Aiming to decrease the time complexity of both the train and the prediction process in indoor target tracking using radio fingerprints in wireless sensor networks, a novel method is proposed in this paper, which is an ideal solution for portable devices tracked in large area. A local match of the anchors and reference positions is introduced before applying the weighted K-nearest neighbors, which significantly decreases the complexity of positioning target. The Kalman filter is used forward with the previous positioning based on acceleration information to further increase the estimation accuracy. The performance of the method is studied thoroughly, indicating an average tracking accuracy of 1.4 m with the reference positions uniformly distributed at 10 m distance and the noise standard deviation of 16. Result shows that the proposed method is applicable for mobile target tracking in indoor environment.