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ABSTRACT This paper presents a novel angle track converter for sinusoidal encoders. These encoders provide electronic signals in which the position is encoded in sinusoidal form. This work aims to reduce the complexity and enhance the conversion speed of the sinusoidal‐to‐angle demodulation system. Considering the periodicity of sine and cosine signals (SCSs), the full range [0,2π)$$ \left[0,2\pi \right) $$ is evenly divided into eight segments to determine the coarse angle. According to the specific coarse angle segment, the SCSs are reshaped for proceeding demodulation. Then a fine angle is derived from reshaped signals based on division and arctangent algorithm. Division operation is achieved by a capacitor digital‐to‐analog converter, dynamic comparator, and successive approximation register. The arctangent value is obtained from the division result with the compensation by a small‐size look‐up table. The new converter fabricated in 0.18‐μ$$ \upmu $$m BCD technology occupies an active area of 0.16 mm2 and consumes 1.5 mW at the sample rate 10 MHz. The measured maximum error is 1.8°, in the full range. Without analog‐to‐digital converters and no nonlinear operation unit, the proposed angle track converter has a significant advantage in cost, speed, and efficiency. [ABSTRACT FROM AUTHOR]

As a classical demodulation method, envelope spectrum (ES) has been used in rotating machinery fault diagnosis. However, for strong noise or multiple faults, the feature extraction ability of ES is not outstanding, even if it is unable to extract obvious fault features. Fourier transform (FT) in ES analysis is also not suitable for analyzing non-stationary signals. Considering the shortcomings of FT, this paper defines the Ramanujan Fourier mixture transform (RFMT). The RFMT has outstanding period feature extraction ability and can accurately extract the periodic features in the envelope signal. Based on this, this paper proposes the iterative Ramanujan Fourier mixture spectrum (IRFMS) method. The IRFMS enhances the fault features in the signal by iterative envelope and selects the envelope signals with obvious fault features by cyclic kurtosis. The results of signal analysis verify that IRFMS has excellent fault feature extraction ability, which is suitable for various fields of rotating machinery fault diagnosis. [ABSTRACT FROM AUTHOR]

In order to realize single-frame three-dimensional (3D) reconstruction, a single-frame two-step phase-shift method based on orthogonal composite pattern projection is proposed to solve the problem that the traditional N-step phase-shift profilometry needs multiple projections for 3D reconstruction. The orthogonal composite pattern uses only two carrier channels to reduce the spectrum overlapping influence on the demodulation accuracy of carrier and modulated fringes. A two-dimensional variational mode decomposition method is adopted to remove the background DC component of the sinusoidal fringe to overcome the mode overlap problem by controlling the size of the bandwidth. Thus, the two-step phase-shift method is applied to calculate the phases for 3D reconstruction. The experimental results show that, compared with the typical Fourier transform profilometry method, 3-step composite method and 2 + 1 composite method, the 3D reconstruction accuracy of the proposed method is improved by 49.1%,31.4% and 23.2% respectively according to mean absolute error, and by 73.0%, 58.4% and 56.8% respectively according to mean squared error as the evaluation index. Finally, the dynamic 3D reconstruction experiment demonstrates the good adaptability of dynamic 3D reconstruction. [ABSTRACT FROM AUTHOR]

Plasmonic tilted fiber Bragg gratings (TFBGs) have emerged as versatile tools for refractometric analyses and biochemical sensing. Their applications have significantly blossomed these last years, from proteins and cellular bioassays to operando monitoring in batteries, to cite just a few. They are widely recognized for their cutting‐edge performance and low limits of detection, arising from their dense multimodal spectral nature featuring tens of narrowband cladding mode resonances. Their comb‐like spectrum is so rich that numerous demodulation techniques have been reported, without benchmark of their relative performance while they possess important distinctions. This review highlights developments in detangling techniques from the pioneering works based on single‐peak analysis up to the most recent approaches involving Fourier analysis, the implementation of machine learning, and cascaded spectral decomposition processes. To fairly compare the different techniques of the literature, we implemented each analysis on original experimental refractometric calibrations, revealing the assets of the most updated methods. This paper therefore reviews these demodulation techniques based on the same datasets, obtained under the same conditions. We show and discuss the results obtained from bioassays and pinpoint the importance of advanced analytical methodologies to maximize the reproducibility, reliability and performance of plasmonic‐based TFBGs biosensors. [ABSTRACT FROM AUTHOR]

We present a simple, highly stable, low noise, and rapid detection scheme using higher harmonic demodulation applied to terahertz time domain spectroscopy (THz-TDS). The presence of higher harmonics in the detected periodic signal is because of the non-sinusoidal shape of a single pulse, which is controlled by an ultrafast current pre-amplifier. Instead of using external signal modulators, the use of the inherent repetition rate ( f rep ) of the femtosecond laser and its harmonics as reference for the lock-in amplifier simplifies the setup, while allows rapid and low noise detection owing to the megahertz modulation frequencies. Unlike the signal detected at the fundamental f rep , signals detected at higher harmonics have much lower offset and are unaffected by perturbations in the environment present during measurements, which is an essential characteristic for an analytical tool. Our proposed technique can be readily integrated to existing THz-TDS systems and is applicable to scans with rapid acquisition times and to scans that require long periods of time (e.g., hyperspectral imaging). [ABSTRACT FROM AUTHOR]

