Search Results (94)

Interferometric fiber optic hydrophones (IFOHs) are highly sensitive for underwater acoustic detection but face challenges owing to the trade-off between laser monochromaticity and coherence length. In this study, we propose a pseudo-random binary sequence (PRBS) phase modulation method for laser coherence length control, establishing the first theoretical model that quantitatively links PRBS parameter to coherence length, elucidating the mechanism underlying its suppression of parasitic interference noise. Furthermore, our research findings demonstrate that while reducing the laser coherence length effectively mitigates parasitic interference noise in IFOHs, this reduction also leads to elevated background noise caused by diminished interference visibility. Consequently, the modulation of coherence length requires a balanced optimization approach that not only suppresses parasitic noise but also minimizes visibility-introduced background noise, thereby determining the system-specific optimal coherence length. Through theoretical modeling and experimental validation, we determined that for IFOH systems with a 500 ns delay, the optimal coherence lengths for link fibers of 3.3 km and 10 km are 0.93 m and 0.78 m, respectively. At the optimal coherence length, the background noise level in the 3.3 km system reaches −84.5 dB (re: rad/√Hz @1 kHz), representing an additional noise suppression of 4.5 dB beyond the original suppression. This study provides a comprehensive theoretical and experimental solution to the long-standing contradiction between high laser monochromaticity, stability and appropriate coherence length, establishing a coherence modulation noise suppression framework for hydrophones, gyroscopes, distributed acoustic sensing (DAS), and other fields. Full article

The random error of fiber optic gyros is a critical factor affecting their measurement accuracy. However, the statistical characteristics of these errors exhibit time-varying properties, which degrade model fidelity and consequently impair the performance of random error suppression algorithms. To address these issues, this study first proposes a recursive dynamic Allan variance calculation method that effectively mitigates the poor real-time performance and spectral leakage inherent in conventional dynamic Allan variance techniques. Subsequently, the recursive dynamic Allan variance is integrated with the process variance estimation of Kalman filtering to construct a dual-adaptive Kalman filter capable of autonomously switching and adjusting between model parameters and noise variance. Finally, both static and dynamic validation experiments were conducted to evaluate the proposed method. The experimental results demonstrate that, compared to existing algorithms, the proposed approach significantly enhances the suppression of angular random walk errors in fiber optic gyros. Full article

In this work, an adaptive robust control method based on Radial Basis Function Neural Network (RBFNN) is proposed. Inspired by the local response characteristics of biological neurons, this method can reduce the influence of nonlinear errors and unknown perturbations in the extreme working conditions of the aircraft, such as high dynamics and strong vibration, so as to achieve high tracking accuracy. In this method, the dynamic model of the nonlinear error of the fiber optic gyroscope is proposed, and then the unknown external interference observer is designed for the system to realize the estimation of the unknown disturbances. The controller design method combines the design of the adaptive law outside the finite approximation domain of the achievable condition design of the sliding mode surface, and adjusts the controller parameters online according to the conditions satisfied by the real-time error state, breaking through the limitation of the finite approximation domain of the traditional neural network. In the finite approximation domain, an online adaptive controller is constructed by using the universal approximation ability of RBFNN, so as to enhance the robustness to nonlinear errors and external disturbances. By designing the output constraint mechanism, the dynamic stability of the system is further guaranteed under the constraints, and finally its effectiveness is verified by simulation analysis, which provides a new solution for high-precision inertial navigation. Full article

The present work reports the evaluation of a sliding mode observer (SMO) for a passive interferometric fiber-optic gyroscope (IFOG). To achieve that, the experimental setup was designed and evaluated to provide two out-of-phase signals as required by the SMO system employed. This led to the operation of the IFOG-SMO implemented in a passive mode with a 3 × 3 optical fiber directional coupler, which dismissed the use of optical phase modulators, such as piezoelectric or electro-optic devices. Simulations were performed and provided a qualitative analysis of the dependence of the system gain as a function of the sigmoid factor and sample rate, which resulted in a method for tuning the gain value according to the expected input signal. The experimental results show proper working of the IFOG-SMO and the capability for measuring large and small amplitude angular velocities and the expansion of the full scale. This is, to the best of our knowledge, the first time a sliding mode control technique has been employed and evaluated for an interferometric fiber-optic gyroscope. Full article

