Square-root Kalman filtering of descriptor systems

Abstract

A novel square-root information filter algorithm is proposed to solve the Kalman filtering problem for discrete-time descriptor systems. Unlike standard square-root information filters, the present approach does not impose restrictions on the state transition matrix or on the noise covariance matrix. The resulting implementation exhibits a moderate computational burden and good numerical properties, and has general applicability to the state estimation of discrete-time linear dynamic descriptor systems.