Flexible switching method and system for UAV dual-polarization antenna based on spatial positioning of interference sources

Abstract

The present invention discloses a method and system for flexible switching of dual-polarized antennas for unmanned aerial vehicles (UAVs) based on spatial positioning of interference sources. The method belongs to the field of wireless communications and includes the following steps: calculating the spatial location of the interference source based on interference signals received by the UAV's dual-polarized antenna array and the UAV's position information using an interference source spatial positioning algorithm; determining an optimal polarization mode control instruction using an optimal polarization mode decision algorithm based on the spatial location of the interference source; and controlling the UAV's dual-polarized antenna to switch to the optimal polarization mode using a flexible polarization switching algorithm based on the optimal polarization mode control instruction. The present invention has the advantages of high intelligence, strong adaptability, good flexibility, and low implementation complexity, and can effectively improve the robustness and reliability of UAV communication systems.

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 elastic switching of dual-polarized antennas of unmanned aerial vehicles (UAVs) based on spatial positioning of interference sources. Background Art

[0002] In recent years, low-altitude drone technology has developed rapidly, finding widespread application in various fields, including communications relay, material distribution, environmental monitoring, public security, and military reconnaissance. However, drones face increasingly complex electromagnetic environments in their practical applications. In particular, various types of interference, both malicious and natural, have severely impacted the reliability and stability of drone communication links. This interference not only degrades communication quality but can even lead to loss of control, resulting in mission failure and financial losses. Therefore, improving the anti-interference capabilities of drone communication systems in complex electromagnetic environments has become a critical issue that needs to be addressed in the development of drone technology.

[0003] Currently, anti-interference technologies for drone communication systems primarily focus on the frequency, time, and spatial domains, while the utilization of the polarization domain remains inadequate and inefficient. Existing polarization anti-interference methods suffer from fixed polarization modes, manual polarization switching, a lack of spatial location information for interference sources, and a single, rigid polarization switching method.

[0004] The current existing technologies include: polarization switching methods based on signal strength detection, anti-interference methods based on polarization diversity reception, anti-interference methods based on smart antenna beamforming, and adaptive polarization adjustment methods based on interference source direction finding. These existing solutions have limitations in terms of anti-interference performance, intelligence, flexibility, and complexity, including the following technical drawbacks:

[0005] (1) Limited anti-interference effect and low efficiency: Existing technical solutions, such as fixed polarization, signal strength switching, and polarization diversity reception, 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 a decline in communication quality.

[0006] (2) Low intelligence and frequent manual intervention: Existing technical solutions, such as manual switching of polarization modes, require manual presetting or simple rule control. They are not very 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 the precise positioning of the spatial position of the interference source and cannot fully utilize the spatial position information of the interference source to accurately adjust the polarization direction. They have poor adaptability and it is difficult to achieve the best interference suppression effect.

[0008] (4) The polarization switching method is single and rigid, and lacks flexibility: Existing technical solutions, such as fixed polarization mode switching or hard switching, have a single and rigid polarization switching method, lack flexibility, and cannot perform fine and continuous polarization adjustments according to the complexity of the interference environment, making it difficult to fully utilize the advantages of polarization resources in anti-interference.

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

[0010] Therefore, based on the above-mentioned technical problems, the present invention proposes a flexible switching method for UAV dual-polarization antennas based on spatial positioning of interference sources. Summary of the Invention

[0011] In order to solve the above technical problems, the present invention proposes a method and system for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources to solve the problems existing in the above-mentioned prior art.

[0012] To achieve the above objectives, the present invention provides a method for flexible switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources, comprising:

[0013] Based on the interference source spatial positioning algorithm, the interference signal received by the UAV dual-polarized antenna array and the position information of the UAV are calculated to obtain the spatial position of the interference source;

[0014] 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;

[0015] Based on the optimal polarization mode control instruction, an elastic polarization switching algorithm is used to control the UAV dual-polarization antenna to switch to the optimal polarization mode.

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

[0017] The dual-polarized antenna array receives the interference signal;

[0018] Processing the interference signal to obtain an analog signal;

[0019] Sampling and analog-to-digital converting the analog signal to obtain a digital signal;

[0020] An arrival angle estimation algorithm is used to estimate the digital signal to obtain an arrival angle of the interference signal;

[0021] 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.

[0022] Optionally, the spatial position calculation expression 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 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.

[0025] Optionally, an optimal polarization mode decision algorithm is used to determine the optimal UAV dual-polarization antenna operating mode, and the process includes:

[0026] estimating 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] Calculating interference suppression ratios under different polarization modes based on the polarization characteristics of the wireless channel between the UAV and the interference source;

[0028] The polarization mode with the highest interference suppression ratio is selected to output the optimal polarization mode control instruction.

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

[0030] Based on the optimal polarization mode control instruction, querying a preset polarization mode parameter table to obtain polarization controller parameters corresponding to the optimal polarization mode;

[0031] generating a polarization controller control signal based on the queried polarization controller parameter;

[0032] The dual-polarization antenna switches to an optimal polarization mode based on the polarization controller control signal.

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

[0034] The ground station is used to communicate wirelessly with the communication module on the UAV platform to achieve data transmission and command interaction;

[0035] UAV-based platform, used to provide flight platform and energy supply.

[0036] Optionally, the UAV-mounted 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 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;

[0039] The positioning module is used to determine the location information of the drone;

[0040] 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 and issue a polarization mode control instruction;

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

[0042] The communication module is used to realize wireless communication between the UAV and the ground station.

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

[0044] 1. Significantly Improved Anti-interference Effectiveness and Higher Efficiency: This invention achieves precise suppression of interfering signals by locating the spatial position of interference sources in real time and dynamically adjusting the antenna polarization pattern accordingly. This anti-interference effect is far superior to traditional fixed polarization and simple polarization switching methods, significantly improving communication quality and reliability and achieving higher anti-interference efficiency. Experimental results show that in strong interference environments, the bit error rate of this invention is more than an order of magnitude lower than that of traditional methods.

[0045] 2. High degree of intelligence, automated anti-interference, and reduced manual intervention: The method of the present invention can automatically complete operations such as interference source positioning, polarization mode decision-making, and polarization switching, without the need for manual pre-setting and manual switching. It realizes intelligent and automated anti-interference, greatly reduces the need for manual intervention, and improves system operation efficiency and reliability.

[0046] 3. Strong adaptability, robustness, and environmental adaptability: The method of the present invention can track and respond to dynamic changes in the spatial position of interference sources in real time, and flexibly adjust the polarization pattern according to the complexity of the interference environment. This method has strong adaptability and robustness, can better adapt to complex and dynamically changing electromagnetic environments, has stronger environmental adaptability, and has a wider range of applications. Experimental results show that the present invention can maintain good anti-interference performance even when the position of the interference source changes dynamically.

[0047] 4. More refined and flexible utilization of polarization resources and richer anti-interference measures: The method of the present invention can flexibly select the optimal polarization mode based on the interference situation. It is not limited to hard switching between horizontal and vertical polarization. It can also select linear polarization at any angle based on the location of the interference source, and even supports more complex polarization modes such as circular polarization and elliptical polarization. This realizes the refined and flexible utilization of polarization resources, provides richer anti-interference measures, and can more fully realize the potential of polarization resources in anti-interference.

[0048] 5. The system complexity and cost are relatively low, and it is 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, using a relatively simple hardware structure and efficient algorithms (for example, although the MUSIC / ESPRIT algorithm has a large amount of computation, it can be efficiently implemented on hardware platforms such as FPGA / DSP). Compared with complex technologies such as intelligent antenna beamforming, the system complexity and cost of the solution of the present invention are relatively low, the power consumption is lower, and it is more suitable for miniaturized and lightweight UAV platforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

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

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

[0052] Figure 3 The impact of interference source positioning error on the flexible polarization switching throughput performance in an embodiment of the present invention;

[0053] Figure 4 This is a comparison of the time-varying performance of spectrum efficiency of different polarization methods in a dynamic interference scenario according to an embodiment of the present invention;

[0054] Figure 5 The throughput performance comparison of different polarization switching methods according to the embodiments of the present invention is as follows;

[0055] Figure 6 The impact of interference source positioning error on the flexible polarization switching throughput performance in an embodiment of the present invention;

[0056] Figure 7 This is a comparison of the time-varying performance of spectrum efficiency in a dynamic interference scenario according to an embodiment of the present invention;

[0057] Figure 8 Schematic diagram of a smooth transition curve for polarization switching according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

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

[0060] Example 1

[0061] The main objectives to be achieved by the present invention include: (1) Improving the anti-interference effect and efficiency: By accurately locating the spatial position of the interference source in real time and dynamically and adaptively adjusting the polarization direction of the UAV dual-polarized antenna according to the location information of the interference source, the interference signal can be accurately suppressed, and the anti-interference effect and efficiency can be significantly improved. (2) Realizing intelligent and automated anti-interference: The present invention can automatically complete operations such as interference source positioning, polarization mode decision and polarization switching without manual intervention, realizing intelligent and automated anti-interference and improving system efficiency and reliability. (3) Improving adaptability and robustness: The present invention can track and respond to the spatial position changes of the interference source in real time, and flexibly adjust the polarization mode according to the complexity of the interference environment. It has good adaptability and robustness and can 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 algorithm, 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 hard switching between horizontal 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 according to the spatial position of the interference source. It 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] This embodiment provides a method for elastic switching of dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources. First, the positioning module and antenna array on the unmanned aerial vehicle platform are used in combination with a signal processing algorithm to accurately locate the spatial position of the interference source in real time. Then, based on the spatial position information of the interference source, an intelligent decision is made on the optimal working mode of the unmanned aerial vehicle dual-polarized antenna (for example, horizontal polarization, vertical polarization, or linear polarization or circular polarization at a specific polarization angle, etc.). Finally, by controlling the polarization switching module of the dual-polarized 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 unmanned aerial vehicle communication link. The present invention is particularly suitable for complex electromagnetic environments and application scenarios with high requirements for communication reliability. The present invention has the advantages of high intelligence, strong adaptability, good flexibility, and low complexity, and can effectively improve the robustness and reliability of the unmanned aerial vehicle communication system.

[0063] The present invention is applicable to low-altitude UAV communication systems that need to operate in complex electromagnetic environments, and is particularly applicable to the following scenarios: (1) Scenarios where there is malicious human 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 is multipath interference, co-frequency interference, etc. (3) Scenarios with high requirements for communication reliability and security: such as military communications, emergency rescue communications, important data transmission, etc. (3) Scenarios that require miniaturized and lightweight UAV platforms: The solution of the present invention strives for low complexity and low cost, and is suitable for small UAV platforms.

[0064] This embodiment provides a method for elastically switching dual-polarized antennas of a UAV based on spatial positioning of interference sources. The method for elastically switching dual-polarized antennas of a UAV is implemented based on a UAV communication system. The UAV communication system mainly includes two parts: a UAV carrier platform and a ground station (or other UAVs).

[0065] The ground station / other drones communicate wirelessly with the communication module on the drone platform to achieve data transmission and command interaction.

[0066] The UAV-mounted platform mainly includes dual-polarization antenna, RF front-end, signal processing module, polarization switching control module, communication module and 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 in this invention.

[0068] Dual-polarized antenna: Use a dual-polarized antenna that can switch between horizontal polarization and vertical polarization modes, or go a step further and use an adjustable polarization antenna that can flexibly switch between multiple polarization modes. Dual-polarized antennas are the physical basis for achieving polarization diversity and polarization interference suppression. Dual-polarized antennas receive desired signals from ground stations or other drones, as well as interference signals from interference sources. 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.). The antenna unit uses metamaterials or reconfigurable structures to support fast polarization switching.

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

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

[0071] Signal processing module: Mainly implemented by hardware such as a digital signal processor (DSP) or a field programmable gate array (FPGA), it is responsible for implementing core algorithms such as the interference source spatial positioning algorithm, the optimal polarization mode decision algorithm, and the polarization switching control algorithm. The signal processing module is the core component of the present invention and implements the processing and control of received signals. The signal processing module is the core of the system. It receives signals from the RF front end and the drone's position and attitude information from the positioning module. It uses the interference source spatial positioning algorithm to estimate the spatial position of the interference source. Then, based on the interference source's position information, the optimal polarization mode decision algorithm is used to determine the optimal polarization mode and send 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, and channel coding and decoding. It realizes data exchange with ground stations or other drones through the communication module. The signal processing module is composed of hardware resources such as high-speed ADC / DAC, DSP / FPGA, and executes the interference source spatial positioning algorithm (AOA / TDOA / RSSI combined measurement), the optimal polarization mode decision algorithm, and baseband signal processing (modulation and demodulation, channel coding / decoding, etc.). This module is the core computing unit of the present invention and needs to ensure real-time performance (processing delay is usually less than 5ms).

