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Millimeter wave radar sparse point cloud reconstruction method based on multi-step neural network structure

A millimeter-wave radar and network structure technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as reconstruction of millimeter-wave radar sparse point clouds, achieve the effect of reducing data dimensions and improving training effects

Pending Publication Date: 2022-04-29
矽杰微电子(厦门)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In the literature, there is currently no efficient method for reconstructing sparse point clouds from mmWave radar

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  • Millimeter wave radar sparse point cloud reconstruction method based on multi-step neural network structure
  • Millimeter wave radar sparse point cloud reconstruction method based on multi-step neural network structure
  • Millimeter wave radar sparse point cloud reconstruction method based on multi-step neural network structure

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[0058] The following description serves to disclose the present invention to enable those skilled in the art to carry out the present invention. The preferred embodiments described below are only examples, and those skilled in the art can devise other obvious variations. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents and other technical solutions without departing from the spirit and scope of the present invention.

[0059] In the preferred embodiment of the present invention, those skilled in the art should note that the electronic equipment and storage media involved in the present invention can be regarded as prior art.

[0060] preferred embodiment.

[0061] The invention discloses a method for reconstructing a sparse point cloud of a millimeter-wave radar based on a multi-step neural network structure, comprising the following steps:

[0062]Step S1: Obtain the...

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Abstract

The invention discloses a millimeter-wave radar sparse point cloud reconstruction method based on a multi-step neural network structure, and the method comprises the steps: S1, obtaining first information including speed, angle and distance through a millimeter-wave radar, and carrying out the Fourier transformation of the obtained speed and distance, and taking the generated speed and distance spectrogram as a first target feature. According to the millimeter wave radar sparse point cloud reconstruction method based on the multi-step neural network structure disclosed by the invention, radar sparse point cloud information is directly normalized through a feed forward neural network to predict high-resolution point cloud information, and a brand-new algorithm is provided for the millimeter wave radar sparse point cloud problem.

Description

technical field [0001] The invention belongs to the technical field of millimeter-wave radar point clouds, and in particular relates to a reconstruction method for millimeter-wave radar sparse point clouds based on a multi-step neural network structure. Background technique [0002] With the rapid development of intelligent perception technology, millimeter-wave radar, as one of the intelligent sensors, has been widely used in object detection and recognition tasks. In the field of automatic driving, millimeter-wave radar is often used as an auxiliary sensor in conjunction with cameras and lidar to achieve high-level automatic driving functions. Compared with lidar and cameras, millimeter-wave radar has the advantage of being able to detect object speed and distance information, with low cost and suitable for various weather and light conditions. However, millimeter-wave radar has a very big defect that its resolution is low, and the point cloud obtained in the field of aut...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06V10/762G06K9/62
CPCG06N3/08G06N3/045G06F18/23213
Inventor 杨澄思卢煜旻朱欣恩
Owner 矽杰微电子(厦门)有限公司