C-E characteristic-based radiation source fingerprint extraction method and device and individual identification system
阅读说明：本技术 基于c-e特征的辐射源指纹提取方法、装置及个体识别系统 (C-E characteristic-based radiation source fingerprint extraction method and device and individual identification system ) 是由 郑娜娥 岳嘉颖 任修坤 王盛 陈松 吴迪 吕品品 张靖志 高亮亮 张龙 高留洋 于 2019-09-10 设计创作，主要内容包括：本发明属于辐射源个体识别技术领域,特别涉及一种基于C-E特征的辐射源指纹提取方法、装置及个体识别系统,该方法包含：提取信号样本中的包络谱信息熵作为指纹特征；针对指纹特征,联合瞬时参数复杂度和熵特征,得到作为用于识别辐射源个体的C-E特征。本发明通过Hilbert包络谱信息熵的辐射源指纹特征提取,联合瞬时参数的复杂度和熵特征,得到用于辐射源个体识别的联合C-E特征；相比单类特征,该特征以微弱的时间代价换取了识别率上较大的提高,在仿真信号实验中对比分形维数和香农熵分别提高了15.2％、19.7％的正确率；在不同应用环境下具有良好的独立性、抗噪性；通过实际测试,将其应用于FM手持机信号,在实测环境中验证本发明技术方案具有一定实用性和鲁棒性。(The invention belongs to the technical field of individual identification of radiation sources, and particularly relates to a C-E characteristic-based radiation source fingerprint extraction method, a device and an individual identification system, wherein the method comprises the following steps: extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics; and aiming at the fingerprint characteristics, combining the instantaneous parameter complexity and the entropy characteristics to obtain C-E characteristics used for identifying the individual radiation source. According to the method, combined C-E characteristics for individual identification of the radiation source are obtained by extracting the fingerprint characteristics of the radiation source of Hilbert envelope spectrum information entropy and combining the complexity and entropy characteristics of instantaneous parameters; compared with single-class characteristics, the characteristics are greatly improved in recognition rate at a weak time cost, and the accuracy of comparing fractal dimension and shannon entropy in a simulation signal experiment is respectively improved by 15.2% and 19.7%; the method has good independence and noise resistance under different application environments; through actual test, the method is applied to FM handset signals, and the technical scheme of the invention has certain practicability and robustness in an actual measurement environment.)
1. A radiation source fingerprint extraction method based on C-E characteristics is characterized by comprising the following steps:
A) extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics;
B) and aiming at the fingerprint characteristics, combining the instantaneous parameter complexity and the entropy characteristics to obtain C-E characteristics used for identifying the individual radiation source.
2. The C-E feature based radiation source fingerprint extraction method according to claim 1, wherein a) comprises the following contents:
A1) acquiring a signal sample, and extracting instantaneous envelope, instantaneous phase and instantaneous frequency of a signal based on Hilbert transform;
A2) and extracting the entropy of envelope spectrum information based on the Hilbert spectrum according to the instantaneous envelope of the signal.
3. The C-E feature based radiation source fingerprint extraction method according to claim 2, wherein, in a1), hilbert transform is performed on real signals in received signal samples; according to the conversion result, and combining the real signal to obtain an analytic signal of the signal sample; and respectively extracting the instantaneous envelope, the instantaneous phase and the instantaneous frequency of the analytic signal, and standardizing the extracted instantaneous envelope, instantaneous phase and instantaneous frequency.
4. The C-E feature based radiation source fingerprint extraction method according to claim 2, wherein, in a2), the instantaneous envelope of the signal is fast fourier transformed to obtain an envelope spectrum; calculating the energy value of the envelope spectrum of each point according to the envelope spectrum, and acquiring the probability of the energy of each point occupying the total energy; and acquiring the entropy of the envelope spectrum information according to the probability.
5. The C-E feature based radiation source fingerprint extraction method according to claim 2, wherein B) comprises the following:
B1) respectively extracting complexity and entropy characteristics of instantaneous envelope, instantaneous phase and instantaneous frequency of a signal;
B2) and combining the entropy and complexity and entropy characteristics of the envelope spectrum information as C-E characteristics for identifying the individual radiation source.
6. The C-E feature-based radiation source fingerprint extraction method according to claim 5, characterized in that, in B1) extracting complexity and entropy features, firstly, three instantaneous parameters of instantaneous envelope, instantaneous phase and instantaneous frequency are respectively placed in a unit square, and fractal box dimension and ensemble element probability are calculated; and then, calculating the set information dimension and the information entropy of instantaneous envelope, instantaneous phase and instantaneous frequency according to a Shannon formula, and obtaining the complexity and entropy characteristics of instantaneous parameters according to the fractal box dimension.
