A vehicle angular motion isolation method for dual-axis rotational laser gyro inertial navigation system

Suppression of the G-sensitive drift of laser gyro in dual-axis rotational inertial navigation system

For the alignment in rotational inertial navigation system (RINS), which takes velocity errors of the navigation calculation as the filter measurements, the velocity error term caused by the coupling of the accelerometer’s inner lever arms (ILAs) and the gimbals’ angular motion will lead to a decline in the alignment accuracy. In view of that, a simplified model of the ILAs is proposed firstly in combination with the specific dual-axis rotation scheme, and then the ILAs are extended into state variables for filtering estimation, thereby improving the alignment accuracy. On this basis, in order to further improve the alignment rapidity, the bidirectional process-based rotation alignment method for dual-axis RINS is proposed in this paper. The bidirectional process, which combines the backward-forward RINS calculation and the backward-forward Kalman filtering, makes the best use of the stored IMU data repeatedly and is able to quickly obtain the IMU attitude matrix for RINS. The simulations and experiments show that the proposed bidirectional process-based rotation alignment method is able to accomplish the rapid and accurate alignment for the dual-axis RINS.

In a dual-axis rotational inertial navigation system (RINS), there are two kinds of installation errors, nonorthogonal installation errors of inertial sensors, and installation errors between the inertial measurement unit (IMU) and rotation axes. Traditionally, these two errors are not considered simultaneously. Thus, they are calibrated separately by different estimation algorithms and rotation schemes. In this paper, a system-level self-calibration method for installation errors of a dual-axis RINS is proposed. Based on the Kalman filter, the measurement model is reestablished to ensure that all installation errors can be estimated together. First, the relationship between the initial attitude and subsequent attitude of IMU during rotation is used as a constraint to estimate nonorthogonal installation errors of accelerometers, and installation errors between the IMU and rotation axes. Then, the angular rate of the rotation mechanism is used as a reference to estimate nonorthogonal installation errors of the gyros. The rotation scheme of the IMU is designed to make all installation errors observable, and the observability of the system is analyzed based on the piecewise constant system method. Simulation and laboratory experiment results suggest that installation errors can be effectively estimated by the proposed method, thereby avoiding the complex separating process.

Rotation modulation technology could effectively improve the accuracy of the inertial navigation system (INS) by compensating for the biases of the inertial sensors automatically. However, the carrier angular motion and rotation control error could reduce the rotation modulation effect and then decrease the navigation accuracy. To address this problem, for the single-axis rotation INS, a novel rotation control scheme is presented. The control scheme employs the fiber optic gyros to control the inertial measurement unit (IMU) rotation angular velocity so that the INS with both rotation modulation and azimuth motion insulation functions. Furthermore, in order to reduce the control error, this study adopts two ways: optimizing the control strategy and shortening the delay time. The former way is to control the IMU rotating about the z-axis of the platform frame with respect to the navigation frame, rather than the up-axis of the navigation frame. The latter way is to apply interrupt mode rather than inquiry mode to complete the data transfer between the navigation and the control processors. The simulation and experimental results demonstrate that: the proposed method would not only realize the rotation modulation of the biases of the inertial sensors, but also achieve the insulation of the azimuth motion. The steady-state control error of the control system is less than 10" and the overshoot control error is less than 50". Compared to the traditional SRINS, the navigation position error in the single-axis rotation/azimuth-motion insulation INS could reduce 50% in some navigation application.

In long endurance underwater vehicle rotational inertial navigation system, the rotation strategy significantly impacts navigation accuracy. To address the limitations of the dual-axis 16-position rotation modulation scheme, specifically, its large rotation angles and inability to modulate errors arising from the coupling of scale factors and Earth’s rotation rate. This paper proposes a geocentric frame based triaxial 32-position rotation modulation method. This method suppresses navigation errors by altering the direction of the rotation axis and increasing the rotation sequence. It simultaneously isolates the Earth’s rotation rate, thereby eliminating the coupling error between inertial sensor scale factors and Earth rotation, and enhancing system navigation accuracy. Experimental results demonstrate that the system achieves a navigation positioning accuracy of approximately 2.2 nautical miles (n mile) over 72 hours. Compared to a single-axis RINS, positioning accuracy is improved by a factor of 8. Compared to a dual-axis RINS, positioning accuracy is enhanced by 0.75 n mile. These results validate the effectiveness of the proposed method in improving navigation accuracy.

