Rotational Inertial Navigation System Research Articles

A Novel Error Modulation Rotation Scheme for Dual-Axis Rotational Inertial Navigation System

Abstract Dual-axis rotational inertial navigation system (RINS) can effectively suppress the error accumulation of inertial navigation system, thereby improve the long-term navigation accuracy through rotating inertial measurement unit (IMU) according to corresponding rotation scheme. The navigation accuracy of RINS is predominantly contingent on the IMU rotation scheme. A reasonable rotation scheme can effectively attenuate or even obviate the navigation errors stemming from IMU errors, whereas an ill-considered scheme may lead to swift divergence of navigation errors. In this paper, the principle of IMU errors suppression is meticulously analyzed during rotation. By comprehensively evaluating the impact of individual IMU errors on navigation accuracy alongside their corresponding error modulation characteristics, a novel 32-position rotation scheme is devised. The proposed scheme demonstrates a notable capacity to minimize the adverse effects of IMU errors on navigation accuracy and to enhance error suppression efficacy within a modulation cycle. Meanwhile, the long-endurance navigation accuracy of RINS is substantially enhanced. The efficacy of the 32-position scheme posited herein is empirically substantiated through a 24-hour simulation and navigation experiment.

Research on propagation mechanism for gyro installation error of dual-axis rotational inertial navigation system in UAV coordinated U-turn

With the development of rotation modulation, dual-axis rotational inertial navigation systems (RINS) are gradually applied to unmanned aerial vehicles (UAV) to cope with the increasing prominence of GNSS spoofing. The urgent need for autonomous navigation has promoted a popular topic of improving RINS accuracy. However, few have delved into error excitation and propagation from the perspective of carrier maneuvering. Starting from the error phenomena in a UAV flight experiment, this paper studies the error propagation mechanism of gyro installation error in dual-axis RINS under coordinated U-turn. Specifically, the coupling between the control strategies of the dual-axis RINS and the UAV typical maneuvers is revealed. On this basis, the error propagation mechanism for the gyro installation error is derived. Simulations validate the analyzed theory and illustrate the severity of this error source through flight and compensation experiments, where regular identification in highly dynamic applications becomes crucial to improve navigation accuracy.

An autonomous and high-accuracy gravity disturbance compensation scheme for rotary inertial navigation system

Abstract With the increasing demands for long-endurance and high-accuracy inertial navigation system (INS), gravity disturbance has been identified as one of the major error sources with decisive effects on the performance of INS. To address the problem, this paper proposes an autonomous and high-accuracy gravity disturbance compensation scheme for rotary INS (RINS). The high-accuracy velocity measured by the laser Doppler velocimeter is fused with the angular velocity measured by the gyroscope to obtain navigation parameters, such as velocity, position and attitude, that are not affected by gravity disturbance. The navigation parameters independent of gravity disturbance are matched with the gravity disturbance-related navigation parameters output by RINS, and a measurement model containing gravity disturbance information is obtained. Besides, the intrinsic coupling relationship between gravity disturbance, gravity disturbance rate and gravity disturbance gradient is revealed, and a state-space model is established to accurately reflect the time-varying characteristics of gravity disturbance. Furthermore, the gravity disturbance is estimated and compensated in real-time through the optimal estimation algorithm. The results of vehicle experiments indicate that the gravity disturbance estimation precision of the proposed scheme is better than 2.15 mGal (1σ), and its horizontal position accuracy is better than 50 m at a driving distance of 80 km.

A rapid alignment method for high-precision rotational INS within group affine

In this paper, a rapid alignment method for high-precision rotation inertial navigation system (RINS) within group affine is proposed based on the Lie group theory. The proposed method can effectively solve the ultimate contradiction of initial alignment: speed and accuracy. It meets the requirements of fast response and high accuracy of high-precision RINS. We abandon the conventional coarse alignment + fine alignment scheme and realize a linear Kalman filter alignment method with arbitrarily initial misalignment based on the Earth-centered Earth-fixed frame RINS mechanization and the Lie group theory. Subsequently, considering the error characteristics of RINS two-position alignment, new left-invariant error model and observation model satisfying the group affine property are constructed to improve the convergence speed and accuracy of alignment. It is verified that the method can complete the initial alignment of arbitrary large misalignment and reach the ultimate accuracy in a short time, and the land vehicle navigation test shows that the proposed alignment method can complete the initial alignment of arbitrary misalignment in 5 min under the swaying disturbance and achieve better pure inertial navigation accuracy compared with the traditional scheme.

