CN118981624B - A radio signal feature automatic extraction system and extraction method thereof - Google Patents
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Abstract
本发明公开了一种无线电信号特征自动提取系统及其提取方法，涉及无线电信号特征提取技术领域，包括计算每组样本无线电信号数据的样本信号质量系数和无线电信号的质量阈值，筛选信号质量主影响特征及其特征权重；当待测信号质量系数大于无线电信号的质量阈值时，向外发出无线电信号干扰分析预警，计算每个信号质量主影响特征的干扰程度，获得每个信号质量主影响特征的干扰权重；接收到无线电信号干扰分析预警后，依次校正信号质量主影响特征，判断校正后的待测无线电信号数据的待测信号质量系数是否小于无线电信号的质量阈值，直至待测信号质量系数小于无线电信号的质量阈值。可以逐步改善信号的整体质量，避免不必要的校正操作。
The present invention discloses a radio signal feature automatic extraction system and an extraction method thereof, which relates to the technical field of radio signal feature extraction, including calculating the sample signal quality coefficient of each group of sample radio signal data and the quality threshold of the radio signal, screening the main influencing features of the signal quality and their feature weights; when the quality coefficient of the signal to be tested is greater than the quality threshold of the radio signal, sending out a radio signal interference analysis warning, calculating the interference degree of each main influencing feature of the signal quality, and obtaining the interference weight of each main influencing feature of the signal quality; after receiving the radio signal interference analysis warning, correcting the main influencing features of the signal quality in turn, judging whether the quality coefficient of the signal to be tested of the corrected radio signal data to be tested is less than the quality threshold of the radio signal, until the quality coefficient of the signal to be tested is less than the quality threshold of the radio signal. The overall quality of the signal can be gradually improved, and unnecessary correction operations can be avoided.
Description
Technical Field
The invention relates to the technical field of radio signal feature extraction, in particular to an automatic radio signal feature extraction method.
Background
With the rapid development of wireless communication technology, radio signals play an increasingly important role in the fields of daily life, industrial production, military applications, and the like. However, the radio signal is susceptible to various interference factors, such as multipath effects, noise interference, signal attenuation, etc., during transmission, which all cause degradation in signal quality, thereby affecting the reliability and stability of communication. In recent years, with the rapid development of artificial intelligence technologies such as machine learning, deep learning and the like, new ideas and methods for automatically extracting radio signal characteristics are provided. These techniques enable automatic classification, identification, and extraction of signals by training models to automatically learn the feature representation of the signals. Compared with the traditional method, the automatic radio signal characteristic extraction method based on artificial intelligence has higher accuracy and faster processing speed, and can be better suitable for complex and changeable wireless communication environments.
In the Chinese application with publication number CN113225145A, a multi-dimensional time-varying characteristic visualization method of radio signals is disclosed, which comprises the steps of acquiring radio signal data, classifying the acquired radio signals, calculating the average center frequency, average bandwidth, average signal intensity and average carrier-to-noise ratio of each type of radio signal, dividing a time period into time slices, calculating the average signal intensity and average carrier-to-noise ratio of each time slice, drawing a radio signal data frequency-time abstract graph, carrying out visual coding, and drawing a radio signal data signal flow graph. The multi-dimensional characteristics of the radio signal are visualized as a time-varying situation, the characteristics of the radio signal are presented in a radio signal river map, and all the characteristics of the required radio signal are available to the user.
In the application of the invention, the complete radio signal diagram is divided into a plurality of visual coding units, and the visual coding design of the 'Morse coding' signal abstract enables a user to integrally know the occurrence and disappearance of the radio signal in a short time, and as the method mainly focuses on the existence (namely the occurrence and the disappearance) of the signal, the signal quality is not concerned, and important information of the signal quality, such as signal strength, signal-to-noise ratio, phase stability and the like, may be ignored, so that the actual situation of the signal cannot be comprehensively known, misjudgment on the communication quality is caused, and the accuracy of decision is further affected.
To this end, the invention provides an automatic extraction system and an extraction method for radio signal characteristics.
