Unmanned aerial vehicle dual-polarized antenna elastic switching method and system based on interference source space positioning

Abstract

The invention discloses an unmanned aerial vehicle dual-polarized antenna elastic switching method and system based on interference source space positioning, and belongs to the field of wireless communication. The method comprises the following steps: calculating an interference signal received by an unmanned aerial vehicle-mounted dual-polarized antenna array and position information of an unmanned aerial vehicle based on an interference source space positioning algorithm to obtain a space position of an interference source; determining an optimal polarization mode control instruction by adopting an optimal polarization mode decision algorithm based on the spatial position of the interference source; and based on the optimal polarization mode control instruction, an elastic polarization switching algorithm is adopted to control the dual-polarized antenna of the unmanned aerial vehicle to be switched to the optimal polarization mode. The method has the advantages of being high in intelligent degree, high in adaptability, good in flexibility, low in implementation complexity and the like, and the robustness and reliability of an unmanned aerial vehicle communication system can be effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a method and system for elastically switching dual-polarized antennas of an unmanned aerial vehicle based on spatial positioning of interference sources. Background Art

[0002] In recent years, low-altitude UAV technology has developed rapidly and is widely used in various fields, such as communication relay, material distribution, environmental monitoring, public safety and military reconnaissance. However, UAVs are facing increasingly complex electromagnetic environments in practical applications. In particular, various human malicious interference and natural environment interference have seriously affected the reliability and stability of UAV communication links. These interferences not only reduce the communication quality, but in severe cases, they may even cause the UAV to lose control, resulting in mission failure and economic losses. Therefore, how to improve the anti-interference ability of UAV communication systems in complex electromagnetic environments has become a key issue that needs to be solved in the development of UAV technology.

[0003] At present, the anti-interference technology for UAV communication systems is mainly concentrated in the frequency domain, time domain and space domain, while the use of polarization domain is not deep enough and intelligent enough. The existing polarization anti-interference methods mainly have the problems of fixed polarization mode, manual switching polarization mode, lack of spatial positioning information of interference source, single and rigid polarization switching mode.

[0004] The current prior art discloses the following technical contents: a polarization switching method based on signal strength detection, an anti-interference method based on polarization diversity reception, a beamforming anti-interference method based on smart antennas, and an adaptive polarization adjustment method based on interference source direction finding. The above-mentioned prior art solutions have certain limitations in terms of anti-interference performance, intelligence, flexibility, and complexity, and specifically have the following technical defects:

[0005] (1) Limited anti-interference effect and low efficiency: Existing technical solutions, such as fixed polarization, signal strength switching, polarization diversity reception, etc., cannot make adaptive adjustments based on the dynamic changes of interference sources in complex electromagnetic environments. They have limited suppression effects on interference signals, low anti-interference efficiency, and are easily affected by interference, resulting in reduced communication quality.

[0006] (2) Low intelligence and frequent manual intervention: Existing technical solutions, such as manual switching of polarization modes, require manual preset or simple rule control. They are not highly intelligent and have poor adaptability. They are unable to track and respond to rapidly changing interference environments in real time and require manual intervention. The operation is cumbersome and inefficient.

[0007] (3) Lack of accurate interference source location information and poor adaptability: Existing technical solutions, such as polarization adjustment based on signal strength or simple direction finding, lack precise positioning of the spatial location of the interference source, cannot make full use of the spatial location information of the interference source for precise polarization direction adjustment, have poor adaptability, and it is difficult to achieve the best interference suppression effect.

[0008] (4) Single and rigid polarization switching method with insufficient flexibility: Existing technical solutions, such as fixed polarization mode switching or hard switching, have a single and rigid polarization switching method, insufficient flexibility, cannot perform fine and continuous polarization adjustment according to the complexity of the interference environment, and it is difficult to give full play to the advantages of polarization resources in anti-interference.

[0009] (5) High system complexity and high cost: Existing technical solutions, such as the anti-interference method of intelligent antenna beamforming, have a high system implementation complexity, require complex antenna arrays and RF front-ends, and also have a high algorithm complexity, resulting in high costs and large power consumption, which are not suitable for small UAV platforms.

[0010] Therefore, based on the above existing technical problems, the present invention proposes a method for elastic switching of a dual-polarization antenna of a UAV based on the spatial location of an interference source. Summary of the Invention

[0011] To solve the above technical problems, the present invention proposes a method and system for elastic switching of a dual-polarization antenna of a UAV based on the spatial location of an interference source to solve the problems existing in the above prior art.

[0012] To achieve the above object, the present invention provides a method for elastic switching of a dual-polarization antenna of a UAV based on the spatial location of an interference source, including:

[0013] Calculating the spatial location of the interference source based on the interference source spatial location algorithm for the interference signals received by the dual-polarization antenna array on the UAV and the position information of the UAV;

[0014] Determining the optimal polarization mode control instruction based on the spatial location of the interference source by using the optimal polarization mode decision algorithm;

[0015] Controlling the UAV dual-polarization antenna to switch to the optimal polarization mode based on the optimal polarization mode control instruction by using the elastic polarization switching algorithm.

[0016] Optionally, the process of calculating the spatial location of the interference source based on the interference source spatial location algorithm includes:

[0017] The dual-polarization antenna array receives interference signals;

[0018] Processing the interference signals to obtain analog signals;

[0019] Sample and perform analog-to-digital conversion on the analog signal to obtain a digital signal;

[0020] Use an angle-of-arrival estimation algorithm to estimate the digital signal and obtain the angle of arrival of the interference signal;

[0021] Calculate the spatial position of the interference source based on the position information of the UAV and the angle of arrival of the interference signal.

