Gait based behavior recognition technology is a new human-computer interaction technology,which plays an important role in many fields such as security monitor ing,image pr ocessing and soon.At present,among all kinds of behavior recognition technologie s,the tech nology based on commercial WiFi equipment is widely used because of its advantag es of easy deployment,low cost of equipment and low requirements for application environment.The existing gait recognition research can only recognize the human gait,but can not recognize the age according to the gait.In this paper,we discuss the F resnel region theory,and propose an age recognition method based on WiFi physical layer infor mation. That is,using gait to recognize age.This work use Fresnel zone model to learn gait fe atures.Firstly, we denoise the motion data set to collect channel state information (CSI).Then, based on the Fresnel region model,the eigenvalues of the channel phase information are extra cted to describe the gait action.Finally,the classification algorithm is used to reali ze the age recognition.Experimental results show that the method has good robustness,and the average recognition accuracy in different experimental environments reaches 91.2%.There fore,the system proposed in this paper can be applied to complex indoor scenes,a nd has a wide range of application prospects.