Recursive filtering for a class of uncertain complex-valued stochastic systems

Abstract

ABSTRACT This paper is concerned with the recursive filtering problem for a class of complex-valued stochastic systems. The uncertain complex-valued parameters are considered to reflect the uncertainty of the system. To facilitate the filter design, an augmented compact form is utilized to rewrite the system model. The main purpose of this paper is to develop a recursive filtering scheme in the complex-valued domain such that an upper bound on the filtering error covariance is guaranteed and minimized through adequately designing the filter gain. Moreover, the second-order statistical characteristics of the complex-valued variables which contribute to the analysis complexity, are all reflected in the minimized upper bound. Finally, a numerical simulation example is presented to illustrate the effectiveness of the proposed filter design scheme.