The advent of location based services has increased the need for accurate positioning of mobile stations (MS). Global Positioning Systems (GPS) is not reliable in indoor and urban environments. Cellular wireless communication systems like the OFDM based 3GPP-LTE provide an alternative via Time Difference of Arrival (TDoA) measurements. Typical Extended Kalman Filter (EKF) algorithms using TDoA make certain assumptions about the mobility model and associated noise statistics of the MS. In this paper, we develop an alternate formulation of the TDoA localization problem and adaptive EKF algorithm that does not make the assumptions made by traditional EKF algorithms. We demonstrate that the proposed algorithm gives better position estimates than a static positioning estimator. © 2016 IEEE.