[0022] Optionally, the calculation expression for the spatial position of the interference source is:

[0023] x i = x u + d cos(φ)sin(θ), y i = y u + d cos(φ)cos(θ), z i = z u + d sin(φ)

[0024] In the formula, (x u , y u , z u ) represents the position coordinates of the UAV, (x i , y i , z i ) represents the spatial position of the interference source, θ represents the azimuth angle of the interference signal, the azimuth angle of the interference signal is the due north direction, φ represents the elevation angle of the interference signal, and d represents the distance from the interference source to the UAV.

[0025] Optionally, use an optimal polarization mode decision algorithm to determine the optimal working mode of the UAV's dual-polarization antenna. The process includes:

[0026] Estimate the polarization characteristics of the wireless channel between the UAV and the interference source based on the spatial position of the interference source and the position information of the UAV;

[0027] Calculate the interference suppression ratio under different polarization modes based on the polarization characteristics of the wireless channel between the UAV and the interference source;

[0028] Select the polarization mode with the highest interference suppression ratio and output the optimal polarization mode control instruction.

[0029] Optionally, use an elastic polarization switching algorithm to control the UAV's dual-polarization antenna to switch to the optimal polarization mode. The process includes:

[0030] Based on the optimal polarization mode control instruction, query the pre-set polarization mode parameter table to obtain the polarization controller parameters corresponding to the optimal polarization mode;

[0031] Generate a polarization controller control signal based on the queried polarization controller parameters;

[0032] Based on the control signal of the polarization controller, the dual-polarized antenna is switched to the optimal polarization mode.

[0033] The present invention also provides a dual-polarized antenna elastic switching system for unmanned aerial vehicles based on the spatial positioning of interference sources, and the system includes:

[0034] A ground station for wireless communication with a communication module on an unmanned aerial vehicle platform to achieve data transmission and command interaction;

[0035] An unmanned aerial vehicle platform for providing a flight platform and energy supply.

[0036] Optionally, the unmanned aerial vehicle platform includes: a dual-polarized antenna, a radio frequency front end, a positioning module, a signal processing module, a polarization switching control module, and a communication module;

[0037] Wherein, the dual-polarized antenna is used to receive a desired signal from the ground and an interference signal from an interference source;

[0038] The radio frequency front end is used to process the interference signal to obtain an analog signal and send the analog signal to the signal processing module;

[0039] The positioning module is used to determine the position information of the unmanned aerial vehicle;

[0040] The signal processing module is used to receive the analog signal output by the radio frequency front end and the position information of the unmanned aerial vehicle output by the positioning module and issue a polarization mode control instruction;

[0041] The polarization switching control module is used to control the dual-polarized antenna of the signal to switch to the optimal polarization mode based on the polarization mode control instruction;

[0042] The communication module is used to achieve wireless communication between the unmanned aerial vehicle and the ground station.

[0043] Compared with the prior art, the present invention has the following advantages and technical effects:

[0044] 1. The anti-interference effect is significantly improved and the efficiency is higher: By real-time positioning the spatial position of the interference source and dynamically adjusting the antenna polarization mode accordingly, the present invention can achieve precise suppression of interference signals. The anti-interference effect is far better than traditional fixed polarization and simple polarization switching methods, and the communication quality and reliability are significantly improved, and the anti-interference efficiency is higher. Experimental results show that in a strong interference environment, the bit error rate of the present invention is reduced by more than one order of magnitude compared with traditional methods.

[0045] 2. High degree of intelligence, automatic anti-interference, and reduced manual intervention: The method of the present invention can automatically complete operations such as interference source localization, polarization mode decision-making, and polarization switching, without manual presetting and manual switching, achieving intelligent and automatic anti-interference, greatly reducing the need for manual intervention, and improving the system operation efficiency and reliability.

[0046] 3. Strong self-adaptability, good robustness, and stronger environmental adaptability: The method of the present invention can track and respond to the dynamic changes in the spatial position of the interference source in real time, and flexibly adjust the polarization mode according to the complexity of the interference environment, with strong self-adaptability and robustness, being able to better adapt to complex and dynamically changing electromagnetic environments, having stronger environmental adaptability and a wider application range. Experimental results show that under the condition of dynamic changes in the interference source position, the present invention can still maintain good anti-interference performance.

[0047] 4. More refined and flexible utilization of polarization resources, and richer anti-interference means: The method of the present invention can flexibly select the optimal polarization mode according to the interference situation, not only limited to the hard switching between horizontal / vertical polarizations, but also can select linear polarizations at any angle according to the interference source position, and even support more complex polarization modes such as circular polarization / elliptical polarization, realizing the refined and flexible utilization of polarization resources, providing richer anti-interference means, and being able to give full play to the potential of polarization resources in anti-interference.

[0048] 5. Relatively low system complexity and cost, more suitable for small UAV platforms: While ensuring high-performance anti-interference, the method of the present invention strives to reduce the complexity of system implementation, adopts a relatively simple hardware structure and efficient algorithms (for example, although the MUSIC / ESPRIT algorithms have a large amount of computation, they can be efficiently implemented on hardware platforms such as FPGA / DSP). Compared with complex technologies such as smart antenna beamforming, the system complexity and cost of the present invention's solution are relatively low, with lower power consumption, and are more suitable for miniaturized and lightweight UAV-mounted platforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings constituting a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0050] Figure 1 is the structural block diagram of the UAV communication system according to the embodiment of the present invention;

[0051] Figure 2 is the comparison of throughput performance of different polarization switching methods according to the embodiment of the present invention;

[0052] Figure 3 is the influence of interference source localization error on the throughput performance of flexible polarization switching according to the embodiment of the present invention;

[0053] Figure 4 For comparing the time-varying performance of the spectral efficiency of different polarization methods in the dynamic interference scenario of the embodiment of the present invention;

[0054] Figure 5 For comparing the throughput performance of different polarization switching methods in the embodiment of the present invention;

