Anti-interference method based on data link physical layer combination

Abstract

The invention discloses an anti-interference method based on data link physical layer combination, and belongs to the technical field of data link communication. The method comprises the following steps: acquiring a data link signal, identifying an interference source, and generating a dynamic high-quality frequency point library; generating an initial frequency hopping sequence based on the dynamic high-quality frequency point library; performing spread spectrum processing on the data link signal after RS coding; performing frequency hopping modulation on the data link signal after the spread spectrum processing; monitoring the quality of a communication channel in real time, and if a self-adaptive frequency selection condition is triggered, carrying out self-adaptive frequency selection; and issuing the adjusted frequency hopping sequence to the unmanned aerial vehicle. According to the invention, by combining the spread spectrum, frequency hopping and adaptive frequency selection technologies and carrying out frequency point quality evaluation and interference source prediction, the defects of adaptive frequency selection in the aspects of frequency point selection accuracy, switching speed and interference prediction capability in the prior art are effectively overcome, and the anti-interference capability and reliability of communication are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data link communication, and in particular to a combined anti-jamming method based on the physical layer of a data link. Background Art

[0002] With the rapid development of modern communication technologies, data links have been widely used in military and civilian fields. Data links are mainly used to achieve information sharing and cooperative operations between different platforms, and their stability, reliability, and anti-jamming capabilities are crucial.

[0003] Existing data link systems mainly rely on a single anti-jamming means, such as frequency hopping technology or spread spectrum technology, to cope with interference.

[0004] However, in the process of implementing the technical solutions of the embodiments of the present invention in this application, it is found that the above technologies have at least the following technical problems: In the prior art, the frequency point switching mode of the frequency hopping technology is relatively fixed and is easily detected and interfered by the enemy; the anti-jamming performance of the spread spectrum technology is limited in a strong interference environment. In addition, although the adaptive frequency selection method in the prior art can effectively avoid interference, there are problems such as inaccurate frequency point selection, large frequency point switching delay, and insufficient prediction ability for interference sources, resulting in an increased risk of communication interruption. Summary of the Invention

[0005] By providing a combined anti-jamming method based on the physical layer of a data link in an embodiment of this application, the problems of inaccurate frequency point selection, large switching delay, and insufficient prediction ability for interference sources in adaptive frequency selection in the prior art are solved, and intelligent and accurate selection, rapid switching of frequency points, and effective prediction of interference sources are realized, thereby improving the anti-jamming ability and reliability of communication.

[0006] An embodiment of this application provides a combined anti-jamming method based on the physical layer of a data link, including the following steps: scanning the working frequency band by a transmitter to obtain a data link signal, identifying interference sources, and generating a dynamic high-quality frequency point library; Real-time synchronizing the dynamic high-quality frequency point library to the UAV terminal; Based on the dynamic high-quality frequency point library, selecting an optimal frequency point set and generating an initial frequency hopping sequence; Performing RS coding on the data link signal, and performing spread spectrum processing on the RS-coded data link signal; Performing frequency hopping modulation on the spread spectrum processed data link signal based on the initial frequency hopping sequence; Real-time monitoring the communication channel quality, and if the adaptive frequency selection condition is triggered, performing adaptive frequency selection to generate an adjusted frequency hopping sequence; Sending the adjusted frequency hopping sequence to the UAV, and the UAV receives the frequency hopping signal according to the adjusted frequency hopping sequence and restores the original data link signal to complete the communication process.

[0007] Further, the steps of obtaining the data link signal, identifying the interference source, and generating the dynamic high-quality frequency point library include: Scanning multiple frequency points within the working frequency band through the spectrum sensing module of the transmitting terminal to obtain the data link signal feature information of each frequency point in real time; Analyzing the obtained data link signal feature information, identifying the interference source signals therein, and obtaining multiple data of the interference source signals; Based on the multiple data of the obtained interference source signals, evaluating the quality of each frequency point, and screening out the frequency points that meet the preset quality standards; Recording the screened frequency points as high-quality frequency points, summarizing and organizing them to generate a dynamic high-quality frequency point library.

[0008] Further, the steps of adaptive frequency selection include: Constructing a real-time spectrum map including each frequency point, and at the same time analyzing the interference source to predict the interference behavior of the interference source; Based on the real-time spectrum map and the interference source analysis results, comprehensively evaluating each frequency point, dynamically adjusting the priority of the frequency points, and forming a backup frequency point library; Based on the interference source prediction results, performing pre-synchronization operations on the backup frequency points in advance; When the switching condition is triggered by the obtained physical data of the current frequency point, performing frequency point switching to complete adaptive frequency selection.

