Stationary human micro-motion trajectory extraction based on edge detection in through-the-wall radar
Stationary human micro-motion trajectory in slow time range domain provides more original motion information, including periodical respiration and heart beating, as well as random body movement and sudden body shaking, whose range often outstrips the periodical movement. Phase contour, amplitude contour and peak locus are all the represent of stationary human micro-motion trajectory. Due to the phase sudden change from π to -π, the phase contour is more robust and stable than the other two loci. In this paper, a stationary human micro-motion trajectory extraction approach based on edge detection is presented. Firstly, the stationary human micro-motion model is established and the effect brought by the wall is analyzed. Then the phase contour in slow-time range domain is introduced as a representation of micro-motion trajectory. Finally, the phase contour extraction based on edge detection is presented. Experimental results demonstrate that the proposed approach can extract stationary human trajectory correctly and accurately, after band pass filtering, the vital sign of human breathing can be extracted effectively.