Search Results (91)

Continuous in situ marine holographic observation generates data volumes that challenge onboard storage and transmission. Parallel phase-shifting digital holography (PPSDH) is especially sensitive to compression because phase retrieval depends on consistent four-channel demodulation. We present a training-free spatiotemporal compression framework for sparse-particle marine PPSDH sequences based on background–residual decomposition and a shared four-channel processing path. The background is coded once per temporal window by a discrete wavelet transform (DWT) followed by principal component analysis (PCA), and the dynamic residual is decorrelated by temporal principal component analysis before quantization and entropy coding. The framework is evaluated on three primary 64-frame marine PPSDH sequences using a common reconstruction-and-evaluation pipeline with wrapped-phase root-mean-square error (PhaseRMSE) as the primary metric and amplitude peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as secondary references; expanded supplementary checks are also reported for nine additional selected 64-frame groups spanning sparse to transitional occupancy. On the primary sequence and within the high-fidelity achieved-rate overlap with the JPEG Pleno anchor codec INTERFERE, the proposed framework reduces PhaseRMSE by about 3.3-fold to 3.4-fold while increasing amplitude PSNR by about 11 dB and preserving amplitude SSIM above 0.99997. Lower-bitrate sweeps further quantify the rate–fidelity trade-off rather than claiming universal low-rate superiority. These results support BG–Res spatiotemporal coding as a practical phase-fidelity-oriented option for the tested sparse-to-transitional marine PPSDH conditions; extension to dense scenes, broader marine conditions, and downstream biological tasks requires separate validation. Full article

This paper presents an absolute distance measurement system based on three-wavelength synchronous phase-shifting interferometry. A synthetic wavelength chain is established using three semiconductor lasers in an all-fiber Fizeau interferometer. By integrating a piezoelectric transducer (PZT)-driven sinusoidal phase modulation with multi-channel synchronous sampling for phase demodulation, and further combining it with a fractional multiplication method, the proposed system achieves high-precision absolute distance measurement over an extended range. Experimental results demonstrate an unambiguous measurement range of 240 μm, a static measurement precision better than 0.6 nm, and a dynamic displacement measurement accuracy superior to 2 nm in comparison with the reference device. The main error sources of the system, including synthetic wavelength uncertainty, phase measurement uncertainty, and air refractive index uncertainty, are systematically modeled and analyzed. In addition, the influence of dynamic factors, such as PZT nonlinearity, is discussed and compensated. The proposed method provides a robust and high-precision solution for absolute ranging and shows strong potential for applications in industrial precision inspection and optical sensing. Full article

Phase-shifting fringe projection (PSFP) is widely used in industrial inspection and three-dimensional measurement, where $\gamma$ nonlinearity of the projector–camera system is traditionally treated as a phase-error source to be calibrated or compensated. In this work, $\gamma$ nonlinearity is reinterpreted from an imaging perspective and shown to act as a statistical distortion mechanism that reshapes modulation stability, overexposure behavior, and defect saliency in fringe-based imaging. Building on the intrinsic DC–AC decomposition of phase-shifting demodulation, we analyze how $\gamma$ nonlinearity interacts with fringe modulation and frequency-selective transfer. An analytical model reveals that $\gamma$ nonlinearity simultaneously suppresses the fringe fundamental and introduces harmonic leakage, leading to systematic compression of mean modulation contrast in high-brightness regions. As a result, $\gamma$ correction does not necessarily enhance mean-based defect contrast and may even reduce it, contrary to common intuition. We further demonstrate that the primary benefit of $\gamma$ correction lies in statistical stabilization rather than contrast amplification. By introducing modulation-domain saliency formulations and a frequency-domain harmonic energy ratio, a physical link is established between $\gamma$ nonlinearity, overexposure, and defect separability. Controlled experiments on highly reflective sheet-metal specimens confirm that while mean-contrast- and SNR-based saliency metrics often decrease after $\gamma$ correction, separability-based metrics consistently improve due to reduced nonlinear- and saturation-induced variance. Cross-channel and cross-condition analyses further show that modulation and reflectance images respond differently to $\gamma$ correction, yet metric-level separability exhibits consistent improvement across channels. These results clarify the true role of $\gamma$ correction in fringe-based inspection and provide theoretical insight and practical guidance for robust defect imaging under nonlinear and near-overexposure conditions. Full article

