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This article investigates the use of angles of arrival (AOAs) in addition to time differences of arrival (TDOAs) for the simultaneous localization of sources and sensors. Based on the notation that both kinds of measurements come from the same set of sources and sensors, new corollaries that govern the rank properties of the matrices formed by the noise free observations are derived. The rank properties are exploited for the noise reduction of TDOAs, the recovery of times of flight (TOFs) and the joint localization of sources and sensors. The utilization of both types of measurements provides more effective TDOA enhancement and TOF recovery. It also enables a closed-form localization solution that is more resilient to noise and simpler to evaluate, compared to using either one. Furthermore, the relative localization ambiguity reduces to translation only. Simulations validate the usefulness of the rank properties and demonstrate the performance of the algorithms.