Broadband multimode antenna suitable for unmanned aerial vehicle countering scene

Abstract

The invention relates to the technical field of antennas, in particular to a broadband multimode antenna suitable for an unmanned aerial vehicle countering scene, which comprises an environment sensing and frequency band scanning module, a mode adaptive selection module, a reflection path optimization module, a multimode cooperative enhancement module and a feedback adjustment module. Automatic identification and tracking of multi-band and multi-protocol unmanned aerial vehicle signals in a complex electromagnetic environment are achieved, intelligent switching between an omnidirectional search mode and a directional strike mode can be achieved according to actual scene requirements, and the optimal radiation performance of the antenna is always kept through closed-loop regulation and control in the countering process. And the action distance, the accuracy and the anti-interference capability of the countering system are improved.

Description

Technical Field

[0001] This invention relates to the field of antenna technology, and in particular to a wideband multimode antenna suitable for UAV countermeasure scenarios. Background Technology

[0002] In recent years, with the popularization and widespread application of drone technology, the threat posed by unauthorized "black flight" drones to public safety, privacy protection, and critical infrastructure has become increasingly serious. Against this backdrop, efficient and reliable drone countermeasure technology has become a research hotspot, with the countermeasure antenna being a core component whose performance directly determines the overall effectiveness of the system. Traditional countermeasure systems often employ single-band or fixed-mode antennas based on structures such as Yagi antennas, which have significant limitations: narrow operating bandwidth, making it difficult to fully cover the diverse communication frequency bands of mainstream drones; lack of mode flexibility, poor adaptability in complex electromagnetic environments, and inability to simultaneously meet the needs of wide-area search and long-range precise directional countermeasures. Therefore, developing an antenna system capable of achieving wide-band coverage, intelligent mode switching, and good environmental adaptability has become a key technical problem that urgently needs to be solved to improve drone countermeasure capabilities. Summary of the Invention

[0003] This invention overcomes the shortcomings of the prior art and provides a wideband multimode antenna suitable for UAV countermeasure scenarios.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: This invention discloses a wideband multimode antenna suitable for UAV countermeasure scenarios, including an environmental perception and frequency band scanning module, a mode adaptive selection module, a reflection path optimization module, a multimode cooperative enhancement module, and a feedback adjustment module; The environmental perception and frequency band scanning module scans the electromagnetic environment in real time, detects the communication frequency band characteristics of the UAV in the target airspace, and identifies the communication protocol type. The mode adaptive selection module adjusts the electromagnetic response parameters of the open resonant ring unit according to the detected UAV communication characteristics, so that the antenna system can adaptively switch between omnidirectional search mode and directional enhancement mode. The reflection path optimization module controls the signal reflection path of the reflector based on the current operating mode, and optimizes the radiation directivity and bandwidth coverage of the antenna by combining the impedance adjustment of the matching slot. In directional mode, the multi-mode collaborative enhancement module coordinates the electromagnetic coupling between the directional oscillator and the open resonant ring unit to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. The feedback adjustment module adjusts the matching slot parameters and reflector phase of the antenna system according to the real-time changes in the UAV signal to maintain the optimal countermeasure effect.

[0005] Furthermore, the electromagnetic environment is scanned in real time to detect the communication frequency band characteristics of UAVs within the target airspace and identify the communication protocol type, specifically: The target spatial domain is continuously sensed by a broadband receiving front-end to obtain raw spectrum data; the raw spectrum data is preprocessed and subjected to fast Fourier transform to generate frequency domain feature vectors. Based on the frequency domain feature vector, the center frequency, bandwidth, and amplitude features of the signal peak are extracted; the center frequency is matched with a preset UAV frequency band knowledge base to identify potential UAV signals; The potential UAV signal is demodulated and analyzed to obtain the modulation index, symbol rate and time-domain pulse characteristics; The time-domain pulse features are matched with the protocol fingerprint feature library using the spectral correlation density function. When the matching degree exceeds the preset matching degree threshold, it is determined to be a specific UAV communication protocol type. Finally, the identification result containing frequency band features and protocol type is output.

