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A new method based on stacked auto-encoders to identify abnormal weather radar echo images

Authors
  • Yang, Ling1
  • Wang, Yun1
  • Wang, Zhongke1
  • Qi, Yang1
  • Li, Yong1
  • Yang, Zhipeng1
  • Chen, Wenle1
  • 1 Chengdu University of Information Technology, Chengdu, Sichuan, 610225, China , Chengdu (China)
Type
Published Article
Journal
EURASIP Journal on Wireless Communications and Networking
Publisher
Springer International Publishing
Publication Date
Sep 10, 2020
Volume
2020
Issue
1
Identifiers
DOI: 10.1186/s13638-020-01769-3
Source
Springer Nature
Keywords
License
Green

Abstract

It is not denied that real-time monitoring of radar products is an important part in actual meteorological operations. But the weather radar often brings out abnormal radar echoes due to various factors, such as climate and hardware failure. So it is of great practical significance and research value to realize automatic identification of radar anomaly products. However, the traditional algorithms to identify anomalies of weather radar echo images are not the most accurate and efficient. In order to improve the efficiency of the anomaly identification, a novel method combining the theory of classical image processing and deep learning was proposed. The proposed method mainly includes three parts: coordinate transformation, integral projection, and classification using deep learning. Furthermore, extensive experiments have been done to validate the performance of the new algorithm. The results show that the recognition rate of the proposed method can reach up to more than 95%, which can successfully achieve the goal of screening abnormal radar echo images; also, the computation speed of it is fairly satisfactory.

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