Search Results (99)

Fiber-optic gyroscopes (FOGs) have become one of the most important elements of modern inertial navigation systems due to their high accuracy, reliability, and independence from external signals such as satellite navigation. This review analyzes and discusses the key FOG architectures: interferometric (IFOG), resonant (RFOG), digital (DFOG), and hybrid (HFOG). The concepts of their functioning, structural features, and the main advantages and limitations of each architecture are examined. Particular focus is placed on advanced signal-processing and error-compensation algorithms, including filtering techniques, noise suppression, mitigation of thermal and mechanical drifts, and emerging machine learning (ML) based approaches. The analysis of these architectures is carried out in terms of major parameters that determine accuracy, robustness, and miniaturization potential. Various applications of FOGs in space systems, ground platforms, marine and underwater navigation, aviation, and scientific research are also being considered. Finally, the latest development trends are summarized, with a particular focus on miniaturization, integration with additional sensors, and the introduction of digital and AI-driven solutions, aimed at achieving higher accuracy, long-term stability, and resilience to real-world disturbances. Full article

Polarization-induced noise remains a primary source of bias drift, fundamentally limiting the performance of hollow-core photonic-crystal fiber optic gyroscopes (HC-RFOGs). To overcome this limitation, we propose and demonstrate a novel resonator design with an intrinsically high polarization extinction ratio (PER). The resonator’s core innovation is a four-port coupler architecture that strategically integrates a pair of polarization beam splitters (PBSs) with conventional beam splitters (BSs). This configuration functions as a high-fidelity polarization filter, suppressing undesired polarization states for both clockwise and counter-clockwise propagating light within the hollow-core fiber loop. Our theoretical model predicts that the effective in-resonator PER can exceed 48 dB, which is sufficient to mitigate polarization-related errors for tactical-grade applications. Experimental validation of a prototype HC-RFOG incorporating this resonator yields a bias instability of 1.34°/h and an angle random walk (ARW) of $0.078°/\sqrt{\mathrm{h}}$ (with a 200 s averaging time). These results confirm that engineering a high-polarization-extinction-ratio resonator (HPERR) is a potent and direct pathway to substantially reducing polarization noise and advancing the performance of HC-RFOGs. Full article

This study investigates multi-level coupled dynamic issues in near-space balloon-borne astronomical observation platforms subjected to multi-source disturbances, proposing an integrated azimuth pointing control scheme combining unified modeling with composite control strategies. A nonlinear dynamic model is established to characterize inertial coupling effects between the gondola system and secondary gimbal platform. The velocity-loop feedback mechanism utilizing fiber-optic gyroscopes achieves base disturbance decoupling, while an adaptive fuzzy PID controller enhances position-loop disturbance rejection capabilities. A gain adaptation strategy coordinates hierarchical control dynamics, complemented by anti-windup constraints safeguarding actuator operational boundaries. Simulation verifications confirm the exceptional high-precision pointing capability and robust stability under representative wind disturbances and sensor noise conditions. The system maintains a superior control performance across parameter perturbation scenarios, demonstrating consistent operational reliability. This study provides an innovative technical paradigm for precision observation missions in near space. Full article

In this paper, a low loss and high polarization-maintaining single-mode hollow-core anti-resonant fiber (PM-HC-ARF) is designed. The elliptical core in the PM-HC-ARF is formed by strategically enlarging selected cladding air holes along the y-axis. Additionally, the variations in the wall thickness in both the x and y directions generate the distinct surface modes. By simultaneously employing an elliptical core and asymmetric core-wall thickness, we enhance the phase birefringence. Theoretical analysis results show that the proposed PM-HC-ARF achieves a transmission loss of 0.00082 dB/m at wavelength 1450 nm, along with a birefringence of 1.38 × 10⁻⁴; it demonstrates CL levels an order of magnitude below state-of-the-art polarization-maintaining HC-ARFs. Moreover, within the S+C+L+U communication bands, it achieves a bandwidth exceeding 380 nm (1420–1800 nm) while maintaining a birefringence of greater than 1.45 × 10⁻⁴. In particular, this PM-HC-ARF demonstrates a maximum higher-order mode extinction ratio of over 32,070; the single-mode transmission characteristics are excellent, along with exceptional bending resistance characteristics. When the bending radius exceeds 3 cm, the impacts on the loss and birefringence are negligible; this also demonstrates that the fiber structure shows good robustness when subjected to harsh environment interference. The proposed PM-HC-ARF is believed to have important applications in fiber optic gyroscopes, optical amplifiers, and hydrophones. Full article

In high-precision inertial navigation systems, suppressing the random errors of a fiber-optic gyroscope is of great importance. However, the traditional rule-based autoregressive moving average modeling method, when applied in Kalman filtering considering colored noise, presents inherent disadvantages in principle, including inaccurate state equations and difficulties in state dimension expansion. To this end, the noise characteristics in the fiber-optic gyroscope signal are first deeply analyzed, a random error model form is clarified, and a new model-order determination criterion is proposed to achieve the high-precision modeling of random errors. Then, based on the effective suppression of the angle random walk error of the fiber-optic gyroscope, and combined with the linear system equation of its colored noise, an adaptive Kalman filter based on noise-spectrum information decoupling is designed. This breaks through the principled limitations of traditional methods in suppressing colored noise and provides a scheme for modeling and suppressing fiber-optic gyroscope random errors under static conditions. Experimental results show that, compared with existing methods, the initial alignment accuracy of the proposed method based on 5 min data of fiber-strapdown inertial navigation is improved by an average of 48%. Full article

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