SAR Target Recognition Method Based on CNN

A target recognition and to-be-recognized technology, applied in the field of radar, can solve the problem of reducing the recognition rate, and achieve the effect of sufficient sample size, good fit, and improved recognition rate

Active Publication Date: 2018-04-17
XIDIAN UNIV
View PDF3 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the target area to be identified in the sample obtained by actual SAR imaging will be at any position in the SAR image, and the existing target recognition method is greatly affected by the position of the target area, resulting in a decrease in the recognition rate.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • SAR Target Recognition Method Based on CNN
  • SAR Target Recognition Method Based on CNN
  • SAR Target Recognition Method Based on CNN

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] refer to figure 1 , the recognition method of the present invention includes two stages of training and testing, and the specific steps are as follows:

[0023] 1. Training stage

[0024] Step 1, obtain SAR image training samples and test samples.

[0025] The data used in the experiment is the public MSTAR dataset. The MSTAR dataset used in this experiment includes three types of targets with pitch angles of 15° and 17°: BMP2, BTR70 and T72. In the experiment, the image data at a pitch angle of 17° is selected as a training sample. The original training samples are 698 target images and corresponding category labels. The image data at a pitch angle of 15° is selected as a test sample. The original test samples are 1365 target images and corresponding class labels. The category labels of all samples are 128*128 pixels in size, and the target area to be recognized of all original sample images is in the center of the image.

[0026] In step 2, the target area of ​​the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a CNN-based SAR target recognition method, the implementation steps of which are as follows: 1. Perform multiple random translation transformations on the target to be recognized in each training image to obtain new samples, and mark these new samples with original The label of the image is expanded into the training sample; 2. Construct the CNN structure of the convolutional neural network in the caffe architecture; 3. Input the expanded training sample into the CNN for training to obtain the trained network model; 4. Test the sample Multiple times of translation and expansion to obtain the expanded test samples; 5. Input the expanded test samples into the trained CNN network model for testing to obtain its recognition rate. The invention has high recognition rate and stable performance for the target to be recognized at any position of the sample image, and solves the problem that the existing SAR target recognition method is greatly affected by the position of the target to be recognized in the sample image.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a radar target recognition method, which is used to solve the problem of translation sensitivity of the existing target recognition method to the target to be recognized in SAR images. Background technique [0002] Synthetic aperture radar (SAR) has the characteristics of all-weather, all-time, high resolution and strong penetrating power, and is widely used in the fields of military reconnaissance and remote sensing. Radar imaging technology has unique advantages in detecting ground targets, especially ground stationary targets. With the continuous maturity of SAR technology and the continuous improvement of imaging resolution, target recognition technology through SAR images has received more and more attention. [0003] Convolutional neural network (CNN) is a kind of artificial neural network, which has become a research hotspot in the field of speech analysis and im...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/08
Inventor 陈渤丁军黄孟缘
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap