Chandrasekhar-type Algorithms with Gain Elimination

Abstract

Chandrasekhar-type algorithms are associated with the Riccati equation emanating from the Kalman filter in linear systems which describe the relationship between the n-dimensional state and the m-dimensional measurement. The traditional Chandrasekhar-type algorithms use the Kalman filter gain to compute the prediction error covariance. In this paper, two variations of Chandrasekhar-type algorithms eliminating the Kalman filter gain are proposed. The proposed Chandrasekhar-type algorithms with gain elimination may be faster than the traditional Chandrasekhar-type algorithms, depending on the model dimensions.