Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Radar target recognition method based on noise backgrounds of plural AGC models

A noise background and radar target technology, applied in the field of target recognition, can solve the problems of inability to have both recognition rate and high calculation amount, and achieve the effect of improving target recognition rate and small calculation amount

Active Publication Date: 2013-12-18
XIDIAN UNIV
View PDF1 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to: provide a radar target recognition method based on the complex AGC model under the noise background, to solve the above-mentioned prior art that cannot have both the high recognition rate and the small amount of calculation under the noise background condition.

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
  • Radar target recognition method based on noise backgrounds of plural AGC models
  • Radar target recognition method based on noise backgrounds of plural AGC models
  • Radar target recognition method based on noise backgrounds of plural AGC models

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] refer to figure 1 , the implementation steps of the present invention are as follows:

[0031] Step 1, obtain training samples under the condition of high SNR.

[0032] The data in the radar database is collected under ideal conditions, and its signal-to-noise ratio is very high, usually above 30dB. The range image echo data of multiple types of targets in the database are selected as the complex range image sample set X: X={ x 1 , X 2 ,...,X c ,…X E}, where X c is the complex range image training sample of the c-th category target, c=1, 2,..., E, E represents the total number of categories of the target.

[0033] Step 2, calculate the modulus average image and variance image.

[0034] 2a) Calculate the modulus average image and variance image of the c-type target

[0035] 2a1) According to the orientation of the target, the training sample X of the complex range image of the c-class target c Divided into F frames: X c ={X c1 , X c2 ,…X ck ,…X cF}, k=1, 2, ...

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 radar target recognition method based on noise backgrounds of plural AGC models. The radar target recognition method mainly solves the problems that high recognition rate and small amount of computation can not be achieved at the same time when target recognition is carried out in a noise background in the prior art. The radar target recognition method includes the steps of using radar repeated distance image training samples to calculate variance images of the radar repeated distance image training samples, calculating signal to noise ratio of radar repeated distance image testing samples, correcting the variance images of the repeated distance image training samples according to the signal to noise ratio, and calculating decision values of posteriori probabilities of lower classes of each category according to the corrected variance images and the repeated distance image testing samples to determine target category labels. The radar target recognition method has the advantages of being high in recognition rate and small in amount of computation under the noise backgrounds, and being applicable to radar target recognition.

Description

technical field [0001] The invention belongs to the technical field of radar and relates to a target identification method, which can be used to identify targets such as airplanes and vehicles under the background of noise. Background technique [0002] The high-resolution distance image is the vector sum of the target scattering point echo projected in the radar ray direction of the broadband radar signal, which can provide the approximate distribution of the target scattering point echo in the distance direction, which is of great value for target identification, so it has become a radar Research hotspots in the field of object recognition. [0003] The recognition method based on statistical model is an important automatic target recognition method of radar high-resolution range profile. The statistical identification of one-dimensional high-resolution range image refers to the identification method of determining the class belonging of the test sample according to the c...

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 Applications(China)
IPC IPC(8): G01S7/41
Inventor 杜兰袁希望王鹏辉和华刘宏伟
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com