Recursive state estimation for a class of quantized coupled complex networks subject to missing measurements and amplify-and-forward relay

This paper investigates the algorithm design problem of recursive state estimation (RSE) for a class of complex networks (CNs) subject to quantized coupled parameter, missing measurements (MMs) and amplify-and-forward (AF) relay. In the node-to-node network channels, the signals before entering into the communication networks are quantized. In addition, a series of Bernoulli random variables is employed to model the phenomenon of MMs and an AF relay is deployed in the sensor-to-estimator network channels with the purpose of achieving the task of remote data transmission. A recursive state estimator is constructed such that, for all quantized coupled signal, MMs and AF relay, a state estimation error covariance (SEEC) upper bound (SEECUB) is presented and then the estimator gain (EG) is parameterized by optimizing the trace of SEECUB. Subsequently, a rigorous theoretical analysis is given to establish the monotonicity relationship between the trace of the minimized SEECUB and the probabilities of MMs. Finally, a simulation study is carried out for the proposed RSE approach to demonstrate the feasibility and validity of such state estimation strategy.