Single-axis Rotation Inertial Navigation System Research Articles

An Initial Alignment Algorithm Based on RSKF Single-axis Rotational Inertial Navigation System

An Initial Alignment Algorithm Based on RSKF Single-axis Rotational Inertial Navigation System

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.

A calibration method for rotary optical encoder temperature error in a rotational inertial navigation system

A rotary optical encoder is an important component in a rotational inertial navigation system (RINS). It is used to form a closed-loop motor control system and calculate the system attitude. The system performance will be affected by the encoder’s error. Ín addition to the installation errors, the working temperature variants can lead to encoder error. Therefore, in this paper we propose a method to calibrate and compensate the temperature errors of rotary optical encoders. First, an independent testing mechanism with position limitation and a rotatable platform is designed and produced to verify the temperature influence on encoders. Then, the temperature error of the rotary optical encoder used in RINS is calculated by a gyroscope whose sensitive axis is parallel to the same motor axis. The method is verified by a self-researched single-axis RINS. According to the experimental results, the measurement accuracy is increased by more than 47.9% compared to the traditional method.

Height measurement method based on one-dimensional laser Doppler velocimeter and integrated navigation system of single-axis rotation inertial navigation system (invited)

Height measurement method based on one-dimensional laser Doppler velocimeter and integrated navigation system of single-axis rotation inertial navigation system (invited)

Thermal Modeling and Calibration Method in Complex Temperature Field for Single-Axis Rotational Inertial Navigation System.

Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused by the temperature should be calibrated accurately. The traditional thermal calibration model consists of the temperature and temperature change rate, which does not reflect the complex temperature field of single-axis RINS. This paper proposed a multiple regression method with a temperature gradient in the model, and in order to describe the complex temperature field thoroughly, a BP neural network method is proposed with consideration of the coupled items of the temperature variables. Experiments show that the proposed methods outperform the traditional calibration method. The navigation accuracy of single-axis RINS can be improved by up to 47.41% in lab conditions and 65.11% in the moving vehicle experiment, respectively.

Error Mechanism and Self-Calibration of Single-Axis Rotational Inertial Navigation System

With the rapid development of inertial technology, the rotational inertial system has been widely used for high-accuracy navigation. In addition, the single-axis rotational inertial navigation system is one of the most popular navigation systems due to its low cost. However, the fact which cannot be ignored is that although single axis rotational inertial navigation system can restrain divergence of attitude error, it cannot eliminate velocity error, which is mainly caused by the gyro misalignment and scale factor error related to rotational axis. A novel calibration method established on filter has been proposed. Position, velocity, and attitude are chosen to be the state variables. In order to estimate the gyro errors related to rotational axis, these errors must be included in the state equation. Correspondingly, zero velocity and rate of turntable are chosen to be measured. Simulation has been carried out to verify the correctness of the theory, and the real test has been performed to further demonstrate the validity of the method. By compensating the main error estimated by filter, it can be found that the accumulated errors in velocity and attitude are decreased. So, the precision of navigation is greatly improved with the proposed method.

Online self-calibration research of single-axis rotational inertial navigation system

Rotary modulation can greatly improve the inertial navigation system (INS) performance. Based on the single-axis rotational inertial navigation system (RINS) with fiber optic gyroscopes (FOGs), this study analyzed the key errors which would affect the navigation accuracy of single-axis RINS and proposed a novel calibration method. The method uses horizontal accelerometer outputs, horizontal attitude errors and heading angle as the measurements of Kalman filter to achieve online self-calibration based on the designed rotation scheme. Through online self-calibration, the non-repeatable errors of each start in system could be estimated and compensated, and then the navigation accuracy of system can be significantly improved. Compared with the traditional methods, using the proposed method can get higher observability degrees of the key errors in system and shorten the calibration time. Simulation and experimental results show that the entire online self-calibration process can be completed within 48 min on stationary base and after online self-calibration, the short-term attitudes vibration is suppressed greatly, and the RINS position accuracy could improve about 50% in long-term navigation applications.

Navigation Information Fusion in a Redundant Marine Rotational Inertial Navigation System Configuration

A Rotational Inertial Navigation System (RINS) redundant configuration is commonly adopted in high-accuracy marine navigation. Single-axis RINS and dual-axis RINS redundant configurations are good choices with single-axis RINS being a hot backup system, and are trade-offs between position accuracy, reliability as well as cost. However, lack of information fusion between systems is common. Therefore, a novel navigation information fusion method based on an augmented error state Kalman filter is proposed for a RINS redundant configuration. The azimuth gyro drift of a single-axis RINS whose influence cannot be averaged out by single-axis rotation can be estimated, whereby the deterministic position error can be predicted and compensated. Hence, the position accuracy in the event of dual-axis RINS failure can be guaranteed by improving the performance of a single-axis RINS. In addition, an online performance evaluation method is proposed to select the better performance dual-axis RINS as master RINS in a triple RINS configuration, including two sets of dual-axis RINS and a single-axis RINS, which is used in some particularly high reliability applications. Semi-physical simulations and experiments show the proposed method works well.

