The covariance matrix transformation method in all-earth integrated navigation considering coordinate frame conversion

Abstract

In the exploration of polar region, navigation is one of the most important issues to be resolved. To avoid the limitations of single navigation coordinate frame, the navigation systems usually use different navigation coordinate frames in polar and nonpolar region, such as the north-oriented geographic frame and the grid frame. However, the error states and covariance matrix are related with the definition of navigation coordinate frame, since the coordinate frame conversion will cause the integrated navigation Kalman filter overshoot and error discontinuity. To solve this problem, the transformation relationship of error states defined in different frames is deduced, whereby the covariance matrix transformation relationship is also analyzed. On this basis, covariance transformation-based the open-loop and the closed-loop Kalman filter integrated navigation algorithms are proposed. The effectiveness of algorithms is verified by flight tests with rotational strapdown inertial navigation system (RSINS)/global navigation satellite system (GNSS) integrated navigation system.

A Polar Robust Kalman Filter Algorithm for DVL-Aided SINSs Based on the Ellipsoidal Earth Model

“…The main idea is to redefine the navigation frame used in the polar region in order to solve the calculation overflow problem and the north reference failure issue. Among the redefined navigation frames, the grid frame and transverse frame are generally used for polar navigation [ 6 , 7 ]. The grid frame adopts the intersection of the grid plane, which is parallel to the Greenwich plane and the tangent plane as grid north, thus the meridian rapid convergence in the polar region is avoided.…”