In this paper, a multi-target recognition and distance detection method based on PE-Kmeans++ and HOC algorithm is proposed and tested experimentally. Firstly, the radar echo signal is preprocessed, and the number and distance of human targets are estimated based on PE-Kmeans++ algorithm. Then the body surface vibration signals of different targets are extracted to detect the vital signs of single target respectively. The respiration signal and heartbeat signal are restored according to the frequency range of respiration and heartbeat, and the corresponding peak frequency is extracted as the respiration and heartbeat frequency by the algorithm of HOC-FFT. Experimental results show that the proposed algorithm can accurately identify multiple human targets in the environment without complex preprocessing of the original echo signal.
KEYWORDS: Signal detection, Radar, Radar signal processing, Signal processing, Signal to noise ratio, Linear filtering, Interference (communication), Vital signs, UWB radar, Electronic filtering
In order to improve the signal-to-noise ratio of ultra-wideband radar life detection echo signals, analyze the causes and types of ultra-wideband radar signal noise, build echo signal models in real measurement environments, and study various mechanisms for dealing with noise. Taking a human body with vital signs as an example, the radar signal echoes at a distance of 1m, 2m and 4m from the radar are tested, the radar signal waves are obtained, and the noise is targeted according to the type of clutter. The results show that the useless signal in the original echo matrix signal is reduced and the signal-to-noise ratio is improved. The local normalization method and automatic gain control method are used to automatically enhance the processed signal strengthened before.
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