Description

A Distributed Finite horizon kalman estimation algorithm is proposed for the networked Multi sensor data fusion system (NMFSs) in a bandwidth and energy constrained wireless. To satisfy the finite bandwidth, only partial components of each local vector estimate are transmitted to the fusion center (FC). At the FC end, we are proposed to compensate the transmitted components of each local estimates. To provide a communication with constrained bandwidth and energy through wireless network. To utilize the information from constrained noisy channel effectively for estimating a unknown parameter. Notice that the designed DFKF update does not need to know the transmitting situation of each component at a particular time, which means that the proposed fusion estimation algorithm is easily implemented for the addressed NMFSs. where a set of nodes are required to collectively estimate the state of a linear dynamic system from their individual measurements. Our focus is on diffusion strategies, where nodes communicate with their direct neighbors only, and the information is diffused across the network and the network must perform repeated averaging steps before arriving at a consensus.a diffusion Kalman filtering strategy for distributed state estimation in linear systems. The algorithm requires every node to communicate with its neighbors: first to share the data, and second to share the estimates. The diffusion procedure ensures that information is propagated throughout the network.