Aiming at the accuracy of pyroelectric infrared（PIR）sensor in indoor human body positioning and recognition

a human body infrared signal sensing model is designed

and a new method of positioning and recognition is proposed.This model node uses a pair of orthogonal PIR sensors and combines with the field angle modulation of the Fresnel lens

to effectively detect human infrared signal in the horizontal and vertical directions.This method through acquiring and analyzing on time-domain output signals of this pair of PIR sensors

using peak time series characteristics of time-domain signals and correlation analysis of fusion of two sensor data

and using SoftMax classification method of machine learning algorithm to classify positions and speed levels.Experimental results show that the design method achieves accuracy of 94.79 % in levelclassification of position and speed

and has good application value in intelligent perception of indoor scenes.