Millimeter wave radar material identification method based on machine learning

Abstract

The invention provides a millimeter-wave radar material identification method based on machine learning, and relates to the technical field of material identification, and the method comprises the steps: collecting target envelope information through a millimeter-wave radar sensor; de-noising the electromagnetic wave envelope, and manually marking the de-noised data to generate a sample library; constructing a machine learning classifier; measuring the distance between a sensor and an object through millimeter-wave radar, and judging the material of the object by combining a machine learningclassifier. Object materials are marked by detecting millimeter waves to obtain a large number of samples, a sample library is generated, a classifier is trained through a machine learning method, andfinally the object materials are judged in combination with the machine learning classifier and the envelope of electromagnetic waves reflected by a detection object. Compared with an existing identification method, the method has the advantages of being free of damage, low in power consumption, low in cost and low in complexity, and materials of to-be-detected targets or targets made of different materials can be normally identified in non-transparent plastic bags or paper bags or plastic boxes or paper boxes.

Description

technical field

[0001] The invention relates to a material identification method, especially a machine learning-based millimeter wave radar material identification method, Background technique

[0002] With the rapid development of all walks of life, the demand for identification and detection of object materials in daily life and industrial supervision is getting higher and higher. For example, a sweeping robot needs to be able to distinguish whether the cleaning area is a carpet or a wooden board, so as to determine the best cleaning mode, and to avoid areas with water on the ground, so it is necessary to distinguish the surface material of the cleaned area; for example, the industrial cleaning industry needs to be based on different cleaning materials. And choose different cleaning agents, so the mechanized cleaning process needs to judge the material in advance. Therefore, there is an urgent need for a material detection method that can be integrated into individual lif...

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