[0055] Figure 6 For the influence of the interference source positioning error on the throughput performance of elastic polarization switching in the embodiment of the present invention;

[0056] Figure 7 For comparing the time-varying performance of the spectral efficiency in the dynamic interference scenario of the embodiment of the present invention;

[0057] Figure 8 For the schematic diagram of the polarization switching smooth transition curve in the embodiment of the present invention. Specific embodiments

[0058] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0059] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0060] Embodiment 1

[0061] The main objectives to be achieved by the present invention include: (1) improving the anti-interference effect and efficiency: by accurately and real-time locating the spatial position of the interference source, and dynamically and adaptively adjusting the polarization direction of the dual-polarization antenna of the unmanned aerial vehicle (UAV) according to the position information of the interference source, precise suppression of the interference signal is achieved, significantly improving the anti-interference effect and efficiency. (2) Realizing intelligent and automatic anti-interference: The present invention can automatically complete operations such as interference source location, polarization mode decision-making, and polarization switching without manual intervention, realizing intelligent and automatic anti-interference, and improving the system efficiency and reliability. (3) Enhancing adaptability and robustness: The present invention can track and respond to changes in the spatial position of the interference source in real time, and flexibly adjust the polarization mode according to the complexity of the interference environment, having good adaptability and robustness, and being able to adapt to complex and dynamically changing electromagnetic environments. (4) Reducing system complexity and cost: While ensuring high-performance anti-interference, the present invention strives to reduce the complexity of system implementation, adopts a relatively simple hardware structure and efficient algorithms, reduces system cost and power consumption, and makes it more suitable for small UAV platforms. (5) Realizing refined and flexible utilization of polarization resources: The present invention is not limited to the hard switching between horizontal polarization and vertical polarization, but can flexibly select the optimal polarization mode according to the interference situation, such as horizontal polarization, vertical polarization, or the optimal polarization angle calculated based on the spatial position of the interference source, and can even support more complex polarization modes such as elliptical polarization, realizing refined and flexible utilization of polarization resources and giving full play to the potential of polarization resources in anti-interference.

[0062] In this embodiment, a method for elastic switching of the dual-polarization antenna of a UAV based on the spatial location of the interference source is provided. First, the positioning module and antenna array on the UAV platform are used, combined with signal processing algorithms, to accurately and real-time locate the spatial position of the interference source; then, according to the spatial position information of the interference source, the optimal working mode of the dual-polarization antenna of the UAV (such as horizontal polarization, vertical polarization, or linear polarization, circular polarization, etc. with a specific polarization angle) is intelligently determined; finally, by controlling the polarization switching module of the dual-polarization antenna, it is flexibly switched to the optimal polarization mode to achieve maximum suppression of the interference signal and improve the anti-interference performance of the UAV communication link. The present invention is particularly suitable for application scenarios with complex electromagnetic environments and high requirements for communication reliability. The present invention has the advantages of high intelligence, strong adaptability, good flexibility, and low complexity, and can effectively enhance the robustness and reliability of the UAV communication system.

[0063] The present invention is applicable to low-altitude UAV communication systems that need to operate in complex electromagnetic environments, especially applicable to the following scenarios: (1) Scenarios with artificial malicious interference: such as electronic countermeasures, malicious signal blocking, etc. (2) Scenarios with complex electromagnetic environments: such as urban environments, industrial parks, battlefield environments, etc., where there are multipath interference, co-frequency interference, etc. (3) Scenarios with high requirements for communication reliability and security: such as military communication, emergency rescue communication, important data transmission, etc. (3) Scenarios that require miniaturized and lightweight UAV platforms: The solution of the present invention aims for low complexity and low cost and is applicable to small UAV platforms.

[0064] In this embodiment, a method for elastic switching of a dual-polarized antenna of a UAV based on spatial positioning of interference sources is provided. The method for elastic switching of the dual-polarized antenna of the UAV is implemented based on a UAV communication system, which mainly includes two parts: a UAV platform and a ground station (or other UAVs).

[0065] The ground station / other UAVs perform wireless communication with the communication module on the UAV platform to achieve data transmission and command interaction.

[0066] The UAV platform mainly includes components such as a dual-polarized antenna, a radio frequency front end, a signal processing module, a polarization switching control module, a communication module, and a positioning module:

[0067] UAV platform: As the carrier of the method of the present invention, it provides a flight platform and energy supply. The UAV platform needs to have a certain load capacity and be able to carry the anti-interference communication system proposed by the present invention.

[0068] Dual-polarized antenna: A dual-polarized antenna capable of switching between two modes of horizontal polarization and vertical polarization is adopted, or further, an adjustable polarization antenna capable of elastically switching between multiple polarization modes is adopted. The dual-polarized antenna is the physical basis for realizing polarization diversity and polarization interference suppression. The dual-polarized antenna receives the desired signal from the ground station or other UAVs and the interference signal from the interference source. Dual-polarized antenna: Used to simultaneously receive and transmit different polarization modes (such as horizontal polarization, vertical polarization, or adjustable linear polarization / circular polarization, etc.), and the antenna unit adopts metamaterials or reconfigurable structures to support fast polarization switching.

[0069] RF front-end: It includes RF devices such as low-noise amplifiers (LNAs), filters, mixers, power amplifiers (PAs), etc., which are responsible for receiving and transmitting RF signals, and converting RF signals into intermediate-frequency or baseband signals, or vice versa. The RF front-end performs processing such as low-noise amplification, filtering, and mixing on the received RF signals, converts the RF signals into intermediate-frequency or baseband signals, and sends them to the signal processing module. The RF front-end consists of devices such as low-noise amplifiers (LNAs), filters, mixers, power amplifiers (PAs), etc., and is used to perform low-noise amplification, filtering, and down-conversion processing on the received signals, convert RF signals into baseband or intermediate-frequency analog signals, and up-convert the transmitted signals from baseband or intermediate-frequency to RF signals.

