Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition
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...
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| Format: | Article |
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MDPI AG
2019-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/9/1962 |
| _version_ | 1811302248429387776 |
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| author | Liubing Jiang Xiaolong Zhou Li Che Shuwei Rong Hexin Wen |
| author_facet | Liubing Jiang Xiaolong Zhou Li Che Shuwei Rong Hexin Wen |
| author_sort | Liubing Jiang |
| collection | DOAJ |
| description | 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 <i>PCC</i>, <i>UQI</i>, and <i>PSNR</i> 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. |
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| language | English |
| last_indexed | 2024-04-13T07:24:38Z |
| publishDate | 2019-04-01 |
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| spelling | doaj.art-4f9f23e9b8ea4d98ae8e2bd864841ad22022-12-22T02:56:30ZengMDPI AGSensors1424-82202019-04-01199196210.3390/s19091962s19091962Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion RecognitionLiubing Jiang0Xiaolong Zhou1Li Che2Shuwei Rong3Hexin Wen4School of Computer and Information Security, Guilin University of Electronic Technology, Guilin 541004, ChinaKey Laboratory of Wireless Broadband Communication and Signal Processing in Guangxi, Guilin University of Electronic Technology, Guilin 541004, ChinaSchool of Computer and Information Security, Guilin University of Electronic Technology, Guilin 541004, ChinaKey Laboratory of Wireless Broadband Communication and Signal Processing in Guangxi, Guilin University of Electronic Technology, Guilin 541004, ChinaKey Laboratory of Wireless Broadband Communication and Signal Processing in Guangxi, Guilin University of Electronic Technology, Guilin 541004, ChinaAs 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 <i>PCC</i>, <i>UQI</i>, and <i>PSNR</i> 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.https://www.mdpi.com/1424-8220/19/9/1962carrier-free UWB Radarhuman motion recognition2D-VMD algorithmfeature extractionreconstruction |
| spellingShingle | Liubing Jiang Xiaolong Zhou Li Che Shuwei Rong Hexin Wen Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition Sensors carrier-free UWB Radar human motion recognition 2D-VMD algorithm feature extraction reconstruction |
| title | Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition |
| title_full | Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition |
| title_fullStr | Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition |
| title_full_unstemmed | Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition |
| title_short | Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition |
| title_sort | feature extraction and reconstruction by using 2d vmd based on carrier free uwb radar application in human motion recognition |
| topic | carrier-free UWB Radar human motion recognition 2D-VMD algorithm feature extraction reconstruction |
| url | https://www.mdpi.com/1424-8220/19/9/1962 |
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