Disclosure of Invention
The invention provides an automatic extraction system and an extraction method for radio signal characteristics, which aims at overcoming the defects of the prior art and filters signal quality main influence characteristics and characteristic weights thereofCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristicThe method is favorable for accurately identifying key factors causing signal quality degradation, optimizing resource allocation according to weight, and adding more resources for monitoring, analyzing and processing the characteristics with higher interference weight, so that the anti-interference capability and stability of the whole system are improved. After receiving the radio signal interference analysis and early warning, correcting the main influence characteristics of signal quality in sequence, and judging the quality coefficient of the signal to be detected of the corrected radio signal to be detected dataWhether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measuredThe signal quality is smaller than the quality threshold Z1 of the radio signal, the overall quality of the signal can be gradually improved, unnecessary correction operation is avoided, if the signal quality reaches the standard, the correction flow can be stopped, so that time and resources are saved, the influence of interference on the signal is effectively reduced, the stability and reliability of the signal are improved, and the technical problems recorded in the background art are solved.
The invention is realized by the following technical scheme that the method for automatically extracting the radio signal characteristics comprises the following steps:
building a standard database and a sample data set of radio signals, and calculating a sample signal quality coefficient of each set of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof;
When the quality coefficient of the signal to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristic;
After receiving the radio signal interference analysis and early warning, correcting the main influence characteristics of signal quality in sequence, and judging the quality coefficient of the signal to be detected of the corrected radio signal to be detected data
Whether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measured
Less than the quality threshold Z1 of the radio signal.
Further, a sample data set containing radio signal characteristics and signal quality indexes is collected, and a sample signal quality coefficient of each group of sample radio signal data is calculated:
Where a denotes the sequential numbering of each set of sample radio signal data in the sample data set,For the signal-to-noise ratio of the sample radio signal,Indicating the bit error rate of the sample radio signal,Representing the signal to noise ratio of a standard radio signal in a standard database of radio signals,Representing the error rate of a standard radio signal in a standard database of radio signals,Is a positive number for preventing a divide-by-zero error,Is the midpoint offset of the Sigmoid function in the signal-to-noise ratio part, is used for adjusting the central position of the influence of the signal-to-noise ratio on the quality coefficient,The offset of the midpoint of the Sigmoid function in the bit error rate part is used for adjusting the central position of the influence of the bit error rate on the quality coefficient.
Further, sample signal quality coefficient means using sample radio signal dataAnd standard deviationTo calculate the quality threshold Z1 of the radio signal, in particular as follows:
Wherein 1.645 is derived from the standard normal distribution table, corresponding to a 2.5% tail probability for the two-sided test.
Further, a sample data set containing radio signal characteristics and a sample signal quality coefficient are to be obtainedIntroducing SPSS analysis software to calculate the characteristics and quality coefficients of each radio signalThe absolute value of the pearson correlation coefficient of (2) is selected from the features before 10 as the main influence features of the signal quality after sorting from large to small, and the absolute value of the pearson correlation coefficient corresponding to the main influence features of the signal quality is recorded as the feature weight。
The pearson correlation coefficient (Pearson Correlation Coefficient) is one of the most commonly used correlation measurement methods for measuring a linear relationship between two consecutive variables, with a value in the range of-1 to 1, where 1 represents a complete positive correlation, -1 represents a complete negative correlation, and 0 represents no correlation.
Further, a receiving antenna is used for receiving the radio signal to be tested, and a digital signal processing technology is utilized for analyzing the signal to noise ratio of the radio signal to be testedAnd error rateCalculating the quality coefficient of the signal to be measured of the radio signal data to be measured:
Where i denotes a reception time of radio signal data, i=1, 2,..and n.
Further, when the quality coefficient of the signal to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCombining feature weightsAnd a standard database of radio signals, calculating the interference level of each signal quality primary influence feature:
Wherein,
k
A number representing a dominant impact characteristic of signal quality,
k=
1、2、...、10,
A standard value representing a dominant impact characteristic of signal quality.
