A UAV communication anti-interference method based on phased-control radar

Abstract

The present invention relates to the field of electronic technology, and provides a method for anti-interference of UAV communication based on phased-control radar, comprising: using the beam pointing of the phased-control radar to track the movement trajectory of the UAV in real time; performing filtering and amplification processing, pulse compression processing and phase subtraction cancellation processing on the collected echo signal to obtain the target echo signal; analyzing the spectrum characteristics of the target echo, identifying the interference source position and type of the interference signal according to the spectrum characteristics, and performing interference detection on the interference signal according to the interference source position and type; analyzing the communication change trend of the UAV according to the interference detection result, and constructing an interference suppression mechanism for the interference signal based on the communication change trend and the real-time beam pointing monitoring result of the UAV; performing anti-interference processing on the UAV communication based on the interference suppression mechanism to obtain the anti-interference result. The present invention aims to improve the anti-interference efficiency of UAV communication.

Description

Technical Field

[0001] The present invention relates to the field of electronic technology, and in particular to an anti-interference method for UAV communication based on phased-control radar. Background Art

[0002] UAV communication anti-interference refers to the safeguard measures taken to ensure that the UAV communication link is not affected by external electromagnetic interference during the execution of the UAV mission. The UAV communication system has high mobility and line-of-sight transmission channels, supporting business needs such as data backhaul of sensor nodes and cellular user communications. With the continuous expansion of the application scope of UAVs, the reliability of UAV communication systems has also attracted more and more attention, making UAV communication anti-interference technology an important guarantee for improving the reliability of UAV communication systems.

[0003] Existing anti-interference technology for drone communications mainly uses direct sequence spread spectrum and frequency hopping technology to resist interference for drone communications. This method distributes the signal over a wider frequency band and quickly changes the carrier frequency. While reducing the signal power spectrum density, it also increases the difficulty for the interferer to lock on to a specific frequency. However, this method requires ample broadband resources, while drone communications often have limited broadband resources, which affects the anti-interference efficiency of drone communications. Summary of the invention

[0004] The present invention provides a UAV communication anti-interference method based on phased-control radar, the main purpose of which is to improve the UAV communication anti-interference efficiency.

[0005] In a first aspect, the present invention provides a UAV communication anti-interference method based on phased-control radar, comprising:

[0006] Obtaining the position coordinates of the UAV, identifying the target beam angle pointing to the UAV using a preset phased-control radar according to the position coordinates, and tracking the movement trajectory of the UAV under the target beam angle in real time;

[0007] Collecting the echo signal under the moving track of the UAV, filtering and amplifying the echo signal to obtain a target signal, performing pulse compression processing on the target signal to obtain a compressed pulse signal, and performing subtraction and cancellation processing on the compressed pulse signal to obtain a target echo signal;

[0008] Performing spectrum analysis on the target echo signal to obtain a signal spectrum, identifying interference signals in the signal spectrum that do not match the expected signal frequency, locating the interference signal to obtain the interference source position, analyzing the spectrum characteristics of the interference signal, identifying the interference type of the interference signal based on the spectrum characteristics, and performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result, wherein the signal interference detection result refers to the data and analysis results obtained in the signal interference detection process, and performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result, including: collecting signal data of the interference signal according to the interference source position and the interference type; calculating the covariance matrix of the signal data; performing eigendecomposition on the covariance matrix to obtain a decomposition eigenvalue; setting a normal signal threshold of the decomposition eigenvalue; performing interference detection on the interference signal according to the normal signal threshold to obtain a signal interference detection result;

[0009] According to the signal interference detection result, the communication signal change trend of the UAV is analyzed, and the beam pointing of the UAV is monitored in real time, and based on the beam pointing and the interference type, an interference suppression mechanism corresponding to the interference signal is constructed;

[0010] Based on the interference suppression mechanism, anti-interference processing is performed on the UAV communication to obtain the anti-interference processing result of the UAV communication.

[0011] In a possible implementation manner of the first aspect, identifying a target beam angle pointing to the drone by using a preset phased control radar according to the position coordinates includes:

[0012] Performing coordinate conversion on the position coordinates to obtain target coordinates;

[0013] Calculating the azimuth and elevation of the UAV relative to the phased-control radar according to the position coordinates and the target coordinates;

[0014] Setting the beam pointing mode of the phased-control radar corresponding to the UAV;

[0015] Based on the azimuth angle, the elevation angle and the beam pointing mode, a target beam angle pointing to the UAV is identified.

[0016] In a possible implementation manner of the first aspect, performing pulse compression processing on the target signal to obtain a compressed pulse signal includes:

[0017] configuring a matched filter for the target signal;

[0018] Extracting a complex conjugate factor of the target signal, and performing time reversal processing on the complex conjugate factor to obtain a complex conjugate signal;

[0019] Identifying the complex conjugate signal and the corresponding frequency domain representation in the matched filter;

[0020] In the frequency domain representation, the target signal and the transfer function of the matched filter are multiplied to obtain a frequency domain product result;

[0021] According to the frequency domain multiplication result, the target signal is pulse compressed to obtain a compressed pulse signal.

[0022] In a possible implementation manner of the first aspect, performing subtraction cancellation processing on the compressed pulse signal to obtain a target echo signal includes:

[0023] Extracting signal samples that need to be subjected to subtraction alignment processing from the compressed pulse signal;

[0024] Performing synchronization processing on the time and phase of the signal sample to obtain a synchronization time and a synchronization phase;

[0025] Based on the synchronization time and the synchronization phase, performing signal alignment processing on the signal samples to obtain an alignment signal;

[0026] Unnecessary signals in the alignment signal are identified, and subtraction and cancellation processing is performed on the unnecessary signals to obtain target echo signals.

[0027] In a possible implementation manner of the first aspect, locating the interference signal to obtain the interference source position includes:

[0028] Collecting multi-directional echo signals of the UAV;

[0029] Performing signal separation processing on the multi-azimuth echo signals to obtain separated signals;

[0030] The phase difference between the separated signals is calculated, and based on the phase difference, the arrival angle of the multi-azimuth echo signal is calculated using the following formula:

[0031] ;

[0032] in, represents the arrival angle of the multi-directional echo signal, n represents the number of antennas in the antenna array corresponding to the multi-directional echo signal, It represents the signal received by the ith antenna in the antenna array at time t, and 2π represents the signal phase increment converted from the angular frequency. represents the distance from the ith antenna to the array reference point, represents the sine value of the arrival angle of the multi-azimuth echo signal, j represents the imaginary unit of the multi-azimuth echo signal, w represents the angular frequency of the multi-azimuth echo signal, and l represents the wavelength of the multi-azimuth echo signal;

[0033] Based on the arrival angle, a location of an interference source of the interference signal is determined.

[0034] In a possible implementation manner of the first aspect, analyzing the frequency spectrum characteristics of the interference signal includes:

[0035] Performing frequency domain conversion on the interference signal to obtain an interference signal spectrum;

[0036] Extracting the amplitude spectrum and phase spectrum of the interference signal from the interference signal spectrum;

[0037] Analyzing the frequency components and distribution of the interference signal according to the amplitude spectrum and the phase spectrum;

[0038] Based on the frequency components and the distribution, the frequency spectrum characteristics of the interference signal are analyzed.

[0039] In a possible implementation manner of the first aspect, performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result includes:

[0040] According to the interference source position and the interference type, collecting signal data of the interference signal;

[0041] The covariance matrix of the signal data is calculated using the following formula:

[0042] ;

[0043] Where R represents the covariance matrix of the signal data, N represents the number of samples of the signal data, and e represents the sample index of the signal data. represents the sample vector of the e-th signal data, represents the conjugate transpose of the e-th signal data sample vector, and H represents the sign of the conjugate transpose of the e-th signal data sample vector;

[0044] Performing eigendecomposition on the covariance matrix to obtain decomposition eigenvalues;

[0045] Setting a normal signal threshold of the decomposed eigenvalue;

[0046] According to the normal signal threshold, interference detection is performed on the interference signal to obtain a signal interference detection result.

[0047] In a possible implementation manner of the first aspect, analyzing a change trend of a communication signal of the drone according to the signal interference detection result includes:

[0048] Obtaining a position change interval of the UAV;

[0049] Analyzing the signal time variation pattern of the UAV within the position variation interval according to the signal interference detection result;

[0050] Extracting signal-to-noise ratio variation data of the communication signal in the signal time variation mode;

[0051] The communication signal change trend of the UAV is analyzed according to the signal time change pattern and the signal-to-noise ratio change data.

[0052] In a possible implementation manner of the first aspect, the real-time monitoring of the beam pointing of the drone includes:

[0053] Setting the beam pointing control mode of the UAV;

[0054] Calculating the beam pointing angle currently required by the UAV;

[0055] Based on the beam pointing angle and the beam pointing control method, the phase of the array antenna corresponding to the UAV is adjusted.

[0056] In a possible implementation manner of the first aspect, calculating the beam pointing angle currently required by the drone includes:

[0057] The following formula is used to calculate the beam pointing angle currently required by the UAV:

[0058] ;

[0059] in, It represents the beam pointing angle currently required by the UAV, L represents the radar wavelength corresponding to the UAV, d represents the spacing of the radar antenna array elements corresponding to the UAV, and M represents the offset of the beam pointing angle corresponding to the UAV.

[0060] The present invention can concentrate the energy of the phased-control radar to detect a specific direction, reduce interference signals from other directions, and improve the anti-interference performance of the drone by using a pre-set phased-control radar according to the position coordinates of the drone, and dynamically adjust the beam pointing according to the real-time position and speed information of the drone to ensure the stability of the drone communication link; secondly, the embodiment of the present invention can identify the interference signal of the drone communication by collecting the echo signal under the moving trajectory of the drone, so as to adopt a targeted anti-interference strategy to ensure the command link of the drone communication, and improve the signal-to-noise ratio of the signal by processing the information of the echo signal, so that the target signal has a relatively large transmission power, and at the same time, the radar resolution can be improved without losing the target detection information, and the influence of clutter can be effectively reduced or removed, and the detection efficiency of the target signal can be improved; further, the embodiment of the present invention can help identify the frequency distribution of the interference signal by performing spectrum analysis on the target echo signal to obtain the signal spectrum, so as to judge the position and type of the interference source, and identify the main components of the interference signal according to the position and type of the interference source, and design a suitable filter according to the main components of the interference to suppress the interference and ensure the accuracy of data transmission. Therefore, the anti-interference method for UAV communication based on phased radar provided in an embodiment of the present invention can improve the anti-interference efficiency of UAV communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A schematic diagram of a flow chart of a UAV communication anti-interference method based on phased-control radar provided by an embodiment of the present invention;

[0062] Figure 2 A functional module diagram of a UAV communication anti-interference method system based on phased-control radar provided in one embodiment of the present invention.

[0063] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0064] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0065] The embodiment of the present application provides a method for anti-interference of UAV communication based on phased-control radar. In the embodiment of the present application, the execution subject of the method for anti-interference of UAV communication based on phased-control radar includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for anti-interference of UAV communication based on phased-control radar can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0066] Reference Figure 1 FIG. 1 is a flow chart of a method for anti-interference of UAV communication based on phased-control radar provided by an embodiment of the present invention. In this embodiment, the method for anti-interference of UAV communication based on phased-control radar includes steps S1-S5.

[0067] S1. Obtain the position coordinates of the UAV, identify the target beam angle pointing to the UAV by using a preset phased-control radar according to the position coordinates, and track the moving trajectory of the UAV under the target beam angle in real time.

[0068] The embodiment of the present invention can ensure that the phased array radar quickly adjusts the beam pointing according to the position information of the drone by obtaining the position coordinates of the drone, and can always aim the beam at the drone. The drone refers to an aircraft that can be remotely controlled or fly autonomously without the need for a pilot in the cockpit, and the position coordinates refer to the coordinates of the drone in three-dimensional space, including longitude, latitude and altitude.

[0069] Optionally, the location coordinates of the drone can be obtained through a GPS positioning system.

[0070] Furthermore, the embodiment of the present invention can concentrate the energy of the phased-control radar to detect a specific direction by using a pre-set phased-control radar according to the position coordinates to identify the target beam angle pointing to the UAV, reduce interference signals from other directions, and improve the anti-interference performance of the UAV. The phased-control radar refers to a radar technology that uses electronic means to control the phase and amplitude of each radiating unit in the radar antenna array to achieve rapid pointing and shape changes of the antenna beam. The target beam angle refers to the optimal beam pointing angle that can accurately detect and track the position of the UAV.

[0071] As an embodiment of the present invention, the method of identifying the target beam angle pointing to the UAV based on the position coordinates using a pre-set phased control radar includes: performing coordinate conversion on the position coordinates to obtain target coordinates; calculating the azimuth and elevation of the UAV relative to the phased control radar based on the position coordinates and the target coordinates; setting the beam pointing mode of the phased control radar corresponding to the UAV; and identifying the target beam angle pointing to the UAV based on the azimuth, the elevation and the beam pointing mode.

[0072] Among them, the target coordinates refer to the position coordinates of the UAV in the coordinate system with the radar position as the origin, the azimuth refers to the angle of the UAV relative to the north of the radar, the elevation refers to the vertical angle of the UAV relative to the horizontal plane of the radar, and the beam pointing method refers to the way in which the phased radar adjusts the phase and amplitude of its antenna array so that the beam points to the azimuth and elevation of the UAV.

[0073] Optionally, the coordinate system conversion of the position coordinates can be obtained by converting the latitude and longitude coordinates of the UAV and the radar into coordinates in a rectangular coordinate system through an earth model, the azimuth and elevation calculation of the UAV relative to the phased array radar can be achieved using azimuth calculation formulas and elevation calculation formulas, and the beam pointing mode setting of the phased array radar corresponding to the UAV can be obtained by adjusting the phase delay of each antenna unit in the phased array radar.

[0074] The embodiment of the present invention can dynamically adjust the beam pointing according to the real-time position and speed information of the drone by real-time tracking the drone's moving trajectory under the target beam angle, thereby ensuring the stability of the drone's communication link. The drone's moving trajectory refers to the position sequence trajectory of the drone that changes with time in three-dimensional space, such as the longitude, latitude and altitude of the drone at different time points.

[0075] Optionally, the UAV movement trajectory tracking under the target beam angle can be obtained through a Kalman filter.

[0076] S2. Collect the echo signal under the moving track of the UAV, filter and amplify the echo signal to obtain the target signal, perform pulse compression processing on the target signal to obtain a compressed pulse signal, and perform subtraction and cancellation processing on the compressed pulse signal to obtain the target echo signal.

[0077] The embodiment of the present invention can identify interference signals of drone communications by collecting echo signals under the moving trajectory of the drone, thereby taking targeted anti-interference strategies to ensure the command link of drone communications. The echo signal refers to the signal reflected back from the drone collected by the phased array radar during the flight of the drone.

[0078] Optionally, the echo signal acquisition under the moving trajectory of the UAV can be obtained by a radar receiver, such as a superheterodyne receiver and a direct sampling receiver.

[0079] The embodiment of the present invention obtains a target signal by filtering and amplifying the echo signal, thereby improving the signal-to-noise ratio of the signal and facilitating subsequent detection and analysis of the signal. The target signal refers to a signal obtained after filtering and amplifying the echo signal.

[0080] Optionally, the filtering and amplification processing of the echo signal can be obtained by a digital signal processor.