[0006] Furthermore, based on the detected UAV communication characteristics, the electromagnetic response parameters of the open-loop resonator are adjusted to enable the antenna system to adaptively switch between omnidirectional search mode and directional enhancement mode, specifically: The system queries the preset protocol-mode mapping database based on the protocol type to obtain the initial mode priority parameters corresponding to the protocol; at the same time, it extracts the corresponding frequency band sensitivity factor based on the frequency band range where the center frequency point is located. The initial mode priority parameter and the frequency band sensitivity factor are input into the mode decision matrix and weighted to obtain the mode fitness score. The pattern fitness score is compared with a preset threshold value. When the pattern fitness score is lower than the preset threshold value, an omnidirectional search pattern identifier is generated. When the pattern fitness score is equal to or higher than the preset threshold value, a directional enhancement pattern identifier is generated. The pattern identifier includes a pattern type code, a pattern confidence index, and a frequency band adaptation coefficient. The pattern confidence index is obtained by normalizing the difference between the pattern fitness score and a preset threshold value, and the frequency band adaptation coefficient is derived from the weighted calculation result of the frequency band sensitivity factor.

[0007] Furthermore, based on the current operating mode, the signal reflection path of the reflecting element is controlled, and combined with the impedance adjustment of the matching slot, the radiation directivity and bandwidth coverage of the antenna are optimized, specifically: The initial phase offset vector of each reflecting oscillator is obtained by querying the preset radiation mode-phase mapping table according to the mode type code. The reflection path compensation factor is determined based on the frequency band adaptation coefficient. The initial phase offset vector is weighted and calculated with the reflection path compensation factor to generate a reflection unit excitation scheme containing the amplitude and phase parameters of each reflection unit. The phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit, and the corresponding phase offset is applied to each reflector to form the phase gradient required for beamforming. Meanwhile, based on the frequency band adaptation coefficient, the impedance-frequency band correspondence database is queried to obtain the initial impedance matching parameters of the matching slot, and the impedance correction is calculated in combination with the reflection path compensation factor to obtain the final impedance adjustment value. Based on the final impedance adjustment value, the capacitance value of the variable capacitor element in the matching slot is adjusted by the digital control circuit to achieve the tuning of the impedance matching network. Finally, the optimization effect of radiation directivity and frequency band coverage was verified by monitoring the voltage standing wave ratio characteristics of the antenna input port.

[0008] Specifically, the phase offset to be applied to each reflecting element is determined according to the excitation scheme of the reflecting unit, and a corresponding phase offset is applied to each reflecting element to form the phase gradient required for beamforming, as follows: Extract the target phase parameters of each reflecting oscillator in the excitation scheme of the reflecting unit, compare the target phase parameters with the current phase state, and calculate the original phase offset difference; The phase offset difference is corrected by amplitude weighting based on the amplitude parameters of the reflection unit to generate the phase offset of each oscillator. The phase offset is converted into control code for a programmable phase shifter array, wherein the generation of the control code requires combining the phase quantization step and calibration lookup table of the phase shifter; The control code is sent to the phase shifter array drive circuit through the serial peripheral interface, and the corresponding phase offset is applied to each reflecting oscillator to form the required wavefront phase distribution.

[0009] Furthermore, in directional mode, the electromagnetic coupling between the guiding oscillator and the open resonant ring unit is coordinated to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. Specifically: Based on the frequency band adaptation coefficient and mode confidence index in the received mode identifier, the preset coupling parameter configuration library is queried to obtain the initial phase offset of the oscillator unit and the reference bias voltage of the open resonator. Based on the frequency band adaptation coefficient and the reference bias voltage, the gradient descent optimization algorithm is used to calculate the optimal bias voltage adjustment for each resonant ring unit, generating an optimized bias voltage sequence. Based on the initial phase offset and the bias voltage optimization sequence, the phase compensation value directed to the oscillator is calculated by phase weighting, where the phase weighting needs to be combined with the oscillator spacing factor and the frequency-wavelength ratio parameter. The phase compensation value is converted into a digital phase control word and sent to the digital phase shifter array that guides the oscillator via a serial interface. The bias voltage optimization sequence is converted into an analog voltage signal and then loaded onto the varactor diodes of each open-loop resonant ring via a digital-to-analog converter. Based on real-time monitored forward gain and sidelobe level data, the electromagnetic coupling efficiency index is calculated, and the bias voltage optimization sequence and phase compensation value are iteratively optimized according to the electromagnetic coupling efficiency index to achieve adaptive closed-loop control of electromagnetic coupling parameters.