[0070] Positioning module: It adopts positioning modules such as global navigation satellite system (GNSS) positioning modules (such as GPS, Beidou, GLONASS, Galileo) or inertial navigation system (INS), etc., and is used to obtain the position and attitude information of the UAV itself. High-precision positioning information is the basis for realizing the spatial positioning of interference sources. The positioning module is responsible for obtaining the position and attitude information of the UAV itself in real time and providing a position reference for the interference source spatial positioning algorithm. The positioning module integrates GNSS (GPS / Beidou / GLONASS / Galileo) or inertial navigation system (INS) to achieve high-precision positioning of the UAV (the accuracy can reach sub-meter level or even centimeter level), and outputs attitude information (such as pitch, yaw, roll) in real time, providing reference coordinates for interference source positioning and antenna polarization decision-making.

[0071] Signal processing module: It is mainly implemented by hardware such as digital signal processors (DSPs) or field-programmable gate arrays (FPGAs), and is responsible for implementing core algorithms such as interference source spatial positioning algorithms, optimal polarization mode decision-making algorithms, and polarization switching control algorithms. The signal processing module is the core component of the present invention and realizes the processing and control of the received signals. The signal processing module is the core of the system. It receives the signals from the RF front-end and the UAV position and attitude information from the positioning module, estimates the spatial position of the interference source using the interference source spatial positioning algorithm, and then, according to the position information of the interference source, decides the optimal polarization mode through the optimal polarization mode decision-making algorithm, and sends the polarization mode control instruction to the polarization switching control module. At the same time, the signal processing module is also responsible for communication functions such as baseband signal processing, modulation and demodulation, channel encoding and decoding, and realizes data interaction with the ground station or other UAVs through the communication module. The signal processing module consists of hardware resources such as high-speed ADC / DAC, DSP / FPGA, etc., and executes the interference source spatial positioning algorithm (joint measurement of AOA / TDOA / RSSI), the optimal polarization mode decision-making algorithm, and baseband signal processing (modulation and demodulation, channel encoding / decoding, etc.). This module is the core operation unit of the present invention and needs to ensure real-time performance (the processing delay is usually less than 5 ms).

[0072] Polarization switching control module: used to control the polarization mode switching of the dual-polarized antenna. According to the decision result of the signal processing module, it controls the polarization controller of the dual-polarized antenna to achieve flexible switching of horizontal polarization, vertical polarization or other polarization modes. The polarization switching control module receives the polarization mode control instruction from the signal processing module, controls the polarization controller of the dual-polarized antenna, and realizes the flexible switching of the polarization mode. The polarization switching control module receives the polarization mode control instruction output by the signal processing module, queries the preset polarization mode parameter table, and generates a polarization control signal (such as voltage, current or digital quantity) to drive the dual-polarized antenna to smoothly switch between different polarization modes. The module has the characteristic of fast response (the switching time can be controlled within 5μs - 10μs).

[0073] Communication module: realizes the wireless communication function between the UAV and the ground station or other UAVs. The communication module needs to support the corresponding communication protocols and modulation and demodulation methods. The communication module realizes two-way communication with the ground station or other UAV nodes, supports multiple communication protocols (such as Wi-Fi, 4G / 5G, dedicated narrowband / broadband protocols, etc.), and can complete data encrypted transmission in combination with a security encryption chip.

[0074] This embodiment also provides an edge computing platform. If more data needs to be processed (such as image recognition, federated learning collaborative decision-making, etc.), an AI accelerator (NPU / GPU) can be deployed on the UAV platform to further improve the algorithm efficiency.

[0075] Through the above module refinement, the present invention can have high implementability and scalability at the hardware and software levels, and can achieve high-efficiency anti-interference in a complex electromagnetic environment.

[0076] This embodiment provides a method for flexible switching of a dual-polarized antenna of a UAV based on the spatial positioning of interference sources, including the following steps: calculating the spatial position of the interference source based on the interference source spatial positioning algorithm for the interference signals received by the UAV-borne dual-polarized antenna array and the position information of the UAV; determining the optimal polarization mode control instruction based on the spatial position of the interference source using the optimal polarization mode decision algorithm; and controlling the UAV dual-polarized antenna to switch to the optimal polarization mode based on the optimal polarization mode control instruction using the flexible polarization switching algorithm.

[0077] The present invention adopts an interference source spatial positioning algorithm based on the Angle of Arrival (AOA). This algorithm uses the interference signals received by the UAV-borne dual-polarized antenna array to estimate the arrival angle of the interference signals, and then combines the position information of the UAV itself to calculate the spatial position of the interference source.

[0078] The specific steps of the interference source spatial positioning algorithm include:

[0079] (1) The dual-polarized antenna array receives interference signals: The airborne dual-polarized antenna array receives electromagnetic signals from all directions in space, including interference signals and noise signals.

[0080] (2) RF front-end signal processing: The RF front-end processes the received interference signals through low-noise amplification, filtering, mixing, etc., and converts them into analog signals, which include intermediate-frequency or baseband signals.

[0081] (3) Signal sampling and digitization: The analog signals output by the RF front-end are sampled and converted by analog-to-digital conversion to obtain digital signals.

[0082] (4) The AOA estimation module estimates the angle of arrival: High-resolution angle-of-arrival estimation algorithms, such as the MUSIC (Multiple Signal Classification) algorithm or the ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm, are used to estimate the angle of arrival of the interference signals, including the azimuth angle and the elevation angle.

