Abstract: In order to deal with the problem of multi-sources data fusion for a homogeneous multi-sensor system during the online measurement of an unknown target without prior knowledge or system model, this paper proposes a new fusion method based on advanced fuzzy clustering. The method utilizes the robust fuzzy clustering, which includes a noise cluster besides the normal clusters, to process the multi-sources data with the some timestamp. It avoids the disadvantage of traditional FCM-clustering-based data fusion method on selecting the number of the clusters, and can remove the ill effects of both the data sources with large system drift and the abnormal signals to the fusion result. Furthermore, an impact factor for membership function is added to guide the current fusion process by historical fusion results. The simulation results verifies the advantages of the proposed method on accuracy and real-timeness.