Abstract: At present, variety of WLAN indoor positioning schemes have been proposed with redeploying extra wireless AP(Access Point), leading to the rise of costs and complexity. This paper make full use of existing wireless local network for indoor positioning research. In this paper, an adaptive network WKNN(Weighed K-nearest Neighbor) algorithm that matching number of APs (Access Points) was monitored real-timely to adapt to the changes of network was proposed, greatly optimizing the fingerprint algorithm. After that, on the basis of the adaptive algorithm, in order to decrease the positioning error caused by the instability of wireless signal, we provided a data correction method. In this method, the final localization coordinate was the average of predicted coordinate and measured coordinate weighted by a certain coefficient . Finally, our proposal has been tested in real environment, and verification of experiment shows that localization accuracy has been improved obviously with 33.5%.