  This letter explores covariance matching-based adaptive robust cubature
Kalman filter (CMRACKF). In this method, the innovation sequence is used to
determine the covariance matrix of measurement noise that can overcome the
limitation of conventional CKF. In the proposed algorithm, weights are
adaptively adjusted and used for updating the measurement noise covariance
matrices online. It can also enhance the adaptive capability of the ACKF. The
simulation results are illustrated to evaluate the performance of the proposed
algorithm.