Codeword position index based sparse code multiple access (CPI‐SCMA) is an effective scheme that expands codeword positions in the time domain and carries extra information by their index. This paper proposes a dual‐mode CPI‐SCMA (DCPI‐SCMA) scheme to improve the error propagation caused by the mismatch between SCMA codewords and information bits. Furthermore, a DCPI‐SCMA with transmit diversity scheme is proposed where index bits are repeatedly transmitted to obtain a transmit diversity gain; hence, a higher reliability can be achieved with a slight loss of spectral efficiency. An optimal approach for the codebook index pattern is derived where the decision of index bits is involved in the demodulation of SCMA. It can be seen from simulation results and system analysis that the proposed schemes achieve better bit error rate performance with a decrease in complexity and obtain better robustness and flexibility compared with the existing CPI‐based SCMA schemes under the same spectral efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the changes in the waveform of a sinusoidal carrier resulting from amplitude modulation (AM) process. Based on this analysis, a novel method for extracting amplitude information is proposed. The proposed method uses the behaviour of the amplitude limitation which does not significantly affect the slope of the sinusoidal signal near zero crossing points. A simple comparator is used to convert the changes in sinusoidal slope near zero crossing points into pulse width changes. A simple circuit is proposed which keeps the output pulse width of the comparator constant by a simple control loop. The accuracy of the method is evaluated through simulation and is experimentally tested. If the modulation index is high and the amplitude of the input signal to the detector is limited, the proposed method can yield up at least 9 dB improvement in relative error power. However, if the modulation index is small, the improvement in relative error power can be at least 35 dB compared to other conventional types of AM demodulators. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the azimuth echoes of forward‐looking scanning imaging are aliased and the angular information of different targets cannot be directly separated, resulting in low azimuth resolution, the authors propose a scanning imaging method based on azimuth modulation and pulse compression in this paper. Firstly, the coupling of slow‐time and scanning angle is utilised to transmit time‐varying azimuth‐modulated pulses while the beam is scanning, and phase demodulation is performed during the echo processing; then the azimuth pulse compression is used to accumulate effective power and obtain the azimuth information of different targets. The proposed method not only obtains high azimuth resolution of the forward‐looking area, but also has a simple processing process and good anti‐noise performance. Simulation and analysis demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Planetary gearboxes are often used for power transmission in wind turbines. It makes the gear fault detection of planetary gearboxes very useful and necessary. Generally, windowed synchronous averaging (WSA) is a widely used method to detect planet gear failure in planetary gearboxes. However, the WSA is not directly suitable for the multi-stage planetary gearbox since different planetary stages are working together and vibrations from different stages are coupled to each other. The coupled interference is the synchronous interference, which cannot be reduced by the WSA. It makes the faulty planet gear of interest difficult to detect. To address this issue, an angle compensation synchronous averaging (ACSA) scheme is proposed. The equi-angle resampling is applied to the obtained vibration first. Then, the synchronous interference can be constructed by applying the synchronous averaging-based angle compensation strategy, and removed by subtracting it from the resampled vibration. Subsequently, the fast spectral kurtosis is utilized on the residual vibration to obtain the envelope signal. Next, the WSA is further applied to the residual vibration and envelope signal for constructing the synthetic vibration and synthetic envelope signal corresponding to the planet gear of interest. Finally, the narrowband demodulation and envelope analysis are used to detect planet gear failure. Experiments on a two-stage planetary gearbox positively support the ACSA scheme. [ABSTRACT FROM AUTHOR]

Most of Optical Camera Communication (OCC) systems benefit from the rolling shutter mechanism of Complementary Metal-Oxide Semiconductor (CMOS) cameras to record the brightness evolution of the Light-Emitting Diode (LED) through dark and bright strips within images. While this technique enhances the maximum achievable data rate, the main difficulty lies in the demodulation of the signal extracted from images, subject to blooming effect. Thus, two main approaches were proposed to deal with this issue, using adaptive thresholds whose value evolves according to amplitude changes or detecting signal variations with the first-order derivative. As the second method is more robust, a new demodulation method based on the detection of the zeros of the first-order derivative of the extracted signal was proposed in this paper. Obtained results clearly show an improvement in the extracted signal demodulation compared to other methods, achieving a raw Bit Error Rate (BER) of 10−3 around 50 cm in a Line-Of-Sight scenario, and increasing the maximum communication distance by 43.5%, reaching 330 cm in the case of a Non-Line-Of-Sight transmission. [ABSTRACT FROM AUTHOR]

In this letter, we consider a system based on LoRa (Long Range), which is one of the widely used IoT (Internet of Things) communication technologies. Recently, as the application areas of LoRa have expanded from low-speed to high-speed moving objects, an increase in error rates due to Doppler shift in high-speed environments has been reported. To address this issue, this letter proposes a new LoRa modulation scheme where information is conveyed by varying the frequency difference between two chirp signals. Additionally, an efficient demodulation algorithm is proposed to successfully demodulate information at the receiver even in the presence of residual carrier frequency offset. Numerical results demonstrate that the proposed LoRa modulation scheme can guarantee low error rates in mobile environments. [ABSTRACT FROM AUTHOR]

