Abstract
As the size of the radar hardware platform becomes smaller and smaller, the cost becomes lower and lower. The application of indoor radar-based human motion recognition has become a reality, which can be realized in a low-cost device with simple architecture. Compared with narrow-band radar (such as continuous wave radar, etc.), the human motion echo signal of the carrier-free ultra-wideband (UWB) radar contains more abundant characteristic information of human motion, which is helpful for identifying different types of human motion. In this paper, a novel feature extraction method by two-dimensional variational mode decomposition (2D-VMD) algorithm is proposed. And it is used for extracting the primary features of human motion. The 2D-VMD algorithm is an adaptive non-recursive multiscale decomposition method for nonlinear and nonstationary signals. Firstly, the original 2D radar echo signals are decomposed by the 2D-VMD algorithm to capture several 2D intrinsic mode function (BIMFs) which represent different groups of central frequency components of a certain type of human motion. Secondly, original echo signals are reconstructed according to the several BIMFs, which not only have a certain inhibitory effect on the clutter in the echo signal, but can also further demonstrate that the BIMFs obtained by the 2D-VMD algorithm can represent the original 2D echo signal well. Finally, based on the measured ten different types of UWB radar human motion 2D echo analysis signals, the characteristics of these different types of human motion are extracted and the original echo signal are reconstructed. Then, the three indicators of the PCC, UQI, and PSNR between the original echo signals and extraction/reconstruction 2D signals are analyzed, which illustrate the effectiveness of 2D-VMD algorithm to extract feature of human motion 2D echo signals of the carrier-free UWB radar. Experimental results show that BIMFs by 2D-VMD algorithm can well represent the echo signal characteristics of this type of human motion, which is a very effective tool for human motion radar echo signal feature extraction.
Highlights
Due to the defense of national defense borders, pedestrian identification of automobile safety, and fall detection for assisting the elderly, research about human motion recognition based on radar attract interests of many researchers [1]
In this paper, inspired by all of the aforementioned papers, a novel method of feature extraction and reconstruction using the 2D-variational mode decomposition (VMD) algorithm application in human motion recognition based on carrier-free UWB radar is proposed
Step 5: Evaluate the effect of the 2D-VMD algorithm application in human motion echo signal feature extraction and reconstruction according to the Pearson correlation coefficient (PCC), Universal Image Quality Index (UQI), and Peak signal noise rate (PSNR) between the carrier-free
Summary
Due to the defense of national defense borders, pedestrian identification of automobile safety, and fall detection for assisting the elderly, research about human motion recognition based on radar attract interests of many researchers [1]. Just like EMD was originally proposed for a 1-D signal and was extended to bidimensional signals by Huang [23], Dragomiretskiy and Zosso extended the VMD method to two-dimensional VMD (2D-VMD), which can adaptively decompose an image/2D analytic signal into a few different modes of separate spectral bands which have specific directional and oscillatory characteristics [24]. In this paper, inspired by all of the aforementioned papers, a novel method of feature extraction and reconstruction using the 2D-VMD algorithm application in human motion recognition based on carrier-free UWB radar is proposed. A new novel method for feature extraction and reconstruction using 2D-VMD algorithm application in human motion recognition by carrier-free UWB radar is proposed. Each mode has a limited spectral bandwidth [18]: each mode is compact around a center pulsation determined during the decomposition
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