Radiation source fingerprint feature extraction method based on wavelet entropy and chaotic features

Abstract

The invention provides a radiation source fingerprint feature extraction method based on wavelet entropy and chaotic features, and relates to the radiation source individual identification field. Theradiation source fingerprint feature extraction method based on wavelet entropy and chaotic features includes the following steps: 1) performing extraction of wavelet entropy features on radiation source signals to obtain feature parameters; and 2) performing analysis of chaotic features on the radiation source signals, extracting the chaotic feature parameters, combining the wavelet entropy feature vector with the chaotic feature vector to obtain the combination feature vector, inputting a feature classifier to realize individual identification of the radiation source. The radiation source fingerprint feature extraction method based on wavelet entropy and chaotic features overcomes the defect that at present a commontime frequency analysis method does not consider the non-linear nature ofthe radiation source signals, gives play to the strong time frequency resolution characteristic of wavelet packet transformation, extracts the multi-scale local features of the signals, and considersthe non-linear situation of the signals by means of chaotic analysis which is a non-linear analysis method so as to more accurately reflect the features of the radiation source signals and enable theextracted feature parameters to be higher in discrimination performance.

Description

technical field [0001] The invention relates to the field of radiation source individual identification, in particular to a radiation source fingerprint feature extraction method based on wavelet entropy and chaotic characteristics. Background technique [0002] The so-called "fingerprint" of the communication signal refers to the subtle characteristics of the individual communication radiation source expressed by the signal as the carrier. It usually refers to the fact that due to the differences in hardware equipment between the individual radiation sources, the transmitted signal is attached to the Individual characteristics that distinguish it from other sources of radiation. In modern naval warfare, underwater target recognition is the premise of discovering the enemy first and effectively conducting underwater acoustic countermeasures against the enemy, using weapons to attack the enemy first, and defeating the enemy. If the fingerprint characteristics of radiation so...

AI Technical Summary

Problems solved by technology

[0003] At present, the commonly used radiation source fingerprint feature extraction method mainly analyzes the time-frequency domain of the radiation source signal. Its defect is that this type of method treats the radiation source signal as a linear signal and does not consider the nonlinear nature of the signal, so it cannot be well reflect its non-linear characteristics

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