The health of mechanical components can be assessed by analyzing the vibration and acoustic signals they produce. These signals contain valuable information about the component's condition, often encoded within specific frequency bands. However, extracting this information is challenging due to noise contamination from various sources. Narrow-band amplitude demodulation presents a robust technique for isolating fault-related information within the signal. This work proposes a novel approach based on cluster-based segmentation for demodulating the signal and extracting the frequency band of interest. The segmentation process leverages the criteria of maximum L-kurtosis and minimum entropy. L-kurtosis maximizes impulsiveness in the signal, while minimum entropy signifies a low degree of randomness and high cyclo-stationarity, and both characteristics are crucial for identifying the desired frequency band. Simulations and experimental tests using vibration signals from different gears demonstrate the effectiveness of this technique. The processed envelope of the signal exhibits distinct improvements, highlighting the ability to accurately extract the fault-related information embedded within the complex noise-ridden signals. This approach offers a promising solution for accurate and efficient fault diagnosis in mechanical systems, contributing to enhanced reliability and reduced downtime. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motors (PMSMs) are widely used due to their unique advantages. Their transmission system mainly relies on rolling bearings; therefore, monitoring the motor's working status and fault diagnosis for the rolling bearings are the key focuses. Traditional resonance demodulation methods analyze the vibration signals of bearings to achieve bearing fault diagnosis, but the limiting condition is that the inherent frequency needs to be known. Based on the resonance demodulation method, deep learning methods, such as the convolutional neural network (CNN) model designed in this article, have improved the practicality and effectiveness of diagnosis. A physical explanation of the deep learning model for bearing fault diagnosis is presented in this article, the relationship between resonance demodulation and the 1D CNN is analyzed, and the model is trained and validated. The experimental results show that the CNN model can identify different types of bearing faults. The analysis results of the trained CNN model and the intermediate results indicate that the CNN model is consistent with the resonance demodulation method. The optimized method is verified, proving that the model can achieve the classification and diagnosis of fault bearing data collected under different environments after the optimized training method is adopted. [ABSTRACT FROM AUTHOR]

Demodulation and decoding are pivotal for the eLoran system's timing and information transmission capabilities. This paper proposes a novel demodulation algorithm leveraging a multiclass support vector machine (MSVM) for pulse position modulation (PPM) of eLoran signals. Firstly, the existing demodulation method based on envelope phase detection (EPD) technology is reviewed, highlighting its limitations. Secondly, a detailed exposition of the MSVM algorithm is presented, demonstrating its theoretical foundations and comparative advantages over the traditional method and several other methods proposed in this study. Subsequently, through comprehensive experiments, the algorithm parameters are optimized, and the parallel comparison of different demodulation methods is carried out in various complex environments. The test results show that the MSVM algorithm is significantly superior to traditional methods and other kinds of machine learning algorithms in demodulation accuracy and stability, particularly in high-noise and -interference scenarios. This innovative algorithm not only broadens the design approach for eLoran receivers but also fully meets the high-precision timing service requirements of the eLoran system. [ABSTRACT FROM AUTHOR]

Real-time detection and classification of bruised apples are critical to appropriate postharvest handling. However, the early bruises are hard to identify by vision inspection due to no or few visual symptoms. In this study, the feasibility of optical property mappings was investigated for the real-time classification of early apple bruises (occurring beneath the peel for 0 h), coupled with machine learning methods. Spatial-frequency domain images of 360 apples at multiple spatial frequencies with three phases were first acquired, followed by image demodulation and inverse estimation for generating optical property mappings, through which the bruised apple tissues were visualized. Then, support vector machine (SVM) and convolutional neural network (CNN) were used to distinguish two-category (intact and bruised) and three-category apples (intact, mildly bruised, and severely bruised). The best classification accuracy of the prediction set for the two-category using SVM was up to 98.33%. CNN for the classification of bruises outperformed SVM, with the accuracies of 99.16% and 91.50% for the two-category and the three-category, respectively. However, the time consumed for CNN classification was three orders of magnitude more than the SVM. Dynamic changes in the optical property mappings of the apples after bruising within 24 h demonstrated that classification accuracy would likely increase with the bruising time. Comparison between our results and other literature further validated the feasibility of the proposed method for real-time classification of apple early bruise. [ABSTRACT FROM AUTHOR]

To solve this issue of phase estimation ambiguity induced by Gaussian-filtered minimum shift keying (GMSK) phase continuity, a GMSK coherent receiving algorithm based on optimal sampling point is proposed. For realizing the decoupling of symbols, a preceding method in constructed to encode original message to modulate and then the receiver samples at optimal time with minimal intersymbol interference to transform GMSK into offset quadrature phase shift keying (OQPSK), effectively avoiding this issue of Doppler frequency and phase inaccurate estimation induced by the introduction of initial phase ambiguity from previous unknown data. A coherent demodulator in built based on optimal sampling time to accomplish reliable receiving with low complexity. Simulation results indicate that the proposed method has a higher estimation range of Doppler frequency, while comparable estimation precision. Meanwhile, compared to optimal receiver, the proposed demodulation algorithm has very small complexity and comparable demodulation performance. [ABSTRACT FROM AUTHOR]

