Recent advances on cooperative wireless localization and their application in inhomogeneous propagation environments

In this survey, we review recent advances on cooperative localization techniques and identify critical challenges in realistic cooperative localization systems. Particularly, we focus on the inhomogeneity of radio propagation environments, which has substantial impact on the accuracy of positioning systems that assume a homogeneous propagation model. Popular cooperative localization algorithms based on maximum-likelihood estimation, convex relaxation and optimization, and message passing are surveyed, with more emphasis placed on Received Signal Strength (RSS) based approaches due to their potential application in low cost devices. It is shown that most existing algorithms are based on the assumption of a propagation environment with a priori known spatially invariant propagation models. The extension of existing algorithms to capture the inhomogeneity of propagation environments are studied.