This paper proposes a fuzzy line of sight (LOS)/non-line of sight (NLOS) smoother based on an adaptive Kalman filter, which can be used for mobile location estimation with the time of arrival (TOA) measurement data in cellular networks to meet the Federal Communications Commission (FCC) requirement for phase . A fuzzy inference scheme is used by the proposed location estimator to detect LOS condition, NLOS condition or LOS/NLOS transition condition and to estimate the noise covariance via fuzzy interpolation. With an accurate estimation of noise covariance, an adaptive Kalman filter is proposed for the range estimation between the base station (BS) and mobile station (MS). Therefore, the proposed mobile location estimator can efficiently mitigate the NLOS effects of the simulated measurement range error even changing condition between LOS and NLOS. Simulation results demonstrate that the performance of the proposed fuzzy LOS/NLOS smoother is improved significantly over the FCC target in both fixed LOS/NLOS and LOS/NLOS transition condition, and outplays other location estimators employing the Kalman filter and NLOS mitigation techniques.