In this study, a phase-generated carrier (PGC) demodulation algorithm combined with the extended Kalman filter (EKF) algorithm based on an electro-optic modulator (EOM) is proposed, which can achieve nonlinear distortion (such as modulation depth drift and carrier phase delay) suppression for high-frequency phase carrier modulation. The improved algorithm is implemented on a field-programmable gate array (FPGA) hardware platform. The experimental results by the PGC-EKF method show that total harmonic distortion (THD) decreases from −32.61 to −54.51 dB, and SINAD increases from 32.59 to 47.86 dB, compared to the traditional PGC-Arctan method. This indicates that the PGC-EKF demodulation algorithm proposed in this paper can be widely used in many important fields such as hydrophone, transformer, and ultrasound signal detection. [ABSTRACT FROM AUTHOR]

Ocean salinity plays an important role in oceanographic research as one of the fundamental parameters. An optical salinometer based on the Michelson interferometer (MI) suitable for in situ measurement in deep-sea environments is proposed in this work, and it features real-time calibration and multichannel multiplexing using the frequency modulated continuous wave (FMCW) technique. The symmetrical sapphire structure used to withstand deep-sea pressure can not only achieve automatic temperature compensation, but also counteract the changes in optical path length under deep-sea pressure. A model formula suitable for optical salinity demodulation is proposed through the nonlinear least squares fitting method. In vertical profile testing, the optical salinometer demonstrated remarkable tracking performance, achieving an error of less than 0.001 psu. The sensor displays a stable salinity demodulation error within ±0.002 psu during a three-month long-term test at a depth of 4000 m. High stability and resolution make this optical salinometer have broad development prospects in ocean observation. [ABSTRACT FROM AUTHOR]

Accurate and high-speed object movement tracking systems often face significant challenges due to signal instability caused by the object's movement and rotation. To address these issues, we present STABack, a novel object tracking system using backscatter tags and accelerometer sensors, designed for high-accuracy, high-speed movement tracking. We developed an amplitude stabilization algorithm which uses envelope detection to reduce the impact of high-frequency movement on the signal, and uses dynamic threshold output to lower the BER in backscatter demodulation. Our method reduces the BER by 0.3757 compared to the regular demodulation method, resulting in a final BER of 0.07. Our evaluation of the STABack prototype shows that it achieves a median distance measurement accuracy of 6.45 cm with a standard deviation of 6.95 cm, under the condition of a speed of 120 cm. The attitude angle estimation's mean error is under 7 degrees. The system's accuracy in detecting the target object's trajectory is as high as 99%, and it can still decode with a bit error rate of no more than 0.034 at a speed of 166 cm/s. The power consumption of our system prototype is only 38.54 μW based on our experimental results. Overall, our results demonstrate that STABack can accurately estimate the movement and rotation of target objects in unstable backscatter channels. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the changes in the waveform of a sinusoidal carrier resulting from amplitude modulation (AM) process. Based on this analysis, a novel method for extracting amplitude information is proposed. The proposed method uses the behaviour of the amplitude limitation which does not significantly affect the slope of the sinusoidal signal near zero crossing points. A simple comparator is used to convert the changes in sinusoidal slope near zero crossing points into pulse width changes. A simple circuit is proposed which keeps the output pulse width of the comparator constant by a simple control loop. The accuracy of the method is evaluated through simulation and is experimentally tested. If the modulation index is high and the amplitude of the input signal to the detector is limited, the proposed method can yield up at least 9 dB improvement in relative error power. However, if the modulation index is small, the improvement in relative error power can be at least 35 dB compared to other conventional types of AM demodulators.

In this review, we summarize the latest advances in the design of optical frequency-domain reflectometers (OFDRs), digital signal processing, and sensors based on special optical fibers. We discuss state-of-the-art approaches to improving metrological characteristics, such as spatial resolution, SNR, dynamic range, and the accuracy of determining back reflection coefficients. We also analyze the latest achievements in the OFDR-based sensors: the accuracy of spatial localization of the impact, the error in detecting temperatures, deformation, and other quantities, and the features of separate measurement of various physical quantities. We also pay attention to the trend of mutual integration of frequency-domain optical reflectometry methods with time-domain optical reflectometry, which provides completely new sensing possibilities. We believe that this review may be useful to engineers and scientists focused on developing a lab setup, complete measurement instrument, or sensing system with specific requirements. [ABSTRACT FROM AUTHOR]

A novel demodulation scheme for a point-type fiber sensor is designed for salinity concentration monitoring based on a Sagnac interferometer (SI) composed of a tapered polarization-maintaining fiber (TPMF) and optical time stretching technology. The SI, constructed using a PMF with a taper region of 5.92 μm and an overall length of 30 cm, demonstrated a notable enhancement in the evanescent field, which intensifies the interaction between the light field and external salinity. This enhancement allows for a direct assessment of salinity concentration changes by analyzing the variations in the SI reflection spectra and the experimental results indicate that the sensitivity of the sensor is 0.151 nm/‰. In contrast to traditional fiber optic sensors that depend on spectral demodulation with slower response rates, this work introduces a new approach where the spectral shift is translated to the time domain, utilizing a dispersion compensation fiber (DCF) with the demodulation rate reaching up to 50 MHz. The experimental outcomes reveal that the sensor exhibits a sensitivity of −0.15 ns/‰ in the time domain. The designed sensor is anticipated to play a pivotal role in remote, real-time monitoring of ocean salinity. [ABSTRACT FROM AUTHOR]