This paper presents a high-precision angle demodulation method for magnetic encoders by integrating orthogonal-signal correction with space–time modulation (STM). The proposed approach specifically addresses a critical vulnerability of STM-based high-frequency pulse interpolation: its interpolation accuracy is highly sensitive to zero-crossing timing jitter of the quadrature signals. In practical magnetic encoders, non-idealities such as DC offsets, amplitude mismatch, and phase non-orthogonality in the sine/cosine outputs induce jitter and shift in the zero-crossing points. This directly leads to fluctuations in high-frequency counts and amplifies the final angle error. To mitigate this issue, an online orthogonal-signal correction module is first developed. This module sequentially performs offset estimation, amplitude normalization, and real-time phase orthogonalization, thereby enhancing the orthogonality and zero-crossing stability of the quadrature signals at the source. This preprocessing significantly reduces the sensitivity of the subsequent interpolation counting to noise and signal imperfections. Based on the corrected signals, an STM pulse-counting interpolator is adopted to convert angle information into a time-domain phase (time) difference, and high-frequency counting is used for fine subdivision. A Kalman-filter-based predictor is employed to estimate angular velocity and compensate the intrinsic latency of counting-based demodulation in dynamic conditions. Experimental results demonstrate that the proposed phase orthogonalization correction markedly suppresses zero-crossing timing jitter and enhances the stability of high-frequency pulse interpolation. Consequently, the overall demodulation error is reduced by more than 30 percent compared with existing methods, and the final angle error is maintained within 0.033°. Full article

A four-quadrant low-coherence envelope detection method was proposed for measuring the surface spacing of optical components, eliminating the requirement for precise control of the delay line scanning step to generate a π/2 phase shift. The method employs an orthogonal polarization Mach–Zehnder (MZ) fiber interferometer, illuminated by a broadband superluminescent diode (SLD), and a four-quadrant polarization-resolved detector to simultaneously acquire spatially phase-shifted interference signals carrying surface spacing information. The interference envelope is directly demodulated to extract surface spacing, thereby decoupling measurement accuracy from mechanical stepping constraints. To enable real-time, high-precision calibration of the delay line, two complementary schemes were implemented: wavelength division multiplexing (WDM)-based calibration and dual optical path calibration. Experimental results confirm that the dual-path scheme exhibits weak dependence on scanning velocity and remains stable across a wide speed range. Repeat measurements of the surface spacing of a 1 mm thick sapphire plate yielded a standard deviation (STD) of 1.3 μm. By relaxing the strict π/2 phase shift condition traditionally imposed on scanning step size, this method improves operational efficiency while maintaining measurement reliability—providing a robust and broadly applicable solution for metrology, including lens surface spacing and transparent plate thickness characterization. Full article

TMR-based magnetic encoders provide sensitive SIN/COS signals, but practical accuracy is degraded by channel mismatch and decoder dynamics. This study evaluates an end-to-end embedded implementation on a PMSM (Permanent Magnet Synchronous Motor) bench. We consider amplitude mismatch, quadrature non-orthogonality, and harmonic/noise disturbances in the measured differential channels. We implement a lightweight compensation chain, including fixed-window moving-average filtering, min–max amplitude normalization, and correlation-based quadrature identification with sample-shift correction. We then compare four demodulation configurations under identical sampling and reference alignment to a 24-bit encoder: (A0) conventional second-order PLL (phase locked loop), (A1) compensation + open-loop atan2, (A2) compensation + fixed-${\omega }_n$ third-order PLL, and (A3) compensation + adaptive-${\omega }_n$ third-order PLL. Experiments with a TMR3081 sensor and an STM32 controller show clear differences among A0–A3. In steady operation, A3 removes the DC bias observed with A0 and keeps the angle error within approximately ±0.3° in the evaluated steady window. During commutation and ramp-like segments, PLL-based tracking (A0/A2/A3) is more robust than open-loop atan2 (A1), and bandwidth adaptation in A3 improves the acquisition–noise trade-off within the preset ${\omega }_n$ bounds. These results are reported for this prototype and the tested parameter settings. Full article