[0083] Brief description of the mathematical principle of the MUSIC algorithm:

[0084] The MUSIC algorithm uses the orthogonality between the signal subspace and the noise subspace to estimate the DOA of the signal. The specific steps are as follows:

[0085] Construct the received signal covariance matrix:

[0086] R = E[x(t)x H (t)]

[0087] where x(t) is the signal vector received by the antenna array, the superscript H represents the conjugate transpose, and E[·] represents the mathematical expectation.

[0088] Eigenvalue decomposition: Perform eigenvalue decomposition on R x :

[0089] R x = U∑U H

[0090] Divide the eigenvector matrix U into the signal subspace U S and the noise subspace U n .

[0091] Construct the spatial spectrum function:

[0092]

[0093] Among them, a(θ, φ) is the array steering vector, representing the array response of the signal in the direction (θ, φ). θ and φ represent the azimuth angle and the elevation angle respectively.

[0094] Spectrum peak search: By searching for (θ, φ) to make P MUSIC reach the maximum value, the corresponding (θ, φ) of the maximum value is the estimated arrival angle of the interference signal.

[0095] As a specific implementation manner of this embodiment, in the airborne signal processing module of the unmanned aerial vehicle, first perform radio frequency front-end preprocessing and analog-to-digital conversion on the received interference signal; use the above MUSIC algorithm to estimate the arrival angle of the interference source; combine the coordinates (x u , y u , z u ) of the unmanned aerial vehicle provided by the positioning module, and further calculate the spatial position (x i , y i , z i ) of the interference source.

[0096] In this way, real-time spatial positioning of the interference source can be achieved, and accurate spatial information support can be provided for subsequent optimal polarization mode decision-making and flexible switching, thereby effectively improving the anti-interference ability of the unmanned aerial vehicle communication system.

[0097] (5) The positioning module obtains the position of the unmanned aerial vehicle: Through the GNSS or INS positioning module, the position coordinates (x u , y u , z u ) of the unmanned aerial vehicle are obtained in real time.

[0098] (6) Calculation of the spatial position of the interference source: According to the estimated arrival angle (θ, φ) (azimuth angle and elevation angle) of the interference signal and the position coordinates (x u , y u , z u ) of the unmanned aerial vehicle, calculate the spatial position (x i , y i , z i ) of the interference source. The calculation formula is as follows (assuming a coordinate system is established with the unmanned aerial vehicle as the origin, the due north direction as the Y-axis, the due east direction as the X-axis, and the zenith direction as the Z-axis):

[0099] x i = x u + d cos(φ)sin(θ), y i = y u + d cos(φ)cos(θ), z i = zu + d sin(φ)

[0100] Among them, P u = (x u , y u, z u ) is the position coordinate of the UAV, unit: meter (m); P i = (x i , y i , z i ) is the spatial coordinate of the interference source, unit: meter (m); d is the distance from the interference source to the UAV. If there is no ranging information, it can be assumed that d is large enough or estimated by multi-UAV cooperation; θ is the azimuth angle of the interference signal, the angle relative to a certain reference direction (such as due north) in the UAV coordinate system, unit: degree or radian; φ is the elevation angle of the interference signal, the angle relative to the horizontal plane, unit: degree or radian; Coordinate system convention: the x-axis points to the due east direction, the y-axis points to the due north direction, and the z-axis is perpendicular upward (zenith).

[0101] If only the azimuth angles (θ, φ) of the interference source are concerned and accurate ranging is not required, d can be regarded as a constant or relative coordinates can be used for polarization decision-making. In this embodiment, more accurate d values can also be obtained through multi-UAV cooperative positioning or other sensors (radar, camera, etc.) to improve the positioning accuracy of the interference source.

[0102] d is the distance from the interference source to the UAV. If the distance is unknown, it can be assumed that the interference source is located far away, and d takes a sufficiently large value, or only the azimuth angle of the interference source is estimated for subsequent polarization mode decision-making. In some cases, ranging can be performed through multi-UAV cooperative positioning or combined with other sensors (such as radar, camera) to improve the positioning accuracy of the interference source.

[0103] (7) Output the spatial position information of the interference source: Output the estimated spatial position information (x i , y i , z i ) of the interference source for subsequent optimal polarization mode decision-making.

[0104] The present invention intelligently decides the optimal working mode of the UAV dual-polarization antenna according to the spatial position information of the interference source to maximize the suppression of interference signals and improve the reception quality of desired signals.

[0105] The specific steps of the optimal polarization mode decision algorithm include:

[0106] (1) Obtain the spatial position information of the interference source: Receive the spatial position information (x i , y i , z i ) output by the interference source spatial positioning algorithm

[0107] (2) Estimate the channel polarization characteristics: According to the spatial position (x i , y i , z i) and the position of the drone (x u , y u , z u ), estimate the polarization characteristics of the wireless channel between the drone and the interference source, such as the polarization direction, polarization ellipticity, etc. Considering the influence of the propagation environment (such as free space propagation model, multipath propagation model, etc.), the channel polarization characteristics can be estimated more accurately. In a simple free space propagation model, the polarization direction of electromagnetic waves remains unchanged during propagation. However, in an actual complex propagation environment, due to the influence of factors such as reflection, refraction, and scattering, the polarization direction may change. The database of channel polarization characteristics under different propagation environments can be established in advance through experimental measurements or electromagnetic simulations, or a channel polarization prediction model can be used for estimation.

[0108] (3) Calculate the interference rejection ratio under different polarization modes: For the multiple polarization modes supported by the drone's dual-polarized antenna (such as horizontal polarization (H), vertical polarization (V), and linear polarizations at different angles, circular polarization / elliptical polarization with different rotation directions and ellipticities), calculate the ratio of the interference signal power received by the drone antenna to the desired signal power under each polarization mode, that is, the interference rejection ratio (Interference Rejection Ratio, IRR). When calculating the IRR, it is necessary to consider the radiation pattern and polarization characteristics of the drone antenna under different polarization modes. For example, for an ideal dual-polarized antenna, the horizontal polarization mode only receives horizontally polarized waves, and the vertical polarization mode only receives vertically polarized waves. However, in an actual antenna, there may be a cross-polarization discrimination (XPD) problem, that is, the horizontally polarized antenna will also receive a part of the vertically polarized waves, and vice versa. The polarization radiation pattern and XPD parameters of the antenna can be obtained through antenna testing or simulation and used to accurately calculate the IRR under different polarization modes.