F-P (Fabry–Perot) pressure sensors have a wide range of potential applications in high-temperature, high-pressure, and high-dynamic environments. However, existing demodulation methods commonly rely on spectrometers, which limits their application to high-frequency pressure signal acquisition. To solve this problem, this study developed a self-compensated, three-wavelength demodulation system composite with an F-P pressure sensor and a thermocouple to construct a comprehensive sensing system. The system produces accurate pressure measurements in high-temperature, high-pressure, and high-dynamic environments. In static testing at room temperature, the sensing system shows excellent linearity, and the pressure sensitivity is 158.48 nm/MPa. In high-temperature testing, the sensing system maintains high linearity in the range of 100 °C to 700 °C, with a maximum pressure-indication error of about 0.13 MPa (0~5 MPa). In dynamic testing, the sensor exhibits good response characteristics at 1000 Hz and 5000 Hz sinusoidal pressure frequencies, with a signal-to-noise ratio (SNR) greater than 37 dB and 45 dB, respectively. These results indicate that the sensing system proposed in this study has significant competitive advantages in the field of high-temperature, high-speed, and high-precision pressure measurements and provides an important experimental basis and theoretical support for technological progress in related fields. [ABSTRACT FROM AUTHOR]

Recently, researchers have achieved the goal of using unified architecture to achieve multiple modulation modes under specific conditions. However, existing research still suffers from the problem of large resource and time overhead. This paper proposes an adaptive modem based on a vector quantization (VQ) long short-term memory autoencoder (LSTM-AE), designed to implement modulation and demodulation of signals from the second to thirty-second order in a lightweight way. By leveraging the memory capacity of the LSTM module and the compression capability of the autoencoder, the model is able to support multi-order modulation methods. This study used the Adam optimizer for training and testing on a simple dataset extended by adding AWGN noise only and made modifications based on the MSE loss function to balance the accuracy and training speed of each part of the model. Experiments demonstrate that the proposed method not only achieves comparable modem performance to existing frameworks for second to thirty-second order signals, but also significantly reduces the number of parameters and training time. Experimental results indicate that the proposed methodology not only matches the performance of existing frameworks for signals ranging from the second to the thirty-second order, but also employs merely 79.6% of the average parameter count and a mere 7.4% of the average training duration. This represents a substantial reduction in resource expenditure. [ABSTRACT FROM AUTHOR]

Pressure sensors prepared from sapphire exhibit excellent characteristics, including high-temperature resistance, high hardness, and resistance to electromagnetic interference. A Fast Fourier Transform and Mean Square Error (FFT-MSE) demodulation algorithm was employed to demodulate a sapphire sandwich-structure Fabry–Perot (F-P) pressure sensor. Through simulation analysis, the experimental results indicated that the demodulation error of the air cavity length in the range of 206 μm to 216 μm was less than 0.0008%. Compared to single demodulation methods and combined demodulation methods based on FFT or Minimum Mean Square Error (MMSE), the method proposed in this work reduced the demodulation error by more than three times and increased accuracy by more than six times. The algorithm was utilized to demodulate the sapphire sandwich-structure F-P pressure sensor, and the test results indicated that the fitting error of the sensor was less than 0.025% within the pressure range of 0 MPa to 10 MPa. The repeatability error was less than 0.066%, the zero-point deviation was 1.26%, and the maximum stability deviation was 0.0063% per 30 min. The algorithm effectively demodulated the actual cavity length variation in the sapphire sandwich-structure F-P pressure sensor, providing a solution for the performance evaluation of the sapphire sandwich-structure F-P pressure sensor. [ABSTRACT FROM AUTHOR]

Several forthcoming Cosmic Microwave Background polarization experiments will employ a Continuously Rotating Half-Wave Plate (CRHWP), the primary purpose of which is to mitigate instrumental systematic effects. The use of a CRHWP necessitates demodulating the time-ordered data during the early stages of data processing. The standard approach is to "lock in" on the polarization signal using the known polarization modulation frequency and use Fourier techniques to filter out the remaining unwanted components. However, an alternative, less well-studied option is to incorporate the demodulation directly into the map-making step. Using simulations, we compare the performance of these two approaches to determine which is most effective for B -mode signal recovery. Testing the two techniques in multiple experimental scenarios, we find that the lock-in technique performs best over the full multipole range explored. However, for the recovery of the largest angular scales (multipoles, |$\ell \lt 100$|⁠) we find essentially no difference in the recovery of the signal between the lock-in and map-making approaches, suggesting that a parallel analysis based on the latter approach could represent a powerful consistency check for primordial B -mode experiments employing a CRHWP. We also investigate the impact of a detector-differencing step, implemented prior to demodulation, finding that, in most scenarios, it makes no difference whether differencing is used or not. However, analysing detectors individually allows the point at which information from multiple detectors is combined to be moved to later stages in the analysis pipeline. This presents alternative options for dealing with additional instrumental systematic effects that are not mitigated by the CRHWP. [ABSTRACT FROM AUTHOR]

Although often viewed as detrimental, fluctuations carry valuable information about the physical system from which they emerge. Femtosecond noise correlation spectroscopy (FemNoC) has recently been established to probe the ultrafast fluctuation dynamics of thermally populated magnons by measurement of their amplitude autocorrelation. Subharmonic lock-in detection is the key technique in this method, allowing us to extract the pulse-to-pulse polarization fluctuations of two femtosecond optical pulse trains transmitted through a magnetic sample. Here, we present a thorough technical description of the subharmonic demodulation technique and the FemNoC measurement system. We mathematically model the data acquisition process and identify the essential parameters that critically influence the signal-to-noise ratio of the signals. Comparing the model calculations to real datasets allows validating the predicted parameter dependences and provides a means to optimize FemNoC experiments. [ABSTRACT FROM AUTHOR]

