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

Unmanned aerial vehicle frequency hopping signal detection and identification method based on clustering analysis

A technology of frequency hopping signal and cluster analysis, applied in character and pattern recognition, computer components, instruments, etc., can solve problems such as long operation time and complicated calculation process

Active Publication Date: 2019-10-15
XIHUA UNIV
View PDF6 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is: in order to solve the problem of complex calculation process and long operation time in order to solve the problem of complex calculation process and long calculation time in order to analyze the frequency hopping signal of unmanned aerial vehicles by using the existing cluster analysis method to complete the detection and identification of unmanned aerial vehicles. A UAV frequency hopping signal detection and recognition method based on cluster analysis based on signal similarity feature analysis

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
  • Unmanned aerial vehicle frequency hopping signal detection and identification method based on clustering analysis
  • Unmanned aerial vehicle frequency hopping signal detection and identification method based on clustering analysis
  • Unmanned aerial vehicle frequency hopping signal detection and identification method based on clustering analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0084] A kind of UAV frequency hopping signal detection and identification method based on cluster analysis provided by the embodiment of the present invention comprises the following steps:

[0085] Step 1. Collect the spectrum data of the specified frequency band for a time period, use the threshold processing method to preprocess the collected spectrum data to obtain the spectrum data of the effective signal, and perform the frequency points in the spectrum data of all effective signals according to the time continuity processing to obtain several effective signal data periods of several groups of frequency points. Include the following steps:

[0086] Step 1.1. Use the radio spectrum monitoring receiver to collect spectrum data of a specified frequency band for a time period, and obtain multi-frame spectrum data on the frequency band.

[0087] Radio spectrum monitoring is carried out in the Radio Management Technology Research Center of Yibin Research Institute of Xihua U...

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 an unmanned aerial vehicle frequency hopping signal detection and identification method based on clustering analysis, and relates to the technical field of unmanned aerial vehicle signal analysis and processing. The method comprises the following steps: acquiring and processing spectral data to obtain an original data set D (that is, an unmanned aerial vehicle frequency hopping signal), detecting the unmanned aerial vehicle frequency hopping signal by adopting a clustering analysis method based on signal similarity feature analysis, and sorting and identifying a detection result. The clustering analysis method comprises the following steps: 1, calculating the distance between each piece of data in an original data set D and other data, forming a distance matrix RS,and finding out the maximum value rmax in all non-zero minimum values ri; 2, setting weights w1 and w2, and calculating a clustering radius R and maximum density data P according to the maximum valuermax and the weights w1 and w2; and 3, classifying the data in the data set D by taking the data P as a center and R as a radius, taking the data which is not successfully classified as a new data setD, and executing the steps 1 to 3 again until a clustering ending condition is met.

Description

technical field [0001] The invention relates to the technical field of UAV signal analysis and processing, in particular to a method for detecting and identifying UAV frequency hopping signals based on cluster analysis. Background technique [0002] With the rapid advancement of information technology, especially in graphics and image processing, wireless communication transmission, navigation and other aspects of technology is becoming more and more perfect, unmanned aerial vehicles have begun to develop in the direction of miniaturization, low cost, simple and flexible operation, etc., the scope of application It has also expanded from military applications such as battlefield reconnaissance, locking and tracking, and precision strikes in the early stage to civilian fields such as weather surveying and mapping, agricultural plant protection, sports events, and film shooting. The rapid development of civilian consumer drones has promoted the formation of a new drone industr...

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): G06K9/00G06K9/62H04B1/713H04B1/715
CPCH04B1/713H04B1/715G06F2218/08G06F2218/12G06F18/22
Inventor 张国敏裴峥孔明明罗冰
Owner XIHUA 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