[0009] Further, the steps of constructing a real-time spectrum map including each frequency point include: Scanning the working frequency band through the broadband RF sensor carried by the UAV to collect the physical data of each frequency point in real time; Binding the collected physical data of each frequency point with the geographical information system coordinates to generate a frequency-space joint distribution matrix; Fusing the historical interference event database, marking the activity trajectories of persistent interference sources and the spatio-temporal distribution hotspots of instantaneous interference; Constructing a three-dimensional spectrum map of each frequency point with a timestamp.

[0010] Further, the steps of analyzing the interference source and predicting the interference behavior of the interference source include: Extracting the time-frequency domain features of the interference source, where the time-frequency domain features include modulation distortion degree, power ramp-up slope, and spectrum diffusion width; Identifying deceptive interference according to the modulation distortion degree, and determining the suppression interference intensity level according to the power ramp-up slope; Calculating the interference coverage radius based on the spectrum diffusion width, and combining the direction of arrival estimation to locate the physical position of the interference source; Input the current time-frequency domain features into the long short-term memory network prediction model to predict the interference migration path and active probability of the interference source.

[0011] Further, the steps of identifying deceptive interference based on the modulation distortion degree and determining the suppression interference intensity level according to the power sudden rise slope include: Extract the modulation signal feature parameters from the interference source, including carrier frequency, modulation index, and symbol rate; Conduct a difference analysis on the extracted modulation signal feature parameters and the preset ideal modulation parameters, and calculate the modulation distortion degree through the modulation distortion degree formula: ; In the formula, is the modulation distortion degree, is the actual modulation parameter, is the ideal modulation parameter, is the average value of the modulation parameters, is the number of modulation parameters; When is not less than the preset distortion degree threshold, it is determined that there is deceptive interference; Real-time monitor the power of the data link signal, and record the occurrence time and the peak time ; Calculate the power sudden rise time , and record the power change amount , where represents the power peak, represents the baseline power before the power sudden rise.

[0012] Further, the steps of calculating the interference coverage radius based on the spectrum diffusion width include: Calculate the power sudden rise slope according to the power sudden rise slope formula: ; In the formula, is the power sudden rise slope; When is not less than the preset slope threshold, it is determined as high-intensity suppression interference; Calculate the interference coverage radius through the interference coverage radius formula: ; In the formula, is the interference coverage radius, is the interference signal power, is the propagation loss at the reference distance, is the reference distance, is the propagation loss exponent, is the spectrum diffusion width.

[0013] Furthermore, the steps of comprehensively evaluating each frequency point include: By combining the spectrum map and interference source analysis results with a machine learning algorithm, a frequency point evaluation index system is constructed to conduct a comprehensive evaluation of each frequency point. The evaluation index system includes the current interference intensity of the frequency point, the expected interference probability, the transmission loss, and the multipath effect index; Dynamically adjust the frequency priority based on comprehensive evaluation results; Arrange the frequencies based on the comprehensive evaluation results, and select the top K frequencies to form a backup frequency library, where K is not 0.

[0014] Furthermore, the steps of real-time monitoring of the communication channel quality include: The signal analysis unit of the drone terminal collects the interference power value, signal-to-noise ratio and bit error rate of the current communication frequency in real time; Compare the collected interference power values, signal-to-noise ratio, and bit error rate with the historical quality baseline of the corresponding frequency points in the dynamic high-quality frequency point library to calculate the channel quality deviation; When the interference power value is not less than the preset interference threshold, or the signal-to-noise ratio continuously drops to the preset signal-to-noise ratio threshold, or the bit error rate mutation value reaches the preset mutation threshold, it is determined that the adaptive frequency selection condition is triggered; If the channel quality deviation is not less than the preset deviation threshold, it is determined that the adaptive frequency selection condition is triggered.

[0015] Furthermore, the step of calculating the channel quality deviation includes: Calculate the deviation of interference power value, signal-to-noise ratio and bit error rate: ; ; ; Where, is the interference power deviation, is the signal-to-noise ratio deviation, is the bit error rate deviation, is the interference power value, is the signal-to-noise ratio, is the bit error rate, is the historical interference power mean, is the historical mean signal-to-noise ratio, is the historical bit error rate average; The channel quality deviation is obtained by the channel quality deviation formula: ; Where, is the channel quality deviation, 、 、 are all weight factors.

