Multi-target detection and positioning method based on constant false alarm rate detection

Abstract

The invention provides a multi-target detection and positioning method for a life detecting radar based on constant false alarm rate detection, comprising the following steps: step A: inputting original signals, and arranging the original signals into B-SCAN maps according to the number of tracks, wherein a fast time direction includes distance information, and a slow time direction includes frequency information; step B: removing static clutters and linear trend items in the original data; step C: performing Fourier transform on all track information obtained at the same sampling time to obtain a distance-Doppler information map; step D: applying a CFAR-based target detection algorithm in a distance-Doppler domain, marking the target body on the distance-Doppler domain; and step E: determining whether there is a non-zero point in the image output by the CFAR, and performing target identification on the output result if there is a non-zero point, wherein the position information and the respiratory frequency of the output target are the same. The invention reduces false targets that occur due to interference from local strong noise.

Description

technical field [0001] The present invention relates to the technical field of life detection radar systems, in particular to a target detection and positioning method for life detection radar. Background technique [0002] In today's post-disaster rescue process, life detection radar has played a very important role, providing first-hand information for rescuers to determine whether there is life under the rubble. The life detection radar uses the principle that the radar echo reflected by the human body is periodic due to the fretting caused by human respiration and heartbeat. After removing the direct clutter, the life fretting signal can be detected in the frequency domain. In the application of life detection radar, the target detection algorithm is obviously an extremely important link, because the accuracy and efficiency of the detection algorithm largely determine the quality and effectiveness of the system results. Detecting targets based on the same threshold valu...

AI Technical Summary

Problems solved by technology

The target is detected based on the same threshold value, which will lead to an unstable false alarm rate on the entire detection plane and increase the number of false targets

In addition, on the entire detection p

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