An adaptive real-time spectral data compression method and system

Abstract

The invention discloses an adaptive real-time spectrum data compression method and system. The compression method includes the steps of: calculating the similarity between the current spectrum and the typical spectrum, and judging whether the current spectrum is similar to the typical spectrum; If a typical spectrum is similar, the sequence number of the typical spectrum is used instead of the current spectrum for storage; if the current spectrum is not similar to all typical spectrums, the current spectrum is regarded as a new typical spectrum, and a sequence number is given to store the current spectrum and corresponding serial number. The method and system of the present invention store the original spectrum data with the serial number of the typical spectrum by calculating the similarity, which can greatly reduce the storage capacity, reduce the requirements for storage space, and can also adapt to the requirements of real-time spectrum data storage, reducing the The cost of network transmission.

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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