Search Results (39)

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. Full article

Acoustic sensing has many applications in engineering, one of which is fiber-optic hydrophones (FOHs). Conventional piezoelectric hydrophones face limitations related to size, electromagnetic interference, corrosion, and narrow operating bandwidth. Fiber-optic hydrophones, particularly those employing distributed feedback (DFB) lasers, offer a compelling alternative due to their mechanical flexibility, resistance to harsh conditions, and broad detection range. DFB lasers are highly sensitive to external perturbations such as temperature and strain, enabling the precise detection of underwater acoustic signals by monitoring the resultant shifts in lasing wavelength. This paper presents an enhanced interrogation mechanism that leverages Mach–Zehnder interferometers to translate wavelength shifts into measurable phase deviations, thereby providing cost-effective and high-resolution phase-based measurements. A dual interferometric setup is integrated with a standard demodulation algorithm to extend the dynamic range of these sensing systems. The experimental results demonstrate a substantial improvement in performance, with the dynamic range increasing from 125 dB to 139 dB at 1 kHz without degrading the noise floor. This enhancement significantly expands the utility of FOH-based systems in underwater environments, supporting applications such as underwater surveillance, submarine communication, and marine ecosystem monitoring. Full article

Kagome lattices have attracted significant research interest due to their unique interplay of geometry, topology, and material properties. They provide deep insights into strongly correlated electron systems, novel quantum phases, and advanced material designs, making them fundamental in condensed matter physics and material engineering. This work presents an efficient method for terahertz (THz) wave generation across the entire THz spectrum, leveraging high-quality-factor Kagome-shaped silicon photonic crystal resonators. In the proposed simulation-based approach, an infrared (IR) single-frequency wave interacts with an induced resonance mode within the resonator, producing a THz beat frequency. This beat note is then converted into a standalone THz radiation (T-ray) wave using an amplitude demodulator. Simulations confirm the feasibility of our method, demonstrating that a conventional single-frequency wave can induce resonance and generate a stable beat frequency. The proposed technique is highly versatile, extending beyond THz generation to frequency conversion in electronics, optics, and acoustics, among other domains. Its high efficiency, compact design, and broad applicability offer a promising solution to challenges in THz technology. Furthermore, our findings establish a foundation for precise frequency manipulation, unlocking new possibilities in signal processing, sensing, detection, and communication systems. Full article

Demodulation of fiber optic Fabry–Pérot (F-P) acoustic sensors with high sensitivity and a large dynamic range continues to pose significant challenges. In this paper, we propose an advanced phase-generated carrier (PGC) demodulation algorithm, applied innovatively to membrane-free F-P acoustic sensors operating under high sound pressure. The algorithm optimizes acoustic demodulation results by adjusting the mixing phase delay, achieving the best signal to noise and distortion ratio (SINAD) and total harmonic distortion (THD) (<1%). Additionally, by introducing the cosine component of the acoustic signal obtained directly after filtering the interference signal, into the demodulation algorithm process, the sensitivity of the sensor at high sound pressure is significantly improved. The experimental results show that the ameliorated algorithm obtains a demodulation sensitivity of $34.95\mathsf{\mu }$rad/Pa and a THD of 0.87%, both of which are superior to traditional PGC demodulation algorithms under the same experimental conditions. At the same time, the minimum detectable sound pressure of $129.73{\mathrm{mPa/Hz}}^{1/2}$ was obtained, and the sound pressure tested in the experiment at a frequency of 1 kHz was as high as 3169.78 Pa (164 dB). With the proposed algorithm, the flatness of the frequency response is ±0.82 dB from 100 Hz to 33 kHz, and a dynamic range of up to 102.6 dB was obtained, making it relevant in the field of aerospace acoustic measurements. Full article

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. Full article

This paper presents Z-OFDM, a high-performance solution for underwater acoustic communication. Traditional underwater orthogonal frequency division multiplexing (OFDM) systems suffer from spectrum leakage and distortion due to the narrowband nature of underwater acoustic signals and the picket fence effect of the fast Fourier transform (FFT). Z-OFDM addresses these issues by integrating zoom-fast Fourier transform (ZoomFFT) with OFDM and redesigning the modulator and demodulator to replace the conventional FFT. This integration enhances spectral resolution, resulting in higher channel capacity, improved Signal to Interference plus Noise Ratio (SINR), and reduced Bit Error Rate (BER). Computer simulations using underwater acoustic channels from Fuxian Lake and Wuyuan Bay demonstrate that the Z-OFDM system achieves a 6 dB gain compared to conventional OFDM systems at a BER of ${10}^{-3}$. These results demonstrate the effectiveness of Z-OFDM in overcoming the limitations of traditional FFT-based OFDM systems in underwater environments. Full article

