This paper investigates the problem of receding horizon state estimation for networked control systems (NCSs) with random network-induced delays less than one sample period,which are formulated as multirate control systems. Based on a batch of recent past slow rate measurements in a finite horizon window,the initial state estimation in this window is solved by minimizing a receding-horizon objective function,and then the fast rate state estimations are calculated by the prediction of dynamic equation to compensate for the network-induced time delays. Furthermore,convergence results and unbiasedness properties are analyzed. An upper bound of estimation error is presented under the assumption of bounded disturbances acting on the system and measurement equations. A simulation example shows the effectiveness of the proposed method. This paper investigates the problem of receding horizon state estimation for networked control systems (NCSs) with random network-induced delays less than one sample period, which are formulated as multirate control systems. Based on a batch of recent past slow rate measurements in a finite horizon window, the initial state estimation in this window is solved by minimizing a receding-horizon objective functions, and then the fast rate state estimations are calculated by the prediction of dynamic equation to compensate for the network-induced time delays. and unbiasedness properties are analyzed. An upper bound of estimation error is presented under the assumption of bounded disturbances acting on the system and measurement equations. A simulation example shows the effectiveness of the proposed method.