[0109] (4) Select the polarization mode with the highest interference rejection ratio: Compare the interference rejection ratios IRR under various polarization modes, and select the polarization mode with the highest IRR value as the optimal polarization mode. The higher the IRR value, the more severely the interference signal is suppressed and the relatively stronger the desired signal is under this polarization mode.

[0110] (5) Output the control instruction for the optimal polarization mode: Output the control instruction for the optimal polarization mode and send it to the polarization switching control module to control the drone's dual-polarized antenna to switch to the optimal polarization mode. The control instruction for the optimal polarization mode can be a simple polarization mode index (such as 0 for horizontal polarization, 1 for vertical polarization, 2 for 45-degree linear polarization, 3 for right-handed circular polarization, etc.), or a more refined polarization controller parameter setting (such as polarization angle, ellipticity control voltage / current value)

[0111] The present invention adopts an elastic polarization switching method. According to the result of the optimal polarization mode decision algorithm, it controls the dual-polarization antenna of the unmanned aerial vehicle to flexibly and quickly switch to the optimal polarization mode, so as to achieve the best interference suppression effect.

[0112] The specific steps of the elastic polarization switching algorithm include:

[0113] (1) Receive the optimal polarization mode control instruction: Receive the optimal polarization mode control instruction output by the optimal polarization mode decision algorithm.

[0114] (2) Query the polarization mode parameters: According to the optimal polarization mode control instruction, query the pre-set polarization mode parameter table to obtain the polarization controller parameters corresponding to the optimal polarization mode, such as control voltage, control current, switching time, etc. The polarization mode parameter table needs to be calibrated and established according to the specific dual-polarization antenna and polarization controller used. The parameter table should include the indexes of various pre-set polarization modes, polarization mode types (horizontal, vertical, linear polarization angle, circular polarization / elliptical polarization rotation direction and ellipticity), polarization controller parameter values, and polarization mode switching time and other information.

[0115] (3) Generate the polarization controller control signal: Generate the corresponding polarization controller control signal according to the queried polarization controller parameters. The control signal can be a voltage signal, a current signal, a digital control signal, etc., depending on the type and interface of the polarization controller.

[0116] (4) The polarization switching control module controls the antenna polarization controller: The polarization switching control module sends the generated control signal to the polarization controller of the dual-polarization antenna to control the polarization controller to perform the polarization mode switching operation. The polarization switching control module needs to adapt the interface and match the communication protocol with the polarization controller. The control module needs to have the ability of fast and accurate polarization switching control to ensure the real-time and accuracy of the polarization mode switching.

[0117] (5) The dual-polarization antenna switches to the optimal polarization mode: The dual-polarization antenna is elastically switched to the optimal polarization mode under the drive of the polarization controller, and starts to receive and transmit signals in the optimal polarization mode to effectively suppress the interference signal. The elastic polarization switching needs to be as fast and smooth as possible to avoid introducing additional signal distortion or interruption during the switching process. For example, a smooth transition polarization switching curve can be adopted, or a pre-calibrated polarization switching timing control can be adopted to optimize the switching performance.

[0118] Furthermore, to achieve a more refined smooth transition, various smoothing functions such as S-curves, Gaussian curves, or piecewise polynomial curves can be explored to design the polarization switching trajectory, and the curve parameters, such as the switching duration and curve slope, can be adaptively adjusted according to the requirements of the actual system for switching speed and signal quality. In addition, to overcome the nonlinear characteristics and delays of polarization control devices, pre-compensation techniques or digital pre-distortion (DPD) algorithms can be introduced to pre-correct these effects at the control signal level to ensure the accuracy and smoothness of the actual polarization switching process. More advanced methods can also incorporate feedback control mechanisms to real-time monitor signal quality metrics (such as EVM, bit error rate, etc.) during the switching process and dynamically adjust the polarization control strategy to achieve optimal elastic polarization switching performance.

[0119] To verify the effectiveness of the proposed method for elastic switching of dual-polarized antennas on drones based on the spatial localization of interference sources, the following three groups of comparative examples were designed and simulation verification was carried out.

[0120] Example 1: Comparison of the performance of polarization switching based on the spatial localization of interference sources and polarization switching based on signal strength.

[0121] Experimental purpose: This experiment aims to directly compare the anti-interference performance differences between the proposed elastic polarization switching (EPS) method based on the spatial localization of interference sources and the polarization switching (RSSI-based PS) method based on signal strength detection in this invention, highlighting the role of location information in anti-interference polarization switching. The polarization switching method based on signal strength detection is a common existing technical solution and has a certain representativeness.

[0122] Experimental scenario: Simulate the communication of a drone in a complex urban electromagnetic environment with a narrowband interference source whose position remains fixed. Test the throughput performance of the drone communication system under the following three conditions respectively:

[0123] (1) Fixed vertical polarization (VP): The drone antenna adopts a fixed vertical polarization mode as a reference.

[0124] (2) Polarization switching based on signal strength (RSSI-based PS): The drone dynamically switches between horizontal and vertical polarization modes according to the received signal strength (RSSI). When the RSSI is lower than a certain threshold, the polarization mode is switched. The threshold is set to the value that optimizes the performance of this method.

