Decentralized attitude estimation using a quaternion covariance intersection approach

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