The attitude accuracy of the rotational inertial navigation system (RINS) is affected by the oscillatory attitude error caused by the installation error of the rotation axes. Data on the specific force, gyro measurement, attitude, or velocity errors are necessary to estimate the installation error. However, these errors are difficult to obtain and even unavailable in autonomous navigation. As the configuration consisting of two RINSs has been installed in the same vessel, we propose a self-calibration method to address the installation error solely using the attitude difference of two RINSs. We then constructed the Kalman filter based on the attitude difference model of two RINSs. The asynchronous time of the rotation sequence of two RINSs is optimized to improve the observability degree of the Kalman model. The proposed algorithm is examined by undertaking a test using two RINSs. Results indicate that the estimation accuracy of the installation error is at 6 arcsec level. The oscillatory attitude errors of RINS 1 are reduced from 305 to 6 arcsec, and those of RINS 2 are decreased from 131 to 6 arcsec after 350 s. The test results prove the effectiveness of the proposed installation error calibration method.

A Self-Calibration Method for the Installation Errors of Rotation Axes Based on the Asynchronous Rotation of Rotational Inertial Navigation Systems

In the rotational inertial navigation system (RINS), the rotation scheme affects the system’s performance directly. Improper rotation scheme may excite devices’ errors instead of reducing the effects caused by them. RINS should choose a suitable rotation scheme based on the error characteristics of its own. The rotation modulation theory for kinds of errors is analyzed, and two rotation schemes, called scheme A and scheme B in this paper, are proposed first. After the merits and demerits of the two schemes are discussed, an improved rotation scheme, called scheme C, is put forward. Scheme C can compensate scale factor errors, biases and installation errors of inertial sensors by rotating inertial measurement unit along the yaw axis and horizontal axis alternately. The simulations based on MATLAB are conducted in specific conditions; the results indicate that the performances of the three schemes are great better than that of general strap-down INS, called scheme D in this paper. Among the three schemes proposed, the performance of scheme C is the best. Experimental results in a real dual-axis rotational inertial navigation system based on fiber optic gyro show that the radical direction position error of the system is about 0.7 n mile in 12 h if scheme C is adopted, which verify the practicability of the rotation scheme proposed in this paper.

An Improved Rotation Scheme for Dual-Axis Rotational Inertial Navigation System

Gyro north finders have been widely used in maneuvering weapon orientation, oil drilling and other areas. This paper proposes a novel Micro-Electro-Mechanical System (MEMS) gyroscope north finder based on the rotation modulation (RM) technique. Two rotation modulation modes (static and dynamic modulation) are applied. Compared to the traditional gyro north finders, only one single MEMS gyroscope and one MEMS accelerometer are needed, reducing the total cost since high-precision gyroscopes and accelerometers are the most expensive components in gyro north finders. To reduce the volume and enhance the reliability, wireless power and wireless data transmission technique are introduced into the rotation modulation system for the first time. To enhance the system robustness, the robust least square method (RLSM) and robust Kalman filter (RKF) are applied in the static and dynamic north finding methods, respectively. Experimental characterization resulted in a static accuracy of 0.66° and a dynamic repeatability accuracy of 1°, respectively, confirming the excellent potential of the novel north finding system. The proposed single gyro and single accelerometer north finding scheme is universal, and can be an important reference to both scientific research and industrial applications.

A Novel MEMS Gyro North Finder Design Based on the Rotation Modulation Technique.

For rotational inertial navigation system(RINS), the system error can be compensated by rotating the inertial measurement unit (IMU) with one or more axis regularly, and the error compensation effect is determined by the rotation scheme of IMU.A reasonable rotation scheme should remove the system errors caused by inertial sensors errors and meanwhile, should not introduce other additional errors by the rotation. The error compensation demerits of two common rotation schemes are discussed. In these two schemes, the attitude errors caused by installation error are not modulated completely in a whole rotation period, which will cause accumulative velocity errors by integration. The accumulative velocity errors will sequentially increase the amplitude of position oscillation error. Based on the aforementioned analysis, a comprehensive error compensation scheme for dual-axis RINS is proposed. The proposed scheme can not only modulate the constant bias of inertial sensors, but also compensate the scale factor errors and installation errors coupled with IMU rotation. Moreover, the coupling errors are modulated into a zero-mean form with half amplitude of those two traditional schemes. As a result, the system errors of RINS with this rotation scheme can be modulated to a maximum extent. The superiority of the proposed scheme is verified through simulations with 4 different error conditions. Under the same synthesized error condition, the position error of the proposed scheme decreases to 0.37nmile/72hours from 0.98nmile/72hours in the other two schemes.

Comprehensive Error Compensation for Dual-Axis Rotational Inertial Navigation System

Rotating modulation technique is a mature method which has been widely used in the rotational inertial navigation system (RINS). A proper rotation scheme can greatly improve the position accuracy of the system. However, if the system is in angular motion, the modulation performance of the rotation scheme will be affected and improvements should be made. The modulation mechanism of a conventional rotation scheme based on tri-axis RINS in static base, which is called Scheme A in this paper, is analyzed firstly. Then the bad effects of system’s yaw angular motion upon the modulation performance are discussed and an improvement of the rotation scheme aiming at dynamic base is put forward after that. Simulations based on Matlab are conducted to demonstrate the effectiveness of the improvement. Vehicle experiments based on a real tri-axis RINS demonstrate that the improvement made on rotation scheme can reduce the maximum radical direction position errors by 0.6 n miles in 12 h roughly compared to the original unimproved scheme.

An improved rotation scheme for Tri-axis rotational inertial navigation system

Inertial Navigation Systems (INS) were large, heavy and expensive until the development of cost-effective inertial sensors constructed with Micro-electro-mechanical systems (MEMS). However, the large errors and poor error repeatability of MEMS sensors make them inadequate for application in many situations even with frequent calibration. To solve this problem, a systematic error auto-compensation method, Rotation Modulation (RM) is introduced and detailed. RM does no damage to autonomy, which is one of the most important characteristics of an INS. In this paper, the RM effects on navigation performance are analysed and different forms of rotation schemes are discussed. A MEMS-based INS with the RM technique applied is developed and specific calibrations related to rotation are investigated. Experiments on the developed system are conducted and results verify that RM can significantly improve navigation performance of MEMS-based INS. The attitude accuracy is improved by a factor of 5, and velocity/position accuracy by a factor of 10.

/pdf/analysis-and-verification-of-rotation-modulation-effects-on-3i8iqir58w.pdf

Xueyun Wang

Papers

Analysis and Verification of Rotation Modulation Effects on Inertial Navigation System based on MEMS Sensors