[0072] Polarization switching control module: used to control the polarization mode switching of the dual-polarization antenna. According to the decision results of the signal processing module, the polarization controller of the dual-polarization antenna is controlled to achieve flexible switching of horizontal polarization, vertical polarization or other polarization modes. The polarization switching control module receives the polarization mode control instructions from the signal processing module, controls the polarization controller of the dual-polarization antenna, and achieves flexible switching of polarization modes. The polarization switching control module receives the polarization mode control instructions 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-polarization antenna to switch smoothly between different polarization modes. The module has a fast response characteristic (the switching time can be controlled within 5μs to 10μs).

[0073] Communication module: This module enables wireless communication between the drone and the ground station or other drones. It must support the appropriate communication protocols and modulation / demodulation methods. It enables two-way communication with the ground station or other drone nodes, supporting multiple communication protocols (such as Wi-Fi, 4G / 5G, and dedicated narrowband / broadband protocols), and can be combined with a secure encryption chip to encrypt data transmission.

[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 drone platform to further improve algorithm efficiency.

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

[0076] This embodiment provides a method for elastic switching of a UAV's dual-polarized antenna based on spatial positioning of an interference source, comprising the following steps: calculating the interference signal received by the UAV's dual-polarized antenna array and the UAV's position information based on an interference source spatial positioning algorithm to obtain the spatial position of the interference source; based on the spatial position of the interference source, using an optimal polarization mode decision algorithm to determine an optimal polarization mode control instruction; based on the optimal polarization mode control instruction, using an elastic polarization switching algorithm to control the UAV's dual-polarized antenna to switch to the optimal polarization mode.

[0077] The present invention uses an interference source spatial positioning algorithm based on the angle of arrival (AOA). The algorithm uses the interference signal received by the drone's dual-polarized antenna array to estimate the arrival angle of the interference signal, and then combines it with the drone's own position information to calculate the spatial position of the interference source.

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

[0079] (1) Dual-polarized antenna array receives interference signals: The dual-polarized antenna array onboard the UAV 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 performs low-noise amplification, filtering, mixing, and other processing on the received interference signal to convert it into an analog signal, which includes an intermediate frequency or baseband signal.

[0081] (3) Signal sampling and digitization: The analog signal output by the RF front end is sampled and converted into analog-to-digital signal to obtain a digital signal.

[0082] (4) AOA estimation module performs arrival angle estimation: It uses a high-resolution arrival angle estimation algorithm, such as the MUSIC (Multiple Signal Classification) algorithm or the ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm, to estimate the arrival angle of the interference signal, including the azimuth and elevation angles.

[0083] A brief description of the mathematical principles of the MUSIC algorithm:

[0084] The MUSIC algorithm uses the orthogonality of 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: for R x Perform eigenvalue decomposition:

[0089] R x =U∑U H

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

[0091] Construct a spatial spectrum function:

[0092]

[0093] Where a(θ,φ) is the array steering vector, representing the array response to the signal in the direction (θ,φ). θ and φ represent the azimuth and elevation angles, respectively.

[0094] Peak search: By searching (θ, φ) so that P MUSIC When the maximum value is reached, the (θ, φ) corresponding to the maximum value is the estimated arrival angle of the interference signal.

[0095] As a specific implementation of this embodiment, in the drone-borne signal processing module, the received interference signal is first subjected to RF front-end preprocessing and analog-to-digital conversion; the above-mentioned MUSIC algorithm is used to estimate the arrival angle of the interference source; combined with the drone coordinates (x u ,y u , z u ), further calculate the spatial position of the interference source (x i ,y i , z i ).

[0096] This enables real-time spatial positioning of interference sources and provides accurate spatial information support for subsequent optimal polarization mode decisions and flexible switching, thereby effectively improving the anti-interference capability of the UAV communication system.

[0097] (5) Positioning module obtains the position of the drone: The position coordinates (x u ,y u , z u ).

[0098] (6) Calculation of the spatial position of the interference source: Based on the estimated arrival angle (θ, φ) of the interference signal (azimuth and pitch angle) and the position coordinates (x u ,y u , z u ), calculate the spatial position of the interference source (x i ,y i , z i The calculation formula is as follows (assuming the coordinate system is established with the drone as the origin, the north direction as the Y axis, the 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, in meters (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 multiple UAVs in collaboration; θ is the azimuth of the interference signal, which is the angle relative to a reference direction (such as due north) in the UAV coordinate system, in degrees or radians; φ is the elevation of the interference signal, which is the angle relative to the horizontal plane, in degrees or radians; the coordinate system convention is: the x-axis points to the east, the y-axis points to the north, and the z-axis is vertically upward (zenith).

