Joint localization and clock offset estimation via time-of-arrival with ranging offset

We develop a novel algorithm for Geo-Spatial location estimation for Internet of Things (IoT) networks by utilizing a One-Way Time-of-Arrival (OW-TOA) technology. Although very popular, OW-TOA based localization techniques are negatively affected by three phenomena: i) wireless connectivity between the target and the receiving nodes is not guaranteed (audibility), resulting in likelihood surface which may produce a non-unique maxima; ii) clock offset imperfection which is a result of a fixed deviation from a reference clock; and iii) a ranging offset which introduces distance dependent bias to the OW-TOA measurements. We develop a new statistical framework which incorporates these aspects and then derive the joint localization and clock offset Maximum Likelihood Estimator to jointly estimate the location of the target and the clock offset. To solve the resulting non-convex optimization problem we propose to use the Cross-Entropy method.