In indoor environment that elderlies live, ultrasonic array sensors which are believed to protect their privacy, are hid-den in the walls for collecting distance signals of all things in the place. The distance signals in term of array which are assumed as distance images are then needed to process for detecting elderly fall. This paper discusses how to process these distance images for fall detection by using machine learning. First of all, moving objects in the indoor environment are detected by subtraction between neighboring frames, all continuing frames of moving objects are classified by machine learning, and classification results of all frames are finalized to recognize elderly fall. The experiments with some samples and constructed prototype based on the fall standard are performed, and the results reveal good performance in accuracy.