This study introduces the design of a nonlinear frequency-modulated continuous wave (FMCW) laser ranging system. In contrast to the commonly used triangular wave linear modulation, this study utilizes sinusoidal wave modulation. The frequency information of the original sinusoidal frequency-modulated signal is extracted using an on-chip interferometer based on SiON waveguides and IQ demodulation technology. After fitting the measured interference signal at equal frequency intervals, the corresponding distance information is derived using the fast Fourier transform (FFT). The principles underlying this method are thoroughly analyzed and derived, with its accuracy confirmed through experimental validation. [ABSTRACT FROM AUTHOR]

Real-time gas sensing based on wavelength modulation spectroscopy (WMS) has been widely adopted for several gas sensing applications. It is attractive for its accurate, non-invasive, and fast determination of critical gas parameters such as concentration, temperature, and pressure. To implement real-time gas sensing, data acquisition and processing must be implemented to accurately extract harmonics of interest from transmitted laser signals. In this work, we present an FPGA-based data acquisition architecture with embedded processing capable of achieving both real-time and accurate gas detection. By leveraging real-time processing on-chip, we minimised the data transfer bandwidth requirement, hence enabling better resolution of data transferred for high-level processing. The proposed architecture has a significantly lower bandwidth requirement compared to both the conventional offline processing architecture and the standard I-Q architecture. Specifically, it is capable of reducing data transfer overhead by 25% compared to the standard I-Q method, and it only requires a fraction of the bandwidth needed by the offline processing architecture. The feasibility of the proposed architecture is demonstrated on a commercial off-the-shelf SoC board, where measurement results show that the proposed architecture has better accuracy compared to the standard I-Q demodulation architecture for the same signal bandwidth. The proposed DAQ system has potential for more accurate and fast real-time gas sensing. [ABSTRACT FROM AUTHOR]

The clarity of radio frequency fingerprint (RFF) features is an important factor affecting the recognition effect of the classifier. Recognition of RFF signals is essential in radio frequency (RF) perception. However, the RF signal is easily affected by interference and noise during transmission, which makes the distribution boundary of the characteristics of the RFF unclear. It then affects the recognition effect of the classifier. The common preprocessing algorithms, such as denoising and channel compensation, can improve the performance of communication demodulation but seriously affect the unique signal distortion of RFF characteristics. The spectral overlap between the useful signal and the noise is serious when the spectrum is broad, so it is difficult to separate the signal from the noise by traditional methods effectively. Therefore, this paper proposes a data enhancement technology for RF signals named random railings to increase the diversity of input samples and improve the overall performance of the model. At the same time, this paper also proposes a bilateral‐branch signal feature enhancement network. The dual branch structure of BBSEN extracts the features of the enhanced time‐domain signal and the spectrum obtained by the short‐time Fourier transform (STFT) of the signal and then achieves feature fusion through the improved self‐attention mechanism to obtain the RFF features, which are more suitable for the interference environment. Experiments show that the algorithm proposed in this paper can effectively improve the antijamming environment of RF signals and even can be used after preprocessing algorithms such as denoising and further improve the recognition rate of high signal‐to‐noise ratio signals. [ABSTRACT FROM AUTHOR]

The paper proposes a method for detecting small oscillations in the length of interference fiber-optic sensors, which makes it possible to compensate for the problem of slow drift of the working point with a remote sensor. The result is achieved by combining homodyne demodulation methods with a tandem low-coherence interferometer. Theoretically and experimentally, the possibility of detecting acoustic effects in the operating frequency band of 4 kHz with a sensitivity of up to 0.3 nm has been shown. [ABSTRACT FROM AUTHOR]

Nondestructive testing (NDT) is of paramount importance in ensuring the safe operation of equipment. Among various NDT techniques, ultrasonic NDT has garnered widespread attention due to its high sensitivity, fast speed, and accurate defect location. Photoacoustic NDT, a burgeoning field in ultrasonic NDT, is particularly attractive due to its immunity to electromagnetic interference. However, existing photoacoustic NDT systems suffer from inadequate excitation intensity and complex ultrasonic signal characteristics, impeding large-area NDT and accurate crack visualization. In this study, we present an all-fiber photoacoustic system for large-area NDT. To address the issues, we have developed a photoacoustic generator unit that can be optimized and controlled to generate stronger ultrasonic signals. Furthermore, we have employed mode decomposition to simplify the detected ultrasonic signals by mitigating the acoustic impedance mismatch-induced mode mixing problem in the system. As a result, the technology allows for large-area crack monitoring of up to 50*50 cm2 with an improved resolution of 1 mm. The present technology paves the way for high-resolution equipment crack monitoring with substantially enhanced accuracy in various environments. [ABSTRACT FROM AUTHOR]