The navigation performance of the rotational inertial navigation system (RINS) could be greatly improved by rotating the inertial measurement unit with gimbals, and self-calibration for error parameters could be achieved in RINS as well. However, accelerometer nonlinearity errors need to be considered and calibrated to further improve the navigation accuracy of RINS, especially in large dynamic applications. In this paper, a self-calibration method is proposed for accelerometer nonlinearity errors in triaxis RINS. Accelerometer nonlinearity errors and other errors are calibrated through optimal estimation with velocity and position error measurements. In order to guarantee that all errors are observable during calibration, some rotation scheme design principles are proposed, which are different from traditional observability analysis methods and could provide instructions for rotation scheme design directly. The effectiveness of the self-calibration method is proved by both simulation and experiment. The accelerometer nonlinearity errors could be accurately calibrated with the proposed method, while other error parameters reach higher calibration accuracy. Furthermore, experiment results from a long-term vehicle navigation show that velocity and position accuracy of the triaxis RINS have improved significantly after compensation with the self-calibration results, fully illustrating the significance of the proposed self-calibration method in improving the navigation performance of RINS.

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.

Navigation of Hypersonic vehicles in the radio frequency (RF) blackout area during atmospheric reentry is challenging as the vehicles can only use the inertial navigation system (INS) as autonomous navigation method in this area. In this paper, strapdown inertial navigation system (SINS) based on the Fiber Optic Gyroscope (FOG) is used for navigation in blackout area. However, without external navigation measurement, the errors of SINS caused by the FOG drift and accelerometer bias would cumulate with time and degrade navigation accuracy. To solve this problem, single axis rotation modulation along with the azimuth axis of the body frame is adopted. The Generic Hypersonic Vehicle (GHV) model designed by NASA Langley Research Center is used to build the reentry fight model which can generate navigation information for simulation. Through derivation the error equations of FOG SINS in the North-East-Down (NED) navigation frame, the principle of error compensation by rotation modulation can be well understood. The simulation results show that rotation modulation can effectively decrease the impact of inertial sensor drift and improve the navigation accuracy in blackout area.

ABSTRACTFibre optic gyros (FOGs) are widely used in the rotation inertial navigation system (RINS). However, FOGs are sensitive to surrounding environments, and thus the drifts of FOGs would vary during the rotation of the gyros. This phenomenon may bring about residual gyro drifts, which are the primary cause for the accumulated navigation errors in the RINS. A recursion least square estimation method based on position errors is proposed to obtain residual drifts. A multi-position calibration method is presented to separate the residual drifts along the body axis. Static experiment results show that the positioning accuracy of a 12-h navigation is improved significantly from 2.24 to 0.54 n mile by compensating the residual drifts along the body axis. A vehicle-mounted motional experiment is conducted to verify the proposed calibration method, and the positioning accuracy is improved from 1.38 to 0.66 n mile.

