Fusion of Distributed Sensor and Its Application in HVDC

The problem of distributed Kalman filtering for sensor network is one of the most fundamental distributed estimation problems for scalable sensor fusion. This article introduced that the sensor-fusion algorithm was based on the least-squares estimate of a vector which is based on the measurements of all the agents and the covariance of this fused least-squares estimate. It also showed that dynamic consensus can be followed by these vectors which can be analyzed by algebraic connectivity of consensus velocity. And its application was validated in HVDC. The simulation proves that it can reduce the promulgation of the noise, implementing the convergence and tracking the fast signal.