Further, the interference degree of each signal quality main influence characteristic of all the radio signals to be measured is countedIs recorded as the mean value of each signal quality main influence characteristic。
Further, after receiving the radio signal interference analysis and early warning, the interference weight of each signal quality main influence characteristic is usedAnd (3) sorting from large to small, correcting the signal quality main influence characteristic from the first position, performing digital filtering, equalization or interpolation algorithm and the like on the radio signal to be detected according to the correction operation of the signal quality main influence characteristic, and correcting the signal quality main influence characteristic to be a standard value.
For example, automatic Gain Control (AGC) is used for signal strength correction, automatic Frequency Control (AFC) is used for frequency offset correction, frequency synchronization is used for frequency offset correction, and phase synchronization, phase estimation and compensation are used for phase error correction.
Digital filtering is the processing of signals by specific algorithms to remove unwanted frequency components or noise while preserving or enhancing desired signal characteristics. Common digital filters include low pass filters, high pass filters, band pass filters, and band reject filters.
Equalization is a signal processing technique that compensates for distortion of a signal during transmission due to channel characteristics (e.g., multipath effects, frequency response non-uniformities, etc.). The equalizer is typically a tunable filter whose parameters are adjusted according to the channel characteristics.
Interpolation is a method of estimating continuous function values between discrete data points. In signal processing, interpolation is often used for resampling, signal recovery, and error correction.
Further, after the primary influence characteristic of the first signal quality is corrected, the quality coefficient of the signal to be measured of the corrected radio signal to be measured data is judgedIf not, correcting the main influence characteristic of the quality of the next corrected signal in sequence until the quality coefficient of the signal to be detectedLess than the quality threshold Z1 of the radio signal.
A radio signal feature automatic extraction system comprising:
The main influence characteristic screening module constructs a standard database and a sample data set of the radio signals and calculates the sample signal quality coefficient of each group of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof;
The interference weight analysis module is used for determining the quality coefficient of the signal to be detectedWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristic;
The interference correction module sequentially corrects the main influence characteristics of signal quality after receiving the radio signal interference analysis and early warning, and judges the quality coefficient of the signal to be detected of the corrected radio signal data to be detected
Whether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measured
Less than the quality threshold Z1 of the radio signal.
The invention provides an automatic extraction system and an extraction method of radio signal characteristics, which have the following beneficial effects:
1. Building a standard database and a sample data set of radio signals, and calculating a sample signal quality coefficient of each set of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereofThe interference characteristics can be more accurately identified by quantitatively evaluating the signal quality and screening the main influence characteristics and the weights thereof, and a basis is provided for the follow-up optimization of the interference characteristics and the quick response of the signal quality problems.
2. When the quality coefficient of the signal to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristicThe method is favorable for accurately identifying key factors causing signal quality degradation, optimizing resource allocation according to weight, and adding more resources for monitoring, analyzing and processing the characteristics with higher interference weight, so that the anti-interference capability and stability of the whole system are improved.
3. After receiving the radio signal interference analysis and early warning, correcting the main influence characteristics of signal quality in sequence, and judging the quality coefficient of the signal to be detected of the corrected radio signal to be detected data
Whether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measured
The signal quality is smaller than the quality threshold Z1 of the radio signal, the overall quality of the signal can be gradually improved, unnecessary correction operation is avoided, and if the signal quality reaches the standard, the correction flow can be stopped, so that time and resources are saved, the influence of interference on the signal is effectively reduced, and the stability and reliability of the signal are improved.
Drawings
FIG. 1 is a flow chart of an automatic extraction method of radio signal characteristics according to the present invention;
Fig. 2 is a schematic structural diagram of an automatic radio signal feature extraction system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a method for automatically extracting radio signal features, comprising the following steps:
step one, constructing a standard database and a sample data set of radio signals, and calculating a sample signal quality coefficient of each group of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof。
The first step comprises the following steps:
And 101, extracting characteristics under the conventional transmission condition of the radio signal, including time domain characteristics, frequency domain characteristics, advanced characteristics, space, time distribution characteristics and signal quality characteristics, and constructing a standard database of the radio signal.