A self-calibration method for temperature errors of non-orthogonal angles between gimbals in rotational inertial navigation system

The rotational inertial navigation system (RINS) employs a rotating modulation technique by introducing rotation gimbals, thereby enhancing accuracy of the RINS in position and velocity estimation. Furthermore, the rotation gimbals provide the self-calibration ability in the RINS. However, it introduces new sources of error, such as non-orthogonal angles between gimbals, which result in inaccuracies in attitude outputs and thus require precise calibration and compensation. Previous research has largely overlooked the influence of temperature on non-orthogonal angles and the calibration accuracy are susceptible to various factors. In this paper, we discuss the causes of temperature-induced errors in non-orthogonal angles and their impact on attitude estimation, and a self-calibration method based on outputs from fiber optic gyroscopes and optical angle encoders is proposed, showing good repeatability by using periodic averaging. The rapid rotation scheme adopted is suitable for calibrating temperature errors during system operation and a temperature-stabilized chamber is not required. The results of navigation experiments validate the effectiveness of the calibration and compensation method. After compensating the temperature errors of non-orthogonal angles, we can see a decrease in the amplitude of attitude output oscillation from 80″ to less than 10″.

Anti-disturbance self-alignment method for dual-axis rotational inertial navigation system under marine mooring conditions

Under the marine mooring conditions, the inertial navigation system (INS) is often disturbed by angular and linear motions, and it is difficult to perform self-alignment with high accuracy. To solve this problem, an anti-disturbance self-alignment method for dual-axis rotational INS is proposed. The method transforms the self-alignment problem into an attitude matrix solving problem, so as to deal with the disturbance of angular motion. By analyzing the relationship between the amount of measurement data and the accuracy of self-alignment, the optimal integration time is designed and a partial integral algorithm is proposed. Furthermore, the influence of initial velocity error on self-alignment under linear motion disturbance conditions is analyzed, and an initial velocity compensation method is proposed. Experimental results show that high-accuracy self-alignment can be achieved using the proposed method under the joint disturbance of angular and linear motions.

A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors.

In order to ensure that dual-axis rotational inertial navigation systems (RINSs) maintain a high level of accuracy over the long term, there is a demand for periodic calibration during their service life. Traditional calibration methods for inertial measurement units (IMUs) involve removing the IMU from the equipment, which is a laborious and time-consuming process. Reinstalling the IMU after calibration may introduce new installation errors. This paper focuses on dual-axis rotational inertial navigation systems and presents a system-level self-calibration method based on invariant errors, enabling high-precision automated calibration without the need for equipment disassembly. First, navigation parameter errors in the inertial frame are expressed as invariant errors. This allows the corresponding error models to estimate initial attitude even more rapidly and accurately in cases of extreme misalignment, eliminating the need for coarse alignment. Next, by utilizing the output of a gimbal mechanism, angular velocity constraint equations are established, and the backtracking navigation is introduced to reuse sensor data, thereby reducing the calibration time. Finally, a rotation scheme for the IMU is designed to ensure that all errors are observable. The observability of the system is analyzed based on a piecewise constant system method and singular value decomposition (SVD) observability analysis. The simulation and experimental results demonstrate that this method can effectively estimate IMU errors and installation errors related to the rotation axis within 12 min, and the estimated error is less than 4%. After using this method to compensate for the calibration error, the velocity and position accuracies of a RINS are significantly improved.

Fast Self-Alignment and Self-Calibration Method for Rotational Inertial Navigation System Based on Environment Function Matrix

Fast Self-Alignment and Self-Calibration Method for Rotational Inertial Navigation System Based on Environment Function Matrix

An Encoder-Based Relative Attitude Observation Method for Self-Calibration in Dual-Axis RINS

This study investigates an encoder-based relative attitude observation method for self-calibration in dual-axis rotational inertial navigation system (RINS). First, the calibration error of the gyroscope parameters caused by the velocity and position observations in systematic calibration is analyzed. Second, a relative attitude observation method utilizing photoelectric encoders for gyroscope parameters estimation is proposed. We apply the proposed method in our designed dual-axis RINS to verify its effectiveness in this work. Experimental results show that the calibration accuracy of the gyroscope can be improved to 0.0005 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^ \circ /h$</tex-math></inline-formula> in bias, and 0.98 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ppm$</tex-math></inline-formula> in scale factor using the proposed method. The proposed self-calibration method can be utilized as a high-accuracy self-calibration method in dual-axis RINS when the vehicle is in static condition.