The demodulation phase error will cause the quadrature error to be coupled to the rate output, resulting in performance deterioration of the MEMS gyroscope. To solve this problem, an in-run automatic demodulation phase error compensation method is proposed in this paper. This method applies square wave angular rate input to the gyroscope and automatically identifies the value of the demodulation phase error through the designed automatic identification algorithm. To realize in-run automatic compensation, the demodulation phase error corresponding to the temperature point is measured every 10 °C in the full-temperature environment (−40~60 °C). The relationship between temperature and demodulation phase error is fitted by a third-order polynomial. The temperature is obtained by the temperature sensor and encapsulated in the ceramic packages of the MEMS gyroscope, and the in-run automatic compensation is realized based on the fitting curve. The temperature hysteresis effect on the zero-rate output (ZRO) of the gyroscope is eliminated after compensation. The bias instability (BI) of the three gyroscopes at room temperature (25 °C) is reduced by four to eight times to 0.1°/h, while that at full-temperature environment (−40~60 °C) is reduced by three to four times to 0.1°/h after in-run compensation. [ABSTRACT FROM AUTHOR]

This paper investigates the channel and misalignment characteristics of a simultaneous wireless power and data transfer (SWPDT) system. Cross talk from the power channel to the data channel in case of misalignment can reduce the reliability of the communication system. To address this problem, this paper proposed to use the moving average filter in the field‐programmable gate array (FPGA) to obtain the optimal threshold and recover the baseband data adaptively. First, considering the parasitic capacitance of high‐frequency data coil, this paper presents a design method for DDQ coil applied in SWPDT systems. Then, the characteristics of the power channel and data channel are analyzed. In addition, the properties of the system are investigated in case of misalignment and the principle of the demodulation in FPGA is presented. Finally, a 1.5 kW prototype proved the correctness of the theoretical analysis in this paper, which can achieve a 500 kb/s communication rate. Meanwhile, the experimental results show that the SWPDT system proposed in this paper can provide reliable communication within 15% of misalignment in both the x‐ and y‐directions. [ABSTRACT FROM AUTHOR]

Bioimpedance sensing is widely used across a spectrum of biomedical applications. Among the different system architectures for measuring tissue impedance, synchronous detection or demodulation (SD) stands out for its lock-in amplifier utilising in-phase (I) and quadrature (Q) demodulation signals to derive real and imaginary impedance components. Typically, the current injected into the tissue is controlled by a voltage-controlled current source (VCCS). However, the VCCS can introduce phase shifts leading to discrepancies in real/imaginary outputs, especially at the highest end of the operating frequency bandwidth. Such discrepancies can significantly impact diagnostic accuracy in applications reliant on precise tissue phase profiling, such as cancer and neuromuscular evaluations. In the present work, we propose an automatic phase error compensation stage for bioimpedance measurement systems to minimise this systematic error. Our experimental findings demonstrated a considerable reduction in phase error, with the Phase Error Compensated Synchronous Detection (PECSD) system exhibiting a maximum phase error of 2° (≤5% error) compared with the uncompensated SD system where error exceeded 20%. The improvements made by our proposed SD system hold great potential for enhancing the accuracy of impedance measurements, particularly in clinical diagnosis and disease detection. [ABSTRACT FROM AUTHOR]

Communication systems face challenges from high-power adjacent channel signals, or blockers, inducing nonlinear behavior in RF front ends. Ensuring robust performance in the presence of blockers is crucial for IoT and other spectrum-consuming devices coexisting with advanced transceivers. This paper proposes a flexible, data-driven solution using a Deep Belief Network (DBN) to mitigate third-order intermodulation distortion (IMD) during demodulation. Numerical evaluations of AI-enhanced receivers employing DBN as an IMD canceler and demodulator show significant improvements in bit error rate (BER) performance. The effectiveness of DBN varies with RF front end characteristics, notably the third-order intercept point (IP3). [ABSTRACT FROM AUTHOR]

Based on the parametric oscillation process, we demonstrate the dual-axis phase-sensitive demodulation (PSD) and single-axis phase-insensitive demodulation (PISD) for the atomic magnetometer in an in situ nuclear magnetic resonance (NMR) detection system, which can separate the precession signals of NMR from the oscillating magnetic fields. The two orthogonal magnetic fields can be detected simultaneously and independently by selecting the optimal demodulation phases with the traditional PSD method. The response signals of the parametric modulation magnetometer demodulated with high order harmonic signals are evaluated, which is a new exploration. The first order harmonic demodulation can present the best sensitivity about 250 fT/Hz1/2. The high order harmonic demodulation technology supplies a twofold 3 dB bandwidth. With the PISD method, a single-axis demodulation technique is proposed. The transverse nuclear spin precession magnetic fields can be extracted effectively with the demodulation R signal outputs by setting a specific longitudinal modulation magnetic field amplitude, which is a new demodulation strategy compared with the traditional demodulation method for the NMR system. [ABSTRACT FROM AUTHOR]

In the permanent magnet synchronous motor (PMSM) high-frequency (HF) rotating voltage injection method, a current demodulation process is usually used to improve the rotor position estimation accuracy. Current demodulation is usually realized by the synchronous frame high-pass filter (SFHF) algorithm. However, the current demodulation process is complicated, and the position estimation error changes with the rotation speed. To this end, an improved HF rotating voltage injection method based on the direct decoupling (DD) current demodulation algorithm is proposed. This method takes into account the comprehensive matching optimization of both the position error cancelation compensation and the current demodulation simplification. In addition, it completely solves the problems of insufficient position estimation accuracy and complex algorithm implementation. Finally, a three-phase PMSM is taken as the research object to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) load voltage, current and other state information need to be sent to the original side for closed-loop control and monitoring processing, the secondary side to the original side of the communication is very important. Firstly, the topology and working principle of capacitive modulated WPT system were introduced. With or without capacitance modulation, the system topology was changed, the original and secondary side topologies were series/series(S/S)structure when unmodulated, and the original and secondary side topologies were series/series-parallel (S/SP)structure during modulation. The switching of the modulation capacitor formed two states to transmit communication information, and the change of the state can be reflected in the primary current. Secondly, the amplitude-shift keying(ASK)demodulation circuit was used to process the primary current to restore the communication signal. In order to improve the demodulation accuracy and anti-interference ability, the ASK demodulation circuit was improved. Finally, the effectiveness of the scheme was verified by simulation and experiments, and the experimental results show that the system can accurately complete communication from the secondary side to the primary side at a power of 100 W and a communication frequency of 2~5 kHz. [ABSTRACT FROM AUTHOR]