The increasing demand for image quality in aerospace remote sensing has led to higher performance requirements for inertial stabilization platforms equipped with image sensors, particularly in terms of bandwidth. To achieve wide-bandwidth control in optical stabilization platforms, engineers employ magneto-hydrodynamic (MHD) sensors as key components to enhance system performance because of their wide measurement bandwidth (5–1000 Hz). While MHD sensors offer a wide-frequency response, they are limited by a narrow measuring range and low sensitivity at low frequencies, making them unsuitable as standalone sensors. To address the challenges of over-range measurement and the loss of low-frequency signals, in this study, we developed a soft-switching adaptive Kalman filter method, which enables us to dynamically adjust the fusion weights in the Kalman filter so we can obtain wide-band measurement signals even when the MHD sensor experiences over-range conditions. The proposed method was validated with fusion experiments involving a fiber-optic gyroscope and an MHD sensor; the results demonstrate its ability to expand the sensing bandwidth, regardless of the operating conditions of the MHD sensor. Full article

Inertial navigation systems (INSs) provide autonomous position estimation capabilities independent of global navigation satellite systems (GNSSs). However, the high cost of traditional sensors, such as fiber-optic gyroscopes (FOGs), limits their widespread adoption. In contrast, micro-electromechanical system (MEMS)-based inertial measurement units (IMUs) offer a low-cost alternative; however, their lower accuracy and sensor bias issues, particularly in maritime environments, remain considerable obstacles. This study proposes an improved method for bias estimation by comparing the estimated values from a trajectory generator (TG)-based acceleration and angular-velocity estimation system with actual measurements. Additionally, for X- and Y-axis accelerations, we introduce a method that leverages the correlation between altitude differences derived from an INS/GNSS/gyrocompass (IGG) and those obtained during the TG estimation process to estimate the bias. Simulation datasets from experimental voyages validate the proposed method by evaluating the mean, median, normalized cross-correlation, least squares, and fast Fourier transform (FFT). The Butterworth filter achieved the smallest angular-velocity bias estimation error. For X- and Y-axis acceleration bias, altitude-based estimation achieved differences of 1.2 × 10⁻² m/s² and 1.0 × 10⁻⁴ m/s², respectively, by comparing the input bias using 30 min data. These methods enhance the positioning and attitude estimation accuracy of low-cost IMUs, providing a cost-effective maritime navigation solution. Full article

The ASE (Amplified Spontaneous Emission) light source, based on erbium-doped fiber (EDF), is a broadband light source with advantages such as high power, excellent temperature stability, and low coherent light generation. It is widely used in the field of fiber optic sensing. However, traditional ASE sources suffer from temperature sensitivity and low efficiency, which can compromise the accuracy and stability of the output light’s average wavelength. This study focuses on optimizing the erbium-doped fiber (EDF) to improve the temperature stability and efficiency of the ASE light source. Through simulations, we found that the appropriate doping concentration and length of the EDF are key factors in enhancing the stability and efficiency of the ASE source. Inorganic metal chloride vapor-phase doping combined with an improved chemical vapor deposition process was used to fabricate the erbium-doped fiber, ensuring low background loss, minimal OH⁻ absorption, and uniform distribution of the erbium ions in the core of the fiber. The optimized EDFs were integrated into the ASE source, achieving a power conversion efficiency of 53.6% and a temperature stability of 0.118 ppm/°C within the temperature range of −50 °C to 70 °C. This study offers a practical approach for improving the performance of ASE light sources and advancing the development of high-precision fiber optic sensing technologies. Full article