[0101] If you only care about the interference source azimuth (θ, φ) without precise ranging, you can treat d as a constant or use relative coordinates for polarization decision making. This embodiment can also obtain a more accurate d value through multi-UAV collaborative positioning or other sensors (radar, camera, etc.), thereby improving the interference source positioning accuracy.

[0102] d is the distance from the interference source to the UAV. If the distance is unknown, the interference source can be assumed to be far away and a sufficiently large value can be used. Alternatively, the interference source's azimuth can be estimated for subsequent polarization mode decisions. In some cases, multi-UAV collaborative positioning or ranging combined with other sensors (such as radar and cameras) can improve interference source location accuracy.

[0103] (7) Output the spatial location information of the interference source: Output the estimated spatial location information of the interference source (x i ,y i , z i ), which is used for subsequent optimal polarization mode decision.

[0104] The present invention intelligently determines the optimal operating mode of the UAV dual-polarized antenna based on the spatial location information of the interference source, so as to suppress the interference signal to the greatest extent and improve the reception quality of the desired signal.

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

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

[0107] (2) Channel polarization characteristic estimation: According to the spatial position of the interference source (x i ,y i ,z i) and the position of the drone (x u ,y u ,z u ) to estimate the polarization characteristics of the wireless channel between the UAV and the interference source, such as polarization direction and polarization ellipticity. Taking into account the influence of the propagation environment (such as the free-space propagation model and the multipath propagation model), the channel polarization characteristics can be estimated more accurately. In a simple free-space propagation model, the polarization direction of the electromagnetic wave remains unchanged during propagation. However, in actual complex propagation environments, the polarization direction may change due to factors such as reflection, refraction, and scattering. A database of channel polarization characteristics under different propagation environments can be pre-established 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 various polarization modes that the UAV dual-polarization antenna can support (such as horizontal polarization (H), vertical polarization (V), linear polarization of different angles, circular polarization / elliptical polarization of different rotation directions and ellipticities), calculate the ratio of the interference signal power received by the UAV antenna to the desired signal power under each polarization mode, that is, the interference rejection ratio (IRR). When calculating the IRR, it is necessary to consider the directional pattern and polarization characteristics of the UAV antenna under different polarization modes. For example, for an ideal dual-polarization antenna, the horizontal polarization mode only receives horizontally polarized waves, and the vertical polarization mode only receives vertically polarized waves. However, the actual antenna may have a polarization cross-polarization discrimination (XPD) problem, that is, the horizontally polarized antenna will also receive a portion of the vertically polarized waves, and vice versa. The polarization pattern and XPD parameters of the antenna can be obtained through antenna testing or simulation to accurately calculate the IRR under different polarization modes.

[0109] (4) Select the polarization mode with the highest interference suppression ratio: Compare the interference suppression ratios (IRRs) of various polarization modes and select the polarization mode with the highest IRR as the optimal polarization mode. A higher IRR value indicates that the interference signal is more strongly suppressed in that polarization mode, and the desired signal is relatively stronger.

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

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

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

[0113] (1) Receiving an optimal polarization mode control instruction: receiving an optimal polarization mode control instruction output by an optimal polarization mode decision algorithm.

[0114] (2) Query 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 index of various preset polarization modes, polarization mode type (horizontal, vertical, linear polarization angle, circular polarization / elliptical polarization rotation and ellipticity), polarization controller parameter value, and polarization mode switching time and other information.

[0115] (3) Generate polarization controller control signal: Generate the corresponding polarization controller control signal based on 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-polarized antenna, instructing the polarization controller to perform polarization mode switching operations. The polarization switching control module needs to perform interface adaptation and communication protocol matching with the polarization controller. The control module needs to have fast and accurate polarization switching control capabilities to ensure the real-time and accuracy of polarization mode switching.

[0117] (5) Dual-polarization antenna switches to the optimal polarization mode: Driven by the polarization controller, the dual-polarization antenna flexibly switches to the optimal polarization mode and begins receiving and transmitting signals in the optimal polarization mode, effectively suppressing interference signals. Flexible 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 or pre-calibrated polarization switching timing control can be used to optimize switching performance.

