Distributed Projection Approximation Subspace Tracking based on Consensus Propagation

Carolina Reyes , Thibault Hilaire (1) , Christoph Mecklenbräuker

1 PEQUAN - Performance et Qualité des Algorithmes Numériques

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.

Domaines: Informatique [cs]

Carolina Reyes, Thibault Hilaire, Christoph Mecklenbräuker. Distributed Projection Approximation Subspace Tracking based on Consensus Propagation. 3rd International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP'09), Dec 2009, Aruba, Netherlands Antilles. pp.340-343, ⟨10.1109/CAMSAP.2009.5413263⟩. ⟨hal-01295145⟩