A Dynamic Generalized Kalman Consensus Filter for Switching Sensor Networks
The Dynamic Generalized Kalman Consensus Filter (DGKCF) was developed to improve distributed state estimation in sensor networks with changing communication links. It solves the problem of fixed consensus weights by using locally available information to dynamically compute consensus weights based on the relative quality of local estimates, allowing it to handle switching topologies and oblivious agents more effectively.