WeChat Mini Program
Old Version Features

Real-Time Frequency Management System (FMS) for Sky-Wave High-Latitude Over-the-Horizon Radar (OTHR)

2022 23RD INTERNATIONAL RADAR SYMPOSIUM (IRS)(2022)

Def Res & Dev Canada

Cited 2|Views12
Abstract
A real-time frequency management system (FMS) is necessary for efficient operation of over-the-horizon-radar (OTHR) in high-latitude locations such as Canada’s Arctic regions. The FMS in this demonstration merges the results of an environmental monitor and a spectrum monitor in real-time. The environmental monitor uses the Assimilation Canadian High Arctic Ionospheric Model (A-CHAIM), which at present is the most accurate model available for real-time use in high-latitude regions. A-CHAIM incorporates near-real-time data into a background model to account for the rapid changes that often occur in the high-latitude and polar ionosphere. This demonstration between a simulated transmitter and four targets in northern Canada was performed during the day and night of October 11, 2020 (fall) and June 21, 2021 (summer). The demonstration showed that the FMS successfully merged the environmental monitor and spectrum monitor results in real-time. The FMS is now ready for around-the-clock operational use.
More
Translated text
Key words
Over-The-Horizon Radar (OTHR),Ionosphere,Assimilation Canadian High Arctic Ionospheric Model (A-CHAIM),High-Latitude,Ray-Tracing,Environmental Monitor,Spectrum Monitor,Real-Time,Frequency Monitoring System (FMS)
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined