Quick radio storm real-time searching method

A radio burst and fast technology, applied in the direction of pattern recognition in instruments and signals, character and pattern recognition, etc., can solve problems such as accuracy and speed bottlenecks, achieve improved work efficiency, high-efficiency real-time search, and solve the problem of low recognition accuracy Effect

Pending Publication Date: 2020-04-28
XINJIANG ASTRONOMICAL OBSERVATORY CHINESE ACADEMY OF SCI
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Problems solved by technology

[0007] The present invention uses deep learning to establish a real-time search method for fast

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  • Quick radio storm real-time searching method
  • Quick radio storm real-time searching method

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Embodiment

[0030] a. Obtain the fast radio burst classification model, the process includes:

[0031] The observation data that does not contain a single pulse is divided into 64ms time length, and it is zero-meanized and normalized to obtain a negative sample data set. The time resolution of the observation data used in this embodiment is dt=64us, and the frequency resolution Rate df = 781.25kHz. According to the detected fast radio burst signals so far, the pulse width ranges from sub-milliseconds to several milliseconds, and every 1000 times of sampling data (that is, 64ms data length) is taken to form a frequency-time spectrogram sample, which can roughly capture fast radio bursts Dispersion duration profile of the burst pulse;

[0032] The interstellar medium is an important material component in the universe. When the radiation signal of a distant celestial body passes through the interstellar medium, it will change, mainly including dispersion and scattering effects. The dispers...

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Abstract

The invention discloses a quick radio storm real-time searching method. The method comprises the following steps: obtaining a quick radio storm classification model; reading a quick radio storm observation data stream in real time; obtaining a frequency-time spectrogram sample of the quick radio storm; preprocessing the frequency-time spectrogram sample data; inputting the frequency-time spectrogram sample data into a quick radio storm classification model for recognition to obtain a quick radio storm candidate body; storing the observation data of the quick radio storm candidate body; and mapping and storing the observation data of the quick radio storm candidate body. According to the method of the invention, the deep learning classification model is utilized to directly search and identify the quick radio storm transient signals in the astronomical observation data; data transfer to pictures is reduced; the data characterization precision loss caused by the fact that the pictures are transferred to the data is avoided, the classification model recognition precision and the speed of the whole data processing flow are improved, the requirements for precision and speed needed by quick radio storm original voltage data dump, interference array telescope tracking observation and real-time mail notification are met, and the working efficiency is greatly improved.

Description

technical field [0001] The invention relates to a real-time search method for fast radio bursts, in particular to a real-time search method for fast radio bursts based on deep learning, which belongs to the technical field of radio astronomy data processing. Background technique [0002] Fast Radio Burst (FRB) is an astronomical phenomenon of explosive, broadband, and highly dispersive pulsed radio radiation with a duration of only a few milliseconds, and the instantaneous radiation flux can reach tens of Jy. The astronomical phenomenon was first discovered by Lorimer in 2007 while analyzing historical data from the pulsar survey at Australia's Parkes Observatory. At present, more than 80 FRB events have been detected on the FRB catalog website, including 2 repeated fast radio storms FRB121102 and FRB180814. However, these discoveries have not yet allowed astronomers to fully determine the "identity" of this mysterious signal, and scientists are only making various speculat...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/02G06F2218/12
Inventor 刘艳玲陈卯蒸李健袁建平裴鑫温志刚王凯闫浩马军李笑飞段雪峰曹亮
Owner XINJIANG ASTRONOMICAL OBSERVATORY CHINESE ACADEMY OF SCI
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