[0010] Specifically, based on real-time monitored radiation pattern forward gain and sidelobe level data, an electromagnetic coupling effectiveness index is calculated, and the bias voltage optimization sequence and phase compensation value are iteratively optimized according to the electromagnetic coupling effectiveness index, as follows: The ratio of forward gain to sidelobe level is calculated as an electromagnetic coupling effectiveness index. The electromagnetic coupling effectiveness index is input into the Lyapunov exponential prediction model. By solving the eigenvalues ​​of the Jacobian matrix of the system state equation, the system stability prediction index is calculated. The system stability prediction index is compared with the preset stability threshold. When the system stability prediction index is greater than the preset stability threshold, an optimization step size adjustment coefficient is generated. The bias voltage optimization sequence is subjected to gradient descent operation based on the optimization step size adjustment coefficient to generate a set of bias voltage correction values; at the same time, the system stability prediction index is convolved with the phase compensation value to obtain the phase compensation correction factor. Based on the bias voltage correction set and the phase compensation correction factor, a weighted fusion algorithm is used to generate a new bias voltage optimization sequence and phase compensation value; After applying the new parameter set to the antenna system, the radiation pattern data is reacquired and the Lyapunov exponential rate of change is calculated. The iteration stops when the rate of change is less than the convergence threshold; otherwise, the optimization process continues with the new parameter set as input.

[0011] Furthermore, based on the real-time changes in the UAV signal, the matching slot parameters and the phase of the reflecting element of the antenna system are adjusted to maintain the optimal countermeasure effect, specifically as follows: Real-time monitoring of the intensity change rate and frequency drift of UAV signals yields signal stability indices. The signal stability index is compared with a preset threshold, and an adaptive adjustment coefficient is generated when the preset threshold is exceeded. The initial impedance adjustment amount of the matching slot and the reference phase compensation value of the reflecting oscillator are obtained by querying the preset impedance-phase joint adjustment mapping table according to the adaptive adjustment coefficient. The frequency drift is weighted by the initial impedance adjustment to generate an impedance correction factor; simultaneously, the signal strength change rate is convolved with the reference phase compensation value to obtain the phase adjustment. The digital control code for the matching slot is obtained by querying the preset variable capacitor control code table according to the impedance correction factor; and the phase offset instruction set required for the reflecting oscillator is determined according to the phase adjustment amount. Digital control code is loaded into the variable capacitor array of the matching slot through a digital control circuit, while a phase offset instruction set is applied to the reflector array through a phase controller. Finally, the voltage standing wave ratio and main lobe width of the antenna system are monitored in real time. When the rate of change of the main lobe width exceeds the tolerance value, the signal stability index is recalculated and a new adjustment cycle is started.

[0012] It also includes an antenna structure, which adopts a multi-layer composite substrate design. The substrate includes an upper first panel and a lower second panel. An active vibrator is disposed on the first panel, and a first reflector is disposed on the second panel. The active vibrator and the first reflector are connected by metal vias.

[0013] Above the active element, multiple guiding elements are arranged along the width of the first panel to enhance the antenna directivity. A second reflecting element is added below the first reflecting element to optimize the signal reflection path. A microstrip line is arranged in the middle of the first reflecting element for power feeding. Matching slots are arranged on both sides of the microstrip line. By adjusting the size and shape of the matching slots, the antenna bandwidth is increased.

[0014] This invention addresses the technical deficiencies in the prior art and has the following beneficial effects: It achieves wideband signal coverage, adaptive switching between omnidirectional and directional modes, and electromagnetic interference suppression, thereby improving the compatibility of the antenna system with different UAV communication protocols and its countermeasure effectiveness in complex electromagnetic environments. It also expands the operating frequency range and enhances the detection and jamming capabilities against various types of UAVs. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0016] Figure 1 This is a block diagram of the module structure of this broadband multimode antenna; Figure 2 This is a simplified flowchart of the operation of this broadband multimode antenna. Detailed Implementation

[0017] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0019] like Figure 1 , 2 As shown, this invention discloses a wideband multimode antenna suitable for UAV countermeasure scenarios, including an environmental perception and frequency band scanning module, a mode adaptive selection module, a reflection path optimization module, a multimode cooperative enhancement module, and a feedback adjustment module; The environmental perception and frequency band scanning module scans the electromagnetic environment in real time, detects the communication frequency band characteristics of the UAV in the target airspace, and identifies the communication protocol type. The mode adaptive selection module adjusts the electromagnetic response parameters of the open resonant ring unit according to the detected UAV communication characteristics, so that the antenna system can adaptively switch between omnidirectional search mode and directional enhancement mode. The reflection path optimization module controls the signal reflection path of the reflector based on the current operating mode, and optimizes the radiation directivity and bandwidth coverage of the antenna by combining the impedance adjustment of the matching slot. In directional mode, the multi-mode collaborative enhancement module coordinates the electromagnetic coupling between the directional oscillator and the open resonant ring unit to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. The feedback adjustment module adjusts the matching slot parameters and reflector phase of the antenna system according to the real-time changes in the UAV signal to maintain the optimal countermeasure effect.

[0020] It should be noted that this invention achieves functions such as wideband signal coverage, adaptive switching between omnidirectional and directional modes, and electromagnetic interference suppression, thereby improving the compatibility of the antenna system with different UAV communication protocols and the countermeasure effectiveness in complex electromagnetic environments, expanding the operating frequency range, and enhancing the detection and jamming capabilities against multiple types of UAVs.

[0021] Furthermore, the electromagnetic environment is scanned in real time to detect the communication frequency band characteristics of UAVs within the target airspace and identify the communication protocol type, specifically: The target spatial domain is continuously sensed by a broadband receiving front-end to obtain raw spectrum data; the raw spectrum data is preprocessed and subjected to fast Fourier transform to generate frequency domain feature vectors; wherein, the raw spectrum data contains key feature information such as signal power, center frequency, bandwidth and amplitude. Based on the frequency domain feature vector, the center frequency, bandwidth, and amplitude features of the signal peak are extracted; the center frequency is matched with a preset UAV frequency band knowledge base to identify potential UAV signals; The preset drone frequency band knowledge base is a pre-built structured database stored in the system memory. It integrates common drone operating frequency bands (such as the 2.4GHz and 5.8GHz ISM bands, as well as other bands such as 1.2GHz and 900MHz that specific manufacturers may use), and associates each frequency band entry with corresponding frequency boundary values, typical bandwidth values, and possible channel allocation information. When the module extracts the center frequency of a signal, it can quickly determine whether the frequency falls within the known range of commonly used drone frequency bands by querying the knowledge base, thereby completing the preliminary screening and classification of potential drone signals and effectively filtering out non-target interference signals in the same frequency band, such as Wi-Fi and Bluetooth.

[0022] The potential UAV signal is demodulated and analyzed to obtain the modulation index, symbol rate and time-domain pulse characteristics; The time-domain pulse features are matched with the protocol fingerprint feature library using the spectral correlation density function. When the matching degree exceeds a preset matching degree threshold (e.g., 0.9), it is determined to be a specific UAV communication protocol type. The final output is the identification result containing frequency band features and protocol type.

[0023] It should be noted that the original spectrum data undergoes preprocessing (such as filtering and noise reduction) and Fast Fourier Transform (FFT) to convert it into a frequency domain feature vector. Based on the generated frequency domain feature vector, key features such as the center frequency, bandwidth, and amplitude of the signal peaks are extracted. Subsequently, the extracted center frequency is matched with a preset UAV frequency band knowledge base to initially screen potential UAV signals. This step effectively narrows the identification range, improves processing efficiency, and avoids unnecessary in-depth analysis of non-target signals, which is crucial for ensuring the real-time performance of the system. The initially screened potential UAV signals are further demodulated and analyzed to obtain deeper information such as their modulation index, symbol rate, and time-domain pulse characteristics. This is because different manufacturers and models of UAVs typically use different communication protocols, and these protocols have unique "fingerprints" in terms of modulation methods, frame structures, and timing, which cannot be accurately identified based solely on frequency domain information. Finally, the parsed time-domain pulse features are matched with the pre-built protocol fingerprint feature library using the spectral correlation density function (SCD). When the matching degree exceeds the preset threshold, it can be determined as a specific UAV communication protocol type, and the final identification result containing accurate frequency band features and protocol type is output.

[0024] Furthermore, based on the detected UAV communication characteristics, the electromagnetic response parameters of the open-loop resonator are adjusted to enable the antenna system to adaptively switch between omnidirectional search mode and directional enhancement mode, specifically: The system queries the preset protocol-mode mapping database based on the protocol type to obtain the initial mode priority parameters corresponding to the protocol; at the same time, it extracts the corresponding frequency band sensitivity factor based on the frequency band range where the center frequency point is located. The initial mode priority parameter and the frequency band sensitivity factor are input into the mode decision matrix and weighted to obtain the mode fitness score. The pattern fitness score is compared with a preset threshold value. When the pattern fitness score is lower than the preset threshold value, an omnidirectional search pattern identifier is generated; when the pattern fitness score is equal to or higher than the preset threshold value, a targeted enhancement pattern identifier is generated. The preset threshold value is specifically selected and adjusted within a normalized range of 0.5 to 0.8. For example, in a preferred embodiment, the preset threshold value can be initially set to 0.6. The pattern identifier includes a pattern type code, a pattern confidence index, and a frequency band adaptation coefficient. The pattern confidence index is obtained by normalizing the difference between the pattern fitness score and a preset threshold value, and the frequency band adaptation coefficient is derived from the weighted calculation result of the frequency band sensitivity factor.

