Abstract
In order to improve the precision of Strapdown Inertial Navigation System (SINS) and reduce the complexity of the traditional calibration method, a novel calibration and compensation scheme is proposed. An optimization calibration method with four-direction rotations is designed to calculate all error coefficients of Ring Laser Gyroscope (RLG) SINS in a series of constant temperatures. According to the actual working environment, the temperature errors of RLG SINS are compensated by a nonlinear interpolation compensation algorithm. The experimental results show that the inertial navigation errors of the proposed method are reduced.
Highlights
Motion error compensation based on a high precision Position and Orientation System (POS) is an effective avenue to improve the imaging quality of the interferometric Synthetic Aperture Radar (SAR) [1, 2]
According to the error model of Ring Laser Gyroscope (RLG) Strapdown Inertial Navigation System (SINS), an optimization calibration method with four-direction rotations is designed for RLG SINS based on a single-axis turntable with temperature control and a high-precision hexahedral fixture
Nonlinear Interpolation Compensation of Temperature Errors. Both the RLG and Quartz Mechanical Accelerometer (QMA) are sensitive to the temperature, and the precision of RLG SINS is limited by the temperature errors
Summary
Motion error compensation based on a high precision Position and Orientation System (POS) is an effective avenue to improve the imaging quality of the interferometric Synthetic Aperture Radar (SAR) [1, 2]. The traditional rotation rate calibration can improve the precision of the angular rate channel error coefficients, but it reduces the precision of acceleration channel. The method improves the precision of the calibrated coefficients in both of the two channels, but increasing the complexity of the calibration It is another key technology for SINS to find a better method to reduce the complexity and error of the calibration at the same time. The method is easy to be implemented, while the precision of compensation is low Other nonlinear methods, such as the high order least-squares approximation method and the Radial Basis Function (RBF) neural network method, improve the precision of the SINS, but they cannot. Based on the theoretical analysis and experimental data, the calibration and compensation methods of the temperature and dynamic error for SINS are studied in this paper, and an optimization calibration method with four-direction rotations and nonlinear interpolation compensation method is proposed for SINS in full temperature ranges
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