In this paper, a genetic least mean square (GLMS) method is proposed to improve the signal-to-noise ratio (SNR) of acoustic signal reconstruction in a phase-sensitive optical time-domain reflectometry system. The raw demodulated signal is processed via applying the least mean square criterion. The SNR of the processed signal was calculated and served as the objective function in the fitness evaluation procedure. The genetic operations of the population selection, crossover, and mutation are sequentially performed and repeated until the suspensive condition is reached. Through multiple iterations, the GLMS method continuously optimized the population to find the optimal solution. Experimental results demonstrate that the SNR is substantially improved by 14.37–23.60 dB in the monotonic scale audio signal test from 60 to 1000 Hz. Furthermore, the improvement of the phase reconstruction of a human voice audio signal is also validated by exploiting the proposed GLMS method. Full article

Acoustic emission (AE) testing is a widely used nondestructive testing method for the early detection of failures in materials and structures. In this paper, an AE detection sensor combining optical fiber sensing with laser self-mixing interference (SMI) technology is proposed. A multi-coil optical fiber ring wound round a cylindrical acrylic skeleton was designed in order to sense the deformation caused by AE elastic waves, which was then demodulated using self-mixing interference technology. Finite element analyses were conducted in order to investigate the deformation of fiber under acoustic sources. AE signals induced via ball-dropping impact experiments were successfully detected by the proposed experimental system. The proposed SMI optical fiber AE sensing system has the advantages of being free from electromagnetic interference and having a simple structure, low implementation cost and high measurement resolution and sensitivity. Full article

Ultra-weak fiber Bragg grating (UWFBG) array-based phase-sensitive optical time-domain reflectometry (Φ-OTDR) utilizes the interference interaction between the reference light and the reflected light from the broadband gratings for sensing. It significantly improves the performance of the distributed acoustic sensing system (DAS) because the intensity of the reflected signal is much higher than that of the Rayleigh backscattering. This paper shows that Rayleigh backscattering (RBS) has become one of the primary noise sources in the UWFBG array-based Φ-OTDR system. We reveal the impact of the Rayleigh backscattering signal on the intensity of the reflective signal and the precision of the demodulated signal, and we suggest reducing the pulse duration to improve the demodulation accuracy. Experimental results demonstrate that using light with a 100 ns pulse duration can improve the measurement precision by three times compared with the use of a 300 ns pulse duration. Full article

This pattern recognition method can effectively identify vibration signals collected by a phase-sensitive optical time-domain reflectometer (Φ-OTDR) and improve the accuracy of alarms. An alignment-free end-to-end multi-vibration event detection method based on Φ-OTDR is proposed, effectively detecting different vibration events in different frequency bands. The pulse accumulation and pulse cancellers determine the location of vibration events. The local differential detection method demodulates the vibration event time-domain variation signals. After the extraction of the signal time-frequency features by sliding window, the convolution neural network (CNN) further extracts the signal features. It analyzes the temporal relationship of each group of signal features using a bidirectional long short-term memory network (Bi-LSTM). Finally, the connectionist temporal classification (CTC) is used to label the unsegmented sequence data to achieve single detection of multiple vibration targets. Experiments show that using this method to process the collected 8563 data, containing 5 different frequency bands of multi-vibration acoustic sensing signal, the system F1 score is 99.49% with a single detection time of 2.2 ms. The highest frequency response is 1 kHz. It is available to quickly and efficiently identify multiple vibration signals when a single demodulated acoustic sensing signal contains multiple vibration events. Full article

To achieve high-quality voice communication technology without noise interference in flammable, explosive and strong electromagnetic environments, the speech enhancement technology of a fiber-optic external Fabry–Perot interferometric (EFPI) acoustic sensor based on deep learning is studied in this paper. The combination of a complex-valued convolutional neural network and a long short-term memory (CV-CNN-LSTM) model is proposed for speech enhancement in the EFPI acoustic sensing system. Moreover, the 3 × 3 coupler algorithm is used to demodulate voice signals. Then, the short-time Fourier transform (STFT) spectrogram features of voice signals are divided into a training set and a test set. The training set is input into the established CV-CNN-LSTM model for model training, and the test set is input into the trained model for testing. The experimental findings reveal that the proposed CV-CNN-LSTM model demonstrates exceptional speech enhancement performance, boasting an average Perceptual Evaluation of Speech Quality (PESQ) score of 3.148. In comparison to the CV-CNN and CV-LSTM models, this innovative model achieves a remarkable PESQ score improvement of 9.7% and 11.4%, respectively. Furthermore, the average Short-Time Objective Intelligibility (STOI) score witnesses significant enhancements of 4.04 and 2.83 when contrasted with the CV-CNN and CV-LSTM models, respectively. Full article