[0025] In practice, based on the identified UAV communication protocol type, a pre-defined protocol-mode mapping database is queried. This database, built upon extensive experimental data, defines the optimal antenna operating mode preference (i.e., initial mode priority parameter) for different communication protocols (such as Wi-Fi, image transmission, and specific vendor-specific protocols). Simultaneously, based on the signal's center frequency, a frequency band sensitivity factor is extracted from another database. This factor reflects the sensitivity of antenna directivity to signal gain at different frequency bands. This dual-query mechanism is employed because decision-making based solely on protocol type or frequency band may be inaccurate; for example, while a certain protocol typically requires directional countermeasures, omnidirectional search might be more prioritized at low frequencies (with strong diffraction capabilities) or when the signal is extremely weak. Therefore, the initial mode priority parameter and the frequency band sensitivity factor are input together into a pre-defined mode decision matrix for weighted calculation, resulting in a quantitative and comprehensive mode fitness score.

[0026] Subsequently, the calculated mode fitness score is compared with a preset threshold. If the score is below the threshold, an omnidirectional search mode identifier is generated, and the antenna prioritizes 360-degree coverage to continue searching for or tracking uncertain targets. If the score is equal to or higher than the threshold, a directional enhancement mode identifier is generated, and the antenna concentrates energy in one-dimensional space for precise and powerful countermeasures. The final generated mode identifier is not a simple instruction, but a dataset containing mode type encoding, mode confidence index (obtained by normalizing the difference between the score and the threshold, reflecting the credibility of this decision), and frequency band adaptation coefficients. This allows subsequent modules (such as reflection path optimization and multi-mode cooperative enhancement) to not only know the target mode but also obtain the frequency band characteristics of this decision, thereby enabling more refined adjustments to cooperative parameters.

[0027] Furthermore, based on the current operating mode, the signal reflection path of the reflecting element is controlled, and combined with the impedance adjustment of the matching slot, the radiation directivity and bandwidth coverage of the antenna are optimized, specifically: The initial phase offset vector of each reflecting oscillator is obtained by querying the preset radiation mode-phase mapping table according to the mode type code. The reflection path compensation factor is determined based on the frequency band adaptation coefficient. The initial phase offset vector is weighted and calculated with the reflection path compensation factor to generate a reflection unit excitation scheme containing the amplitude and phase parameters of each reflection unit. It is worth mentioning here that the frequency band adaptation coefficient is a normalized parameter that quantifies the deviation between the current operating frequency and the antenna center frequency, and its value reflects the impact of electrical size changes on the wavefront. First, based on the specific operating frequency corresponding to the frequency band adaptation coefficient, and combined with the physical layout parameters of the antenna array (such as element spacing and arrangement), the path difference phase error caused by frequency changes is calculated in real time, thereby determining the reflection path compensation factor. The reflection path compensation factor is essentially a set of phase correction values ​​calculated individually for each reflection element, used to compensate for beam pointing deviation and focusing defocus caused by frequency offset. Subsequently, the real-time calculated reflection path compensation factor is weighted and fused with the initial phase offset vector obtained from a preset database. The weighting strategy is adjusted based on the requirements of the current operating mode; for example, in directional mode, more emphasis is placed on the accuracy of the compensation factor to maintain beam sharpness. Finally, a reflection element excitation scheme that fully adapts to the current real-time operating frequency and mode requirements is generated. This scheme precisely specifies the amplitude and phase parameters of each element, providing control data for achieving precise beamforming.

[0028] The phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit, and the corresponding phase offset is applied to each reflector to form the phase gradient required for beamforming. Meanwhile, based on the frequency band adaptation coefficient, the impedance-frequency band correspondence database is queried to obtain the initial impedance matching parameters of the matching slot, and the impedance correction is calculated in combination with the reflection path compensation factor to obtain the final impedance adjustment value. It should be noted that, firstly, the phase offset of each reflecting element (derived from the reflection path compensation factor) is mapped to an equivalent reactance disturbance component on the overall input impedance of the antenna system. Then, this equivalent reactance disturbance component is vector-superimposed with the initial impedance matching parameters obtained by querying the impedance-frequency band correspondence library. During superposition, a frequency-varying weighting coefficient is automatically introduced based on the characteristics of the current operating frequency band to correct for differences in the sensitivity of phase changes to impedance at different frequencies. Finally, the superposition result is normalized and converted into an equivalent capacitance control value for the variable capacitor element, thus obtaining the final impedance adjustment value used for precise tuning and matching network.

[0029] Based on the final impedance adjustment value, the capacitance value of the variable capacitor element in the matching slot is adjusted by the digital control circuit to achieve the tuning of the impedance matching network. Finally, the optimization effect of radiation directivity and frequency band coverage was verified by monitoring the voltage standing wave ratio characteristics of the antenna input port.

[0030] Specifically, the phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit, and a corresponding phase offset is applied to each reflector unit to form the phase gradient required for beamforming. This involves: extracting the target phase parameters of each reflector unit in the excitation scheme; comparing the target phase parameters with the current phase state to calculate the original phase offset difference; performing amplitude-weighted correction on the phase offset difference based on the reflector unit amplitude parameters to generate the phase offset of each reflector unit; converting the phase offset into control code for a programmable phase shifter array, wherein the generation of the control code requires combining the phase quantization step and calibration lookup table of the phase shifter; and sending the control code to the phase shifter array drive circuit through a serial peripheral interface to apply a corresponding phase offset to each reflector unit, forming the required wavefront phase distribution.

[0031] It should be noted that traditional antenna systems often fall short in complex UAV countermeasure scenarios requiring frequent switching between omnidirectional search and directional strike modes, and involving targets in various frequency bands. Their performance is often inadequate, either lacking sufficient search range or insufficient gain and bandwidth during directional strikes. This solution proposes a software-defined, real-time reconfigurable mechanism for joint control of the reflector and impedance. The specific implementation process is as follows: When the module receives the mode type code (e.g., indicating that it needs to switch to "directional enhancement mode") and frequency band adaptation coefficient (e.g., indicating that the current target signal is located in the 5.8 GHz band) from the upper-level decision system, it first queries a radiation mode-phase mapping table that has been pre-calibrated through electromagnetic simulation and field measurements based on the mode type code. This mapping table stores the initial phase offset vectors of each reflecting element required to achieve a specific radiation pattern (such as a pencil beam with a high front-to-back ratio). This is because different radiation modes have different requirements for the shape of the wavefront, and a specific phase value must be assigned to each reflecting element.

[0032] Next, a reflection path compensation factor is determined based on the frequency band adaptation coefficient to correct beam pointing offset and shape distortion caused by changes in operating frequency. Because the electrical dimensions of antenna elements change with frequency, their phase centers and mutual coupling relationships also change; a fixed phase setting cannot form an optimal beam across all frequency bands. By weighting the initial phase offset vector with the reflection path compensation factor, a precise reflection element excitation scheme adapted to the current frequency is generated. This scheme includes the specific amplitude and phase parameters required to drive each reflector.

[0033] Then, the phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit. Specifically, the target phase parameter of each reflector in the scheme is extracted and compared with the current phase state of each reflector fed back by the sensor to calculate the original phase offset difference. To further improve accuracy, the phase offset difference is also corrected by amplitude weighting based on the amplitude parameter of the reflector unit (because a large amplitude excitation unit has a greater weight in the overall beam), thus generating the final phase offset to be applied to each reflector unit. Subsequently, these digitized offsets are converted into control code for the programmable phase shifter array. The generation of the control code is not a simple conversion; it also requires combining the phase quantization step of the phase shifter itself (e.g., 5.625°) and a pre-stored calibration lookup table to compensate for the nonlinear error and channel inconsistency of the phase shifter device, ensuring the accuracy of phase control. Finally, the control code is sent to the drive circuit of the phase shifter array through a serial peripheral interface, thereby applying independent phase control to each reflector unit, ultimately forming a precise phase gradient on all reflector units and synthesizing a strong directional beam pointing towards the target direction.

