The invention relates to an indoor localization method based on clustering algorithm analytical data optimization, which is used for carrying out accurate localization on an unknown node in a complex index environment. The indoor localization method comprises the steps of: executing an RSSI (Received Signal Strength Indicator) signal processing optimization strategy, i.e., optimizing an RSSI value by using a clustering analysis Gaussian hybrid filtering model so as to eliminate the problems of dispersed intersection and serious jitter of the RSSI value, which exist due to factors of a multipath effect, a barrier and the like, and obtain one more reliable and reasonable RSSI value; adopting a fitting RSSI distance measurement model, i.e., according to an RSSI-distance conversion curve, carrying out fitting of the curve by adopting a least square method so as to obtain a logarithm path loss model suitable for a current environment; and then estimating out position information of the unknown node by using a weighted centroid localization algorithm. According to the indoor localization method disclosed by the invention, by an optimal RSSI distance measurement algorithm, accuracy of localization and distance measurement is improved, so that adaptability and localization accuracy of the localization algorithm are improved; and the indoor localization method is suitable to apply and popularize in the complex indoor environment.