7. The C-E feature-based radiation source fingerprint extraction method according to claim 1 or 5, characterized in that, for the C-E features extracted from the signal samples, the feature data is divided to obtain training samples, the training samples are divided by K-fold cross validation, and the training samples are input into a linear SVM classifier for training test to identify the individual radiation source through classification.
8. A radiation source fingerprint extraction device based on C-E characteristics is characterized by comprising: an extraction module and a combination module, wherein,
the extraction module is used for extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics;
and the combination module is used for combining the instantaneous parameter complexity and the entropy characteristic aiming at the fingerprint characteristic to obtain the C-E characteristic used for identifying the individual radiation source.
9. The C-E feature based radiation source fingerprint extraction device according to claim 8, wherein said extraction module comprises a first sub-module and a second sub-module, wherein,
the first submodule is used for acquiring a signal sample and extracting instantaneous envelope, instantaneous phase and instantaneous frequency of a signal based on Hilbert transform;
and the second sub-module is used for extracting envelope spectrum information entropy based on the Hilbert spectrum according to the instantaneous envelope of the signal.
10. A radiation source individual identification system is characterized by comprising the C-E feature-based radiation source fingerprint extraction device and an SVM classifier, wherein the C-E features extracted by the radiation source fingerprint extraction device are input to the SVM classifier for classification learning so as to identify radiation source individuals through feature clustering.
Technical Field
The invention belongs to the technical field of individual identification of radiation sources, and particularly relates to a radiation source fingerprint extraction method and device based on C-E characteristics and an individual identification system.
Background
The individual identification of the radiation source refers to the identification of unintentional modulation caused by factors such as internal hardware process difference of the radiation source, device nonlinearity and the like. Like intentional modulation, unintentional modulation information may be present on the amplitude, frequency, and phase of the signal. If all the information of the three can be obtained, theoretically, more classified information can be possessed; conversely, if one of the items of information is lost, the result of the classification may be affected. However, since the amplitude, phase and frequency are directly used, a large amount of redundant information is included, and classification information is interfered, so that the identification effect is influenced. Therefore, such methods generally extract secondary features again on the basis of three.
In a changeable application scene and an electromagnetic environment, by extracting a single certain characteristic or a certain type of characteristic, once a characteristic value drift or a outlier point occurs in the measurement process, misjudgment may be generated, so that the validity and the stability required in the actual application of radiation source individual identification are difficult to meet; meanwhile, under the condition that the individual difference of the radiation source is extremely weak, the extraction of a feature capable of reflecting the individual difference information to a large extent is difficult to achieve.
Disclosure of Invention
Therefore, the invention provides a radiation source fingerprint extraction method, a radiation source fingerprint extraction device and an individual identification system based on C-E characteristics, which are used for identifying individual radiation sources by combining various characteristics of signals into the C-E characteristics, meet the requirements of effectiveness and stability required in the actual application function of radiation source individual identification, are also suitable for individual identification under the condition of extremely weak individual differences of the radiation sources, and have stronger robustness.
According to the design scheme provided by the invention, in order to obtain effective and robust radio frequency fingerprint characteristics, the invention provides a radiation source fingerprint extraction method based on C-E characteristics, Hilbert envelope spectrum information Entropy is used as fingerprint characteristics, Instantaneous parameter Complexity and Entropy characteristics are combined, and the combined C-E characteristics based on the Instantaneous parameter Complexity and Entropy (JointCharacteristics of Complexity and Entropy based on instant Parameters) are used for identifying individual radiation sources.
Further, extracting the entropy of the envelope spectrum information in the signal samples as the fingerprint feature comprises the following contents:
A1) acquiring a signal sample, and extracting instantaneous envelope, instantaneous phase and instantaneous frequency of a signal based on Hilbert transform;
A2) and extracting the entropy of envelope spectrum information based on the Hilbert spectrum according to the instantaneous envelope of the signal.
Further, performing Hilbert transform on a real signal in the received signal samples; according to the conversion result, and combining the real signal to obtain an analytic signal of the signal sample; and respectively extracting the instantaneous envelope, the instantaneous phase and the instantaneous frequency of the analytic signal, and standardizing the extracted instantaneous envelope, instantaneous phase and instantaneous frequency.
