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High-Density(HD)Head-related transfer function(HRTF)measurements are extremely time consuming and complicated.This problem can be solved by continuously rotate a dummy head and using online de-convolution of binaural signals to obtain the HD HRTFs.In this work,we use a generalized frequency-domain adaptive filter(GFDAF)for HD HRTF measurements,which has significant better convergence performance than the normalized least mean square(NLMS)method,so as to admit faster rotation speed.The performance is validated based on a well-established HD HRTF database.