Radio heavy fog weather monitoring method and system, computer equipment and medium

A radio and radio signal technology, applied in the field of electronic information, can solve the problems of difficult maintenance, high installation cost, fixed-point measurement, etc., and achieve high spatial and temporal resolution, low cost, and simple reception

Pending Publication Date: 2022-08-05
LANZHOU JIAOTONG UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] (1) The existing method of using a droplet spectrometer to monitor foggy weather has the limitation that it can only be measured at fixed points
[0008] (2) The method of using a visibility meter to monitor fogg...

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
  • Radio heavy fog weather monitoring method and system, computer equipment and medium
  • Radio heavy fog weather monitoring method and system, computer equipment and medium
  • Radio heavy fog weather monitoring method and system, computer equipment and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] like figure 1 Show, the monitoring method of radio heavy fog weather based on deep learning provided by the invention embodiment includes the following steps:

[0062] S101 uses a dedicated radio monitoring receiver (3900A) to collect low -frequency band radio signal data in different concentrations of fog.

[0063] S102, uses the orthogonal digital inverter technology to convert the received signal to IQ signal, and then convert it to FFT to the frequency domain and draw the spectrum waterfall map. Perform performance evaluation of multiple data pre -processing schemes, and select the appropriate data pre -processing scheme. And the characteristics of the low -frequency band radio signal in different concentrations through the S103 and S104 are discriminated.

[0064] S103 extracts the characteristics of input data through convolutional neural networks.

[0065] S104, using the characteristics of withdrawal of convolutional neural networks to obtain hotspots in the input d...

Embodiment 2

[0077] Based on embodiment 1 based on deep learning -based radio motion monitoring methods, as preferred embodiment, in step S101, the low -frequency band radio signal is the low -frequency band baseband signal of the receiving frequency band. Continuously change the position of the receiver in the fog area to exclude the effects of the same channel on the characteristics of the fog of wireless telecommunications.

Embodiment 3

[0079] Based on embodiment 1 based on deep learning -based radio and fog weather monitoring methods, as preferred embodiments, in step S102, the use of orthogonal digital inverter technology will be converted to IQ signals. The

[0080] I = h LP (s (t) cos (2πft))

[0081] Q = h LP (s (t) sin (2πft))

[0082] Among them, s (t) is the receiving signal, F represents the carrier frequency of the transmission signal, H LP Represents the system function of a low -pass filter.

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 belongs to the technical field of electronic information, and discloses a radio foggy weather monitoring method and system, computer equipment and a medium. According to the radio heavy fog weather monitoring method, a radio + deep learning method is applied, and a deep artificial neural network technology with supervision-learning capability is adopted to extract the characteristics of low-frequency-band radio signals passing through fog zone environments with different concentrations, so that the defects of weak generalization capability and the like of the traditional technology are overcome, and the monitoring accuracy is improved. A deep learning special model for low-frequency-band fog spectrum feature recognition is innovatively designed, spectrum features of fog with different concentrations can be recognized in a low frequency band, and then heavy fog weather is monitored. According to the invention, additional equipment does not need to be installed, and the foggy weather can be monitored by directly using common broadcast signals or base station signals and the like. The method has the advantages of high time resolution, low cost, no need of maintenance and the like. And continuous real-time monitoring can be realized, and the defect of insufficient spatial resolution of a traditional monitoring method can be overcome.

Description

Technical field [0001] The invention is an electronic information technology field, especially involving a radio monitoring method, system, computer equipment and media. Background technique [0002] At present, the detection of fog in the meteorological business is mainly based on visual inspection. Only at the airport and other places, the fog spectrometer, the visibility instrument, and the microwave radiation meter are used. [0003] With the development of radar technology in the 1960s, radio communication and the interaction of the environment have begun to be used as a way to monitor the changes in the atmospheric environment. For example, the meteorological radar with Doppler frequency shift technology can monitor the atmospheric environment such as rain, fog, cloud, snow, and ice. It transmits the pulse -type electromagnetic wave that is approximately straight through the radar to the sky. When this electromagnetic wave encounters meteorological targets such as clouds an...

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): G01N15/06G01N22/00
CPCG01N15/0656G01N22/00Y02A90/10
Inventor 郑礼程倩严天峰汤春阳
Owner LANZHOU JIAOTONG 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