Rapid online dynamic calibration method for zero offset of GNSS (Global Navigation Satellite System) auxiliary MEMS (Micro Electro Mechanical Systems) inertial sensor

Abstract

The invention relates to a rapid online dynamic calibration method for the zero offset of a GNSS auxiliary MEMS inertial sensor. The MEMS inertial sensor comprises an MEMS accelerometer and an MEMS gyroscope which form an MEMS inertia measurement unit; in a GNSS/MEMS INS combined navigation system, the zero offset of the accelerometer is calibrated in real time through carrying out online comparison on the modulus of a total specific force obtained by GNSS deduction and the modulus of a total specific force output by the MEMS accelerometer; the zero offset of the gyroscope calibrated in real time through deducting attitude information online by utilizing speed information measured by a GNSS and adding the dynamic or static constraint of the uniform motion or the approximate uniform linearmotion. The invention has the advantages that the method is not limited by the motion state of a carrier, has small calculated amount and strong real-time performance, can rapidly complete the onlinedynamic calibration of the zero offset of the inertial sensor and is beneficial to realizing the rapid starting of the GNSS/MEMS INS combined system and the batch application thereof.

Description

technical field [0001] The invention relates to the technical field of satellite navigation, in particular to a fast online dynamic calibration method for GNSS-assisted MEMS inertial sensor zero offset in an integrated navigation system combining global satellite navigation system GNSS and MEMS-based inertial navigation system (MEMS INS). Described MEMS refers to microelectromechanical system, and described MEMS inertial sensor comprises MEMS accelerometer and MEMS gyroscope, constitutes the inertial measurement unit of integrated navigation system; The measurement error of MEMS inertial sensor is mainly by the zero bias of MEMS accelerometer and MEMS gyroscope. The error determines that in order to eliminate the measurement error of the MEMS inertial sensor, it is very necessary to calibrate the zero bias of the MEMS inertial sensor. Background technique [0002] GNSS (Global Navigation Satellite System) can provide global users with all-weather, continuous real-time, high-...

AI Technical Summary

Problems solved by technology

[0005] The traditional zero-bias calibration method is to use a high-precision turntable to collect data information off-line to calibrate the main error coefficients of the MEMS accelerometer and MEMS gyroscope. Although the turntable calibration method is relatively mature, it has the following shortcomings: First, mathematical modeling It is complex and requires a large number of offline data samples; second, it can only calibrate the single-power-on error characteristics of MEMS accelerometers and gyroscopes, such as bias stability, but cannot calibrate the zero bias of previous power-on errors; Third, it needs to use special testing equipment, and has specific requirements for the motion state of the carrier, the calibration takes a long time, and the cost of manpower and material resources is high; fourth, the environmental factors during the offline calibration of the turntable are different from the environmental factors (temperature , humidity, installation error, vibration, electromagnetic interference, etc.), may cause the calibration parameters to be unsuitable for the use environment; fifth, as the storage time increases, the calibration parameters of MEMS accelerometers and gyroscopes will change with time. Time drift, MEMS INS navigation ability will be reduced

For many systems, the cost of recalibration is too high, which is not conducive to the maintenance and improvement of system performance, and is not conducive to the real-time and rapid response of the system

Sixth, during the use of the INS calibrated by the traditional method, the working accuracy of the system depends heavily on the zero-bias repeatability of the high-performance inertial device error, but the MEMS inertial device does not have excellent zero-bias repeatability characteristics

Seventh, the traditional calibration method requires the system to be in the initial working state of the non-dynamic environment

To sum up, with the expansion of the application of GNSS / MEMS integrated navigation system, traditional calibration methods (such as requiring initial static state) are difficult to apply to the increasingly wide use environment

Images