Fine-grained breathing waveform reconstruction method based on MIMO millimeter wave radar
The invention belongs to the field of non-contact vital sign monitoring, and discloses a fine-grained breathing waveform reconstruction method based on an MIMO millimeter-wave radar, which comprises the following steps: setting radar parameters and carrying out data acquisition, processing the data...
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| creator | CHEN MING GUO JIAN WANG ZHEYU XIANG YASHAN WANG JUAN SUN LIJUAN WANG SHUXUAN HAN CHONG |
| description | The invention belongs to the field of non-contact vital sign monitoring, and discloses a fine-grained breathing waveform reconstruction method based on an MIMO millimeter-wave radar, which comprises the following steps: setting radar parameters and carrying out data acquisition, processing the data by using two-dimensional Fourier transform to obtain a time-distance-azimuth radar matrix, and carrying out fine-grained breathing waveform reconstruction on the basis of the time-distance-azimuth radar matrix; the method comprises the steps that a time-distance-azimuth radar matrix is obtained, reflected signals of static objects in the time-distance-azimuth radar matrix are removed through a loopback filter, a human body area is positioned through a 2D-CFAR algorithm, rotation processing, label normalization processing and data set division are conducted on I/Q components in the human body area, an IQ-Transformer model is built, radar data to be predicted are input into a trained network model, and the radar data |
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HAN CHONG</creatorcontrib><description>The invention belongs to the field of non-contact vital sign monitoring, and discloses a fine-grained breathing waveform reconstruction method based on an MIMO millimeter-wave radar, which comprises the following steps: setting radar parameters and carrying out data acquisition, processing the data by using two-dimensional Fourier transform to obtain a time-distance-azimuth radar matrix, and carrying out fine-grained breathing waveform reconstruction on the basis of the time-distance-azimuth radar matrix; the method comprises the steps that a time-distance-azimuth radar matrix is obtained, reflected signals of static objects in the time-distance-azimuth radar matrix are removed through a loopback filter, a human body area is positioned through a 2D-CFAR algorithm, rotation processing, label normalization processing and data set division are conducted on I/Q components in the human body area, an IQ-Transformer model is built, radar data to be predicted are input into a trained network model, and the radar data</description><language>chi ; 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| language | chi ; eng |
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| subjects | ANALOGOUS ARRANGEMENTS USING OTHER WAVES CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES DIAGNOSIS ELECTRIC DIGITAL DATA PROCESSING HUMAN NECESSITIES HYGIENE IDENTIFICATION LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES MEASURING MEDICAL OR VETERINARY SCIENCE PHYSICS RADIO DIRECTION-FINDING RADIO NAVIGATION SURGERY TESTING |
| title | Fine-grained breathing waveform reconstruction method based on MIMO millimeter wave radar |
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