Strong interference signal detection method based on power spectrum and multiple dimensioned wavelet transformation analysis

Abstract

The invention provides a strong interference signal detection method based on power spectrum and multiple dimensioned wavelet transformation analysis, comprising: a receiving terminal sampling received signals, calculating a sampled received signal power spectrum, and performing smooth filtering on the received signal power spectrum through a sliding filter; performing gauss curve fitting on the power spectrum after smooth filtering, and performing multiple dimensioned wavelet transformation on the fitted power spectrum to obtain each scale wavelet transformation coefficient; calculating a sum wavelet coefficient and a threshold thereof to obtain a new sum wavelet coefficient; employing an extreme point searching algorithm to search for a new sum wavelet coefficient maximum point; and verifying the accuracy of the searched maximum point. The method overcomes the problem of difficult threshold setting of a traditional threshold detection method, has the advantages of high detection precision, strong robustness, and convenient realization, and can be used for detection and identification of a plurality of interference signals in a communication system.

Description

technical field [0001] The invention relates to a signal detection method. Background technique [0002] Wireless communication has become an indispensable part of people's life, scientific research, military and other fields. Especially in war, effective and reliable battlefield communication is an important guarantee for the final victory. However, the complex electromagnetic environment and artificial malicious interference have a great impact on communication quality big threat. In order to ensure reliable communication, certain anti-jamming techniques must be adopted. At present, the most important anti-interference method is to use spread spectrum communication technology. However, the spread spectrum gain of the spread spectrum communication system is limited, and the communication quality cannot be guaranteed when encountering strong interference. If the receiving end can periodically detect the surrounding electromagnetic environment before and during the communic...

AI Technical Summary

Problems solved by technology

[0004] The frequency domain threshold method transforms the signal into the frequency domain, sets the threshold according to the probability distribution of the signal, and records the spectral lines exceeding the threshold to obtain the interference parameters. However, the selection of the threshold has a great influence on the result, and it is difficult to choose a suitable threshold.

The wavelet packet decomposition method performs wavelet decomposition on the signal, which is equivalent to dividing the signal into N segments in the frequency domain, and calculating the energy value of each segment. If the energy value of a certain frequency band signal is obviously too large, it is considered that there is interference in this frequency band, but the detection resolution The frequency of the interference is low, and the exact location of the interference cannot be determined, so all the spectrum segments containing the interference can only be discarded, resulting in a waste of spectrum

The core part of the DT-FCME algorithm is the iterative process of high and low thresholds. However, when there are many data samples, the iterative process is very slow, and the real-time performance is poor in practical applications.

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