[0081] Furthermore, the embodiment of the present invention can make the target signal have a relatively large transmission power by performing pulse compression processing on the target signal, and at the same time can improve the radar resolution without losing target detection information. The compressed pulse signal refers to a narrow pulse signal compressed by a wide pulse signal using a matched filter.

[0082] As an embodiment of the present invention, the pulse compression processing of the target signal to obtain a compressed pulse signal includes: configuring a matching filter for the target signal; extracting the complex conjugate factor of the target signal, and time-reversing the complex conjugate factor to obtain a complex conjugate signal; identifying the complex conjugate signal and the corresponding frequency domain representation in the matched filter; in the frequency domain representation, multiplying the target signal and the transfer function of the matched filter to obtain a frequency domain product result; and according to the frequency domain product result, performing pulse compression processing on the target signal to obtain a compressed pulse signal.

[0083] Among them, the matched filter refers to a linear filter used for signal detection and processing in radar and communication systems, the complex conjugate factor refers to a complex operation that keeps the real part of the signal unchanged and inverts the imaginary part, the complex conjugate signal refers to a signal obtained after complex conjugation and time reversal processing, the frequency domain representation refers to the conversion of a signal in the time domain into a representation in the frequency domain, the transfer function refers to a mathematical representation that describes the characteristics of a linear time-invariant system (LTI system), and the frequency domain product result refers to the result of multiplying the target signal and the transfer function of the matched filter in the frequency domain.

[0084] Optionally, the matched filter configuration of the target signal can be obtained through a linear filter, the extraction of the complex conjugate factor of the target signal can be implemented using Python, the time reversal processing of the complex conjugate factor can be obtained through MATLAB, the complex conjugate signal and the corresponding frequency domain representation in the matched filter can be implemented using fast Fourier transform, and the pulse compression processing of the target signal based on the frequency domain product result can be obtained through inverse fast Fourier transform.

[0085] Furthermore, the embodiment of the present invention can effectively reduce or remove the influence of clutter and improve the detection efficiency of the target signal by performing subtraction cancellation processing on the compressed pulse signal. The target echo signal refers to a signal obtained by performing subtraction cancellation processing on the reflection signal of the ground or other static objects, in which the influence of clutter has been removed or reduced.

[0086] As an embodiment of the present invention, the subtraction and cancellation processing of the compressed pulse signal to obtain the target echo signal includes: extracting signal samples that need to be subtracted and aligned in the compressed pulse signal; synchronizing the time and phase of the signal samples to obtain the synchronization time and the synchronization phase; based on the synchronization time and the synchronization phase, performing signal alignment processing on the signal samples to obtain an aligned signal; identifying unnecessary signals in the aligned signal, and performing subtraction and cancellation processing on the unnecessary signals to obtain the target echo signal.

[0087] Among them, the subtraction alignment processing refers to a signal processing technology used for noise suppression and speech enhancement in audio signal processing, the signal sample refers to a partial signal selected from a compressed pulse signal that needs to be subjected to subtraction cancellation processing, the synchronization time refers to the time synchronization of the sample signal, the synchronization phase refers to the phase synchronization of the signal sample, the alignment signal refers to a signal after time alignment and phase alignment processing, and the unnecessary signal refers to an unnecessary component in the alignment signal, such as interference, noise or other non-target signals.

[0088] Optionally, the synchronization processing of the time and phase of the signal samples can be obtained through numpy, the signal alignment processing of the signal samples based on the synchronization time and the synchronization phase can be implemented using the alignsignals function, the identification of unnecessary signals in the aligned signals can be obtained through a Doppler filter, and the subtraction cancellation processing of the unnecessary signals can be implemented using array operations in the numpy library.

[0089] S3. Perform spectrum analysis on the target echo signal to obtain a signal spectrum, identify interference signals in the signal spectrum that do not match the expected signal frequency, locate the interference signal to obtain the interference source position, analyze the spectrum characteristics of the interference signal, identify the interference type of the interference signal based on the spectrum characteristics, perform interference detection on the interference signal according to the interference source position and the interference type, and obtain a signal interference detection result.

[0090] The embodiment of the present invention performs spectral analysis on the target echo signal to obtain a signal spectrum, which can help identify the frequency distribution of the interference signal, thereby determining the location and type of the interference source. The signal spectrum refers to the amplitude and phase of each frequency component of the signal in the frequency domain.

[0091] Optionally, the spectrum analysis of the target echo signal may be obtained by Fourier transform, such as continuous Fourier transform, discrete Fourier transform, short-time Fourier transform, and the like.

[0092] Furthermore, the embodiments of the present invention can provide a basis for changing the carrier frequency of the UAV communication system by identifying interference signals in the signal spectrum that do not match the expected signal frequency, thereby avoiding these interference frequencies. The expected signal frequency refers to a specific frequency used in the UAV communication system during normal operation, and the interference signal refers to a signal that has a negative impact on the normal communication signal.

[0093] Optionally, the identification of interference signals in the signal spectrum that do not match the expected signal frequency may be obtained through a spectrum analyzer.

[0094] The embodiment of the present invention can achieve all-round coverage of spatial signals by utilizing the multi-channel receiving component of the phased array radar to locate the interference signal, thereby more accurately determining the location of the interference source. The multi-channel receiving component refers to a technical component that utilizes multiple antenna units inherent in the phased array radar to receive signals.

