Radar target identification method based on label maintaining multitask factor analyzing model

A factor analysis model and radar target technology, applied in the field of radar target recognition, can solve the problems of not using beneficial data category information for classification, model recognition performance is not ideal, etc.

Active Publication Date: 2017-02-22
XIDIAN UNIV +1
View PDF2 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the multi-task factor analysis model proposed in this article is the same as the traditional factor analysis model. It is an unsupervised model and does

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 identification method based on label maintaining multitask factor analyzing model
  • Radar target identification method based on label maintaining multitask factor analyzing model
  • Radar target identification method based on label maintaining multitask factor analyzing model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The present invention carries out radar target identification based on the label keeping multi-task factor analysis model, and the model is solved by Gibbs sampling technique. The reason for using the Gibbs sampling technique is that the label-preserving multi-task factor analysis model can be described by a probability framework, so it can be estimated by the Gibbs sampling algorithm, which greatly simplifies the complexity of the model solution.

[0039] refer to figure 1 , the statistical identification method based on the tag-keeping multi-task factor analysis model of the present invention is divided into two steps of training and testing, specifically described as follows:

[0040] 1. Training steps

[0041] Step 1: Divide the azimuth frame for the received radar high-resolution range image HRRP.

[0042] The high-resolution range image HRRP obtained by the radar is divided into multiple data segments at equal intervals according to the target azimuth, and each ...

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 identification method based on a label maintaining multitask factor analyzing model and mainly solves the problem that the prior art is poor in target identification performance under a small sample condition. The radar target identification method includes the steps of firstly, performing normalization and alignment pretreatment on a radar high range resolution profile; secondly, using the preprocessed high range resolution profile to build a label maintaining multitask factor analyzing model; thirdly, performing Gibbs sampling on the parameters of the model, and saving sampling average of the model parameters; fourthly, performing normalization and alignment pretreatment on a to-be-tested sample; fifthly, calculating the frame probability density function value of the to-be-tested sample according to the sampling average, learned by the training steps, of the parameters of the label maintaining multitask factor analyzing model; sixthly, judging the category attribute of the to-be-tested sample according to the frame probability density function value. The radar target identification method has the advantages that supervised learning of the model is achieved, the identification performance under the small sample condition is increased, and the method is applicable to the radar target identification under the small sample condition.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to a radar target recognition method, which can be used for statistical target recognition of radar high-resolution range profile HRRP. Background technique [0002] The high-resolution range profile HRRP is the superposition of projections of broadband radar target scattering point echoes along the radar line of sight direction, which reflects the distribution of the scattering cross-sectional area of ​​the target scatterer along the radar line of sight direction, including the size of the target and the distribution of scattering points, etc. Rich structural information. As an important feature of radar targets, high-resolution range images are easy to obtain and process, and have become a research hotspot in the field of radar target recognition. [0003] Statistical identification based on Bayesian theorem refers to determining the class belonging of the test sample according to ...

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
IPC IPC(8): G01S7/41
CPCG01S7/418
Inventor 杜兰胡靖陈健李洋和华刘宏伟
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