[0118] Furthermore, in order to achieve a more refined smooth transition, we can explore the use of various smooth functions such as S-curves, Gaussian curves, or piecewise polynomial curves to design the polarization switching trajectory, and adaptively adjust the curve parameters, such as switching duration and curve slope, according to the actual system's requirements for switching speed and signal quality. In addition, in order to overcome the nonlinear characteristics and delays of polarization control devices, pre-compensation technology 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 combine feedback control mechanisms to monitor signal quality indicators (such as EVM, bit error rate, etc.) during the switching process in real time and dynamically adjust the polarization control strategy to achieve optimal elastic polarization switching performance.

[0119] In order to verify the effectiveness of the proposed flexible switching method for UAV dual-polarization antennas based on spatial positioning of interference sources, the following three groups of comparative examples were designed and simulated.

[0120] Example 1: Performance comparison between polarization switching based on spatial location of interference sources and polarization switching based on signal strength.

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

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

[0123] (1) Fixed vertical polarization (VP): The UAV antenna uses a fixed vertical polarization pattern as a reference.

[0124] (2) RSSI-based polarization switching: The drone dynamically switches between horizontal and vertical polarization modes based on the received signal strength (RSSI). When the RSSI falls below 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 spatial positioning of the interference source proposed in the present invention is adopted. The experimental parameters are as follows: ① Carrier frequency: 2.4GHz; ② Signal bandwidth: 2MHz; ③ Modulation mode: 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 100kHz; ⑥ Interference signal strength: the ratio of interference signal power to desired signal power (INR) varies from 0dB to 20dB; ⑦ Signal-to-noise ratio (SNR): 20dB (desired signal, no interference); ⑧ Polarization antenna: ideal dual-polarization antenna (XPD infinite); ⑨ Interference source position: 60° azimuth angle relative to the drone, 30° pitch angle (fixed); ⑩ Number of simulations: 1000 Monte Carlo simulations; Throughput calculation: Throughput = signal bandwidth x bit rate x (1-bit error rate).

[0126] like Figure 2 The figure shows a throughput performance comparison of fixed vertical polarization, polarization switching based on signal strength detection, and the flexible polarization switching method of the present invention under different interference intensities. It can be seen that the flexible polarization switching method of the present invention has the highest throughput, especially under high interference intensities, significantly outperforming the polarization switching method based on signal strength detection, highlighting the role of positioning information in polarization switching anti-interference.

[0127] Experimental results clearly demonstrate that the proposed flexible polarization switching (EPS) method significantly outperforms the RSSI-based polarization switching method and the fixed vertical polarization (VP) method in throughput performance. The EPS method's throughput advantage is particularly pronounced in areas with high interference intensity (INR > 10dB).

[0128] Compared to the RSSI-based PS method: Although the RSSI-based PS method can switch polarization based on signal strength, its performance improvement is limited, and even approaches fixed polarization performance under high interference. This is because the RSSI-based PS method relies solely on scalar information of received signal strength and cannot distinguish whether a signal strength drop is due to interference or channel fading. It also cannot use the spatial polarization characteristics of the interfering 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 intelligently decide the optimal polarization mode based on this information for flexible switching. Experimental results show that the EPS method can more effectively suppress interference signals, thereby achieving higher throughput and better communication quality. The experimental results strongly verify the innovation and superiority of polarization switching based on spatial positioning of interference sources, and highlight the key role of positioning information in improving the anti-interference performance of polarization switching. The performance improvement of the EPS method over the RSSI-based PS method is further highlighted by the shaded areas and text annotations in the chart, which enhances the expressiveness and persuasiveness of the chart.

[0130] Example 2: Changes in throughput performance of flexible polarization switching under different interference source positioning errors.

[0131] Experimental purpose: This example aims to investigate the impact of the spatial positioning error of the interference source on the throughput performance of the elastic polarization switching method of the present invention and verify the robustness of the method of the present invention to positioning errors.

[0132] Experimental scenario and parameters: Similar to Example 1, the main change is the interference source azimuth estimation error.

[0133] like Figure 3 The figure shows the throughput performance of the flexible polarization switching method of the present invention under different interference source azimuth estimation errors. It can be seen that as the positioning error increases, the throughput decreases slightly, but even with a larger error of 10°, the throughput remains at a high level, demonstrating that the method of the present invention has a certain degree of robustness to positioning errors.

