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An ultra-wideband radar human body action recognition method based on a deep convolutional neural network

A human action recognition and ultra-wideband radar technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as low recognition rate, achieve high recognition accuracy, improve recognition rate, and improve recognition accuracy. Effect

Inactive Publication Date: 2019-06-28
GUILIN UNIV OF ELECTRONIC TECH
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AI Technical Summary

Problems solved by technology

[0005] What the present invention aims to solve is the problem of low recognition rate when using radar as a sensor to perceive and recognize human body movements, and provides an ultra-wideband radar human body movement recognition method based on a deep convolutional neural network

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  • An ultra-wideband radar human body action recognition method based on a deep convolutional neural network
  • An ultra-wideband radar human body action recognition method based on a deep convolutional neural network
  • An ultra-wideband radar human body action recognition method based on a deep convolutional neural network

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific examples.

[0035] Ultra-wideband (Ultra-Wide-Band, UWB) radar, also known as pulse radar, is widely used in precise positioning, target recognition and other research. Ultra-wideband refers to one of the main technical characteristics of this radar - occupying a very large bandwidth. UWB radars generally do not use carrier waves, but time-domain pulses to transmit information. The most commonly used transmitting signal is a carrier-free signal in the form of a narrow pulse. Although this signal is limited by the average power and thus limits the range of the radar, it is very suitable for the study of target characteristics. In the present invention, this signal is used to perceive and analyze For human body movements, Gaussian signals are often used in theoretical research to repr...

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Abstract

The invention discloses an ultra wide band radar human body action recognition method based on a deep convolutional neural network. The method comprises the following steps: firstly extracting distance-time two-dimensional characteristics of a human body target by utilizing high distance resolution of an ultra wide band radar and aiming at dynamic characteristics of human body actions, making up for the deficiency of single distance characteristics, and then designing a deep convolutional neural network model for training and identification, and by employing Drop-out layer, an L2 regularization item and an LRN (Local Response Normalization) layer and the like are added by optimizing and improving convolutional neural network to avoid an overfitting phenomenon and improve the recognition accuracy. Experiments prove that the method can obtain higher recognition accuracy in a plurality of human body action recognition tasks, and the method has better feasibility and effectiveness.

Description

technical field [0001] The invention relates to the technical field of human motion detection and recognition, in particular to an ultra-wideband radar human motion recognition method based on a deep convolutional neural network. Background technique [0002] Human motion detection and recognition are of great significance to safety monitoring, human-computer interaction, assisted driving, and human health monitoring. Most of the current research is based on the camera for identification. The camera has high requirements on the environment such as illumination and line-of-sight, and there is a hidden danger of privacy violation. For this reason, it is of great significance to replace the camera with other sensors to sense the motion. In view of the fact that radar has extremely low environmental requirements such as light and line-of-sight, and can even ignore static obstacles to achieve wall recognition, it has a good prospect. When using radar as a sensor to perceive and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G01S13/88G06N3/04G06N3/08
Inventor 蒋留兵魏光萌车俐杨凯郑朋汪林
Owner GUILIN UNIV OF ELECTRONIC TECH
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