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Ionospheric backscatter propagation mode identification method based on transfer learning

A technology of backscattering and propagation mode, which is applied in neural learning methods, character and pattern recognition, biological neural network models, etc. It can solve the difficulties in the extraction of discrete point distribution of echo energy distribution characteristics and the accuracy of backscattering ionogram pattern recognition And other issues

Active Publication Date: 2020-11-10
中国电波传播研究所
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Problems solved by technology

In the process of recognizing the propagation mode of the backscatter ionogram, limited by the traditional image method, it is impossible to completely extract the echo energy distribution characteristics and the distribution of discrete points, and at the same time, it is affected by the echo clutter-to-noise ratio. There are many types, which makes it difficult to improve the accuracy of pattern recognition of backscattered ionograms

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  • Ionospheric backscatter propagation mode identification method based on transfer learning
  • Ionospheric backscatter propagation mode identification method based on transfer learning
  • Ionospheric backscatter propagation mode identification method based on transfer learning

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Embodiment 1

[0033] Embodiment 1. This embodiment discloses a method for recognizing ionospheric backscatter propagation mode based on migration learning, setting multiple ionospheric backscatter propagation mode types, and manually labeling the accumulated backscatter detection data samples Collected 10,291 sets of data, using the labeled sample data to conduct network training and network model testing after construction, including the following steps:

[0034] Step 1. Preprocessing of training data:

[0035] The ionosphere is a time-varying medium. Therefore, for backscatter detection, the coverage characteristics of the echo received at different times have different changes and have different characteristics, so it is necessary to perform preprocessing operations on the training data. The returned scattering detection data contains the mode information of the ionosphere of the propagation medium. The read mode information can be seen in the returned scattering image information. In order t...

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Abstract

The invention discloses an ionospheric backscatter propagation mode identification method based on transfer learning. The method comprises the following steps: step 1, preprocessing training data; 2,constructing a deep convolutional network based on model migration; 3, constructing a domain confusion network; and 4, setting network training parameters. According to the ionospheric backscatter propagation mode recognition method based on transfer learning disclosed by the invention, mode recognition can be accurately performed on ionospheric backscatter ionogram data, so that the ionospheric state can be mastered, and important support is quickly and effectively provided for a short-wave equipment information system.

Description

Technical field [0001] The invention relates to the field of interpretation and recognition of ionospheric detection backscatter ionization maps, in particular to a migration learning-based ionospheric backscatter propagation pattern recognition method in this field. Background technique [0002] Ionospheric backscatter detection technology (abbreviated as backscatter) is to project high-frequency radio waves obliquely onto the ionosphere, and reflect them to the ground (or sea) far away. The unevenness and electrical characteristics of the ground (or sea) are not Uniformity causes the radio waves to scatter in all directions, and a part of the radio waves will be reflected along the original (or other possible) path through the ionosphere back to the launch point, and be received by the receiver there, thereby achieving the effect of the ionosphere and the ground (or Sea surface) status and detection of beyond-horizon target information. [0003] The echo signal of the backscatte...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08G06N3/04
CPCG06N3/08G06N3/045G06F2218/08G06F18/217G06F18/214Y02A90/10
Inventor 华彩成史军强李雪雍婷鲁转侠冯静娄鹏杨东升王俊江
Owner 中国电波传播研究所
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