This paper explores the feasibility of using acoustic wave propagation, particularly in the ultrasonic range, as a solution for data transmission in environments where traditional radio frequency (RF) communication is ineffective due to signal attenuation—such as in liquids or dense media like metal or stone. Leveraging GNU Radio and commercially available audio hardware, a low-cost, SDR (Software Defined Radio) system was developed to transmit data blocks (e.g., images, text, and audio) through various substances. The system employs BFSK (Binary Frequency Shift Keying) and BPSK (Binary Phase Shift Keying), operates at ultrasonic frequencies (typically 40 kHz), and has performance validated under real-world conditions, including water, viscous substances, and flammable liquids such as hydrocarbon fuels. Experimental results demonstrate reliable, continuous communication at Nyquist–Shannon sampling rates, with effective demodulation and file reconstruction. The methodology builds on concepts originally developed for Ad Hoc Sensor Networks in shipping containers, extending their applicability to submerged and RF-hostile environments. The modularity and flexibility of the GNU Radio platform allow for rapid adaptation across different media and deployment contexts. This work provides a reproducible and scalable communication solution for scenarios where RF transmission is impractical, offering potential applications in underwater sensing, industrial monitoring, railways, and enclosed infrastructure diagnostics. Across controlled laboratory experiments, the system achieved 100% successful reconstruction of transmitted image files up to 100 kB and sustained packet delivery success exceeding 98% under stable coupling conditions. Full article

Spatial resolution is a critical parameter for optical frequency domain reflectometry (OFDR). Phase-sensitive OFDR (Φ-OFDR) measures strain by detecting phase variations between adjacent sampling points, having the potential to achieve the theoretical limitation of spatial resolution. However, the results of Φ-OFDR suffer from large fluctuations due to multiple types of noise, including coherent fading and system noise. This work presents an OFDR-based strain sensing method that combines phase demodulation with cross-correlation analysis to achieve high spatial resolution. In the phase demodulation, the frequency-shift averaging (FSAV) and rotating vector summation (RVS) algorithms are first employed to suppress coherent fading noise and achieve accurate strain localization. Then the cross-correlation approach with an adaptive window is proposed. Guided by the accurate strain boundary obtained from phase demodulation, the length and position of the cross-correlation window are automatically adjusted to fit for continuous and uniform strain regions. As a result, an accurate and complete strain distribution along the entire fiber is finally obtained. The experimental results show that, within a strain range of 100–700 με, the method achieves a spatial resolution of 0.27 mm for the strain boundary, with a root-mean-square error approaching 0.94%. The processing time reaches approximately 0.035 s, with a demodulation length of 1.6 m. The proposed approach offers precise spatial localization of the strain boundary and stable strain measurement, demonstrating its potential for high-resolution OFDR-based sensing applications. Full article

The graph Hilbert transform (GHT) is a key tool in constructing analytic signals and extracting envelope and phase information in graph signal processing. However, its utility is limited by confinement to the graph Fourier domain, a fixed phase shift, information loss for real-valued spectral components, and the absence of tunable parameters. The graph fractional Fourier transform introduces domain flexibility through a fractional order parameter $\alpha$ but does not resolve the issues of phase rigidity and information loss. Inspired by the dual-parameter fractional Hilbert transform (FRHT) in classical signal processing, we propose the graph FRHT (GFRHT). The GFRHT incorporates a dual-parameter framework: the fractional order $\alpha$ enables analysis across arbitrary fractional domains, interpolating between vertex and spectral spaces, while the angle parameter $\beta$ provides adjustable phase shifts and a non-zero real-valued response ($cos\beta$) for real eigenvalues, thereby eliminating information loss. We formally define the GFRHT, establish its core properties, and design a method for graph analytic signal construction, enabling precise envelope extraction and demodulation. Experiments on anomaly identification, speech classification and edge detection demonstrate that GFRHT outperforms GHT, offering greater flexibility and superior performance in graph signal processing. Full article

This work presents a novel microwave sensor system for volatile gas detection, integrating sensing elements based on rectangular cavity resonators (RCR) and multiport demodulation circuitry. Initially, a pump-through gas sensing element utilizing an RCR was developed, and its core sensing functionality was experimentally validated. Subsequently, a rat-race coupler was employed to seamlessly integrate two such rectangular cavity resonator elements—serving as reference and sensing branches—within the multiport demodulation network. This configuration enabled an in-depth investigation of the network’s operating principle, elucidating the critical relationship between the reference and sensing arms. The demodulation network translates the critical output phase shift into corresponding power readings. The quantitative relationship linking phase shift to power output was rigorously characterized and utilized as the basis for estimating volatile gas concentration. Finally, a dedicated LabVIEW-based platform was developed for real-time, quantitative volatile gas monitoring. This integrated measurement system demonstrates excellent detection limits (300 ppm for acetone, 200 ppm for ethanol) and exhibits robust mitigation of measurement artifacts caused by ambient temperature and humidity fluctuations. Comprehensive theoretical analysis and experimental results jointly validate the efficacy of the proposed multiport network and RCR volatile gas sensing architecture. Full article

Long-range, high-resolution distance measurement with high ambient-light tolerance has been achieved using a 720 × 488-resolution short-pulse indirect time-of-flight (SP-iToF) image sensor featuring six-tap, one-drain pixels fabricated by a front-side illumination (FSI) process. The sensor performs 30-phase demodulation through six-tap pixels in each subframe, combined with five range-shifted subframe (SF) readouts. The six-tap demodulation pixel, designed with a lateral drift-field pinned photodiode, demonstrates over 90% demodulation contrast for a 20 ns light-pulse width. High-speed column-parallel 12-bit cyclic ADCs enable all six-tap subframe signals to be read within 4.38 ms. This high-speed subframe readout, together with efficient exposure-time allocation across the five subframes, enables a depth-image frame rate of 10 fps. The multi-phase demodulation in SP-iToF measurements, operating with an extremely small duty ratio of 0.2%, effectively suppresses ambient-light charge accumulation and the associated shot noise in the pixel. As a result, distance measurements up to 100 m under 100 klux illumination are achieved, with depth noise maintained below 1%. Full article

Narrowband Internet of Things (NB-IoT) was designed as a key Low-Power Wide-Area Network technology when 5G networks were established. The ideal quadrature demodulation in NB-IoT relies on the fundamental symmetry between the in-phase (I) and quadrature (Q) branches, characterized by a perfect 90-degree phase shift and matched amplitude. However, practical hardware imperfections in mixers, filters, and ADCs break this symmetry, leading to I/Q imbalances. Moreover, I/Q imbalance is coupled with carrier frequency offset (CFO), which arises from asymmetry in the frequency of the transceiver oscillator. In this paper, we propose a model-embedded lightweight network for joint CFO and I/Q imbalance estimation for NB-IoT systems. An I/Q imbalance compensation model is embedded as a layer to connect two subnetworks, I/Q estimation network (IQENET) and CFO estimation network (CFOENET). By embedding the physical model, the network gains the capability to learn the features of coupling effects during the training process, as the image signals caused by I/Q imbalance are removed before CFO estimation. A phased training strategy is also proposed. In the first phase, the two subnetworks are pre-trained independently. In the second phase, they are fine-tuned jointly to deal with the coupling effects. Simulation results show that the proposed network achieves high estimation accuracy while maintaining low complexity. Full article