A multi-axis alternating continuous rotation scheme for tri-axis rotational inertial navigation system (RINS) with fiber optic gyro

Benefiting from the rotational modulation technique and the gimbal structure, rotational inertial navigation system (RINS) can improve navigation accuracy by about one order of magnitude compared with the strap-down inertial navigation system (SINS). By continuously rotating around a fixed axis, the constant and slow variability errors perpendicular to the direction of the rotation axis can be effectively restrained while the errors in the direction of the rotation axis cannot be suppressed. Therefore, a multi-axis rotation scheme needs to be designed. Meantime, the fiber optic gyro (FOG), as a very popular inertial device, is well suited for RINS but has a larger scale factor error and poorer stability than the laser gyro; thus, it is not suitable to flip the inertial measurement unit (IMU) around the horizontal axis too much in the rotation scheme to avoid the rapid accumulation of horizontal misalignment angle. Accordingly, we propose a multi-axis alternating continuous rotation scheme for tri-axis RINS with FOG. During the navigation process, the inner, middle and outer gimbals rotate forward and reverse in sequence. The IMU rotates continuously in the three-axis direction can effectively suppress the effects of constant and slow-varying errors and also avoid the large velocity errors oscillation caused by flipping the IMU. The simulations and navigation tests show that the multi-axis alternating continuous rotation scheme can achieve navigation accuracy comparable to the multi-position rotation scheme and reduce the oscillation of velocity errors, which has important research significance and engineering value for the research of RINS with FOG.

An Improved Rotational Modulation Scheme for Tri-Axis Rotational Inertial Navigation System (RINS) with Fiber Optic Gyro (FOG)

An optimized scheme can improve the navigation accuracy of RINS without changing the inertial devices. In the multi-position stop scheme, the IMU remains stationary for most of the time, which makes motor control easier. However, the installation errors and the scale factor errors of FOG can cause platform misalignment after a certain angle of rotation around the horizontal axis, resulting in a velocity error. Continuous rotation can suppress time-varying errors better, which is of particular importance for FOG, but it can also increase the sawtooth error of the navigation output, and the error in the direction of rotation cannot be offset. To integrate the advantages of both rotation schemes, we propose an improved rotational modulation scheme for tri-axis RINS. In this scheme, the inner gimbal rotates in a two-position and four-order manner, while the middle and outer gimbals rotate continuously in the order of forward-reverse-reverse-forward. Simulation and navigation test results demonstrate that this improved rotational modulation scheme can effectively improve navigation accuracy by 50% and 25% compared with continuous rotation around the azimuth axis and a 16-position scheme with the same inertial devices, which is of great importance for RINS with FOG.

Alignment scheme optimization when gyro accuracy inconsistency for inertial navigation system

Rotation modulation technology can average out constant errors in fiber optic gyro (FOG) rotational inertial navigation system (RINS). As a result, angle random walk (ARW) of FOGs plays a significant role in the precision of initial alignment. Using different gyros as horizontal gyros gradually transitioned from theory to practical application with the advancement of design philosophy. The theoretical formula between azimuth alignment accuracy and random walk coefficients (RWCs) of two horizontal gyros is deduced in this paper. A completely new multiple rotations and stationary alignment scheme is suggested. A recursive least-squares filter with azimuth variation in body reference frame and accelerometer outputs in navigation frame as measurements is constructed. The efficiency of this method is demonstrated through simulation and experimentation. The findings demonstrate that using this formula and alignment scheme, azimuth alignment accuracy could be greatly increased, which can be improved by 10.85% compared to common continuous rotation alignment scheme.

