Method for locating static human body through wall based on respiratory character

Abstract

The invention provides a method for locating a human body through a wall and belongs to the technical field of radar detection. The method comprises the following steps: 1) preprocessing echo signals of two receiving antennae to form two quick and slow time data matrixes; 2) performing moving target indication (MTI) filtering; 3) performing band-pass filtering; 4) performing fast Fourier transform (FFT) spectrum analysis on two quick and slow time data matrixes which are subjected to the band-pass filtering respectively to form two range delay-Doppler frequency (RD) data matrixes; 5) detecting two-dimensional adaptive cell average constant false alarm rate; 6) estimating the echo distance delay of a static human body corresponding to the two receiving antennae by use of a moving window extremum method on two detected RD planes to; and 7) carrying out elliptical cross positioning. The method ensures the accuracy of static human body echo delay estimation through frequency domain accumulation of respiratory character signals, combined inhibition of various different clutters and elimination of range delay fuzzy so as to realize the accurate positioning of a static human body, and has the prominent advantages of strong interference resistance, high positioning accuracy and strong practicality.

Description

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine

Login to view more

AI Technical Summary

Problems solved by technology

Because through-wall detection usually faces a complex detection environment, the scattering intensity of strong scatterers such as walls and furniture is much higher than that of a stationary human body, causing the image edges of strong scatterers to interfere with images of stationary human bodies, especially when the human body is close to strong scatterers The situation is more serious, which is not conducive to the detection and positioning based on still human images

At the same time, the complex detection environment brings serious multipath clutter and multipath echoes from static human bodies, resulting in human body image defocus and image signal-to-clutter ratio reduction, which reduces the static human body positioning performance

Aiming at the edge interference of the wall image, Ohio State University adopted the adaptive CLEAN algorithm to eliminate the wall image in the image domain. The image

Images