The three-axis gyroscope is the core sensitive device of the inertial navigation system, and its measurement accuracy directly affects the accuracy of the attitude calculation of the inertial navigation system. Therefore, how to reduce the measurement error of the three-axis gyroscope and improve its measurement accuracy has become a crucial issue. For a single-axis gyroscope, the main factors that affect its static measurement accuracy are the sensor’s zero bias error, scale coefficient error and random drift error; but for a three-axis gyroscope, the accuracy of its measurement results and the composition of the three-axis gyroscope The zero bias error, scale coefficient error, random drift error of each single-axis gyroscope of the gyroscope and the non-orthogonal installation error between the sensitive axes of each single-axis gyroscope are related. Compared with single-axis sensors, three-axis sensors have more calibration parameters and the calibration process is more complicated. At present, the calibration of gyroscopes usually adopts position calibration and rate calibration methods. These two methods have the advantages of simple principle, easy implementation, and high accuracy. However, as the calibration parameters increase, the amount of data increases sharply, time-consuming, and test conditions It is more demanding and requires high-precision test equipment. The calibration result depends on the accuracy of the test equipment; In addition, a system-level calibration method is adopted, which uses the output of the inertial instrument to directly perform the navigation solution, and uses the navigation solution error as a quantitative measurement to estimate Gyro error parameters. This method does not require sophisticated test equipment. Filtering algorithms are usually used to estimate the error parameters, but the amount of calculation is large, the observability analysis is complicated, and the calibration time is long.
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