Joint estimation and identification for stochastic systems with two kinds of unknown inputs

This paper discusses the joint estimation and identification of a class of discrete-time stochastic systems with two kinds of unknown inputs (UIs). A general framework of the stochastic system model with two kinds of UIs is built. Furthermore, a new joint estimation and identification method is proposed for dealing with the problem via iterative optimization. An numerical example of tracking a maneuvering target accompanied range gate pull-off(RGPO) is utilized to illustrate the proposed method and its performance in parameter identification and state estimation.