A Distributed Quaternion Kalman Filter With Applications to Smart Grid and Target Tracking
Sayed Pouria Talebi, Sithan Kanna, Danilo P. Mandic · IEEE Transactions on Signal and Information Processing over Networks · 2016
Recent advances in sensor and communication technologies have made the deployment of sensor networks in a variety of roles feasible, including smart grid management applications and collaborative target tracking solutions. While most research in distributed adaptive signal processing is conducted in the real and complex domains, inherently in many real-world applications the data sources are three-dimensional. This scenario is ideally suited for quaternions in terms of both convenience of representation and mathematical tractability. In this paper, we expand the concept of distributed Kalman filtering to the quaternion domain in order to develop a robust distributed quaternion Kalman filtering algorithm for data fusion over sensor networks dealing with three-dimensional data. For rigor, the mean and mean square behavior of the algorithm are analyzed. Finally, the developed algorithm is used to estimate the nominal system frequency in power distribution networks and for collaborative target tracking applications.