[0016] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By combining adaptive frequency selection with machine learning algorithms, high-quality frequency points are intelligently screened, thereby accurately identifying and avoiding interfering frequency points, realizing intelligent and accurate selection of frequency points, and effectively solving the problem of inaccurate frequency point selection in adaptive frequency selection in the prior art.

[0017] 2. Through pre-synchronization operations, the synchronization of backup frequency points is completed in advance, so that frequency points can be quickly switched when interference occurs, realizing fast switching of frequency points, effectively solving the problem of large time delay in frequency point switching in adaptive frequency selection in the prior art, and improving the real-time performance and reliability of communication.

[0018] 3. Through multi-dimensional spectrum environment perception and interference source behavior prediction, using a long short-term memory network prediction model, the interference behavior of interference sources is predicted in advance, realizing effective prediction of interference sources, effectively solving the problem of insufficient interference source prediction ability in adaptive frequency selection in the prior art, and enhancing the anti-interference ability and communication quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart of a combined anti-interference method based on the physical layer of a data link provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] By providing a combined anti-interference method based on the physical layer of a data link in the embodiments of the present application, the deficiencies of adaptive frequency selection in terms of frequency point selection accuracy, switching speed, and interference prediction ability in the prior art are solved. Through comprehensive evaluation of frequency point quality, combined with pre-synchronization operations to achieve fast frequency point switching, and using a long short-term memory network prediction model to accurately predict the behavior of interference sources, intelligent and accurate selection and fast switching of frequency points are realized, enhancing the adaptability of the system to complex electromagnetic environments and the reliability of communication links.

[0021] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0022] As Figure 1 shown, it is a flowchart of a combined anti-interference method based on the physical layer of a data link provided by an embodiment of the present application. The method includes the following steps: The transmitting machine scans the working frequency band, acquires data link signals, identifies interference sources, and generates a dynamic high-quality frequency point library; Synchronize the dynamic high-quality frequency point library to the UAV terminal in real time; Based on the dynamic high-quality frequency point library, select the optimal frequency point set and generate an initial frequency hopping sequence; The steps of generating the initial frequency hopping sequence include: selecting a certain number of high-quality frequency points from the dynamic high-quality frequency point library to form a high-quality frequency point set; sorting or combining the selected high-quality frequency point set according to a preset frequency hopping rule or algorithm, and determining the sorted or combined frequency point set as the initial frequency hopping sequence; Perform RS encoding on the data link signal, and perform spread spectrum processing on the RS-encoded data link signal; Perform frequency hopping modulation on the spread spectrum processed data link signal based on the initial frequency hopping sequence; Real-time monitor the communication channel quality. If the adaptive frequency selection condition is triggered, that is, when it is detected that the interference power of the interference source is not less than the preset interference threshold, or the signal-to-noise ratio continuously drops to the preset signal-to-noise ratio threshold, or the mutation value of the bit error rate reaches the preset mutation threshold, perform adaptive frequency selection to generate an adjusted frequency hopping sequence; Send the adjusted frequency hopping sequence to the unmanned aerial vehicle (UAV). The UAV receives the frequency hopping signal according to the adjusted frequency hopping sequence and restores the original data link signal to complete the communication process.

[0023] Furthermore, in this embodiment, the steps of obtaining the data link signal and identifying the interference source to generate the dynamic high-quality frequency point library include: Scan multiple frequency points within the working frequency band through the spectrum sensing module of the transmitting end machine to obtain the data link signal characteristic information of each frequency point in real time; Analyze the obtained data link signal characteristic information, identify the interference source signals therein, and obtain multiple data of the interference source signals; Based on the multiple data of the obtained interference source signals, perform quality evaluation on each frequency point. The steps of performing quality evaluation include: through the spectrum sensing module of the transmitting end machine, monitor and analyze the data link signal characteristic information of each frequency point within the working frequency band in real time, identify the interference source signals and their multiple data; evaluate the performance of each frequency point under interference through a preset frequency point quality standard, and screen out the frequency points that meet the preset quality standard.

[0024] Record the screened frequency points as high-quality frequency points, and perform summary and collation to form a dynamic high-quality frequency point library.