The time domain feature extraction comprises calculating time domain statistics such as mean value, variance, root mean square, peak factor, kurtosis coefficient and the like of signals, the frequency domain feature extraction comprises utilizing frequency domain analysis methods such as Fourier transformation and the like to extract frequency domain features such as frequency distribution, bandwidth, center of gravity frequency, mean square frequency and the like of the signals, the advanced feature extraction comprises adopting modern signal processing methods such as wavelet transformation, empirical Mode Decomposition (EMD), blind Signal Processing (BSP) and the like to further extract high-order features of the signals, the space and time distribution features comprise extracting features such as position distribution, energy distribution and the like, and the signal quality features comprise signal strength, signal to noise ratio and bit error rate.
Step 102, collecting sample data sets containing radio signal characteristics and signal quality indexes through experimental measurement, simulation or record of actual communication system, and calculating sample signal quality coefficients of each group of sample radio signal data:
Wherein,
a
A sequential number representing each set of sample radio signal data in the sample data set,
For the signal-to-noise ratio of the sample radio signal,
Indicating the bit error rate of the sample radio signal,
Representing the signal to noise ratio of a standard radio signal in a standard database of radio signals,
Representing the error rate of a standard radio signal in a standard database of radio signals,
Is a positive number for preventing a divide-by-zero error,
Is the midpoint offset of the Sigmoid function in the signal-to-noise ratio part, is used for adjusting the central position of the influence of the signal-to-noise ratio on the quality coefficient,
The offset of the midpoint of the Sigmoid function in the bit error rate part is used for adjusting the central position of the influence of the bit error rate on the quality coefficient.
Step 103, sample signal quality coefficient mean value of sample radio signal dataAnd standard deviationTo calculate the quality threshold Z1 of the radio signal, in particular as follows:
Wherein 1.645 is derived from the standard normal distribution table, corresponding to a 2.5% tail probability for the two-sided test.
Step 104, sample data set including radio signal characteristics and sample signal quality coefficientIntroducing SPSS analysis software to calculate the characteristics and quality coefficients of each radio signalThe absolute value of the pearson correlation coefficient of (2) is selected from the features before 10 as the main influence features of the signal quality after sorting from large to small, and the absolute value of the pearson correlation coefficient corresponding to the main influence features of the signal quality is recorded as the feature weight。
The pearson correlation coefficient (Pearson Correlation Coefficient) is one of the most commonly used correlation measurement methods for measuring a linear relationship between two consecutive variables, with a value in the range of-1 to 1, where 1 represents a complete positive correlation, -1 represents a complete negative correlation, and 0 represents no correlation.
In use, the contents of steps 101 to 104 are combined:
building a standard database and a sample data set of radio signals, and calculating a sample signal quality coefficient of each set of sample radio signal data
And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficient
Absolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof
The interference characteristics can be more accurately identified by quantitatively evaluating the signal quality and screening the main influence characteristics and the weights thereof, and a basis is provided for the follow-up optimization of the interference characteristics and the quick response of the signal quality problems.
Step two, when the quality coefficient of the signal to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristic。
The second step comprises the following steps:
step 201, receiving a radio signal to be tested by using a receiving antenna, and analyzing the signal-to-noise ratio of the radio signal to be tested by using a digital signal processing technology And error rateCalculating the quality coefficient of the signal to be measured of the radio signal data to be measured:
Where i denotes a reception time of radio signal data, i=1, 2,..and n.
Step 202, when the signal quality coefficient to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCombining feature weightsAnd a standard database of radio signals, calculating the interference level of each signal quality primary influence feature:
Where k denotes the number of the signal quality primary influencing feature, k=1, 2,..10,A standard value representing a dominant impact characteristic of signal quality.
Step 203, counting the interference degree of each signal quality main influence characteristic of all the radio signals to be testedIs recorded as the mean value of each signal quality main influence characteristic。
In use, the contents of steps 201 to 203 are combined:
When the quality coefficient of the signal to be measured
When the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extracted
Calculating the interference degree of each signal quality main influence characteristic
Obtaining interference weight of each signal quality main influence characteristic
The method is favorable for accurately identifying key factors causing signal quality degradation, optimizing resource allocation according to weight, and adding more resources for monitoring, analyzing and processing the characteristics with higher interference weight, so that the anti-interference capability and stability of the whole system are improved.
