Distributed Projection Approximation Subspace Tracking based on consensus propagation

We develop and investigate a distributed algorithm for signal subspace tracking with a wireless sensor network without the need for a fusion center, in order to improve the robustness and scalability. We assume that all sensor nodes may broadcast messages to sensors in their neighborhood defined by a finite (small) communication radius. To this aim, we start from projection approximation subspace tracking (PAST) which is a well-investigated algorithm suitable for implementation in a fusion center. We arrive at a distributed approximation of the PAST algorithm by letting each sensor broadcast its local observation variable xn(t) and a filtered observation vector y-n(t) to its neighborhood. Vice versa, the received messages at sensor node n from its neighborhood are fused by employing consensus propagation. Finally, we investigate the proposed distributed algorithm in simulation runs.