In the dual-axis rotation inertial navigation system (INS), besides the gyro error, accelerometer error, rolling misalignment angle error, and the gimbal angle error, the shaft swing angle and the axis non-orthogonal angle also affect the attitude accuracy. Through the analysis of the structure, we can see that the shaft swing angle and axis non-orthogonal angle will produce coning errors which cause the fluctuation of the attitude. According to the analysis of the rotation vector, it can be seen that the coning error will generate additional drift velocity along the rotating shaft, which can reduce the navigation precision of the system. In this paper, based on the establishment of the modulation average frame, the vector projection is carried out, and then the attitude conversion matrix and the attitude error matrix mainly including the shaft swing angle and axis non-orthogonal are obtained. Because the attitude angles are given under the static condition, the shaft swing angle and the axis non-orthogonal angle are estimated by the static Kalman filter (KF). This kind of KF method has been widely recognized as the standard optimal estimation tool for estimating the parameters such as coning angles (α1 , α2), initial phase angles (ϕ1,ϕ2), and the non-perpendicular angle (η). In order to carry out the system level verification, a dual axis rotation INS is designed. Through simulation and experiments, the results show that the amplitudes of the attitude angles’ variation are reduced by about 20%–30% when the shaft rotates. The attitude error equation is reasonably simplified and the calibration method is accurate enough. The attitude accuracy is further improved.

For its obvious high accuracy in a long term, rotary inertial navigation system becomes popular. However, as errors increasing with time are changed into periodic errors with zero mean, the accuracy of its azimuth angle decreases in view of short term and can’t fully satisfy the need of users such as flight control system. The precision of azimuth angle is studied by analyzing its influence factor and establishing the scale factor error model and drift models of fiber optic gyro and the measurement error model of photoelectric encoder. Correction for fiber optic gyro and photoelectric encoder based on their mutual assistance is designed to improve the short-term accuracy of rotary inertial navigation system’s azimuth angle. Experimental results in a fiber optic gyro based rotary inertial navigation system verify the proposed method.

The medium accuracy standard ring laser gyro (RLG) inertial navigation unit (INU) exemplified by Litton's LN-93 system has benefited from continual improvements during the production process such that the present navigational accuracy and reliability are better by a factor of two or more over the original requirements as defined by SNU 84-1. Performance enhancements are now available which further improve navigation performance to the high-accuracy category while maintaining the reliability of the production system. Two enhancement mechanizations are described-one that requires software-only changes to improve inertial performance, and one that employs a self-contained (embedded) GPS to augment the inertial performance. These enhancements may be applied in combination to provide uniquely effective immunity to GPS spoofing countermeasures. These enhancements retain the present standard RLG INU form factor, mounting, and electrical interface, and are therefore particularly advantageous for retrofit application. Potential retrofit applications with various aircraft avionics architectures are discussed. >

With the rotation modulation, a strapdown inertial navigation system (INS) can keep high accuracy navigation without high accuracy gyro and high accuracy accelerometer. Firstly we give the error equation of strapdown INS, and then deduct the navigation error propagation of system. From partial analysis way, the modulation process of gyro constant error is obtained. Form global analysis way, the navigation error roused by constant error and the modulation effects are deducted here.

Demonstration that updating an inertial navigation system (INS) with VOR/DME information (from one or two stations) by means of a maximum-likelihood filter results in substantial improvements in navigational accuracy over that obtained by the use of a single VOR/DME (current practice). When continuously updating, the use of a high-quality INS (0.01 deg/hr gyro drift) instead of a low-quality INS (1.0 deg/hr gyro drift) does not substantially improve position accuracy. In-flight alignment (or realignment) of an INS to an accuracy comparable to that of ground alignment can be accomplished by using two DMEs. Several reduced-order suboptimal filters were found to perform nearly optimally.

Rotation modulation (RM) technology can effectively improve the navigation accuracy of strapdown inertial navigation system (SINS) by the periodic rotation of the rotation mechanism. But the original error characteristics of SINS will be changed after introducing the rotation modulation technology. Aiming at the practical micro-electro-mechanical system RMSINS, the error characteristics are comprehensively analyzed, and then a complete error model is established. At the same time, a reasonable parameter calibration scheme and the compensation method are designed to compensate the error in this paper. On this basis, static and dynamic experiments are carried out. The position accuracies of the rotation modulation state in the static and dynamic experiments are about ten times and about three times than that of the non-rotation state. The experimental results show that the proposed error analysis and compensation method are feasible which have been applied to the practical engineering.