[0095] As an embodiment of the present invention, the method of locating the position of the interference signal to obtain the interference source position includes: collecting multi-directional echo signals of the drone; performing signal separation processing on the multi-directional echo signals to obtain separated signals; calculating the phase difference between the separated signals, and analyzing the arrival angle of the multi-directional echo signals based on the phase difference; and determining the interference source position of the interference signal based on the arrival angle.

[0096] Among them, the multi-directional echo signal refers to the signal from all directions of the UAV received simultaneously by multiple antenna units of the phased array radar, the separated signal refers to the signal after the received multi-directional echo signal is separated according to each antenna unit, the phase difference refers to the phase difference between two periodic signals with the same frequency, and the arrival angle refers to the direction angle of the signal relative to the receiver antenna array when it arrives at the receiver from the signal source.

[0097] Optionally, the phase difference between the separated signals can be obtained by a phase difference calculation formula.

[0098] Furthermore, in an optional embodiment of the present invention, the arrival angle of the multi-azimuth echo signal is calculated using the following formula:

[0099] ;

[0100] in, represents the arrival angle of the multi-directional echo signal, n represents the number of antennas in the antenna array corresponding to the multi-directional echo signal, It represents the signal received by the ith antenna in the antenna array at time t, and 2π represents the signal phase increment converted from the angular frequency. represents the distance from the ith antenna to the array reference point, represents the sine value of the arrival angle of the multi-azimuth echo signal, j represents the imaginary unit of the multi-azimuth echo signal, w represents the angular frequency of the multi-azimuth echo signal, and l represents the wavelength of the multi-azimuth echo signal.

[0101] The embodiment of the present invention can identify the main components of the interference signal by analyzing the spectral characteristics of the interference signal, and avoid these interference frequency bands through frequency hopping technology. The spectral characteristics refer to the manifestation of the signal in the frequency domain, which describes how the energy of a signal is distributed on different frequencies.

[0102] As an embodiment of the present invention, the analysis of the spectral characteristics of the interference signal includes: performing frequency domain conversion on the interference signal to obtain an interference signal spectrum; extracting the amplitude spectrum and phase spectrum of the interference signal in the interference signal spectrum; analyzing the frequency components and distribution of the interference signal based on the amplitude spectrum and the phase spectrum; and analyzing the spectral characteristics of the interference signal based on the frequency components and the distribution.

[0103] Among them, the interference signal spectrum refers to the spectrum representation of the interference signal converted from the time domain to the frequency domain, the amplitude spectrum refers to the spectrum amplitude representing the intensity or energy of the signal at each frequency, the phase spectrum refers to the phase spectrum representing the phase offset of the signal at each frequency, the frequency component refers to the different frequency components of the signal in the frequency domain, and the distribution refers to the layout of the frequency components of the signal in the frequency domain.

[0104] Optionally, the frequency domain conversion of the interference signal can be obtained through FFT, and the extraction of the amplitude spectrum and phase spectrum of the interference signal in the interference signal spectrum can be achieved using the frequency domain conversion results of FFT. Based on the amplitude spectrum and the phase spectrum, the frequency component and distribution analysis of the interference signal can be obtained by implementing a spectrum analyzer.

[0105] Furthermore, the embodiments of the present invention can identify the interference type of the interference signal based on the spectral characteristics, and can design a suitable filter according to the frequency range of the interference to suppress the interference and ensure the accuracy of data transmission. The interference type refers to the interference classification based on the source and characteristics of the interference signal and its impact on the communication system.

[0106] Optionally, the interference type identification of the interference signal based on the spectrum characteristics can be obtained by a GPS interference detector.

[0107] The embodiment of the present invention can help us more accurately identify and confirm the interference signal by performing interference detection on the interference signal according to the interference source location and the interference type, so as to design a more powerful anti-interference system. The signal interference detection result refers to the data and analysis results obtained during the signal interference detection process.

[0108] As an embodiment of the present invention, interference detection is performed on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result, including: collecting signal data of the interference signal according to the interference source position and the interference type; calculating the covariance matrix of the signal data; performing eigendecomposition on the covariance matrix to obtain decomposition eigenvalues; setting a normal signal threshold of the decomposition eigenvalues; and performing interference detection on the interference signal according to the normal signal threshold to obtain a signal interference detection result.

[0109] Among them, the signal data refers to signal sample data containing noise and interference, the covariance matrix refers to a matrix that describes the correlation between elements in the signal data, the decomposed eigenvalues ​​refer to the eigenvalues ​​decomposed from the signal covariance matrix, and the normal signal threshold refers to a numerical value used to distinguish normal signals from abnormal signals in signal processing.

[0110] In an optional embodiment of the present invention, the covariance matrix of the signal data is calculated using the following formula:

[0111] ;

[0112] Where R represents the covariance matrix of the signal data, N represents the number of samples of the signal data, and e represents the sample index of the signal data. represents the sample vector of the e-th signal data, represents the conjugate transpose of the e-th signal data sample vector, and H represents the sign of the conjugate transpose of the e-th signal data sample vector.

[0113] Optionally, the normal signal threshold setting of the decomposed eigenvalue may be obtained based on the statistical characteristics of the eigenvalue distribution.

[0114] S4. According to the signal interference detection result, analyze the communication signal change trend of the UAV, monitor the beam pointing of the UAV in real time, and build an interference suppression mechanism corresponding to the interference signal based on the beam pointing and the interference type.