Step three, after receiving radio signal interference analysis and early warning, correcting signal quality main influence characteristics in sequence, and judging the signal quality coefficient to be detected of corrected radio signal data to be detectedWhether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measuredLess than the quality threshold Z1 of the radio signal.
The third step comprises the following steps:
Step 301, after receiving the radio signal interference analysis and early warning, according to the interference weight of each signal quality main influence characteristic And (3) sorting from large to small, correcting the signal quality main influence characteristic from the first position, performing digital filtering, equalization or interpolation algorithm and the like on the radio signal to be detected according to the correction operation of the signal quality main influence characteristic, and correcting the signal quality main influence characteristic to be a standard value.
For example, automatic Gain Control (AGC) is used for signal strength correction, automatic Frequency Control (AFC) is used for frequency offset correction, frequency synchronization is used for frequency offset correction, and phase synchronization, phase estimation and compensation are used for phase error correction.
Digital filtering is the processing of signals by specific algorithms to remove unwanted frequency components or noise while preserving or enhancing desired signal characteristics. Common digital filters include low pass filters, high pass filters, band pass filters, and band reject filters.
Equalization is a signal processing technique that compensates for distortion of a signal during transmission due to channel characteristics (e.g., multipath effects, frequency response non-uniformities, etc.). The equalizer is typically a tunable filter whose parameters are adjusted according to the channel characteristics.
Interpolation is a method of estimating continuous function values between discrete data points. In signal processing, interpolation is often used for resampling, signal recovery, and error correction.
302, After the correction of the primary influence characteristic of the primary signal quality is completed, judging the signal quality coefficient to be measured of the corrected radio signal data to be measuredIf not, correcting the main influence characteristic of the quality of the next corrected signal in sequence until the quality coefficient of the signal to be detectedLess than the quality threshold Z1 of the radio signal.
In use, the contents of steps 301 and 302 are combined:
After receiving the radio signal interference analysis and early warning, correcting the main influence characteristics of signal quality in sequence, and judging the quality coefficient of the signal to be detected of the corrected radio signal to be detected data
Whether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measured
The signal quality is smaller than the quality threshold Z1 of the radio signal, the overall quality of the signal can be gradually improved, unnecessary correction operation is avoided, and if the signal quality reaches the standard, the correction flow can be stopped, so that time and resources are saved, the influence of interference on the signal is effectively reduced, and the stability and reliability of the signal are improved.
Referring to fig. 2, the present invention provides an automatic radio signal feature extraction system, comprising:
The main influence characteristic screening module constructs a standard database and a sample data set of the radio signals and calculates the sample signal quality coefficient of each group of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof;
The interference weight analysis module is used for determining the quality coefficient of the signal to be detectedWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristic;
The interference correction module sequentially corrects the main influence characteristics of signal quality after receiving the radio signal interference analysis and early warning, and judges the quality coefficient of the signal to be detected of the corrected radio signal data to be detectedWhether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measuredLess than the quality threshold Z1 of the radio signal.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (10)
1. The automatic extraction method of the radio signal characteristics is characterized by comprising the following steps:
building a standard database and a sample data set of radio signals, and calculating a sample signal quality coefficient of each set of sample radio signal data And a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereof;
When the quality coefficient of the signal to be measuredWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristic;
After receiving the radio signal interference analysis and early warning, correcting the main influence characteristics of signal quality in sequence, and judging the quality coefficient of the signal to be detected of the corrected radio signal to be detected dataWhether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measuredLess than the quality threshold Z1 of the radio signal.
2. A method for automatically extracting characteristics of a radio signal according to claim 1, wherein:
collecting a sample data set containing radio signal characteristics and signal quality indicators, and calculating a sample signal quality coefficient for each set of sample radio signal data :
Where a denotes the sequential numbering of each set of sample radio signal data in the sample data set,For the signal-to-noise ratio of the sample radio signal,Indicating the bit error rate of the sample radio signal,Representing the signal to noise ratio of a standard radio signal in a standard database of radio signals,Representing the error rate of a standard radio signal in a standard database of radio signals,Is a positive number for preventing a divide-by-zero error,Is the midpoint offset of the Sigmoid function in the signal-to-noise ratio part, is used for adjusting the central position of the influence of the signal-to-noise ratio on the quality coefficient,The offset of the midpoint of the Sigmoid function in the bit error rate part is used for adjusting the central position of the influence of the bit error rate on the quality coefficient.
