An adaptive real-time spectrum data compression method and system

Abstract

The invention discloses an adaptive real-time spectrum data compression method and a system thereof. The compression method comprises the following steps: similarity between a current spectrum and a typical spectrum is calculated, and whether the current spectrum is similar to the typical spectrum is judged; if the current spectrum is similar to one of the typical spectra, the serial number of thetypical spectrum is used to store instead of the current spectrum; if the current spectrum is not similar to all the typical spectrum, the current spectrum is treated as a new typical spectrum, and asequence number is given to store the current spectrum and the corresponding sequence number. The method and the system of the invention can greatly reduce the storage amount, reduce the requirementon storage space, adapt to the requirement of real-time spectrum data storage, and reduce the cost of network transmission by substituting the serial number of a typical spectrum for the original dataof the spectrum for storage through similarity calculation.

Description

technical field [0001] The invention relates to the technical field of radio monitoring, in particular to an adaptive real-time frequency spectrum data compression method and system. Background technique [0002] When performing radio monitoring, a large amount of spectrum data will be continuously generated, which will occupy a large amount of storage space, making the requirements for storage devices very high, and will take up a large amount of time for a long time when performing subsequent data operations. Memory. Taking the broadcast frequency band scanning as an example, the start frequency is 87MHz, the end frequency is 108MHz, and the step size is 25kHz. About 55 frames of data are received per second, and each frame of data has 841 points, and each point occupies two bytes. It can be obtained About 8GB of data is stored a day. [0003] Compressing data before storing it is a commonly used storage method at present to reduce storage space. However, the previous c...

AI Technical Summary

Problems solved by technology

However, the previous compression methods are all processed after the data is collected, which requires reading, computing and storing the entire data file.

If the compression algorithm of the file is used directly, the consumption of decompression will also occur

In addition, due to the fast scanning rate during monitoring, the amount of data received each time is relatively large, which is disastrous for real-time network transmission

It is difficult for a general network to load such a large amount of data without interruption, so it is necessary to use a high-performance network. However, the cost of a high-performance network is too high and lacks practical value.

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