[0034] Furthermore, while adjusting the phase, coordinated impedance matching is crucial. When the antenna's operating frequency changes, its input impedance changes. Failure to adjust this will lead to severe mismatch, preventing effective energy radiation, even with a correct beamform. Therefore, the system queries an impedance-frequency band correspondence database based on the same frequency band adaptation coefficient to obtain the initial impedance matching parameters for the matching slot in the current frequency band. Similarly, this parameter needs to be combined with the reflection path compensation factor for impedance correction calculation (because changes in the phase state of the reflection element also slightly affect the input impedance) to obtain the final impedance adjustment value. Based on the final value, the capacitance of the variable capacitor element (such as a varactor diode) in the matching slot is adjusted via a digital control circuit (e.g., through an I²C interface) to achieve dynamic tuning of the impedance matching network, ensuring that its input port remains in a good matching state (low VSWR) even when the antenna's operating state changes drastically.

[0035] Finally, the effectiveness of this joint modulation can be quantitatively verified by monitoring the voltage standing wave ratio (VSWR) characteristics at the antenna input port in real time. If the VSWR remains at a low level (e.g., less than 1.5) and the main lobe gain of the radiation pattern reaches the expected level, then the optimization is considered successful.

[0036] In summary, through the aforementioned closed-loop control process involving both hardware and software, this invention achieves synchronous adaptive optimization of antenna radiation characteristics (directivity) and circuit characteristics (bandwidth, efficiency), solving the problem of insufficient performance of traditional fixed antennas in complex and ever-changing UAV countermeasure scenarios, and improving the effective range and signal interference efficiency of the countermeasure system.

[0037] Furthermore, in directional mode, the electromagnetic coupling between the guiding oscillator and the open resonant ring unit is coordinated to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. Specifically: Based on the frequency band adaptation coefficient and mode confidence index in the received mode identifier, the preset coupling parameter configuration library is queried to obtain the initial phase offset of the oscillator unit and the reference bias voltage of the open resonator. Based on the frequency band adaptation coefficient and the reference bias voltage, the gradient descent optimization algorithm is used to calculate the optimal bias voltage adjustment for each resonant ring unit, generating an optimized bias voltage sequence. Based on the initial phase offset and the bias voltage optimization sequence, the phase compensation value directed to the oscillator is calculated by phase weighting, where the phase weighting needs to be combined with the oscillator spacing factor and the frequency-wavelength ratio parameter. The phase compensation value is converted into a digital phase control word and sent to the digital phase shifter array that guides the oscillator via a serial interface. The bias voltage optimization sequence is converted into an analog voltage signal and then loaded onto the varactor diodes of each open-loop resonant ring via a digital-to-analog converter. Based on real-time monitored forward gain and sidelobe level data, the electromagnetic coupling efficiency index is calculated, and the bias voltage optimization sequence and phase compensation value are iteratively optimized according to the electromagnetic coupling efficiency index to achieve adaptive closed-loop control of electromagnetic coupling parameters.

[0038] Specifically, based on real-time monitored forward gain and sidelobe level data of the radiation pattern, an electromagnetic coupling effectiveness index is calculated. The bias voltage optimization sequence and phase compensation value are then iteratively optimized according to this index. Specifically, the ratio of forward gain to sidelobe level is calculated as the electromagnetic coupling effectiveness index. This index is input into a Lyapunov exponential prediction model. By solving for the eigenvalues ​​of the Jacobian matrix in the system state equation, a system stability prediction index is calculated. This index is then compared with a preset stability threshold (e.g., 1.0). When the system stability prediction index is greater than the preset threshold, an optimization is generated. Step size adjustment coefficient; gradient descent operation is performed on the bias voltage optimization sequence based on the optimized step size adjustment coefficient to generate a bias voltage correction set; simultaneously, the system stability prediction index and the phase compensation value are convolved to obtain the phase compensation correction factor; based on the bias voltage correction set and the phase compensation correction factor, a weighted fusion algorithm is used to generate a new bias voltage optimization sequence and phase compensation value; after applying the new parameter set to the antenna system, the radiation pattern data is reacquired and the Lyapunov exponent change rate is calculated. When the change rate is less than the convergence threshold (e.g., 0.02 / s), the iteration stops; otherwise, the optimization process continues with the new parameter set as input.

