AN ALGORITHM FOR INFORMATION FUSION OF GNSS/GYROS ATTITUDE SENSORS OF A MOVING VEHILCLE
Abstract
The purpose of this paper is to increase the accuracy and stability of moving vehicle attitude estimation by GNSS/gyros attitude sensors information fusion. To this end, an algorithm is pro-posed which integrates carrier phase measurements of multi-antennas GNSS signal receiver and angular rate measurements provided by gyros. The algorithm estimates attitude parameters (di-rection cosine matrix, quaternion), angular rate vector and vector of gyro biases. The difference of the proposed method from the majority of previously developed methods is that the attitude solu-tion is obtained in two stages: first, attitude quaternion is estimated using a batch algorithm; next, this quaternion is used as an effective measurement in linear Kalman filter. GNSS signal receiver measures carrier phase differences between signals of navigation satellites detected by antennas placed at different points in space. These phase differences are converted to vector form. This makes it possible to use one of the well-known fast algorithms developed for Wahba problem solu-tion. Covariance analysis of this solution is presented and an expression for error covariance matrix is derived. The quaternion (direction cosine matrix) obtained is a maximum likelihood es-timate of the attitude. Therefore, this quaternion can be used as an effective measurement in linear Kalman filter. The filter state vector includes attitude quaternion and vector of gyro biases. This approach makes it possible to increase computational efficiency of the algorithm by avoiding the use of extended Kalman filter and to enhance numerical stability. Mathematical simulation results demonstrate stable algorithm performance under the influence of GNSS receiver measurement noise as well as dynamic system model noise caused be gyros measurement noise and rate random walk noise. Simulation results also indicate that the proposed algorithm allows for substantially increased accuracy of attitude estimates in comparison with the accuracy provided by batch algo-rithm. The proposed algorithm also enhances stability of navigation information user to the GNSS faults by propagating attitude and angular velocity estimates through GNSS signal outage without substantial loss in accuracy.
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