MEMS inertial sensor array fusion method based on Kalman filter

Abstract

The invention discloses a MEMS inertial sensor array fusion method based on Kalman filtering, which adopts the combination of sensor array technology and Kalman filtering technology to perform error calibration on triaxial angular rate values ​​and triaxial acceleration values ​​in motion information data packets, The fusion of temperature compensation and Kalman filter algorithm reduces the noise of the inertial sensor and improves the measurement accuracy of the inertial sensor for moving objects. At the same time, in order to improve the performance of the inertial sensor array under dynamic conditions, an adaptive fading factor is introduced into the Kalman filter, and the filtering effect is improved by reducing the proportion of the previous estimated value in the existing estimated value. The method has high accuracy and strong applicability, which helps to solve the problems of low accuracy of existing low-cost inertial sensors and difficulty in meeting the needs of many practical applications.

Description

technical field [0001] The invention belongs to the field of inertial sensors, and in particular relates to a MEMS inertial sensor array fusion method based on Kalman filtering. Background technique [0002] Inertial sensors, including accelerometers and gyroscopes, are sensors for detecting acceleration information and angular velocity information, respectively. Due to the advantages of complete autonomy, no interference, large amount of output information, and strong real-time output information, inertial sensors have been widely used in military and aerospace fields. With the development of MEMS (Micro Electro Mechanical System) technology, the cost and power consumption of inertial sensors based on MEMS technology have been continuously reduced, and their performance has gradually improved. At present, micro gyroscopes and micro accelerometers can be seen everywhere in the consumer field. However, due to limitations in technology, detection circuits, etc., the accuracy ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a MEMS inertial sensor array fusion method based on Kalman filter, which uses the combination of sensor array technology and Kalman filter technology to solve the problem that the existing low-cost inertial sensor has too low precision and is difficult to meet the needs of many practical applications And other issues

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