Further, performing fast Fourier transform on the instantaneous envelope of the signal to obtain an envelope spectrum; calculating the energy value of the envelope spectrum of each point according to the envelope spectrum, and acquiring the probability of the energy of each point occupying the total energy; and acquiring the entropy of the envelope spectrum information according to the probability.
Further, the instantaneous parameter complexity and entropy characteristics are combined to obtain the C-E characteristics used for identifying the individual radiation source, which comprise the following contents:
B1) respectively extracting complexity and entropy characteristics of instantaneous envelope, instantaneous phase and instantaneous frequency of a signal;
B2) and combining the entropy and complexity and entropy characteristics of the envelope spectrum information as C-E characteristics for identifying the individual radiation source.
Further, in the extraction of complexity and entropy characteristics, three instantaneous parameters of instantaneous envelope, instantaneous phase and instantaneous frequency are respectively placed in a unit square, and fractal box dimension and set element probability are calculated; and then, calculating the set information dimension and the information entropy of instantaneous envelope, instantaneous phase and instantaneous frequency according to a Shannon formula, and obtaining the complexity and entropy characteristics of instantaneous parameters according to the fractal box dimension.
Further, the characteristic data are divided according to the C-E characteristics extracted from the signal samples to obtain training samples, the training samples are divided through K-fold cross validation, and the training samples are input into a linear SVM classifier to be trained and tested, so that individual radiation sources are identified through classification.
Further, the invention also provides a radiation source fingerprint extraction device based on the C-E characteristics, which comprises: an extraction module and a combination module, wherein,
the extraction module is used for extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics;
and the combination module is used for combining the instantaneous parameter complexity and the entropy characteristic aiming at the fingerprint characteristic as the C-E characteristic for identifying the individual radiation source.
The invention further provides a radiation source individual identification system which comprises the radiation source fingerprint extraction device based on the C-E characteristics and the SVM classifier, wherein the C-E characteristics extracted by the radiation source fingerprint extraction device are input to the SVM classifier for classification learning so as to identify the radiation source individual through characteristic clustering.
The invention has the beneficial effects that:
according to the method, combined C-E characteristics for individual identification of the radiation source are obtained by extracting the fingerprint characteristics of the radiation source of Hilbert envelope spectrum information entropy and combining the complexity and entropy characteristics of instantaneous parameters; compared with single-class characteristics, the characteristics are greatly improved in recognition rate at a weak time cost, and the accuracy of comparing fractal dimension and shannon entropy in a simulation signal experiment is respectively improved by 15.2% and 19.7%; the method has good independence and noise resistance under different application environments; and through actual test, the technical scheme of the invention is applied to FM handset signals, and further verified to have certain practicability and robustness in an actual measurement environment.
Description of the drawings:
FIG. 1 is a schematic diagram of a fingerprint extraction process in an embodiment;
FIG. 2 is a schematic diagram of individual identification of radiation sources in an embodiment;
FIG. 3 is a characteristic curve diagram of the Taylor power amplifier model in the embodiment;
FIG. 4 is an information entropy distribution diagram of instantaneous amplitude-instantaneous frequency-instantaneous phase in the embodiment;
FIG. 5 is a characteristic distribution diagram based on Hilbert envelope spectrum information entropy in an embodiment;
FIG. 6 is a box-dimensional feature distribution diagram of instantaneous amplitude-instantaneous frequency-instantaneous phase in an embodiment;
FIG. 7 is an information dimension feature distribution diagram of instantaneous amplitude-instantaneous frequency-instantaneous phase in the embodiment;
FIG. 8 is a graph of magnitude box dimension-frequency box dimension-envelope spectrum Shannon entropy characteristics in an example;
FIG. 9 is an average identification result of five types of radio station individuals when different fingerprint features are adopted in the embodiment;
FIG. 10 is a graph of individual identification rate of 16QAM signals under AWGN channel in the example;
FIG. 11 is a graph of individual identification rates for different modulation schemes in an AWGN channel in an embodiment;
FIG. 12 is a result of the identification rate of the measured FM modulated walkie-talkie signals in the embodiment;
FIG. 13 is an identification ROC curve of the measured FM modulated walkie-talkie signals in the example.
The specific implementation mode is as follows:
in order to make the objects, technical solutions and advantages of the present invention clearer and more obvious, the present invention is further described in detail below with reference to the accompanying drawings and technical solutions.