The linear demodulation range and background noise of the Michelson interferometer system are investigated with a laser phase noise measurement system. We have theoretically and experimentally analyzed the performance of the interferometer system by changing the frequency modulation amplitude of the laser and the optical path difference (OPD) of the interferometer, respectively. It is shown that the linear demodulation range of the Michelson interferometer system is finite, which depends on the parameters of the system, such as the sample frequency, the delay time between two interferometer arms, and the system bandwidth. Furthermore, the experimental results indicate that the background noise of the interferometer system can be reduced by using a sufficiently long OPD so that the smaller true phase information can be detected with the demodulation system. The parameters of the measurement system could be optimized to satisfy the demand of the phase demodulation with different levels, which is of great significance for the phase monitoring interrogator, such as fiber-optical interferometer sensors and distributed acoustic sensors. Full article

Orthogonal frequency division multiplexing (OFDM) is the preferred scheme for high-speed communication in the field of underwater acoustic communication. However, it is very sensitive to the carrier frequency offset (CFO). This study used a time-varying CFO estimation method aided by the differential evolution (DE) algorithm to accurately estimate the CFO of an OFDM system. This method was based on the principle that the received OFDM signal with inter-carrier interference could be considered by a Multi Carrier-code division multiple access (MC-CDMA) system on the receiver side because MC-CDMA is a technology that combines OFDM and code division multiple access (CMDA). Because it is suitable for solving problems where there are dependencies between adjacent variables, the DE algorithm was used to capture the varying CFO values on the adjacent blocks. The spreading code of the MC-CDMA was obtained based on the estimated CFO values, which were elements in the DE solutions. Then the received signal was reconstructed. The Root-Mean-Square Error between the reconstructed and actual received signals was used as the cost function, and the CFO was estimated using the DE algorithm because of its powerful parallel search capability. The simulation results showed that the proposed method had a high estimation accuracy. Compared with other intelligent optimization algorithms such as the genetic algorithm and simulated annealing mutated-genetic algorithm, the time-varying CFO estimation performance of the DE algorithm was better because of its unique ability to solve problems with dependencies between adjacent variables. Specifically, under the condition of a high signal-to-noise ratio, the improvement of estimation accuracy reaches 36.13%, and the Bit Error Rate of demodulation is thus reduced by 75%, compared with the reference algorithms. In addition, the proposed method also has good applicability to modulation methods. For phase-shift keying and quadrature amplitude modulation, in particular, the proposed method not only achieved high-precision time-varying CFO estimation values, but also reduced the demodulation deterioration caused by noise. Full article

The objective of this study is to evaluate Grassmannian constellations combined with a spread spectrum multiple access scheme for underwater acoustic mobile multiple access communication systems. These communication systems enable the coordination of a fleet of Autonomous Underwater Vehicles (AUVs) from a surface or bottom control unit, e.g., a boat. Due to its robustness against phase rotation, the demodulator of Grassmannian constellations uses non-coherent detection, and the main advantage of such modulation lies in the spectrum efficiency gain with respect to conventional differential modulation. The communication system under study in this paper consists of (i), at the transmitter side, a Grassmannian modulation used in an orthogonal spread spectrum multiple access scheme called Multiuser Hyperbolic Frequency Modulation (MU-HFM) and (ii), at the receiver side, a non-coherent array decoder. The modulation and demodulation are presented as well as the considered spreading sequences. Finally, performances of the proposed transmission scheme are evaluated over replayed underwater acoustic channel responses collected at sea by a multi-sensor acoustic acquisition system. Full article

Sonobuoy is a disposable device that collects underwater acoustic information and is designed to transmit signals collected in a particular area to nearby aircraft or ships and sink to the seabed upon completion of its mission. In a conventional sonobuoy signal transmission and reception system, collected signals are modulated and transmitted using techniques such as frequency division modulation or Gaussian frequency shift keying. They are received and demodulated by an aircraft or a ship. However, this method has the disadvantage of a large amount of information being transmitted and low security due to relatively simple modulation and demodulation methods. Therefore, in this paper, we propose a method that uses an autoencoder to encode a transmission signal into a low-dimensional latent vector to transmit the latent vector to an aircraft or vessel. The method also uses an autoencoder to decode the received latent vector to improve signal security and to reduce the amount of transmission information by approximately a factor of a hundred compared to the conventional method. In addition, a denoising autoencoder, which reduces ambient noises in the reconstructed outputs while maintaining the merit of the proposed autoencoder, is also proposed. To evaluate the performance of the proposed autoencoders, we simulated a bistatic active and a passive sonobuoy environments. As a result of analyzing the sample spectrograms of the reconstructed outputs and mean square errors between original and reconstructed signals, we confirmed that the original signal could be restored from a low-dimensional latent vector by using the proposed autoencoder within approximately 4% errors. Furthermore, we verified that the proposed denoising autoencoder reduces ambient noise successfully by comparing spectrograms and by measuring the overall signal-to-noise ratio and the log-spectral distance of noisy input and reconstructed output signals. Full article