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Gesture radar signal processing method based on RDTM and ATM fusion

A radar signal processing and baseband signal technology, applied in the direction of radio wave reflection/re-radiation, using re-radiation, measurement devices, etc., can solve problems such as large data sets, clutter and noise, complex network structure, etc.

Active Publication Date: 2020-05-15
CENT SOUTH UNIV
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Problems solved by technology

The "range-Doppler-time map" generated by this method has more clutter and noise and requires a large amount of data sets. The network structure is complex, and the recognition accuracy is about 93%. In terms of network structure design and recognition effect, there are still relatively large [References: Xia Chaoyang, Zhou Chenglong, Jie Junyu, Micro gesture recognition based on multi-channel FM continuous wave millimeter-wave radar, Journal of Electronics and Information Technology, 2020, 42(1): 164-172]

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  • Gesture radar signal processing method based on RDTM and ATM fusion
  • Gesture radar signal processing method based on RDTM and ATM fusion
  • Gesture radar signal processing method based on RDTM and ATM fusion

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Embodiment Construction

[0077] A kind of gesture radar signal processing method based on RDTM and ATM fusion, comprises the following steps,

[0078] A. The gesture radar emits a linear frequency modulation signal, detects the gesture and records the echo, and obtains the intermediate frequency signal after mixing and sampling; the intermediate frequency echo x 0 (t) is a complex signal, including two mutually orthogonal baseband signals. Let the radar echo recorded by a single gesture include L frames, each frame includes M intermediate frequency signals, and the number of sampling points of each intermediate frequency signal after A / D sampling is N points; 0 (t) rearrange to obtain a two-dimensional signal x(n, t); 1≤n≤N, 1≤t≤T, where T=L×M is the intermediate frequency echo x 0 (t) the total number of IF signals. Perform moving target display processing on x(n, t), suppress interference signals, and obtain a two-dimensional signal S IF (n,t);

[0079] For x(n, t) to display the moving target, ...

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Abstract

The invention discloses a gesture radar signal processing method based on RDTM and ATM fusion. The method comprises the steps of A, carrying out detection on a gesture, recording an intermediate frequency signal, and carrying out two-dimensional rearrangement and moving target display processing on a one-dimensional intermediate frequency echo; B, performing framing rearrangement to obtain L frames of echo signals; c, performing two-dimensional windowing processing on each single-frame signal; D, performing two-dimensional Fourier transform and modulus operation on the windowed single-frame signal to obtain RDM; E, conducting wavelet decomposition, wavelet coefficient processing and wavelet reconstruction processing on each column of data of the RDM to obtain the reconstructed RDM; F, performing combination and mask processing on the RDM obtained by the L frames of echo signals to obtain an RDTM; G, performing data processing on the intermediate frequency echoes received by all receiving antennas according to a virtual array antenna mode to obtain an ATM; H, performing image fusion on the RDTM and the ATM; and I, completing image classification through a neural network to perform gesture recognition. According to the method, the defects in the prior art can be overcome, and the gesture recognition accuracy is improved by 7.5%.

Description

technical field [0001] The invention belongs to the technical field of gesture radar detection and application, in particular to a gesture radar signal processing method based on the fusion of RDTM and ATM. Background technique [0002] Human hand gesture recognition is a new technology that has emerged in recent years. It uses optical or radar sensors to distinguish human gestures and is used in human-computer interaction fields such as games, industrial control, medical care, and automotive electronics. In the field of gesture recognition research, research on gesture recognition using camera-based, computer vision, and wearable devices has been extensively conducted. However, gesture recognition based on cameras and computer vision is highly dependent on the surrounding environment. For example, in low light conditions, the performance of optical sensors will be significantly reduced or even invalidated. The main disadvantage of wearable devices is that users must wear t...

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Application Information

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IPC IPC(8): G01S13/88G01S7/36
CPCG01S13/88G01S7/36
Inventor 雷文太谭倩颖江文思王驰誉许孟迪
Owner CENT SOUTH UNIV
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