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Falling is a common health problem for elderly. It is reported that more than one third of adults 65 and older fall each year in the United States. To address the problem, we are currently developing an acoustic fall detection system, FADE, which automatically detects a fall and reports it to the caregiver. In a previous version, FADE used a 3-microphone linear array to eliminate the false alarms produced by sounds produced well above the floor level. To improve the fall detection in noisy and reverberant environments, we replaced the linear array by an 8-microphone circular array that can provide a better 3-D estimation of the sound location. Preliminary experiments show that the sound location estimation performed by the circular array is reliable and robust to interference. We obtained encouraging classification results on a pilot dataset with 55 falls and 120 non-fall sounds.