Abstract
This paper presents an innovative model for integrating thermal compensation of gyro bias error into an augmented state Kalman filter. The developed model is applied in the Zero Velocity Update filter for inertial units manufactured by exploiting Micro Electro-Mechanical System (MEMS) gyros. It is used to remove residual bias at startup. It is a more effective alternative to traditional approach that is realized by cascading bias thermal correction by calibration and traditional Kalman filtering for bias tracking. This function is very useful when adopted gyros are manufactured using MEMS technology. These systems have significant limitations in terms of sensitivity to environmental conditions. They are characterized by a strong correlation of the systematic error with temperature variations. The traditional process is divided into two separated algorithms, i.e., calibration and filtering, and this aspect reduces system accuracy, reliability, and maintainability. This paper proposes an innovative Zero Velocity Update filter that just requires raw uncalibrated gyro data as input. It unifies in a single algorithm the two steps from the traditional approach. Therefore, it saves time and economic resources, simplifying the management of thermal correction process. In the paper, traditional and innovative Zero Velocity Update filters are described in detail, as well as the experimental data set used to test both methods. The performance of the two filters is compared both in nominal conditions and in the typical case of a residual initial alignment bias. In this last condition, the innovative solution shows significant improvements with respect to the traditional approach. This is the typical case of an aircraft or a car in parking conditions under solar input.
Highlights
In recent years, several innovative solutions for transport systems have been developed, such as Unmanned Aircraft Systems, Unmanned Underwater Systems, Autonomous Ships, Autonomous LandVehicles, Micro Satellites, and Space Probes [1,2,3,4,5,6,7,8]
This paper presents an innovative model for integrating thermal compensation of gyro bias error into an augmented state Kalman filter to improve performance of inertial units manufactured by exploiting Micro Electro-Mechanical System (MEMS) gyros
Despite the advantages of low-cost, light-weight, high reliability and low power consumption, MEMS gyros are characterized by a strong correlation of the systematic error with temperature variations
Summary
Several innovative solutions for transport systems have been developed, such as Unmanned Aircraft Systems, Unmanned Underwater Systems, Autonomous Ships, Autonomous Land. It requires that the unit is held fixed with respect to the locally level frame for some minutes [21], since the assumption that the unit is stationary is the aiding information used by the Kalman filter, i.e., the filter measurement model. When the unit is turned on in stationary condition no information is provided about how long it is going to stay motionless For this reason, the ZUPT filter has a significant practical interest for IMUs equipped with standard grade gyros, such as the Attitude and Heading Reference Systems or AHRS installed on aircraft [14] or the Land. The paper shows how those applications could benefit by exploiting the reported innovative augmented Kalman Filter model
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