[0025] Furthermore, the physical data of the current frequency point are obtained in real time through the spectrum sensing module of the transmitting end machine, including the interference intensity and communication quality of the frequency point, and the electromagnetic environment is sensed to construct a real-time spectrum map including the interference intensity, signal quality and surrounding environment characteristics of each frequency point, and perform dynamic update; at the same time, analyze the interference source, identify the type, location and interference mode of the main interference source through the signal analysis algorithm, and predict its interference behavior; Based on machine learning algorithms, combined with the spectrum map and the analysis results of interference sources, comprehensively evaluate each frequency point, considering indicators such as the current interference intensity, expected interference probability, transmission loss, and multipath effect of the frequency point. Based on the comprehensive evaluation results, dynamically adjust the priority of the frequency points, and preferentially select those frequency points with less interference, high transmission quality, and matching communication service priorities. At the same time, consider the diversity and dispersion of the frequency points, and form a backup frequency point library; Based on the interference source prediction results, perform pre-synchronization operations on the backup frequency points in advance, that is, while communicating on the current frequency point, the receivers and transmitters of the backup frequency points exchange and calibrate synchronization signals in advance; Real-time monitor the communication channel quality. If the adaptive frequency selection condition is triggered, perform adaptive frequency selection, perform frequency point switching, and complete the adaptive frequency selection. Since the pre-synchronization operation has been completed, the switching process is almost seamless and will not cause obvious communication interruption or data loss.

[0026] Further, the steps of constructing a real-time spectrum map including each frequency point are as follows: Scan the working frequency band through the broadband RF sensors carried by the UAV, and collect the physical data of each frequency point in real time. The physical data includes signal power intensity, signal-to-noise ratio, and multipath fading coefficient; Bind the physical data of each frequency point collected to the coordinates of the geographic information system to generate a frequency-space joint distribution matrix; Fuse the historical interference event database, and mark the activity trajectories of persistent interference sources and the spatio-temporal distribution hotspots of instantaneous interference; Construct a three-dimensional spectrum map of each frequency point with a timestamp.

[0027] Further, the steps of analyzing the interference source and predicting the interference behavior of the interference source are as follows: Extract the time-frequency domain features of the interference source. The time-frequency domain features include modulation distortion degree, power ramp slope, and spectrum diffusion width; Identify spoofing interference according to the modulation distortion degree, and determine the suppression interference intensity level according to the power ramp slope; Calculate the interference coverage radius based on the spectrum diffusion width, and combine the direction of arrival estimation to locate the physical position of the interference source; Input the current time-frequency domain features into the long short-term memory network prediction model to predict the interference migration path and activity probability of the interference source.

[0028] Further, the steps of identifying spoofing interference according to the modulation distortion degree and determining the suppression interference intensity level according to the power ramp slope are as follows: Extract the modulation signal characteristic parameters from the interference source, including carrier frequency, modulation index, and symbol rate; Analyze the difference between the extracted modulation signal characteristic parameters and the preset ideal modulation parameters, and calculate the modulation distortion degree through the modulation distortion formula: ; In the formula, is the modulation distortion degree, is the actual modulation parameter, is the ideal modulation parameter, is the average value of the modulation parameters, is the number of modulation parameters; When is not less than the preset distortion threshold, it is determined that there is spoofing interference; Real-time monitor the power of the data link signal and record the occurrence time and the time to reach the peak ; Calculate the power rise time , and record the power change , where represents the power peak, represents the baseline power before the power rise.

[0029] Furthermore, the steps for calculating the interference coverage radius based on the spectral diffusion width include: Calculate the power rise slope according to the power rise slope formula: ; In the formula, is the power rise slope; When is not less than the preset slope threshold, it is determined that there is high-intensity jamming; Calculate the interference coverage radius through the interference coverage radius formula: ; In the formula, is the interference coverage radius, is the interference signal power, is the propagation loss at the reference distance, is the reference distance, is the propagation loss exponent, is the spectral diffusion width.

[0030] Furthermore, the steps for comprehensively evaluating each frequency point include: Construct a frequency point evaluation index system through machine learning algorithms combined with spectral maps and interference source analysis results, and comprehensively evaluate each frequency point; The evaluation index system includes the current interference intensity, expected interference probability, transmission loss, and multipath effect index of the frequency point; Based on the comprehensive evaluation results, dynamically adjust the priority of the frequency points; Arrange the frequencies based on the comprehensive evaluation results, and select the top K frequencies to form a backup frequency library, where K is not 0.

