An Adaptive Distributed Asynchronous Algorithm with Application to Target Localization

Abstract : This paper introduces a constant step size adaptive algorithm for distributed optimization on a graph. The algorithm is of diffusion-adaptation type and is asynchronous: at every iteration , some randomly selected nodes compute some local variable by means of a proximity operator involving a locally observed random variable, and share these variable with neighbors. The algorithm is built upon a stochastic version of the Douglas-Rachford algorithm. A practical application to target localization using measurements from multistatic continuous active sonar systems is investigated at length.