Study on Integration of FOG Single-Axis Rotational INS and Odometer for Land Vehicle

Obtaining the land vehicle’s position, azimuth and attitudes autonomously and accurately is significant for vehicle-based weapon’s combat effectiveness. High performance inertial navigation system (INS) can provide high precision attitudes and azimuth reference information, however, it is usually very expensive. In addition, due to gyroscope drifts and accelerometer biases, INS navigation errors would diverge with time. To solve the problem, this paper proposed an integrated positioning and orientation method based on the FOG single-axis rotational INS (FRINS) and the odometer (OD). The proposed method adopted the rotation modulation technique to suppress the inertial sensor errors, particularly $z$ -axis FOG drift, by which the navigation accuracy, especially the azimuth accuracy, can be improved. At the same time, the proposed method integrated the FRINS with OD to suppress INS error’s divergence with time. Combining the above rotation modulation technique and the integration of FRINS and OD, the proposed method could improve the integrated system positioning and orientation accuracy as well as reduce the integrated system cost. This paper presented the FRINS/OD integrated navigation system configuration, established the FRINS/OD integrated system errors model, and then verified the performance of proposed method by simulations. The results show that the proposed method could achieve positioning accuracy of 0.03% (of total traveled distance) and orientation of ±20, respectively, using rotational INS with FOGs of 0.1°/h and accelerometers of 500 ug.

A Novel Information Fusion Method for Redundant Rotational Inertial Navigation Systems Based on Reduced-Order Kalman Filter

The redundant rotational inertial navigation systems can satisfy not only the high-accuracy but also the high-reliability demands of underwater vehicle on navigation system. However, different systems are usually independent, and lack of information fusion. A reduced-order Kalman filter is designed to fuse the navigation information output of redundant rotational navigation systems which usually include a dual-axis rotational inertial navigation system being master system and a single-axis rotational inertial navigation system being hot-backup system. The azimuth gyro drift of single-axis rotational inertial navigation system can be estimated by the designed filter, whereby the position error caused by that can be compensated with the aid of designed position error prediction model. As a result, the improved performance of single-axis rotational inertial navigation system can guarantee the position accuracy in the case of dual-axis system failure. Semi-physical simulation and experiment verify the effectiveness of the proposed method.

Single-axis rotation/azimuth-motion insulation inertial navigation control system with FOGs

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.

Research on Nonlinear Comprehensive Calibration Algorithm for the Single-Axis Rotation Inertial Navigation System Based on Modified Unscented Kalman Filter

Research on Nonlinear Comprehensive Calibration Algorithm for the Single-Axis Rotation Inertial Navigation System Based on Modified Unscented Kalman Filter

Identifying Z -axis gyro drift and scale factor error using azimuth measurement in fiber optic gyroscope single-axis rotation inertial navigation system

In the fiber optic gyroscope (FOG) single-axis rotation inertial navigation system (SRINS), the Z-axis gyro drift (ϵz) dramatically limits its navigation precision and the Z-axis gyro scale factor error (δKGz) can cause greater navigation error because of the rotation process compared with the strap-down inertial navigation system. Hence, identification and compensation for the ϵz and δKGz are important in SRINS. An approach based on the azimuth error model of open-loop algorithm is proposed. This approach considers azimuth angle as a measurement and uses a least recursive square algorithm for identifying the ϵz and δKGz. Compared with the traditional method, which takes velocity and position errors as measurements, the time required for identifying ϵz with the proposed method is only approximately 10 min, while the traditional method requires 6 h to 12 h. Experimental results from an SRINS with FOGs demonstrate that the accuracy of identifying the ϵz reaches 0.002°/h and that of the δKGz reaches 8 ppm in 10 min. The positioning accuracy of the SRINS improves greatly after the identification and compensation.

Error analyses and calibration methods with accelerometers for optical angle encoders in rotational inertial navigation systems

By rotating a strapdown inertial navigation system (INS) over one or more axes, a number of error sources originating from the employed sensors cancel out during the integration process. Rotary angle accuracy has an effect on the performance of rotational INS (RINS). The application of existing calibration methods based on gyroscope measurements is restricted by the structure of the inertial measurement unit (IMU) and scale factor stability of the gyroscope. The multireadhead method has problems in miniaturization and cost. Hence, optical angle encoder calibration methods using accelerometers are proposed, on the basis of navigation error and accuracy requirement analyses for a single-axis RINS. The test results show that the accuracy of calibration methods proposed is higher than 4 arcsec (1σ).

单轴旋转惯导系统轴向陀螺漂移预测方法

单轴旋转惯导系统轴向陀螺漂移预测方法