An external cavity wavelength-fiber ring laser (ECWTFL) based on a semiconductor optical amplifier and a combined wavelength scanning filter in the Littrow configuration is proposed and experimentally demonstrated. With the benefit of the combination of an external cavity wavelength filter and a Lyot filter, the laser achieves a single-mode narrow linewidth output with a linewidth of 1.75 kHz. The wavelength tuning range reaches 133 nm, covering the entire S + C band. The proposed ECWTFL is used for demodulation of a fiber EFPI sensor; the result shows that the proposed ECWTFL has the ability to demodulate the small cavity-length FPI sensor. [ABSTRACT FROM AUTHOR]

Synchrosqueezed transform (SST) is a time–frequency analysis method that can improve energy aggregation and reconstruct signals, which has been applied in the fields of medical treatment, fault diagnosis, and seismic wave processing. However, when dealing with time-varying signals, SST suffers from poor time–frequency resolution and is unable to deal with long signals. In order to accurately extract the characteristic frequency of variable speed rolling bearing faults, this paper proposes a synchrosqueezed transform method based on fast kurtogram and demodulation and piecewise aggregate approximation (PAA). The method firstly filters and demodulates the original signal using fast kurtogram and Hilbert transform to reduce the influence of background noise and improve the time–frequency resolution. Then, it compresses the signal by using piecewise aggregate approximation, so that the SST can deal with long signals and, thus, extract the fault characteristic frequency. The experimental data verification results indicate that the method can effectively identify the fault characteristic frequency of variable-speed rolling bearings. [ABSTRACT FROM AUTHOR]

Scaling technology and shrinking transistor size have enabled the integration of multicore modules on a single chip for high-performance computing. Wireless Network-On-Chips has been demonstrated to be a viable choice for on-chip communication compared with wired communication, considering latency, energy, and data rate as performance metrics. Limitations in on–off keying modulation schemes have been addressed using OFDM modulation methods. In this paper, a new method based on the compressed sensing integrated dual tree complex wavelet transform (CS-DTCWT) is presented for OFDM modulation and demodulation operating in the mm-wave band. The CS-DTCWT-based OFDM model is developed in MATLAB and evaluated for its performance in the mm-wave operating frequency band of 20–60 GHz and for subcarriers of 128–1024. The BER performances of CS-DTCWT-based OFDM are demonstrated to be an improvement of 80% compared to FFT-based OFDM techniques. In addition, it can save 3.11% more energy than existing works. The proposed OFDM model is suitable for wireless NOC applications. [ABSTRACT FROM AUTHOR]

An improved multi-channel symmetric network (MCSNet) is proposed to reconstruct high-channel-density random images after long-term transmission through multimode fibers (MMFs). Temporal correlation within a period of 25 minutes is calculated to investigate the time-varying characteristics of speckles. The results demonstrated that due to noise accumulation along the MMF path, the quality of speckles deteriorates significantly after long-term transmission. The MCSNet integrates U-Net and ConvNeXt Block, which enables to more fully extract the features of each channel within the entire speckle. After being trained by different random image datasets within the initial moment, tests on random images and realistic scenes of endoscopic surgery after 25 min of transmission are carried out, and all of them demonstrate a near-perfect reconstruction performance and superior scalability, which indicates that MCSNet is suitable for long-term imaging demodulation of endoscopes. [ABSTRACT FROM AUTHOR]

The five-hole pressure probe based on Micro-Electro-Mechanical Systems (MEMS) technology is designed to meet the needs of engine inlet pressure measurement. The probe, including a pressure-sensitive detection unit and a five-hole probe encapsulation structure, combines the advantages of a five-hole probe with fiber optic sensing. The pressure-sensitive detection unit utilizes silicon-glass anodic bonding to achieve the integrated and batch-producible manufacturing of five pressure-sensitive Fabry–Perot (FP) cavities. The probe structure and parameters of the sensitive unit were optimized based on fluid and mechanical simulations. The non-scanning correlation demodulation technology was applied to extract specific cavity lengths from multiple interference surfaces. The sealing platform was established to analyze the sealing performance of the five-hole probe and the pressure-sensitive detection unit. The testing platform was established to test the pressure response characteristics of the probe. Experimental results indicate that the probe has good sealing performance between different air passages, making it suitable for detecting pressure from multiple directions. The pressure responses are linear within the range of 0–250 kPa, with the average pressure sensitivity of the five sensors ranging from 11.061 to 11.546 nm/kPa. The maximum non-linear error is ≤1.083%. [ABSTRACT FROM AUTHOR]

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