[0125] (3) Elastic Polarization Switching (EPS) of the present invention: The elastic polarization switching method based on the spatial positioning of interference sources proposed by the present invention is adopted. The experimental parameters are as follows: ① Carrier frequency: 2.4 GHz; ② Signal bandwidth: 2 MHz; ③ Modulation method: QPSK, channel coding: convolutional code (1 / 2 code rate); ④ Channel model: urban macrocellular channel model (ITU-RP.1411); ⑤ Interference type: single-tone interference, interference bandwidth 100 kHz; ⑥ Interference signal strength: the ratio of interference signal power to desired signal power (INR) varies from 0 dB to 20 dB; ⑦ Signal-to-noise ratio (SNR): 20 dB (for the desired signal, without interference); ⑧ Polarization antenna: ideal dual-polarization antenna (XPD is infinite); ⑨ Interference source position: azimuth angle 60° relative to the UAV, elevation angle 30° (fixed); ⑩ Number of simulation times: 1000 Monte Carlo simulations; Throughput calculation: Throughput = signal bandwidth × code rate × (1 - bit error rate).

[0126] As Figure 2 shown, the throughput performance comparison of fixed vertical polarization, signal strength detection-based polarization switching, and the elastic polarization switching method of the present invention under different interference intensities is presented. It can be seen that the elastic polarization switching method of the present invention has the highest throughput, and its advantage is more obvious especially under high interference intensities, significantly superior to the signal strength detection-based polarization switching method, highlighting the role of positioning information in anti-interference polarization switching.

[0127] The experimental results clearly show that the throughput performance of the elastic polarization switching (EPS) method proposed by the present invention is significantly superior to the signal strength detection-based polarization switching (RSSI-based PS) method and the fixed vertical polarization (VP) method. Especially in the high interference intensity (INR > 10 dB) region, the throughput advantage of the EPS method is more prominent.

[0128] Comparison with the RSSI-based PS method: Although the RSSI-based PS method can perform polarization switching according to the signal strength, its performance improvement is limited, and it even approaches the fixed polarization performance under high interference. This is because the RSSI-based PS method only relies on the scalar information of the received signal strength, and cannot distinguish whether the signal strength decrease is due to interference or channel fading, nor can it utilize the spatial polarization characteristics of the interference signal for targeted suppression.

[0129] Advantages of the EPS method of the present invention: The EPS method of the present invention can accurately estimate the spatial position of the interference source by introducing the spatial positioning information of the interference source, and then make an intelligent decision on the optimal polarization mode for flexible switching based on this. The experimental results prove that the EPS method can more effectively suppress the interference signal, thereby obtaining higher throughput and better communication quality. The experimental results strongly verify the innovation and superiority of the polarization switching based on the spatial positioning of the interference source, highlighting the key role of the positioning information in improving the anti-interference performance of the polarization switching. The performance improvement of the EPS method compared with the RSSI-based PS method is further highlighted by the shaded area and text annotation in the chart, enhancing the expressiveness and persuasiveness of the chart.

[0130] Example 2: Throughput performance variation of flexible polarization switching under different interference source positioning errors.

[0131] Experimental purpose: This embodiment aims to investigate the influence of the spatial positioning error of the interference source on the throughput performance of the flexible polarization switching method of the present invention, and verify the robustness of the method of the present invention to the positioning error.

[0132] Experimental scenario and parameters: Similar to Example 1, mainly changing the azimuth estimation error of the interference source.

[0133] As Figure 3 shown, it shows the throughput performance variation of the flexible polarization switching method of the present invention under different azimuth estimation errors of the interference source. It can be seen that as the positioning error increases, the throughput decreases slightly, but even under a relatively large error of 10°, the throughput still remains at a relatively high level, indicating that the method of the present invention has a certain robustness to the positioning error.

[0134] The experimental results show that the spatial positioning error of the interference source has a certain influence on the throughput performance of the flexible polarization switching method of the present invention. As the azimuth estimation error of the interference source increases from 0° to 10°, the throughput decreases slightly. However, even under a relatively large positioning error of 10°, the throughput still remains at a relatively high level (close to 0.85 Mbps). This means that the method of the present invention has good robustness to the interference source positioning error. In practical applications, even if the positioning accuracy is limited to a certain extent, the method of the present invention can still work effectively and provide good anti-interference performance. The robustness of the method of the present invention to the positioning error is emphasized by text annotation in the chart, highlighting its advantages in practical applications.

[0135] Example 3: Time-varying performance of spectral efficiency of flexible polarization switching in a dynamic interference scenario.

[0136] Purpose of the experiment: This experiment aims to investigate the adaptability of the elastic polarization switching method of the present invention in a dynamic interference scenario. The dynamic interference scenario can more realistically reflect the characteristics of a complex electromagnetic environment. Spectral efficiency is an indicator that comprehensively reflects the ability of a communication system to effectively utilize spectral resources and is closer to the actual application requirements.

[0137] Experiment scenario and parameters: Similar to Example 1, the main change is that the position of the interference source changes dynamically.

[0138] ① Position of the interference source: The azimuth angle changes dynamically (randomly jumps every 10 seconds, uniformly distributed within the range of 30° to 90°), and the elevation angle is 30° (fixed); ② Interference intensity: INR = 15 dB (fixed); ③ Simulation duration: 60 seconds; ④ Performance indicator: Spectral efficiency, unit: bps / Hz, calculation formula: Spectral efficiency = throughput / signal bandwidth = code rate x (1 - bit error rate).

[0139] As Figures 4 - 8 shown, it shows the comparison of the time-varying performance of the spectral efficiency of fixed vertical polarization and the elastic polarization switching method of the present invention in a dynamic interference scenario. It can be seen that the elastic polarization switching method of the present invention can track the change of the interference source position in real time and dynamically adjust the polarization mode, and the spectral efficiency is always higher than that of the fixed vertical polarization method, reflecting good adaptability to the dynamic environment.