[0115] The embodiment of the present invention analyzes the communication signal change trend of the drone according to the signal interference detection result, and can identify the degree of interference to the communication signal at the drone's location, thereby adopting different anti-interference strategies to reduce the interference impact from a specific direction. The communication signal change trend refers to the change in the quality, strength or availability of the communication signal of the drone over time and space during the drone's mission execution.

[0116] As an embodiment of the present invention, analyzing the change trend of the communication signal of the UAV according to the signal interference detection result includes: obtaining the position change interval of the UAV; analyzing the signal time change pattern of the UAV within the position change interval according to the signal interference detection result; extracting the signal-to-noise ratio change data of the communication signal in the signal time change pattern; analyzing the change trend of the communication signal of the UAV according to the signal time change pattern and the signal-to-noise ratio change data.

[0117] Among them, the position change interval refers to the flight range interval of the UAV under interference during flight, the signal time change mode refers to the change of the communication signal strength of the UAV over time within a specific position change interval, the communication signal refers to the electromagnetic wave or sound wave used by the UAV to transmit information in the communication system, and the signal-to-noise ratio change data refers to the data on the change of the signal-to-noise ratio of the communication signal over time in the signal time series.

[0118] Optionally, the position change interval of the UAV can be obtained through a positioning system, such as GPS, the signal time change pattern analysis of the UAV can be achieved by utilizing the signal quality monitoring function built into the UAV system, and the signal-to-noise ratio change data extraction of the communication signal in the signal time change pattern can be obtained through the logarithmic ratio of signal power to noise power.

[0119] Furthermore, the embodiment of the present invention can dynamically adjust the beam direction according to the location of the interference source by real-time monitoring of the beam pointing of the UAV, so as to avoid the interference source or find the direction with the strongest signal to restore the communication connection and ensure flight safety. The beam pointing refers to the angular pointing of the radar antenna beam relative to a reference coordinate system.

[0120] As an embodiment of the present invention, the real-time monitoring of the beam pointing of the UAV includes: setting the beam pointing control mode of the UAV; calculating the beam pointing angle currently required by the UAV; adjusting the array antenna phase of the phased array radar based on the beam pointing angle and the beam pointing control mode; and monitoring the beam pointing of the UAV in real time according to the beam pointing angle and the array antenna phase.

[0121] Among them, the beam pointing control method refers to a method for controlling the direction of the radar beam, which can be achieved through radar beam pointing control. The position data refers to the longitude and latitude coordinates, altitude, speed and other position data of the UAV during flight. The beam pointing angle refers to the direction angle that the radar beam needs to point to. The array antenna phase refers to the position of the electromagnetic waves emitted or received by each antenna unit in the array antenna.

[0122] In an optional embodiment of the present invention, the following formula is used to calculate the beam pointing angle currently required by the UAV:

[0123] ;

[0124] in, It represents the beam pointing angle currently required by the UAV, L represents the radar wavelength corresponding to the UAV, d represents the spacing of the radar antenna array elements corresponding to the UAV, and M represents the offset of the beam pointing angle corresponding to the UAV.

[0125] The embodiment of the present invention constructs an interference suppression mechanism corresponding to the interference signal based on the beam pointing and the interference type, which can realize dynamic adjustment of the beam to avoid the interference source and improve the stability and reliability of the UAV communication system. The interference suppression mechanism refers to an anti-interference mechanism designed to reduce or eliminate various interference factors encountered during the communication process.

[0126] As an embodiment of the present invention, the interference suppression mechanism corresponding to the interference signal is constructed based on the beam pointing and the interference type, including: setting the beam synthesis channel of the beam pointing; extracting the auxiliary channel data of the beam synthesis channel, and performing adaptive sidelobe cancellation on the auxiliary channel data to obtain an adaptive sidelobe cancellation result; constructing a mainlobe beam blocking matrix of the beam synthesis channel; and constructing the interference suppression mechanism corresponding to the interference signal according to the adaptive sidelobe cancellation result and the mainlobe beam blocking matrix.

[0127] Among them, the beam synthesis channel refers to an independent path for controlling the transmission or reception of signals by each antenna unit in the antenna array, the auxiliary channel data refers to the data generated by an additional channel used to assist the main beam synthesis channel in the phased array radar or communication system, the adaptive sidelobe cancellation result is the result obtained after adaptive sidelobe cancellation processing is performed using the auxiliary channel in the phased array radar system, and the main beam blocking matrix refers to a mathematical matrix that uses matrix operations to eliminate or reduce interference in the main lobe direction.

[0128] Optionally, the beam synthesis channel setting of the beam pointing can be obtained through the main channel and auxiliary channel of the berberis, the adaptive sidelobe cancellation of the auxiliary channel data can be achieved using the weighting coefficient of the auxiliary channel receiving signal, and the main lobe beam blocking matrix construction of the beam synthesis channel can be obtained through the incident angle of the interference signal.

[0129] S5. Based on the interference suppression mechanism, anti-interference processing is performed on the UAV communication to obtain the anti-interference processing result of the UAV communication.