To address the issues of quadrature component attenuation and signal-to-noise ratio (SNR) degradation caused by carrier phase delay in Phase-Generated Carrier (PGC) demodulation, this paper proposes a phase delay compensation method based on sampling-point shift pre-calibration. By establishing a discrete phase offset model, we derive the mathematical relationship between sampling point shift and carrier cycle duration, and introduce a compensation mechanism that adjusts the starting point of the sampling sequence to achieve carrier phase pre-alignment. Theoretical analysis demonstrates that this method restricts the residual phase error to within Δθ_max = πf₀/f_s, thereby fundamentally avoiding the denominator-zero problem inherent in traditional compensation algorithms when θ approaches 45°. Experimental validation using an Extrinsic Fabry–Perot Interferometric (EFPI) ultrasonic sensor shows that, at a sampling rate of 10 MS/s, the proposed pre-alignment algorithm improves the minimum demodulation SNR by 35 dB and reduces phase fluctuation error to 2% of that of conventional methods. Notably, in 1100 consecutive measurements, the proposed method eliminates demodulation failures at critical phase points (e.g., π/4, π/2), which are commonly problematic in traditional techniques. By performing phase pre-compensation at the signal acquisition level, this method significantly enhances the long-term measurement stability of interferometric fiber-optic sensors in complex environments while maintaining the existing PGC demodulation architecture. Full article

Optical interferometry provides high-precision displacement and angle measurement solutions for a wide range of cutting-edge industrial applications. One of the key factors to achieve such precision lies in highly accurate optical encoder signal processing, as well as the calibration and compensation techniques customized for specific measurement principles. Optical interferometric techniques, including laser interferometry and grating interferometry, are usually classified into homodyne and heterodyne systems according to their working principles. In homodyne interferometry, the displacement is determined by analyzing the phase variation of amplitude-modulated signals, and common demodulation methods include error calibration methods and ellipse parameter estimation methods. Heterodyne interferometry obtains displacement information through the phase variation of beat-frequency signals generated by the interference of two light beams with shifted frequencies, and its demodulation techniques include pulse-counting methods, quadrature phase-locked methods, and Kalman filtering. This paper comprehensively reviews the widely used signal processing techniques in optical interferometric measurements over the past two decades and conducts a comparative analysis based on the characteristics of different methods to highlight their respective advantages and limitations. Finally, the hardware platforms commonly used for optical interference signal processing are introduced. Full article

To address the demand of equivalent self-noise suppression in a distributed hydroacoustic sensing system, this study proposes a method to enhance the acoustic sensitivity and signal-to-noise ratio (SNR) using space division multiplexed (SDM) technology based on multi-core fiber (MCF). Specifically, a dual-channel demodulation system for distributed acoustic sensing is designed using MCF. The responses of different cores in MCF are almost consistent under external acoustic pressure, while their self-noise is inconsistent. Accordingly, the acoustic pressure phase sensitivity (APPS) and SNR gain based on the accumulation of dual-channel signals are analyzed, which are verified by experiments. It is shown that the self-noise correlation coefficient between the two cores is 0.11, increasing the noise power by 3.46 dB. The APPS is increased by 5.97 dB re 1 rad/μPa after the accumulation of two-core signals, which is close to the theoretical value (6 dB). The equivalent self-noise is reduced by 2.54 dB. The experimental results reveal that the enhancement of acoustic pressure phase shift sensitivity and SNR can be achieved by the space division multiplexing (SDM) of multi-core signals, which is of great significance for suppressing the equivalent self-noise of the system and realizing the acoustic pressure detection of weak underwater signals. Full article