A Combination Scheme of Pure Strapdown and Dual-Axis Rotation Inertial Navigation Systems

Compared with the strapdown inertial navigation system (SINS), the rotation strapdown inertial navigation system (RSINS) can effectively improve the accuracy of navigation information, but rotational modulation also leads to an increase in the oscillation frequency of attitude errors. In this paper, a dual-inertial navigation scheme that combines the strapdown inertial navigation system and the dual-axis rotation inertial navigation system is proposed, which can effectively improve the attitude error accuracy in the horizontal direction by using the high-position information of the rotation inertial navigation system and the stability characteristics of the attitude error of the strapdown inertial navigation system. Firstly, the error characteristics of the strapdown inertial navigation system and the rotation strapdown inertial navigation system are analyzed, and then the combination scheme and Kalman filter are designed according to the error characteristics, and finally, the simulation experiment shows that the pitch angle error of the dual inertial navigation system is reduced by more than 35% and the roll angle error is reduced by more than 45% compared with the rotation strapdown inertial navigation system. Therefore, the combination scheme of double inertial navigation proposed in this paper can further reduce the attitude error of the rotation strapdown inertial navigation system, and at the same time, the two sets of inertial navigation systems can also enhance the reliability of ship navigation.

A Fast Continuous Self-Calibration Method for FOG Rotational Inertial Navigation System Based on Invariant Extended Kalman Filter

For a given device, the rapidity and accuracy of device error coefficient calibration and attitude alignment of the rotational inertial navigation system mainly depend on the convergence rate of the nonlinear filtering algorithm. The traditional extended Kalman filter method has no theoretical convergence guarantee for nonlinear systems and requires a long time in the actual calibration process. Since the attitude is subject to the 3-D rotation transformation group, the error transfer equation can be better linearized by defining the error on the lie group to use the new observation information fully. This article proposes a primary method of using the invariant extended Kalman filter to carry out an inertial navigation system. In the continuous rotation of the framework, the accelerometer, gyroscope, and framework angle are used to calibrate the error coefficient of the accelerometer and gyroscope and estimate the base alignment error angle. Simulation and experiment results show that the proposed method can accomplish alignment and calibration in 10 min under a large initial attitude error.

Self-Calibration Method for the Errors of Dual-Axis Turntable in Redundant Rotational Inertial Navigation System

Attitude measurement is an important capability of a redundant rotational inertial navigation system (RRINS). The attitude of RRINS is converted from the attitude of the redundant inertial measurement unit (RIMU) using a turntable. The attitude measurement accuracy of RRINS is reduced greatly by turntable errors because the turntable is rotated frequently when the RRINS is working. Therefore, it is important to calibrate the turntable errors for improving the attitude measurement accuracy of RRINS. In this study, a self-calibration method for the errors of a dual-axis turntable in RRINS is proposed. First, an error model of the dual-axis turntable is established, and the influence of turntable errors on RRINS attitude measurement is analyzed. Second, a self-calibration method, including rotation scheme, numerical algorithm (NA) errors calculation, and fruit fly optimization algorithm (FOA) errors estimation, is proposed. The influence of Earth’s rotational rate and gyroscope biases is eliminated during calibration using the designed rotation scheme, NA calculates the errors directly when they are minor angles, and FOA estimates the errors whether they are minor or large angles. The simulations and experiment results show that the proposed method can improve the attitude measurement accuracy of RRINS.

A Dual-Axis Rotation Scheme for Redundant Rotational Inertial Navigation System

A redundant rotational inertial navigation system (RRINS) comprises a redundant inertial measurement unit (RIMU) and a turntable for improving reliability and navigation accuracy. Because of the multi-sensor configuration, the RIMU has a more complex error model compared with the traditional orthogonal inertial measurement unit (IMU). Therefore, the RIMU-based rotation scheme cannot simply replicate the traditional IMU-based rotation scheme. In this study, a dual-axis rotation scheme for RIMU characteristics is proposed. First, the error model of the RIMU was established, and the error compensation of RIMU caused by rotation was analyzed. Second, the principles of rotation axis switching and reciprocating rotation were summarized, and a dual-axis rotation scheme was designed by these principles. Finally, the rotation scheme was applied to an RRINS prototype consisting of RIMU (four fiber optic gyroscopes + four quartz accelerometers) and a dual-axis turntable, and then simulations and experiments were performed. The results of the simulations and experiments show that the positioning accuracy of RRINS can be obviously improved by using the proposed rotation scheme.