[0130] The embodiment of the present invention performs anti-interference processing on UAV communications based on the interference suppression mechanism, thereby expanding the effective communication range of the UAV and extending the communication distance, thereby ensuring that the communication system can maintain normal communication capabilities in the presence of interference. The UAV communication anti-interference result refers to the effect achieved after implementing a series of anti-interference technologies during the UAV communication process.

[0131] The present invention can concentrate the energy of the phased-control radar to detect a specific direction, reduce interference signals from other directions, and improve the anti-interference performance of the drone by using a pre-set phased-control radar according to the position coordinates of the drone, and dynamically adjust the beam pointing according to the real-time position and speed information of the drone to ensure the stability of the drone communication link; secondly, the embodiment of the present invention can identify the interference signal of the drone communication by collecting the echo signal under the moving trajectory of the drone, so as to adopt a targeted anti-interference strategy to ensure the command link of the drone communication, and improve the signal-to-noise ratio of the signal by processing the information of the echo signal, so that the target signal has a relatively large transmission power, and at the same time, the radar resolution can be improved without losing the target detection information, and the influence of clutter can be effectively reduced or removed, and the detection efficiency of the target signal can be improved; further, the embodiment of the present invention can help identify the frequency distribution of the interference signal by performing spectrum analysis on the target echo signal to obtain the signal spectrum, so as to judge the position and type of the interference source, and identify the main components of the interference signal according to the position and type of the interference source, and design a suitable filter according to the main components of the interference to suppress the interference and ensure the accuracy of data transmission. Therefore, the anti-interference method for UAV communication based on phased radar provided in an embodiment of the present invention can improve the anti-interference efficiency of UAV communication.

[0132] like Figure 2 As shown, it is a functional module diagram of a UAV communication anti-interference method system based on phased-control radar provided by one embodiment of the present invention.

[0133] The anti-interference method system 200 for UAV communication based on phased-control radar described in the present invention can be installed in an electronic device. According to the functions implemented, the anti-interference method system 200 for UAV communication based on phased-control radar can include a beam tracking module 201, an echo processing module 202, a signal analysis module 203, an anti-interference configuration module 204, and an anti-interference processing module 205. The module described in the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0134] In this embodiment, the functions of each module / unit are as follows:

[0135] The beam tracking module 201 is used to obtain the position coordinates of the UAV, identify the target beam angle pointing to the UAV by using a preset phased-control radar according to the position coordinates, and track the movement trajectory of the UAV under the target beam angle in real time;

[0136] The echo processing module 202 is used to collect the echo signal under the moving track of the UAV, filter and amplify the echo signal to obtain the target signal, perform pulse compression processing on the target signal to obtain a compressed pulse signal, and perform subtraction and cancellation processing on the compressed pulse signal to obtain the target echo signal;

[0137] The signal analysis module 203 is used to perform spectrum analysis on the target echo signal to obtain a signal spectrum, identify interference signals in the signal spectrum that do not match the expected signal frequency, locate the interference signal to obtain the interference source position, analyze the spectrum characteristics of the interference signal, identify the interference type of the interference signal based on the spectrum characteristics, perform interference detection on the interference signal according to the interference source position and the interference type, and obtain a signal interference detection result;

[0138] The anti-interference configuration module 204 is used to analyze the change trend of the communication signal of the UAV according to the signal interference detection result, and monitor the beam pointing of the UAV in real time, and build an interference suppression mechanism corresponding to the interference signal based on the beam pointing and the interference type;

[0139] The anti-interference processing module 205 is used to perform anti-interference processing on the UAV communication based on the interference suppression mechanism to obtain the anti-interference processing result of the UAV communication.

[0140] In detail, each module described in the anti-interference method system 200 for UAV communication based on phased-control radar described in the embodiment of the present application is used in the same manner as described above. Figure 1 The technical means described in the article are the same as the anti-interference method of UAV communication based on phased array radar, and can produce the same technical effects, so I will not go into details here.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A UAV communication anti-interference method based on phased-control radar, characterized in that: The method comprises: Obtaining the position coordinates of the drone, identifying the target beam angle pointing to the drone using a preset phased-control radar according to the position coordinates, and tracking the movement trajectory of the drone under the target beam angle in real time; Collecting the echo signal under the moving track of the UAV, filtering and amplifying the echo signal to obtain a target signal, performing pulse compression processing on the target signal to obtain a compressed pulse signal, and performing subtraction and cancellation processing on the compressed pulse signal to obtain a target echo signal; Performing spectrum analysis on the target echo signal to obtain a signal spectrum, identifying interference signals in the signal spectrum that do not match the expected signal frequency, locating the interference signal to obtain the interference source position, analyzing the spectrum characteristics of the interference signal, identifying the interference type of the interference signal based on the spectrum characteristics, and performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result, wherein the signal interference detection result refers to the data and analysis results obtained in the signal interference detection process, and performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result, including: collecting signal data of the interference signal according to the interference source position and the interference type; calculating the covariance matrix of the signal data; performing eigendecomposition on the covariance matrix to obtain a decomposition eigenvalue; setting a normal signal threshold of the decomposition eigenvalue; performing interference detection on the interference signal according to the normal signal threshold to obtain a signal interference detection result; According to the signal interference detection result, the communication signal change trend of the UAV is analyzed, and the beam pointing of the UAV is monitored in real time, and based on the beam pointing and the interference type, an interference suppression mechanism corresponding to the interference signal is constructed; Based on the interference suppression mechanism, anti-interference processing is performed on the UAV communication to obtain the anti-interference processing result of the UAV communication.