When using a fiber optic gyroscope as the core measurement element in an inertial navigation system, its work stability and reliability directly affect the accuracy of the navigation system. The modeling and fault diagnosis of the gyroscope is of great significance in ensuring the high accuracy and long endurance of the inertial system. Traditional diagnostic models often encounter challenges in terms of reliability and accuracy, for example, difficulties in feature extraction, high computational cost, and long training time. To address these challenges, this paper proposes a new fault diagnostic model that performs a fault diagnosis of gyroscopes using the enhanced capsule neural network (iCaps NN) optimized by the improved gray wolf algorithm (NIGWO). The wavelet packet transform (WPT) is used to construct a two-dimensional feature vector matrix, and the deep feature extraction module (DFE) is added to extract deep-level information to maximize the fault features. Then, an improved gray wolf algorithm combined with the adaptive algorithm (Adam) is proposed to determine the optimal values of the model parameters, which improves the optimization performance. The dynamic routing mechanism is utilized to greatly reduce the model training time. In this paper, effectiveness experiments were carried out on the simulation dataset and real dataset, respectively; the diagnostic accuracy of the fault diagnosis method in this paper reached 99.41% on the simulation dataset; the loss value in the real dataset converged to 0.005 with the increase in the number of iterations; and the average diagnostic accuracy converged to 95.42%. The results show that the diagnostic accuracy of the NIGWO-iCaps NN model proposed in this paper is improved by 13.51% compared with the traditional diagnostic methods. It effectively confirms that the method in this paper is capable of efficient and accurate fault diagnosis of FOG and has strong generalization ability. Full article

In the last decade, substantial progress has been made to improve the performance of optical gyroscopes for inertial navigation applications in terms of critical parameters such as bias stability, scale factor stability, and angular random walk (ARW). Specifically, resonant fiber optic gyroscopes (RFOGs) have emerged as a viable alternative to widely popular interferometric fiber optic gyroscopes (IFOGs). In a conventional RFOG, a single-wavelength laser source is used to generate counter-propagating waves in a ring resonator, for which the phase difference is measured in terms of the resonant frequency shift to obtain the rotation rate. However, the primary limitation of RFOG performance is the bias drift, which can be attributed to nonreciprocal effects such as Rayleigh backscattering, back-reflections, polarization instabilities, Kerr nonlinearity, and environmental fluctuations. In this paper, we review the challenges and opportunities of achieving performance enhancement in RFOGs. Full article

Since the fiber optic gyroscope (FOG) is rigidly strapped down to the earth’s crust, there are various errors that affect the universal time (UT1) measurements. In this paper, the errors caused by various physical factors and mechanisms are analyzed in detail, with precession and nutation errors being taken into account, and modeling of the observation equations based on precession and nutation error correction is proposed. The mapping relationship with UT1 is established based on this observation equation; after the corresponding error correction and VLBI calibration, the high-accuracy solution of UT1 is finally completed. Through 14-day measurement experiments under a room temperature environment without any vibration isolation and magnetic shielding devices, the error variation of UT1 solution compared with the earth orientation parameter (EOP) 14 C04 data is calculated at less than 3.57 ms, with UT1 solution accuracy improved by 56% compared with the traditional method. These results indicate that this work facilitates the study of giant FOG error modeling and correction, advancing our understanding of errors in giant FOG measurements and improving the accuracy of UT1 solution. Full article

The refractive index change obtained after annealed proton exchange (APE) in lithium niobate (LiNbO₃) crystals depends on both the proton exchange process carried out in hot acid and the structure of the crystals. In devices produced by the APE method, dislocations and lattice defects within the crystal structure are considered to be primary contributors to refractive index discontinuities and waveguide instability. In this study, the effects of pre-annealing LiNbO₃ crystals at 500 °C on multifunctional integrated optical chips (MIOCs) were investigated through interferometric fiber-optic gyroscope (IFOG) system-level tests. It was observed that the pre-annealing process resulted in an improvement in the optical throughput of MIOCs (from %34 to %51) and the temperature-dependent bias drift stability of the IFOG (from 0.031–0.038°/h to 0.012–0.019°/h). The angle random walk (ARW) was measured as 0.0056 deg/√h. Full article

