Decentralized Attitude Estimation Using a Quaternion Covariance Intersection Approach

Abstract

This paper derives an approach to combine estimates and covariances for decentralized attitude estimation using a quaternion parameterization. The approach is based on the covariance intersection method, which is modified to maintain quaternion normalization in the combination process. A practical simulation result is provided where local extended Kaiman filters are used on two star trackers, each running with common gyro measurements. The covariance intersection approach is shown to provide more accurate estimates than either of the local filters.