Large-scale systems that are composed of multiple sensors require the utilization of innovative methods for real-time system state estimator implementation. In fact, the classical approach of centralized estimation cannot provide satisfactory performance, since it requires the transmission of all sensor observations to a central location at large communication bandwidth. Therefore, a decentralized estimation system that distributes the processing is currently the focus of much attention. The gain transfer algorithm developed herein provides a method for decentralized hierarchical estimator implementation. Localized estimators process measurement observations locally within their own microprocessors. A global estimator independently receives information in the form of a Kalman gain transfer from these local systems. This global estimator models the overall system and thereby formulates the state estimates and state error covariance of global interest.