[0134] The experimental results show that the spatial positioning error of the interference source has a certain impact on the throughput performance of the elastic 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 with a larger positioning error of 10°, the throughput remains at a high level (close to 0.85Mbps). This means that the method of the present invention has good robustness to the positioning error of the interference source. In practical applications, even if the positioning accuracy is subject to certain limitations, 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 positioning errors is emphasized through text annotation in the chart, highlighting its advantages in practical applications.

[0135] Example 3: Time-varying performance of spectrum efficiency of elastic polarization switching in dynamic interference scenarios.

[0136] Experimental Purpose: This experiment aims to examine the adaptability of the proposed flexible polarization switching method in dynamic interference scenarios. Dynamic interference scenarios more realistically reflect the characteristics of complex electromagnetic environments. Spectral efficiency is a comprehensive indicator that reflects a communication system's ability to effectively utilize spectrum resources and is more closely aligned with practical application requirements.

[0137] Experimental scenario and parameters: Similar to Example 1, the main change is the dynamic change of the interference source location.

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

[0139] like Figure 4-Figure 8 The figure shows a comparison of the time-varying spectrum efficiency performance of fixed vertical polarization and the flexible polarization switching method of the present invention in a dynamic interference scenario. It can be seen that the flexible polarization switching method of the present invention can track the changes in the location of the interference source in real time and dynamically adjust the polarization mode. The spectrum efficiency is always higher than that of the fixed vertical polarization method, demonstrating good adaptability to dynamic environments.

[0140] Experimental results show that in dynamic interference scenarios, the spectrum efficiency of the elastic polarization switching (EPS) method proposed in the present invention is always significantly higher than that of the fixed vertical polarization (VP) method. The spectrum efficiency of the fixed vertical polarization method fluctuates at a low level and cannot effectively adapt to dynamically changing interference. However, the EPS method of the present invention can track the changes in the position of the interference source in real time and dynamically adjust the polarization mode, maintaining the spectrum efficiency at a high and stable level, fully demonstrating the dynamic adaptability and spectrum efficiency advantages of the method of the present invention in dynamic and complex electromagnetic environments. The dynamic adaptability of the method of the present invention is emphasized through text annotations in the chart, further highlighting its value in practical applications.

[0141] Compared with the existing technology, the flexible switching method of dual-polarized antennas for UAVs based on spatial positioning of interference sources proposed in the present invention has the following significant beneficial effects and advantages:

[0142] The present invention introduces the spatial location information of the interference source into the anti-interference design of the UAV communication system. Unlike previous passive anti-interference methods that rely solely 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 flexible switching, which is the basis for achieving precise interference suppression.

[0143] This method intelligently determines the optimal operating mode for a drone's dual-polarized antenna based on the spatial location of interference sources. The algorithm selects the most appropriate polarization mode based on different interference scenarios and interference source locations, achieving maximum interference suppression and ensuring the desired signal reception quality.

[0144] The present invention uses flexible polarization switching technology, enabling flexible, rapid, and smooth switching to the optimal polarization mode based on the optimal polarization mode decision. This flexible switching approach, unlike traditional hard switching, allows for more refined utilization of polarization resources, improving system performance.

[0145] The present invention integrates a UAV anti-interference communication system that integrates an interference source spatial positioning module, an optimal polarization mode decision module, and a flexible polarization switching module, forming a complete UAV anti-interference system. This system provides intelligent, automated, and adaptive anti-interference capabilities, significantly improving the reliability and stability of UAV communications in complex electromagnetic environments.

[0146] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection 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's dual-polarized antenna array and the UAV's position information are calculated to obtain the spatial position 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, and the process includes: estimating 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; Selecting the polarization mode with the highest interference suppression ratio and outputting the optimal polarization mode control instruction; Based on the optimal polarization mode control instruction, 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, querying 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.

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 converting the analog signal to obtain a digital signal; An arrival angle estimation algorithm is used 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 flexible switching method 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. A flexible switching system for dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources, used to implement the method according to any one of claims 1 to 3, 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; UAV-based platform, used to provide flight platform and energy supply.

5. The flexible switching system for dual-polarized antennas of unmanned aerial vehicles based on spatial positioning of interference sources according to claim 4 is characterized in that: The UAV-mounted 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 and issue a polarization mode control instruction; The polarization switching control module is used to control the dual-polarized antenna to switch to the optimal polarization mode based on the polarization mode control instruction signal; The communication module is used to realize wireless communication between the UAV and the ground station.

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