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Human behavior classification method based on multi-station radar micro Doppler motion direction finding

A technology of micro-Doppler motion and classification method, which is applied in the direction of measuring device, radio wave measurement system, radio wave reflection/re-radiation, etc., can solve the problems such as the decline in the accuracy rate of human behavior classification, and achieve accurate and robust multi-station Effects of Radar Micro-Doppler Human Behavior Classification, Reduction of Dependency, Simplification of Fusion Network Structure

Active Publication Date: 2021-09-03
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, since the azimuth and angle of the human body are constantly changing during the actual movement, there are certain differences in the micro-Doppler information of the human body obtained by the same radar at different times or at different positions. Leading to a decline in the accuracy of human behavior classification

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  • Human behavior classification method based on multi-station radar micro Doppler motion direction finding
  • Human behavior classification method based on multi-station radar micro Doppler motion direction finding
  • Human behavior classification method based on multi-station radar micro Doppler motion direction finding

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Embodiment 1

[0067] This embodiment explains: the process of applying the "human behavior classification method based on multi-station radar micro-Doppler motion direction finding" of the present invention to the actually collected human behavior classification.

[0068] In this example, the experimental system is ANCORTEK SDR-KIT 580B radar, and the parameters are set as follows: carrier frequency 5.8GHz, transmit waveform continuous wave, transmit power 19dBm, scan time 10ms, sampling points 128 points, acquisition time 5s. The multi-station radar structure adopted in this embodiment is as follows: figure 2 As shown, it contains one transmitting antenna and three receiving antennas. Wherein, the receiving antenna 1 and the transmitting antenna are placed together to form a monostatic radar system. The receiving antenna 2 and the receiving antenna 3 are separately placed on both sides of the transmitting antenna, and form a bistatic radar system with them. Since the equipment used is a...

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Abstract

The invention discloses a human behavior classification method based on multi-station radar micro Doppler motion direction finding, and belongs to the field of radar target detection signal processing. According to the implementation method, azimuth angles of human motion relative to different radar receivers are measured in real time by using a human motion direction estimation method based on multi-station radar Doppler frequency. The method comprises the following steps: performing interval division on multi-station data according to different influences of measured angle values and different azimuth angles on classification performance, performing data-level fusion according to divided intervals, and performing feature extraction and classification on the data of different intervals by using a dual-channel convolutional principal component analysis network (CPCAN), and carrying out adaptive weighted decision level fusion on classification results of the two channels to obtain a final behavior category result. According to the method, the influence of the micro Doppler data caused by the movement azimuth change is fully considered, so that a multi-station classification network structure can be simplified, and better classification performance and a more stable classification effect are achieved.

Description

technical field [0001] The invention relates to a human behavior classification method based on multi-station radar micro-Doppler motion direction finding, and belongs to the field of radar target detection signal processing. Background technique [0002] Human behavior monitoring and gait recognition are of great value in modern life. After decades of research, human behavior recognition technology has made great progress, and various methods have been proposed. Currently, commonly used human behavior and health monitoring methods include: wearable devices (accelerometers, three-axis gyroscopes), video, infrared , radar, etc. Compared with other methods, radar monitoring has the following advantages: First, radar detects by actively emitting electromagnetic waves with low power consumption and harmless to the human body. Discomfort caused by users and easy to be lost; Second, the electromagnetic wave signal emitted by the radar has a strong propagation ability, a long det...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41G01S13/87G01S13/88G06K9/00G06K9/62G06N3/04
CPCG01S7/415G01S13/87G01S13/88G06N3/045G06F2218/12G06F18/2135G06F18/2411G06F18/253Y02A90/10
Inventor 陶然乔幸帅单涛白霞赵娟
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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