Asynchronous time-of-arrival-based source localization

In this paper, asynchronous wireless source localization using time-of-arrival (TOA) measurements is studied. In TOA localization, the travel time of the signal between the source node and anchor nodes is measured and used to estimate range. In synchronous networks, the anchor nodes know when the source node starts transmission. In asynchronous networks, however, the source transmit time is unknown and TOA measurements have a positive bias due to the synchronization error which could lead to a large localization error. One way to tackle this problem is to use time-difference-of-arrival (TDOA) measurements which do not depend on the source transmission time. However, in this work, applying an alternative approach, we estimate the source transmit time as a nuisance parameter jointly with the source location. The optimal maximum likelihood (ML) estimator is derived. To avoid the ML convergence problem, a novel semidefinite programming (SDP) technique is proposed by converting the noncovex ML problem into a convex one. Computer simulations showing superior performance of the proposed SDP estimator are conducted.