenarios. A series of denoising techniques, including Robust locally weighted scatterplot smoothing (LOWESS), Moving Median, and Wavelet Denoising, were evaluated for their effectiveness in enhancing signal quality, with performance metrics such as root mean square error (RMSE) and signal-to-noise ratio SNR employed for comparison. Our findings reveal that Wavelet denoising outperforms other methods in preserving the integrity of speech signals, while also highlighting the challenges posed by background noise and interference. Additionally, we present mathematical models to estimate the maximum detectable distance based on SNR, providing a framework for understanding the limitations and capabilities of the reconstruction process. This research contributes to the field of audio signal processing and has significant implications for security applications, emphasizing the need for tailored denoising strategies in varying environments or barriers.