[0140] The experimental results show that in a dynamic interference scenario, the spectral efficiency of the elastic polarization switching (EPS) method proposed by the present invention is always significantly higher than that of the fixed vertical polarization (VP) method. The spectral efficiency of the fixed vertical polarization method fluctuates at a low level and cannot effectively adapt to the dynamically changing interference. While the EPS method of the present invention can track the change of the interference source position in real time and dynamically adjust the polarization mode, and the spectral efficiency remains at a high and stable level, fully reflecting the dynamic adaptability and spectral efficiency advantage of the method of the present invention in a dynamic complex electromagnetic environment. The dynamic adaptability of the method of the present invention is emphasized through text annotation in the chart, further highlighting its value in practical applications.

[0141] Compared with the prior art, the drone dual-polarization antenna elastic switching method based on the spatial positioning of the interference source proposed by the present invention has the following remarkable beneficial effects and advantages:

[0142] The present invention introduces the spatial position information of the interference source into the anti-interference design of the drone communication system. Different from the previous passive anti-interference methods that only rely on signal strength or simple direction finding, the present invention actively locates the interference source, providing accurate interference source information for subsequent polarization mode decision-making and elastic switching, which is the basis for realizing precise interference suppression.

[0143] The present invention makes an intelligent decision on the optimal working mode of the UAV dual-polarized antenna based on the spatial position information of the interference source. This algorithm can select the most suitable polarization mode according to different interference scenarios and the position of the interference source, achieve the maximum degree of interference suppression, and ensure the reception quality of the desired signal.

[0144] The present invention adopts the elastic polarization switching technology, which can flexibly, quickly and smoothly switch to the optimal polarization mode according to the decision result of the optimal polarization mode. This elastic switching method is different from the traditional hard switching, and can utilize the polarization resources more precisely to improve the system performance.

[0145] The UAV anti-jamming communication system of the present invention integrates an interference source spatial positioning module, an optimal polarization mode decision module and an elastic polarization switching module to form a complete UAV anti-jamming system. This system can achieve intelligent, automatic and adaptive anti-jamming, and significantly improve the communication reliability and stability of the UAV in a complex electromagnetic environment.

[0146] The above is only the preferred specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the technical field of the present application within the technical scope disclosed by the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A flexible switching method for dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources, characterized in that: The following steps are involved: Based on the interference source spatial positioning algorithm, the interference signal received by the UAV dual-polarization antenna array and the location information of the UAV are calculated to obtain the spatial location of the interference source; Based on the spatial position of the interference source, an optimal polarization mode decision algorithm is used to determine an optimal polarization mode control instruction; Based on the optimal polarization mode control instruction, an elastic polarization switching algorithm is used to control the dual-polarization antenna of the UAV to switch to the optimal polarization mode.

2. The method for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 1 is characterized in that: The process of calculating the spatial position of the interference source based on the interference source spatial positioning algorithm includes: The dual-polarized antenna array receives the interference signal; Processing the interference signal to obtain an analog signal; Sampling and analog-to-digital conversion are performed on the analog signal to obtain a digital signal; Using an arrival angle estimation algorithm to estimate the digital signal to obtain an arrival angle of the interference signal; The spatial position of the interference source is calculated based on the position information of the UAV and the arrival angle of the interference signal.

3. The method for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 2 is characterized in that: The calculation expression of the spatial position of the interference source is: x i =x u +dcos(φ)sin(θ),y i =y u +dcos(φ)cos(θ),z i =z u +dsin(φ) In the formula, (x u ,y u , z u ) represents the position coordinates of the drone, (x i ,y i , z i ) represents the spatial position of the interference source, θ represents the azimuth of the interference signal, the azimuth of the interference signal is due north, φ represents the pitch angle of the interference signal, and d represents the distance from the interference source to the UAV.

4. The method for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 1 is characterized in that: The optimal polarization mode decision algorithm is used to determine the optimal UAV dual-polarization antenna working mode. The process includes: Estimate the polarization characteristics of the wireless channel between the UAV and the interference source based on the spatial position of the interference source and the position information of the UAV; Calculating interference suppression ratios under different polarization modes based on the polarization characteristics of the wireless channel between the UAV and the interference source; The polarization mode with the highest interference suppression ratio is selected to output the optimal polarization mode control instruction.

5. The method for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 1 is characterized in that: The elastic polarization switching algorithm is used to control the UAV dual-polarization antenna to switch to the optimal polarization mode. The process includes: Based on the optimal polarization mode control instruction, query a preset polarization mode parameter table to obtain polarization controller parameters corresponding to the optimal polarization mode; generating a polarization controller control signal based on the queried polarization controller parameter; The dual-polarization antenna switches to an optimal polarization mode based on the polarization controller control signal.

6. A flexible switching system for dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources, used to implement the method described in any one of claims 1 to 5, characterized in that: The system comprises: The ground station is used to communicate wirelessly with the communication module on the UAV platform to achieve data transmission and command interaction; Unmanned aerial vehicle platform, used to provide flight platform and energy supply.

7. The flexible switching system for dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 6 is characterized in that: The unmanned aerial vehicle platform includes: a dual-polarized antenna, a radio frequency front end, a positioning module, a signal processing module, a polarization switching control module and a communication module; Wherein, the dual-polarized antenna is used to receive a desired signal from the ground and an interference signal from an interference source; The RF front end is used to process the interference signal to obtain an analog signal, and send the analog signal to the signal processing module; The positioning module is used to determine the location information of the drone; The signal processing module is used to receive the analog signal output by the RF front end and the position information of the UAV output by the positioning module to issue a polarization mode control instruction; The polarization switching control module is used to control the signal dual-polarization antenna to switch to the optimal polarization mode based on the polarization mode control instruction; The communication module is used to realize wireless communication between the UAV and the ground station.

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