[0031] Furthermore, the steps of real-time monitoring of the communication channel quality include: The signal analysis unit of the drone terminal collects the interference power value, signal-to-noise ratio and bit error rate of the current communication frequency in real time; Compare the collected interference power values, signal-to-noise ratio, and bit error rate with the historical quality baseline of the corresponding frequency points in the dynamic high-quality frequency point library to calculate the channel quality deviation; When the interference power value is not less than the preset interference threshold, or the signal-to-noise ratio continuously drops to the preset signal-to-noise ratio threshold, or the bit error rate mutation value reaches the preset mutation threshold, it is determined that the adaptive frequency selection condition is triggered; If the channel quality deviation is not less than the preset deviation threshold, it is determined that the adaptive frequency selection condition is triggered.

[0032] Furthermore, the step of calculating the channel quality deviation includes: Calculate the deviation of interference power value, signal-to-noise ratio and bit error rate: ; ; ; Where, is the interference power deviation, is the signal-to-noise ratio deviation, is the bit error rate deviation, is the interference power value, is the signal-to-noise ratio, is the bit error rate, is the historical interference power mean, is the historical mean signal-to-noise ratio, is the historical bit error rate average; The channel quality deviation is obtained by the channel quality deviation formula: ; Where, is the channel quality deviation, 、 、 are all weight factors.

[0033] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0034] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 a flow or flows and / or block or blocks Figure 1 or blocks for implementing the specified functions.

[0035] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 a flow or flows and / or block or blocks Figure 1 or blocks.

[0036] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and / or block or blocks. Figure 1 a flow or flows and / or block or blocks Figure 1 or blocks.

[0037] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0038] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A combined anti-jamming method based on the physical layer of the data link, characterized in that, It includes the following steps: The transmitter scans the working frequency band, obtains the data link signal, identifies the interference source, and generates a dynamic high-quality frequency point library; The dynamic high-quality frequency point library is synchronized to the UAV terminal in real time; Based on the dynamic high-quality frequency point library, the optimal frequency point set is selected to generate an initial frequency hopping sequence; RS coding is performed on the data link signal, and the spread spectrum processing is performed on the RS-coded data link signal; Frequency hopping modulation is performed on the spread spectrum processed data link signal based on the initial frequency hopping sequence; The communication channel quality is monitored in real time. If the adaptive frequency selection condition is triggered, adaptive frequency selection is performed to generate an adjusted frequency hopping sequence; The adjusted frequency hopping sequence is sent to the UAV. The UAV receives the frequency hopping signal according to the adjusted frequency hopping sequence and restores the original data link signal to complete the communication process.

2. The method for combined anti-interference based on the physical layer of a data link according to claim 1, characterized in that The steps of obtaining the data link signal and identifying the interference source to generate a dynamic high-quality frequency point library include: The spectrum sensing module of the transmitter scans multiple frequency points in the working frequency band to obtain the data link signal feature information of each frequency point in real time; The obtained data link signal feature information is analyzed to identify the interference source signal therein, and multiple data of the interference source signal are obtained; Based on the multiple data of the obtained interference source signal, the quality of each frequency point is evaluated, and the frequency points meeting the preset quality standard are screened out; The screened frequency points are recorded as high-quality frequency points, and are summarized and sorted to generate a dynamic high-quality frequency point library.

3. The method for combining anti-interference based on the physical layer of a data link according to claim 2, wherein The steps of adaptive frequency selection include: Construct a real-time spectrum map including each frequency point, and at the same time analyze the interference source to predict the interference behavior of the interference source; Based on the real-time spectrum map and the interference source analysis result, a comprehensive evaluation is performed on each frequency point, the priority of the frequency point is dynamically adjusted, and a standby frequency point library is formed; Based on the interference source prediction result, pre-synchronization operation is performed on the standby frequency point in advance; Based on the physical data of the current frequency point obtained, when the switching condition is triggered, frequency point switching is performed to complete adaptive frequency selection.

4. The method for combined anti-interference based on the physical layer of a data link according to claim 3, wherein The steps of constructing a real-time spectrum map including each frequency point include: The broadband RF sensor carried by the UAV scans the working frequency band to collect the physical data of each frequency point in real time; The physical data of each frequency point collected is bound to the geographic information system coordinates to generate a frequency-space joint distribution matrix; Fusing the historical interference event database, marking the activity trajectory of the persistent interference source and the spatio-temporal distribution hot zone of the instantaneous interference; Construct a three-dimensional spectrum map of each frequency point with a timestamp.

