Performance analysis of the fiber coils combining hybrid polarization-maintaining fiber designs and symmetrical winding patterns.

Research on the performance of polarization-maintaining fiber (PMF) for fiber coils is significant for the precision improvement of an interferometric fiber optic gyroscope (IFOG) working in harsh environments. In this paper, we firstly report analytical models of the fiber polarization theory and present two types of hybrid PMF structures by a collaboration of geometry and stress effects: a Panda-type horizontal-elliptical core PMF (Panda-type HE-PMF) based on a superposition of geometry and stress, and a Panda-type longitudinal-elliptical core PMF (Panda-type LE-PMF) with geometry offset stress effect, achieving enhanced and suppressed modal performance by adjusting geometric anisotropy of elliptical-core in different directions. Then, the influence mechanisms of the geometric birefringence on the modal performance of both PMFs as the variation of fiber structural parameters are investigated via numerical simulations to determine the target fiber designs. The other significant attribute, including effective mode area (Aeff), nonlinear coefficient (γ), and chromatic dispersion (D), and their tolerance to PMF parameter fluctuations are also evaluated. Finally, both target PMFs with structural optimization are practically fabricated and wound into four fiber coils with quadrupolar (QAD) and 16-polar symmetrical winding patterns, respectively. The polarization ability and thermal performance are further demonstrated by experiments conducted on both PMFs, wound fiber coils, and built IFOGs under static and dynamic environments (over a wide temperature range of -40 °C to 70 °C), and compared with a conventional PMF. The testing results suggest that designed HE-PMF coils both achieve high birefringence, static extinction ratio (ER) values of up to 30.80 dB and 31.93 dB, respectively, corresponding to an almost one-fold increase over conventional coils. Remarkably, the ER property of the HE-PMF coil by combining this HE-PMF design and a 16-polar winding pattern consistently remains above 29.5 dB with a minimal fluctuation in ER of only 3.0 dB across the entire variable temperature conditions. The bias stability of the IFOG assembled with this coil is strongly enhanced to 0.0019 °/h and 0.082 °/h under static and dynamic conditions, respectively, which is a significant improvement over conventional coils of 0.136 °/h. Also, the static angle random walk performance of the improved IFOG is reduced to 0.000624 °/√h. In contrast, the LE-PMF as a comparison is shown to limited polarization characteristics with a low birefringence and ER due to the suppression effect of the geometric birefringence, and the applied IFOG output also exhibits larger drift, indicating a poor thermal ability. Experimental results show great agreement with theoretical analysis and numerical simulations, confirming the validity of design principles. The advances in both designs are instructive for the engineering applications of PMFs for IFOGs and for improving the accuracy of fiber sensors.

Variational Bayesian-Based Improved Maximum Mixture Correntropy Kalman Filter for Non-Gaussian Noise.

The maximum correntropy Kalman filter (MCKF) is an effective algorithm that was proposed to solve the non-Gaussian filtering problem for linear systems. Compared with the original Kalman filter (KF), the MCKF is a sub-optimal filter with Gaussian correntropy objective function, which has been demonstrated to have excellent robustness to non-Gaussian noise. However, the performance of MCKF is affected by its kernel bandwidth parameter, and a constant kernel bandwidth may lead to severe accuracy degradation in non-stationary noises. In order to solve this problem, the mixture correntropy method is further explored in this work, and an improved maximum mixture correntropy KF (IMMCKF) is proposed. By derivation, the random variables that obey Beta-Bernoulli distribution are taken as intermediate parameters, and a new hierarchical Gaussian state-space model was established. Finally, the unknown mixing probability and state estimation vector at each moment are inferred via a variational Bayesian approach, which provides an effective solution to improve the applicability of MCKFs in non-stationary noises. Performance evaluations demonstrate that the proposed filter significantly improves the existing MCKFs in non-stationary noises.

High extinction ratio elliptical core Panda-type polarization-maintaining fiber coil.

The polarization-maintaining performance of the traditional Panda-type polarization-maintaining fiber (PMF) coil is significantly affected by winding stress and temperature. Here, we present an elliptical core Panda-type PMF coil based on a fiber that employs both geometric and stress birefringence. The extinction ratio of the elliptical core PMF coil was found to be 20.13 dB at a temperature of 20°C, corresponding to an increase of 3.71 dB compared to the traditional Panda-type PMF coil. In addition, results from distributed polarization cross talk and gyroscope output tests also revealed a low sensitivity of the fiber to stress caused by the winding process and temperature. In summary, the proposed fiber coil has better polarization-maintaining ability compared to conventional coil and is promising for applications in high-precision optical fiber sensors.

Curvefusion-A Method for Combining Estimated Trajectories with Applications to SLAM and Time-Calibration.

Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.

Integrate Point-Cloud Segmentation with 3D LiDAR Scan-Matching for Mobile Robot Localization and Mapping.