3. A method for automatically extracting radio signal features according to claim 2, wherein the average value of sample signal quality coefficients of the sample radio signal data is usedAnd standard deviationTo calculate the quality threshold Z1 of the radio signal, in particular as follows: Wherein 1.645 is derived from the standard normal distribution table, corresponding to a 2.5% tail probability for the two-sided test.
4. A method for automatically extracting radio signal features according to claim 3, wherein the sample data set containing the radio signal features and the sample signal quality coefficients are obtainedIntroducing SPSS analysis software to calculate the characteristics and quality coefficients of each radio signalThe absolute value of the pearson correlation coefficient of (2) is selected from the features before 10 as the main influence features of the signal quality after sorting from large to small, and the absolute value of the pearson correlation coefficient corresponding to the main influence features of the signal quality is recorded as the feature weight。
5. A method for automatically extracting characteristics of a radio signal according to claim 1, wherein:
receiving a radio signal to be measured by using a receiving antenna, and analyzing the signal-to-noise ratio of the radio signal to be measured by using a digital signal processing technology And error rateCalculating the quality coefficient of the signal to be measured of the radio signal data to be measured:Where i denotes a reception time of radio signal data, i=1, 2,..and n.
6. The method for automatically extracting radio signal features according to claim 1, wherein when the quality coefficient of the signal to be detected isWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCombining feature weightsAnd a standard database of radio signals, calculating the interference level of each signal quality primary influence feature:Where k denotes the number of the signal quality primary influencing feature, k=1, 2,..10,A standard value representing a dominant impact characteristic of signal quality.
7. The method for automatically extracting radio signal features according to claim 1, wherein the interference level of each signal quality main influence feature of all radio signals to be detected is countedIs recorded as the mean value of each signal quality main influence characteristic。
8. The method for automatically extracting radio signal features according to claim 7, wherein the interference weight of each signal quality main influence feature is used after the radio signal interference analysis and early warning is receivedAnd (3) sorting from large to small, correcting the signal quality main influence characteristic from the first digit, and correcting the signal quality main influence characteristic to be a standard value.
9. The method for automatically extracting radio signal features according to claim 8, wherein after correction of the primary influence feature of the quality of the first signal, the quality coefficient of the signal to be measured of the corrected radio signal to be measured is determinedIf not, correcting the main influence characteristic of the quality of the next corrected signal in sequence until the quality coefficient of the signal to be detectedLess than the quality threshold Z1 of the radio signal.
10. A radio signal feature automatic extraction system for implementing the method of any one of claims 1 to 9 is characterized by comprising a main influence feature screening module for constructing a standard database and a sample data set of radio signals and calculating sample signal quality coefficients of each set of sample radio signal dataAnd a quality threshold Z1 of the radio signal, and calculates each radio signal characteristic and signal quality coefficientAbsolute value of pearson correlation coefficient, and screening signal quality main influence characteristic and characteristic weight thereofAn interference weight analysis module for determining the quality coefficient of the signal to be testedWhen the signal quality is larger than the quality threshold Z1 of the radio signal, the interference analysis and early warning of the radio signal are sent outwards, and the main influence characteristics of the signal quality of the radio signal to be detected are extractedCalculating the interference degree of each signal quality main influence characteristicObtaining interference weight of each signal quality main influence characteristicThe interference correction module sequentially corrects the main influence characteristics of signal quality after receiving the radio signal interference analysis and early warning, and judges the quality coefficient of the signal to be detected of the corrected radio signal data to be detectedWhether or not it is smaller than the quality threshold Z1 of the radio signal until the quality coefficient of the signal to be measuredLess than the quality threshold Z1 of the radio signal.
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