Echolocating bats can make nocturnal flights in acoustically cluttered environments with the use of echolocation. Their marvelous ability to evaluate natural targets in complete darkness provides us an opportunity to learn target detection, classification, and identification with similar biomimetic platforms. In this work, natural landmark classification with a binaural system, a sequential sensing strategy, and a frequency after reconstruction algorithm are adopted to provide sequential acoustic images for target classification. Experimental results suggest that considerable improvements in classification accuracy can be achieved by the use of this sequential classification method.