Localization and mapping are key requirements for autonomous mobile systems to perform navigation and interaction tasks. Iterative Closest Point (ICP) is widely applied for LiDAR scan-matching in the robotic community. In addition, the standard ICP algorithm only considers geometric information when iteratively searching for the nearest point. However, ICP individually cannot achieve accurate point-cloud registration performance in challenging environments such as dynamic environments and highways. Moreover, the computation of searching for the closest points is an expensive step in the ICP algorithm, which is limited to meet real-time requirements, especially when dealing with large-scale point-cloud data. In this paper, we propose a segment-based scan-matching framework for six degree-of-freedom pose estimation and mapping. The LiDAR generates a large number of ground points when scanning, but many of these points are useless and increase the burden of subsequent processing. To address this problem, we first apply an image-based ground-point extraction method to filter out noise and ground points. The point cloud after removing the ground points is then segmented into disjoint sets. After this step, a standard point-to-point ICP is applied into to calculate the six degree-of-freedom transformation between consecutive scans. Furthermore, once closed loops are detected in the environment, a 6D graph-optimization algorithm for global relaxation (6D simultaneous localization and mapping (SLAM)) is employed. Experiments based on publicly available KITTI datasets show that our method requires less runtime while at the same time achieves higher pose estimation accuracy compared with the standard ICP method and its variants.

Temperature Dependence of Faraday Effect-Induced Bias Error in a Fiber Optic Gyroscope.

Improving the performance of interferometric fiber optic gyroscope (IFOG) in harsh environments, such as magnetic field and temperature field variation, is necessary for its practical applications. This paper presents an investigation of Faraday effect-induced bias error of IFOG under varying temperature. Jones matrix method is utilized to formulize the temperature dependence of Faraday effect-induced bias error. Theoretical results show that the Faraday effect-induced bias error changes with the temperature in the non-skeleton polarization maintaining (PM) fiber coil. This phenomenon is caused by the temperature dependence of linear birefringence and Verdet constant of PM fiber. Particularly, Faraday effect-induced bias errors of two polarizations always have opposite signs that can be compensated optically regardless of the changes of the temperature. Two experiments with a 1000 m non-skeleton PM fiber coil are performed, and the experimental results support these theoretical predictions. This study is promising for improving the bias stability of IFOG.

A Thermal Performance Analysis and Comparison of Fiber Coils with the D-CYL Winding and QAD Winding Methods.

The thermal performance under variable temperature conditions of fiber coils with double-cylinder (D-CYL) and quadrupolar (QAD) winding methods is comparatively analyzed. Simulation by the finite element method (FEM) is done to calculate the temperature distribution and the thermal-induced phase shift errors in the fiber coils. Simulation results reveal that D-CYL fiber coil itself has fragile performance when it experiences an axially asymmetrical temperature gradient. However, the axial fragility performance could be improved when the D-CYL coil meshes with a heat-off spool. Through further simulations we find that once the D-CYL coil is provided with an axially symmetrical temperature environment, the thermal performance of fiber coils with the D-CYL winding method is better than that with the QAD winding method under the same variable temperature conditions. This valuable discovery is verified by two experiments. The D-CYL winding method is thus promising to overcome the temperature fragility of interferometric fiber optic gyroscopes (IFOGs).

Design of a pentagonal photonic crystal fiber with high birefringence and large flattened negative dispersion.

Novel pentagonal photonic crystal fiber with high birefringence, large flattened negative dispersion, and high nonlinearity is proposed. The dispersion and birefringence properties of this structure are simulated and analyzed numerically based on the full vector finite element method (FEM). Numerical results indicate that the fiber obtains a large average dispersion of -611.9 ps/nm/km over 1,460-1,625 nm and -474 ps/nm/km over 1425-1675 nm wavelength bands for two kinds of optimized designs, respectively. In addition, the proposed PCF shows a high birefringence of 1.67×10-2 and 1.75×10-2 at the operating wavelength of 1550 nm. Moreover, the influence of the possible variation in the parameters during the fabrication process on the dispersion and birefringence properties is studied. The proposed PCF would have important applications in polarization maintaining transmission systems, residual dispersion compensation, supercontinuum generation, and the design of widely tunable wavelength converters based on four-wave mixing.

Design of highly nonlinear photonic crystal fibers with flattened chromatic dispersion.

A novel (to our knowledge) type of photonic crystal fiber (PCF) with high nonlinearity and flattened dispersion is proposed. The propagation characteristics of chromatic dispersion, effective area, and nonlinearity are studied numerically by using the full-vector finite element method. Several PCF designs with high nonlinearity and nearly zero flattened dispersion or broadband flattened, and even ultraflattened, dispersion over different wavelength bands are obtained by optimizing the structural parameters. One optimized PCF has a nearly zero ultraflattened dispersion of 2.3 ps/(nm·km) with a dispersion variation of 0.2 ps/(nm·km) over the C+L+U wavelength bands. In addition, the dispersion slope and nonlinear coefficient at 1.55 µm can be up to 2.2×10(-3) ps/nm(2)·km and 33.2 W(-1)·km(-1), respectively. The designs proposed in this paper have bright prospects for applications in all-optical format conversion, supercontinuum generation, optical wavelength conversion, and many other fields.