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Gesture recognition method based on 77GHz millimeter wave radar signals

A millimeter-wave radar and gesture recognition technology, which is applied to pattern recognition in signals, character and pattern recognition, instruments, etc., can solve the problems of increasing the application scenarios of gesture recognition technology and low amount of gesture information description

Active Publication Date: 2019-10-18
HARBIN INST OF TECH AT WEIHAI
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AI Technical Summary

Problems solved by technology

Compared with the traditional gesture recognition technology, on the one hand, it can recognize close-range gesture signals, which further increases the application scenarios of gesture recognition technology; problem, and is conducive to simplifying the design of the convolutional neural network in the later stage, and it is convenient to realize the accurate classification of various gestures

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  • Gesture recognition method based on 77GHz millimeter wave radar signals
  • Gesture recognition method based on 77GHz millimeter wave radar signals
  • Gesture recognition method based on 77GHz millimeter wave radar signals

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0050] Take four gestures as an example:

[0051] Step 1. Design the four gesture actions of ticking, radial waving, clockwise rotation and counterclockwise rotation, such as figure 2 As shown, first configure the relevant parameters of the 77GHz millimeter-wave radar. In this patent, the sampling frequency is set to 2000kHz, the frame period is 55ms, and 100 frames of data are collected each time. There are 128 chirp signals in each frame, and each chirp signal has 64 sampling points. The antenna adopts one sending and four receiving, that is, one transmitting antenna and four receiving antennas, and the corresponding gesture data is collected by three volunteers in the microwave anechoic room environment;

[0052] Step 2, the signal S will be transmitted T (t) and received signal S R (t) Mixing by a mixer to obtain a mixed signal S MIX ...

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Abstract

The invention provides a gesture recognition method based on 77GHz millimeter wave radar signals. The method comprises the following steps: acquiring intermediate frequency signals of different gesture actions through radar; innovatively utilizing an improved wavelet threshold function to preprocess a low-frequency coefficient of the wavelet threshold function so as to solve the problem that a close-range gesture cannot be recognized due to an antenna coupling phenomenon; secondly, extracting a time-distance spectrogram, a time-speed spectrogram and a time-angle spectrogram from the preprocessed intermediate frequency signal; innovatively splicing the three characteristic spectrograms to obtain the diversified characteristic diagram, and inputting the diversified characteristic diagram into the convolutional neural network for training. The problem of incomplete information expression of a traditional identification algorithm is optimized, the network structure is simplified, and a relatively good identification effect is finally obtained.

Description

technical field [0001] The invention relates to the technical field of radar signal processing and recognition, in particular to a gesture recognition method based on 77GHz millimeter-wave radar signals. Background technique [0002] Since the 21st century, with the rapid development of computer technology, human-computer interaction technology has become one of the major subject technologies today. At present, the commonly used human-computer interaction methods use mouse and keyboard as mechanical input devices. However, these methods cannot achieve simple, efficient, and highly free information interaction between humans and computers. In the development of computer and signal processing fields, gesture recognition technology has more and more application scenarios due to its vivid, vivid, intuitive and efficient expression characteristics, such as smart home systems, real-time sign language teaching systems, gesture control game systems, etc. Wait. With the rapid devel...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/28G06F2218/02G06F2218/08G06F2218/12G06F18/24G06F18/214
Inventor 赵占锋刘多周志权赵宜楠冯翔陈雄兰
Owner HARBIN INST OF TECH AT WEIHAI
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