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Solar radio interference filtering method, readable storage medium and electronic equipment

A solar radio and filtering technology, which is applied in the field of solar radio spectrum instrument, can solve the problems of a large amount of historical data, errors, and unsuitable filter processing for multiple outbreak events, etc., and achieve large operating space, accurate prediction, and multi-solar outbreak information. Effect

Active Publication Date: 2019-12-31
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, wavelet transform is used to remove interference for different burst events, and finally extract the burst structure, but this method is mostly used to process the grayscale image of the spectrum, and there are artificial factors in the selection of interference signals and thresholds, which is not suitable for multiple bursts Filtering processing of events; or adopting a calibration method and giving results, it is possible to obtain a clear solar radio spectrum map, but the calibration of the spectrum analyzer requires a large amount of historical data, and there are certain errors in itself
Therefore, there is currently no better method to effectively remove radio interference signals in the solar eruption area

Method used

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  • Solar radio interference filtering method, readable storage medium and electronic equipment
  • Solar radio interference filtering method, readable storage medium and electronic equipment
  • Solar radio interference filtering method, readable storage medium and electronic equipment

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Embodiment 1

[0052] Such as figure 1 As shown, Embodiment 1 of the present disclosure provides a solar radio interference filtering method. In this embodiment, a recurrent neural network is used to process interference signals in solar radio. The predicted value consists of two stages.

[0053] In the first stage, the data set must first be established. After preprocessing, the data set enters the built network for training, and then continuously optimizes the network structure and adjusts network hyperparameters according to the training results. Finally, the test set enters the test network for numerical prediction. In the second stage, this embodiment filters out the interference signal of the solar radio spectrum, and the interference signal processed by the cyclic neural network is a radio signal with a wider frequency band or a signal strength close to or even greater than that of the solar eruption.

[0054] (1) Radio station data source

[0055] Different from ordinary image proc...

Embodiment 2

[0088] Embodiment 2 of the present disclosure provides a readable storage medium on which a program is stored, and when the program is executed by a processor, the solar radio interference filtering method described in Embodiment 1 of the present disclosure is implemented.

Embodiment 3

[0090] Embodiment 3 of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and operable on the processor. When the processor executes the program, the method described in Embodiment 1 of the present disclosure is implemented. Solar radio interference filtering method.

[0091] The electronic devices described in this embodiment include but are not limited to computers, solar radio spectrum analyzers, various microprocessors, processors, servers, or various solar radio observation devices.

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PUM

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Abstract

The invention provides a solar radio interference filtering method, a readable storage medium and electronic equipment. The method comprises the following steps: collecting intensity data in a set time period before and after a solar burst event, and screening out frequency channels where eligible radio signals are located according to radio flux value data of all frequency channels at a certain moment in a non-burst time period; preprocessing the acquired eligible radio station signal data, and establishing a data set; establishing a recurrent neural network, training the recurrent neural network by using the preprocessed radio station signal data, and predicting the signal value of a radio station in a solar burst area by using the trained recurrent neural network; and according to the linear additive property of the signal, subtracting the predicted radio station value from the original radio flux value of the burst area at the corresponding moment to obtain a value of a clean puresolar burst event. Radio station interference signals can be predicted more accurately, and more solar burst information can be reserved. The final solar burst observation effect of the method is obviously superior to that of a common image filtering method.

Description

technical field [0001] The present disclosure relates to the technical field of solar radio spectrum instruments, and in particular to a solar radio interference filtering method, a readable storage medium and a solar radio spectrum instrument. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] Space observation of solar activities requires the use of solar radio spectrum instruments, but while receiving solar radio signals, solar radio spectrum instruments will also receive various radio interference signals and other electromagnetic interference signals in space. The existence of these interference signals leads to It is impossible to obtain a clean and clear solar radio dynamic spectrum map, especially some interference signals that occupy a wide frequency band and whose signal strength is greater than that of the solar radio current, wi...

Claims

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Application Information

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IPC IPC(8): G01R23/16G06N20/00
CPCG01R23/16G06N20/00
Inventor 杜清府张巧曼李昕赵一笼纪仕鑫高昌林
Owner SHANDONG UNIV
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