An ionospheric phase scintillation detection method based on nonlinear SVM algorithm

A technology of phase scintillation and detection method, which is applied in computing, computer components, instruments, etc., and can solve the problems of phase scintillation and the accuracy needs to be improved.

Active Publication Date: 2019-03-22
SOUTHEAST UNIV
View PDF6 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The most common ionospheric phase scintillation detection method is based on experience, by judging the phase scintillation index Whether it exceeds a certain threshold, if it exceeds the threshold, it is judged that phase flicker has occurred. Since this method is limited by the non-optimized empirical threshold, its accuracy needs to be improved

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
  • An ionospheric phase scintillation detection method based on nonlinear SVM algorithm
  • An ionospheric phase scintillation detection method based on nonlinear SVM algorithm
  • An ionospheric phase scintillation detection method based on nonlinear SVM algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] Below in conjunction with the accompanying drawings, a kind of ionospheric phase scintillation detection method based on nonlinear SVM algorithm proposed by the present invention is described in detail:

[0049] The present invention implements a nonlinear SVM algorithm based on machine learning, and its overall structure is as follows figure 1 As shown: First, the signal measured in the receiver is processed to extract the characteristic parameters and marked. The specific methods are as follows: use the phase data to detrend the signal measured in the receiver, the low bandwidth design of the receiver carrier loop and the geometric phase After center offset calibration and other techniques, new carrier phase data are obtained Calculate the ionospheric phase scintillation index every 30s Calculated as follows:

[0050]

[0051] Among them, E(·) represents the mathematical expectation, and the time length is taken as 30s.

[0052] Divide all processed data into ...

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 provides an ionospheric phase scintillation detection method based on a nonlinear SVM algorithm, The method uses nonlinear SVM algorithm in machine learning to judge the phase flicker ofthe detected signal. The purpose of SVM algorithm is to find a super-flat surface sample with certain characteristics and classify it, and then apply it to new samples. In this proces, Firstly, the received GPS signal is processed by high-pass filter and the maximum value and average value of the phase scintillation index are calculated. Take it as a learning sample to label the corresponding blinking event, and set the label to 1 or 1, indicate that that phase flicker event occurs or does not occur, then the samples are input into the nonlinear SVM classifier for learning, When the new phasescintillation event eigenvector enters the SVM classifier, it will automatically classify the new phase scintillation event. The detection method can classify a large number of scintillation events at the same time, and the use of nonlinear SVM algorithm improves the accuracy of the classification model.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, in particular to an ionospheric phase scintillation detection technology based on a nonlinear SVM algorithm. Background technique [0002] With the development of the GPS system and the demand for higher positioning accuracy, the monitoring and research of ionospheric scintillation needs to be paid attention to. Ionospheric scintillation is caused by irregular structures in the ionospheric plasma and refers to rapid fluctuations in the amplitude and phase of radio frequency signals propagating in the ionosphere. There are many reasons for this phenomenon, including but not limited to solar activity, magnetic storms, local electric fields, electrical conductivity, wave interactions, etc. The high-frequency occurrence areas of ionospheric scintillation are near equatorial and polar regions, and amplitude scintillation and phase scintillation caused by ionospheric scintillation do no...

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): G06K9/62
CPCG06F18/2411G06F18/214
Inventor 祝雪芬林梦颖陈熙源汤新华
Owner SOUTHEAST 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