2. The method according to claim 1, characterized in that The method of identifying a target beam angle directed to the UAV by using a preset phased-control radar according to the position coordinates includes: Performing coordinate conversion on the position coordinates to obtain target coordinates; Calculating the azimuth and elevation of the UAV relative to the phased-control radar according to the position coordinates and the target coordinates; Setting the beam pointing mode of the phased control radar corresponding to the UAV; Based on the azimuth angle, the elevation angle and the beam pointing mode, a target beam angle pointing to the UAV is identified.

3. The method according to claim 1, characterized in that The step of performing pulse compression processing on the target signal to obtain a compressed pulse signal includes: configuring a matched filter for the target signal; Extracting a complex conjugate factor of the target signal, and performing time reversal processing on the complex conjugate factor to obtain a complex conjugate signal; Identifying the complex conjugate signal and the corresponding frequency domain representation in the matched filter; In the frequency domain representation, the target signal and the transfer function of the matched filter are multiplied to obtain a frequency domain product result; According to the frequency domain multiplication result, the target signal is pulse compressed to obtain a compressed pulse signal.

4. The method according to claim 1, characterized in that The performing subtraction cancellation processing on the compressed pulse signal to obtain the target echo signal includes: Extracting signal samples that need to be subjected to subtraction alignment processing from the compressed pulse signal; Performing synchronization processing on the time and phase of the signal sample to obtain a synchronization time and a synchronization phase; Based on the synchronization time and the synchronization phase, performing signal alignment processing on the signal samples to obtain an alignment signal; Unnecessary signals in the alignment signal are identified, and subtraction and cancellation processing is performed on the unnecessary signals to obtain target echo signals.

5. The method according to claim 1, characterized in that The step of locating the interference signal to obtain the interference source position includes: Collecting multi-directional echo signals of the UAV corresponding to the interference signal; Performing signal separation processing on the multi-azimuth echo signals to obtain separated signals; The phase difference between the separated signals is calculated, and based on the phase difference, the arrival angle of the multi-azimuth echo signal is calculated using the following formula: ； in, represents the arrival angle of the multi-directional echo signal, n represents the number of antennas in the antenna array corresponding to the multi-directional echo signal, It represents the signal received by the ith antenna in the antenna array at time t, and 2π represents the signal phase increment converted from the angular frequency. represents the distance from the ith antenna to the array reference point, represents the sine value of the arrival angle of the multi-directional echo signal, j represents the imaginary unit of the multi-directional echo signal, w represents the angular frequency of the multi-directional echo signal, Indicates the wavelength of multi-directional echo signals; Based on the arrival angle, a location of an interference source of the interference signal is determined.

6. The method according to claim 1, characterized in that The analyzing the frequency spectrum characteristics of the interference signal includes: Performing frequency domain conversion on the interference signal to obtain an interference signal spectrum; Extracting the amplitude spectrum and phase spectrum of the interference signal from the interference signal spectrum; Analyzing the frequency components and distribution of the interference signal according to the amplitude spectrum and the phase spectrum; Based on the frequency components and the distribution, the frequency spectrum characteristics of the interference signal are analyzed.

7. The method according to claim 1, characterized in that The performing interference detection on the interference signal according to the interference source position and the interference type to obtain a signal interference detection result includes: According to the interference source position and the interference type, collecting signal data of the interference signal; The covariance matrix of the signal data is calculated using the following formula: ； Where R represents the covariance matrix of the signal data, N represents the number of samples of the signal data, and e represents the sample index of the signal data. represents the sample vector of the e-th signal data, represents the conjugate transpose of the e-th signal data sample vector, and H represents the sign of the conjugate transpose of the e-th signal data sample vector; Performing eigendecomposition on the covariance matrix to obtain decomposition eigenvalues; Setting a normal signal threshold of the decomposed eigenvalue; According to the normal signal threshold, interference detection is performed on the interference signal to obtain a signal interference detection result.

8. The method according to claim 1, characterized in that Analyzing the change trend of the communication signal of the UAV according to the signal interference detection result includes: Obtaining a position change interval of the UAV; Analyzing the signal time variation pattern of the UAV within the position variation interval according to the signal interference detection result; Extracting signal-to-noise ratio variation data of the communication signal in the signal time variation mode; The communication signal change trend of the UAV is analyzed according to the signal time change pattern and the signal-to-noise ratio change data.

9. The method according to claim 1, characterized in that The real-time monitoring of the beam pointing of the UAV includes: Setting the beam pointing control mode of the UAV; Calculating the beam pointing angle currently required by the UAV; Adjusting the phase of the array antenna corresponding to the UAV based on the beam pointing angle and the beam pointing control method; The beam pointing of the UAV is monitored in real time according to the beam pointing angle and the array antenna phase.

10. The method according to claim 9, characterized in that The calculating the beam pointing angle currently required by the UAV includes: The following formula is used to calculate the beam pointing angle currently required by the UAV: ； in, It represents the beam pointing angle currently required by the UAV, L represents the radar wavelength corresponding to the UAV, d represents the spacing of the radar antenna array elements corresponding to the UAV, and M represents the offset of the beam pointing angle corresponding to the UAV.

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