Research on a High-Precision Measurement Algorithm Using FOG-Based Single-Axis RINS for Core Drilling

It is much important for core drilling to measure the orientation and trajectory of the drill bit precisely. Presently, with the higher and higher accuracy requirements of orientation and positioning, the utilization of inertial navigation system, especially the use of fiber optic gyroscope (FOG), has become a general trend. However, the realization of high precision and small size simultaneously is still a difficult challenge. In this paper, a FOG-based single-axis rotational inertial navigation system (RINS) instrument was used to suppress the inertial sensor errors automatically through rotation modulation technology. Based on the limited movement of the drill bit in lateral and vertical directions, this paper proposed a new dead reckoning (DR) algorithm which performed much better than normal inertial navigation algorithm due to the reduction of error sources. But the actual accuracy of DR algorithm was affected by the installation errors between the axes of the instrument and the pipeline. Therefore, this paper further proposed a new and practical calibration method of the installation errors to improve the accuracy of DR algorithm. To verify the rationality and the validity of the algorithm, the simulations and semi-physics simulation experiments were conducted under laboratory conditions. The results showed that the proposed DR algorithm with installation errors corrected could reach a high positioning accuracy of 0.5% utilizing FOGs with a drift of 0.015°/h. This study provided an innovative solution for high positioning precision based on a small-sized and low-cost RINS instrument in core drilling.

Analysis of Gyro Bias Depending on the Position of Inertial Measurement Unit in Rotational Inertial Navigation Systems.

In this paper, a calibration method for gyro bias that changes depending on the position of the IMU (inertial measurement unit) is proposed to improve the navigation performance of RLG-based RINS (ring-laser-gyro-based rotational inertial navigation system). RINS is a navigation device that compensates for the inertial sensor errors by utilizing the rotation of the IMU. In previous studies, the rotation scheme of the IMU is designed assuming that inertial sensor errors are not affected by position of the IMU. However, changes in temperature distribution, direction of gravity, and dithering according to the rotation of the IMU affect the inertial sensor errors, such as gyro bias. These errors could degrade the long-term navigation performance of RLG-based RINS. To deal with this problem, this paper proposed a compensation method of the gyro bias that changes depending on the position of the IMU. First, RINS is reviewed using a dual-axis 16-position rotation scheme and RLG. Next, the attitude error of RLG-based RINS is derived utilizing navigation equations. The effect of the gyro bias change caused by the change in the IMU attitude for the navigation performance of RINS is analyzed based on navigation equations and simulations. Finally, system-level indirect calibrations for the Z-axis up position and Z-axis down position are performed to calculate the gyro bias change caused by the IMU attitude. The accuracy of the proposed calibration method is verified by long-term navigation test. The test results show that the proposed calibration method improves the navigation performance of RINS compared with the conventional calibration method.

Analysis and compensation of residual gyro drifts on azimuth alignment accuracy in the RINS

The rotational inertial navigation system (INS) uses rotational alignment to improve azimuth alignment accuracy significantly. However, due to the existence of magnetic drifts in the fiber optic gyro, under the comprehensive influence of outside conditions, there will be residual drifts that cannot be averaged out along the body frame or the geographic frame, which will have a significant impact on azimuth alignment accuracy. An innovative and effective calibration compensation strategy is proposed by analyzing the generation mechanism of residual drifts and their influence on alignment accuracy, which can significantly improve azimuth alignment accuracy. With the aid of a high-precision total station, the experimental results of initial alignment in four directions show that the accuracy of azimuth alignment is improved from to by compensating residual drifts, which has significant theoretical significance and practical value in engineering applications for improving the overall performance of the INS.

An Improved System-Level Calibration Scheme for Rotational Inertial Navigation Systems.

The system-level calibration technology of rotational inertial navigation is one of the main methods to improve the accuracy of inertial navigation, and the design of the calibration scheme is the key to calibration technology. By the establishment of the error model of inertial navigation system, a 30-position calibration scheme is designed in this study. Based on the 30-dimensional Kalman filter, the constant errors, scale factor errors and installation error of gyroscope and accelerometer are identified. Comparing the traditional schemes and the 30-position scheme with the simulation experiment, the observability of the 30-position scheme is higher, the residual error of the estimated sensor is smaller and the navigation positioning accuracy after the estimated inertial sensor error parameter compensation is higher, which verifies the feasibility of the 30-position scheme. Finally, the measured experiment uses the 30-position scheme to estimate the error of a certain type of IMU sensor, and the calibration curve of the error parameter is well converged before the end of the calibration experiment, so it has certain practical value.