A Distributed Steered Response Power Approach to Source Localization in Wireless Acoustic Sensor Networks

Abstract

In wireless acoustic sensor networks (WASNs), the conventional steered response power (SRP) approach to source localization requires each node to transmit its microphone signal to a fusion center. As an alternative, this paper proposes two different fusion strategies for local, single-node SRP maps computed using only the microphone pairs within a node. In the first fusion strategy, we sum all single-node SRP maps in a fusion center, requiring less communication than the conventional SRP approach because the single-node SRP maps typically have less parameters than the raw microphone signals. In the second fusion strategy, the single-node SRP maps are distributively averaged without using a fusion center, requiring communication amongst connected nodes only. Simulations show that we achieve a good trade-off between communicational load and localization performance.

Distributed Adaptive Norm Estimation for Blind System Identification in Wireless Sensor Networks

“…In this paper, we extend our algorithm in [9] with a distributed averaging-based [13] estimation scheme for the global variable. This approach allows us, similarly to [14,15], to compute the global variable without needing a fully connected network or broadcasting. We also introduce a mixing factor to include instantaneous values into the averaging recursion, which then allows us (i) to reduce the number of secondary iterations significantly (from 50 in existing approaches down to 1) and (ii) track time-varying systems.…”