This paper presents hardware-efficient phase demodulation schemes for FPGA-based digital phase-sensitive optical time-domain reflectometry ($\varphi$-OTDR) receivers. We first derive a signal model for the heterodyne $\varphi$-OTDR frontend, then propose and analyze three demodulation methods: (1) a baseband reconstruction approach via zero-IF downconversion, (2) an analytic signal generation technique using the Hilbert transform (HT), and (3) a wavelet transform (WT)-based alternative for analytic signal extraction. Algorithm-hardware co-design implementations are detailed for both RFSoC and conventional FPGA platforms, with resource utilization comparisons. Additionally, we introduce an incremental DC-rejected phase unwrapper (IDRPU) algorithm to jointly address phase unwrapping and DC drift removal, minimizing computational overhead while avoiding numerical overflow. Experiments on simulated and real-world $\varphi$-OTDR data show that the HT method matches the performance of zero-IF demodulation with simpler hardware and lower resource usage, while the WT method offers enhanced robustness against fading noise (3.35–22.47 dB SNR improvement in fading conditions), albeit with slightly ambiguous event boundaries and higher hardware utilization. These findings provide actionable insights for demodulator design in distributed acoustic sensing (DAS) applications and advance the development of single-chip DAS systems.

This article introduces an interrogation algorithm designed for low-cost tunable laser-based fiber Bragg grating (FBG) interrogation systems, specifically targeting general-purpose audio sensing. The algorithm leverages the inherent continuity and regularity present in acoustic signals by employing a prediction filter to forecast future samples. The algorithm determines the scan region based on the prediction and then acquires the narrowest optical bands that encompass solely the necessary information. Peak detection is performed on a subwindow of adaptive size. Compared with conventional full-band acquisition, the proposed algorithm has a much shorter laser engine scan path thus the overall sampling rate is augmented. Numerical simulations demonstrate a signal-to-noise ratio of 76.9 dB and an interrogation error of $\pm$ 9.747 pm (99.7% confidence) using properties of real-world optoelectronic devices and diversified audio samples. The algorithm presents consistent performance across audio content and a significant sampling rate improvement of maximum 40 times compared to conventional full-band scanning. The algorithm offers flexible configuration, hardware efficiency, and scalability for dynamic FBG sensing applications.

The spatial response of rectangular pulse heterodyne phase-sensitive optical time-domain reflectometry ($\varphi$-OTDR) to an acoustic event is characterized by a windowing function rather than a point-like sensitivity. This effect degrades the system’s spatial resolution and introduces systematic errors in array signal processing. This work presents modeling analysis and a mitigation strategy for this fundamental limitation. The spatial windowing effect is modeled as a point spread function (PSF) derived from physical mechanisms and system parameters, including the pulse width, gauge length, and intra-pulse intensity dynamics. The PSF model is validated against measurements under near-ideal conditions using a fiber-coupled tuning fork. A Wiener filter-based deconvolution method is utilized to invert the windowed spatial response towards a point-like response. The effectiveness of this inversion is demonstrated through enhanced spatial resolution and accurate reconstruction of two-dimensional wavefront geometry. Furthermore, the impact of this effect on array signal processing is quantitatively evaluated. The results demonstrate that the proposed method effectively suppresses systematic errors in wavefield analysis, and specifically enhances the accuracy and confidence of steered response power—phase transform (SRP-PHAT) spatial spectrum estimation. This study provides a systematic framework for understanding, quantifying, and inverting the spatial response in $\varphi$-OTDR, enabling accurate and interpretable acoustic field sensing.

In this paper, we investigate the physical mechanics of vibration wave detection in distributed acoustic sensing (DAS) systems with the aim of enhancing the interpretation of the quantitative wavefield. We investigate the nonlinear relationship of DAS gauge length and pulse width on the seismic wave response, and the result is explained by the trigonometric relationship of backscattered Rayleigh wave phases. We further demonstrate the influence of spiral winding on DAS performance and also build phase response models for P-waves and S-waves in helically wound cables. These models suggest that the winding angle controls the measurement interval spacing and the angle of wave incidence. Additionally, integration of structural reinforcement improves the amplitude response characteristics and SNR. The experimentally inspired results show, using simulations and field tests, that the same vibration sources can give helically wound cables with larger winding angles the largest phase amplitudes, which would substantially exceed that of straight cables. SNR increased significantly (approximately 10% to 30%). The efficacy of the method was also checked using experiments for different vibration amplitudes and frequencies. Such results provide evidence for the design and installation of fiber-optic cables for use in practical engineering applications involving safety monitoring.