Legs Components Micro-Doppler Estimation of Human Target Based on Doppler Radar

Abstract

The radar based human micro-motion research is a new technology rapidly developed in recent years. Radar detection of human target has advantages that other sensors do not have. The radar system is not affected by light or weather condition, which makes it possible to achieve detection in various environments. Besides, targets hidden behind obstacles can be detected, because electromagnetic waves can penetrate barriers of a certain thickness. Doppler frequency shift caused by the modulation of electromagnetic waves by the swing of hands and legs during human motion can be obtained by various signal processing methods. Separation and estimation of multi-components signals is a prerequisite for studying micro-motion characteristics of human target. Because there are a lot of aliasing in the time-frequency diagram of component with each other, separation of multi-components signals is a difficult but urgent problem at present. In addition, kinematic parameters of human legs play a key role in distinguishing human and animal targets. Therefore, in order to extract human leg signal and estimate its frequency accurately, a signal separation method based on Bezier curve fitting is proposed in this paper. Because human radar echo signals are often non-stationary time-varying signals, we need to process the collected signals with time-frequency transforms. The accuracy of this method for extracting components of legs is precise, and it has met the accuracy requirement of Micro-Doppler research. The simulation and experimental results prove the effectiveness of this method.