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A Neural Network-Based Collaborative Target Detection and Recognition Method of Millimeter-Wave Radar and Vision

A millimeter-wave radar and neural network technology, applied in the field of millimeter-wave radar and vision collaborative target detection and recognition, can solve the problems of low accuracy, occupied time, missed detection, etc. Check the effect of the phenomenon

Active Publication Date: 2021-05-25
烟台芯扬聚阵微电子有限公司
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Problems solved by technology

The former takes a lot of time to obtain the region of interest and becomes the main time bottleneck of the target detection algorithm; the latter has low accuracy in identifying small objects and is prone to missed detection.

Method used

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  • A Neural Network-Based Collaborative Target Detection and Recognition Method of Millimeter-Wave Radar and Vision
  • A Neural Network-Based Collaborative Target Detection and Recognition Method of Millimeter-Wave Radar and Vision
  • A Neural Network-Based Collaborative Target Detection and Recognition Method of Millimeter-Wave Radar and Vision

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[0040] The present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments, and the purpose and effect of the present invention will become clearer. It should be understood that the specific embodiments described here are only used to explain the present invention and are not intended to limit the present invention.

[0041] figure 1 It is an algorithm flow chart of the present invention.

[0042] The millimeter-wave radar emits high-frequency millimeter waves, which are collected by the receiving system after being reflected by the target, and the distance of the target is determined by frequency measurement, thereby forming point cloud data. After the image data captured by the camera at the same time is scaled to 256x256, it is sent to the DarkNet-53 network structure for processing, and an image feature map with a size of n×n×c is obtained. Such as figure 2 It is the network structure diagram of DarkNet-53.

[0...

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Abstract

The invention relates to a neural network-based millimeter-wave radar and vision collaborative target detection and recognition method. The millimeter-wave radar can obtain information such as the position and speed of an object by emitting and receiving millimeter waves, and the camera can obtain the visual image of the object. The position information obtained by the millimeter-wave radar is mapped to the image, and then the region of interest is delineated in the image feature map and sent to the deep learning neural network for processing, that is, the identification and positioning information of the target can be obtained. The invention adopts the fusion of millimeter-wave radar and visual processing to complete the task of target detection and recognition. With the help of deep learning neural network technology, it not only shortens the time for locating objects, but also increases the accuracy of recognition.

Description

technical field [0001] The invention relates to the field of target recognition and positioning by sensor fusion, in particular to a neural network-based millimeter-wave radar and vision collaborative target detection and recognition method. Background technique [0002] At present, the known image target recognition and positioning algorithms mainly use neural networks to directly process images, mainly including RCNN series, YOLO series, SSD and so on. These neural network processing methods are mainly divided into two types: one is to extract the region of interest on the image through exhaustive search or neural network structure, and then send the region of interest to the neural network for position regression and category recognition; the other is Use neural networks to directly regress object locations and classes across images. The former takes a lot of time to obtain the region of interest and becomes the main time bottleneck of the target detection algorithm; the...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/62G01S7/41G06N3/08
CPCG01S7/417G06N3/08G06V20/10G06V20/62G06F18/23213
Inventor 宋春毅宋钰莹徐志伟赵自豪陈钦
Owner 烟台芯扬聚阵微电子有限公司
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