In a changeable application scene and an electromagnetic environment, by extracting a single certain characteristic or a certain type of characteristic, once a characteristic value drift or a outlier point occurs in the measurement process, misjudgment can be generated, so that the validity and the stability required in the actual application of radiation source individual identification are difficult to meet; meanwhile, under the condition that the individual difference of the radiation source is extremely weak, the extraction of a feature capable of reflecting the individual difference information to a large extent is difficult to achieve. Therefore, in practical use, the more mature the individual identification system of the radiation source, the more the joint prediction of various characteristics is required. In order to obtain effective and robust radio frequency fingerprint features, an embodiment of the present invention, as shown in fig. 1, provides a C-E feature-based radiation source fingerprint extraction method, including:
s101) extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics;
s102) combining the instantaneous parameter complexity and the entropy characteristics aiming at the fingerprint characteristics to obtain the C-E characteristics used for identifying the individual radiation source.
In the embodiment of the invention, the individual radiation source is identified by combining the Complexity and entropy Characteristics of Instantaneous Parameters and the C-E Characteristics (Joint Characteristics of Complexity and enhanced on instant Parameters) based on Hilbert envelope spectrum information entropy as fingerprint Characteristics.
Further, in the embodiment of the present invention, in the process of extracting the entropy of the envelope spectrum information in the signal sample as the fingerprint feature, the instantaneous envelope, the instantaneous phase and the instantaneous frequency of the signal are extracted based on the hilbert transform for the obtained signal sample; and extracting the entropy of envelope spectrum information based on the Hilbert spectrum according to the instantaneous envelope of the signal.
Further, in the embodiment of the present invention, hilbert transform is performed on a real signal in a received signal sample; according to the conversion result, and combining the real signal to obtain an analytic signal of the signal sample; and respectively extracting the instantaneous envelope, the instantaneous phase and the instantaneous frequency of the analytic signal, and standardizing the extracted instantaneous envelope, instantaneous phase and instantaneous frequency. The normalization process can be designed as follows:
hilbert transformation of received real signals u (n)
Further, in the embodiment of the invention, the instantaneous envelope of the signal is subjected to fast Fourier transform to obtain an envelope spectrum; calculating the energy value of the envelope spectrum of each point according to the envelope spectrum, and acquiring the probability of the energy of each point occupying the total energy; and acquiring the entropy of the envelope spectrum information according to the probability.
According to the signal envelope a (n), FFT conversion is carried out on the signal envelope a (n) to obtain an envelope spectrum:
Further, in the embodiment of the present invention, the instantaneous parameter complexity and entropy characteristics are combined to obtain C-E characteristics used for identifying the individual radiation source, which include the following: respectively extracting complexity and entropy characteristics of instantaneous envelope, instantaneous phase and instantaneous frequency of a signal; and combining the entropy and complexity and entropy characteristics of the envelope spectrum information as C-E characteristics for identifying the individual radiation source.
Furthermore, in the embodiment of the invention, in the extraction of complexity and entropy characteristics, three instantaneous parameters of instantaneous envelope, instantaneous phase and instantaneous frequency are respectively arranged in a unit square, and fractal box dimension and set element probability are calculated; and then, calculating the set information dimension and the information entropy of instantaneous envelope, instantaneous phase and instantaneous frequency according to a Shannon formula, and obtaining the complexity and entropy characteristics of instantaneous parameters according to the fractal box dimension.
From normalized instantaneous envelope
Furthermore, in the embodiment of the invention, the characteristic data is divided according to the C-E characteristics extracted from the signal samples to obtain the training samples, the training samples are segmented by adopting K-fold cross validation, and the segmentation is input into a linear SVM classifier to carry out training test so as to identify the individual radiation source through classification.
Further, an embodiment of the present invention further provides a radiation source fingerprint extraction apparatus based on C-E characteristics, including: an extraction module and a combination module, wherein,
the extraction module is used for extracting the entropy of the envelope spectrum information in the signal sample as fingerprint characteristics;
and the combination module is used for combining the instantaneous parameter complexity and the entropy characteristics aiming at the fingerprint characteristics so as to obtain the C-E characteristics used for identifying the individual radiation source.
Further, the embodiment of the invention also provides a radiation source individual identification system, which comprises the radiation source fingerprint extraction device based on the C-E characteristics and an SVM classifier, wherein the C-E characteristics extracted by the radiation source fingerprint extraction device are input into the SVM classifier for classification learning, so that the radiation source individual is identified through characteristic clustering.
In order to verify the effectiveness of the technical scheme of the present invention, the following is further explained with reference to the preferred embodiment of fig. 2 and the simulation experimental data in fig. 3 to 13:
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