Autonomous Underwater Vehicles (AUVs) are widely used for hydrological monitoring, underwater exploration, and geological surveys. However, AUVs face limitations in underwater navigation due to the high costs associated with Strapdown Inertial Navigation System (SINS) and Doppler Velocity Log (DVL), hindering the development of low-cost vehicles. Micro Electro Mechanical System Inertial Measurement Units (MEMS IMUs) are widely used in industry due to their low cost and can output acceleration and angular velocity, making them suitable as an Attitude Heading Reference System (AHRS) for low-cost vehicles. However, poorly calibrated MEMS IMUs provide an inaccurate angular velocity, leading to rapid drift in orientation. In underwater environments where AUVs cannot use GPS for position correction, this drift can have severe consequences. To address this issue, this paper proposes Underwater Gyros Denoising Net (UGDN), a method based on dilated convolutions and LSTM that learns and extracts the spatiotemporal features of IMU sequences to dynamically compensate for the gyroscope’s angular velocity measurements, reducing attitude and heading errors. In the experimental section of this paper, we deployed this method on a dataset collected from field trials and achieved significant results. The experimental results show that the accuracy of MEMS IMU data denoised by UGDN approaches that of fiber-optic SINS, and when integrated with DVL, it can serve as a low-cost underwater navigation solution. Full article

This paper investigates the mechanism of thermal-induced errors in interferometric fiber optic gyroscopes (IFOGs) caused by temperature changes in a vacuum environment, proposing a method for calculating thermal-induced errors in small fiber coils. Firstly, based on the Shupe effect and the thermal stress caused by temperature changes around the fiber coil, a three-dimensional thermal-induced error model for small fiber coils is established. Secondly, a spatial fiber optic inertial measurement unit (IMU) model is designed using the Creo 3D modeling software (creo 7.0.0). The model is then imported into the Ansys finite element simulation software (ANSYS Workbench 15.0), where a temperature field is applied to the IMU based on actual temperature profiles to obtain the temperature distribution of the fiber coil at different times in a vacuum state. These data are then used in the three-dimensional thermal-induced error model to calculate the thermal-induced error of the FOG. Finally, a thermal vacuum experimental platform is set up to collect temperature variation data from the inertial measurement components. The experimental data are compared with the three-dimensional error model proposed in this paper as well as traditional error models. The root mean square error is approximately 33% lower than that of traditional error calculation methods, which also proves the theoretical accuracy. Full article

The pipe jacking guidance system based on a fiber optic gyroscope (FOG) has gained extensive attention due to its high degree of safety and autonomy. However, all inertial guidance systems have accumulative errors over time. The zero-velocity update (ZUPT) algorithm is an effective error compensation method, but accurately distinguishing between moving and stationary states in slow pipe jacking operations is a major challenge. To address this challenge, a “MV + ARE + SHOE” three-conditional zero-velocity detection (TCZVD) algorithm for the fiber optic gyroscope inertial navigation system (FOG-INS) is designed. Firstly, a Kalman filter model based on ZUPT is established. Secondly, the TCZVD algorithm, which combines the moving variance of acceleration (MV), angular rate energy (ARE), and stance hypothesis optimal estimation (SHOE), is proposed. Finally, experiments are conducted, and the results indicate that the proposed algorithm achieves a zero-velocity detection accuracy of 99.18% and can reduce positioning error to less than 2% of the total distance. Furthermore, the applicability of the proposed algorithm in the practical working environment is confirmed through on-site experiments. The results demonstrate that this method can effectively suppress the accumulated error of the inertial guidance system and improve the positioning accuracy of pipe jacking. It provides a robust and reliable solution for practical engineering challenges. Therefore, this study will contribute to the development of pipe jacking automatic guidance technology. Full article

The current new type of inertial navigation system, including rotating inertial navigation systems and three-autonomy inertial navigation systems, has been increasingly widely applied. Benefited by the rotating mechanisms of these inertial navigation systems, alignment accuracy can be significantly enhanced by implementing IMU (Inertial Measurement Unit) rotation during the alignment process. The principle of suppressing initial alignment errors using rotational modulation technology was investigated, and the impact of various component error terms on alignment accuracy of IMU during rotation was analyzed. A corresponding error suppression scheme was designed to overcome the shortcoming of the significant scale factor error of fiber optic gyroscopes, and the research content of this paper is validated through corresponding simulations and experiments. The results indicate that the designed alignment scheme can effectively suppress the gyro scale factor error introduced by angular motion and improve alignment accuracy. Full article