5. The combination anti-interference method based on the physical layer of the data link according to claim 3, characterized in that, The steps of analyzing the interference source and predicting the interference behavior of the interference source include: Extract the time-frequency domain features of the interference source, and the time-frequency domain features include modulation distortion degree, power sudden rise slope, and spectrum diffusion width; Identify spoofing interference according to the modulation distortion degree, and determine the suppression interference intensity level according to the power sudden rise slope; Calculate the interference coverage radius based on the spectrum diffusion width, and combine the direction of arrival estimation to locate the physical position of the interference source; Input the current time-frequency domain features into the long short-term memory network prediction model to predict the interference migration path and activity probability of the interference source.

6. The method for combining anti-interference based on the physical layer of the data link according to claim 5, characterized in that The steps of identifying spoofing interference according to the modulation distortion degree and determining the suppression interference intensity level according to the power sudden rise slope include: Extract the modulation signal characteristic parameters from the interference source, including carrier frequency, modulation index, and symbol rate; Perform a difference analysis on the extracted modulation signal characteristic parameters and the preset ideal modulation parameters, and calculate the modulation distortion degree through the modulation distortion degree formula: ; In the formula, is the modulation distortion degree, is the actual modulation parameter, is the ideal modulation parameter, is the average value of the modulation parameters, is the number of modulation parameters; When is not less than a preset distortion threshold, it is determined that there is spoofing interference; Monitor the signal power of the real-time monitoring data link in real time, and record the occurrence time of the power sudden increase event and the time when the peak value is reached ; Calculate the power ramp-up time and record the power change where represents the power peak and represents the baseline power before the power ramp-up 7. The anti-interference method based on the combination of the physical layer of the data link according to claim 6, characterized in that, The steps for calculating the interference coverage radius based on the spectral diffusion width include: Calculate the power ramp rate according to the power ramp rate formula: ; In the formula, is the power ramp-up slope; When is not less than a preset slope threshold, it is determined as high-intensity suppression jamming; Calculate the interference coverage radius through the interference coverage radius formula: In the formula, is the interference coverage radius, is the interference signal power, is the propagation loss at the reference distance, is the reference distance, is the propagation loss exponent, is the spectral spreading width.

8. The method for combining anti-interference based on the physical layer of a data link according to claim 3, wherein The steps for comprehensively evaluating each frequency point include: Construct a frequency point evaluation index system through a machine learning algorithm combined with the spectral map and the interference source analysis results, and comprehensively evaluate each frequency point; The evaluation index system includes the current interference intensity, expected interference probability, transmission loss, and multipath effect index of the frequency point; Dynamically adjust the priority of the frequency points based on the comprehensive evaluation results; Arrange the frequency points according to the comprehensive evaluation results, and select the top K frequency points to form a backup frequency point library, where K is not 0.

9. The combined anti-interference method based on the physical layer of the data link according to claim 1, characterized in that, The steps for real-time monitoring of the communication channel quality include: The signal analysis unit of the UAV terminal device is used to collect the interference power value, signal-to-noise ratio, and bit error rate of the current communication frequency point in real time; Compare the collected interference power value, signal-to-noise ratio, and bit error rate with the historical quality baseline of the corresponding frequency point in the dynamic high-quality frequency point library, and calculate the channel quality deviation; When the interference power value is not less than the preset interference threshold, or the signal-to-noise ratio continuously drops to the preset signal-to-noise ratio threshold, or the bit error rate mutation value reaches the preset mutation threshold, it is determined that the adaptive frequency selection condition is triggered; If the channel quality deviation is not less than the preset deviation threshold, it is determined that the adaptive frequency selection condition is triggered.

10. The method for combining anti-interference based on the physical layer of a data link according to claim 9, characterized in that The steps for calculating the channel quality deviation include: Calculate the deviation degrees of the interference power value, signal-to-noise ratio, and bit error rate: ; ; ; Wherein, is the interference power deviation degree, is the signal-to-noise ratio deviation degree, is the bit error rate deviation degree, is the interference power value, is the signal-to-noise ratio, is the bit error rate, is the historical average interference power, is the historical average signal-to-noise ratio, is the historical average bit error rate; Obtain the channel quality deviation through the channel quality deviation formula: ; In the formula, is the channel quality deviation degree, , , are all weighting factors.

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