A unified approach for hybrid source localization based on ranges and video

This paper presents a hybrid method for single-source localization in wireless sensor networks, fusing noisy range measurements with angular information extracted from video. Although recent works found in the literature explore hybrid schemes, these include several cumbersome assumptions. We develop and test, both numerically and experimentally, a hybrid localization algorithm which surpasses the limitations of previous fusing approaches. The proposed method (FLORIS) is based on a nonconvex least-squares joint formulation, for which a tight convex relaxation is applied to obtain a semidefinite program. Numerical simulations show that FLORIS has comparable performance to state-of-the-art methods, even outperforming them in some scenarios. Real experiments show that FLORIS is feasible in practical application scenarios, achieving very good accuracy and robustness. Importantly, coverage requirements for the infrastructure in a given area are more flexible than resorting to a single type of sensor, which may simplify practical deployments.