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In this paper, we introduce a new algorithm λ -WFC based on fuzzy cluster into the indoor location of WSN. First, a location fingerprint database is set up and we calculate an optimal value of λ which is a threshold for classifying the RSS vectors in the off-line training phase. Then in the locating phase, after fuzzy clustering has been done, we estimate the degree of similarity between two vectors by Jffreys&Matusita formula, and assign different weights to the coordinates of reference nodes to calculate the location of the unknown node. Finally it is proved in our simulation experiments that this algorithm could be effective to avoid the dilemma caused by the multipath and abnormal signal attenuation as well as that it has the advantages of low complexity, fast execution, high accuracy and practical applicability for the large-scale of indoor location of WSN.