[0039] In practice: Upon receiving the mode identifier, a pre-defined coupling parameter configuration library is first queried. This library stores the initial phase offset of the director element and the reference bias voltage of the open resonator for different frequency bands and confidence levels. Then, with the core optimization objectives of improving target direction gain and suppressing sidelobes, the optimal bias voltage adjustment for each resonator element is calculated using a gradient descent optimization algorithm based on the frequency band adaptation coefficient and the reference bias voltage. The gradient descent algorithm determines the adjustment direction that maximizes performance improvement by calculating the gradient of the current pattern performance index (such as gain) relative to the bias voltage of each resonator, thus generating a bias voltage optimization sequence. Simultaneously, based on the initial phase offset and this optimization sequence, the phase compensation value of the director is calculated using phase weighting. This phase weighting is not a simple linear superposition but a comprehensive calculation combining the oscillator spacing factor and the frequency-to-wavelength ratio parameter to ensure that the correction of the director phase accurately compensates for electromagnetic coupling disturbances caused by changes in the resonator state, maintaining wavefront consistency.

[0040] Then, a digital-to-analog conversion is performed: the phase compensation value is converted into a digital phase control word and sent to the digital phase shifter array of the director oscillator through a serial interface, thereby precisely controlling the phase of each director; at the same time, the bias voltage optimization sequence is converted into an analog voltage signal and loaded onto the varactor diodes of each open-loop resonator through a digital-to-analog converter, thereby changing the resonance characteristics of each resonator and regulating the electromagnetic coupling strength between it and the director.

[0041] Most importantly, the system calculates an electromagnetic coupling effectiveness index (such as the ratio of forward gain to sidelobe level) based on real-time monitored radiation pattern forward gain and sidelobe level data. This index is then input into the Lyapunov exponential prediction model, and the system stability prediction index is calculated by solving the eigenvalues ​​of the Jacobian matrix in the system state equation. This mathematically predicts whether the system will converge or diverge after parameter adjustments. If the prediction index indicates potential system instability (greater than a preset threshold), an optimization step size adjustment coefficient is generated, automatically reducing the gradient descent step size to ensure a smooth optimization process. Subsequently, a new round of gradient descent calculation is performed on the bias voltage optimization sequence based on this coefficient, generating a set of correction values. The stability prediction index is then convolved with the phase compensation value to obtain the phase compensation correction factor. Finally, a new, better parameter set is generated using weighted fusion and applied to the antenna. It is also worth mentioning that the system continuously re-acquires radiation pattern data and calculates the Lyapunov exponential rate of change until the rate of change is less than the convergence threshold, indicating that the system has reached a stable optimal state. This enables self-optimization of the antenna pattern in directional mode, improves the main lobe gain and effectively suppresses side lobes and interference, making the energy of the UAV counter-signal more concentrated and pure, and enhancing the effective range of the system and its robustness in complex electromagnetic environments.

[0042] Furthermore, based on the real-time changes in the UAV signal, the matching slot parameters and the phase of the reflecting element of the antenna system are adjusted to maintain the optimal countermeasure effect, specifically as follows: Real-time monitoring of the intensity change rate and frequency drift of UAV signals yields signal stability indices. It should be noted that the time-domain IQ data and frequency-domain spectrum of the target signal are continuously acquired by a broadband receiver and a spectrum analysis unit. First-order difference operations are performed on the signal power sequence within a continuous time window, and the moving average of the absolute values ​​is used to obtain the intensity change rate. Simultaneously, by tracking the center frequency of the main peak of the signal spectrum, the difference in center frequencies between adjacent time windows is calculated to obtain the frequency drift. Subsequently, the intensity change rate and frequency drift are normalized to eliminate the influence of dimensions. Finally, the two normalized parameters are linearly weighted and fused according to preset weighting coefficients to generate a comprehensive signal stability index. A higher index value indicates a more unstable signal, requiring the activation of an adaptive control mechanism.

[0043] The signal stability index is compared with a preset threshold, and an adaptive adjustment coefficient is generated when the preset threshold is exceeded. It is important to note that setting the preset threshold is crucial, as it determines whether the system initiates adaptive adjustment. Its specific value needs to be calibrated based on the system's response speed, antenna reconfiguration capability, and typical UAV maneuvering characteristics. In a preferred embodiment, the preset threshold can be set within a normalized value range of 0.3 to 0.4 (e.g., 0.35). When the stability index exceeds this threshold, it indicates that the target signal change has been drastic enough to render the current antenna configuration ineffective, and the system then generates an adaptive adjustment coefficient.

[0044] The real-time calculated signal stability index (denoted as S) is compared with the preset threshold (denoted as S). threshold = 0.35) for comparison. When S is greater than S threshold When this occurs, the adjustment mechanism is triggered. The specific calculation of the adaptive adjustment coefficient K uses the following exponential function relationship: Where e is the natural constant, This represents the magnitude by which the indicator exceeds the threshold. This exponential function ensures that when signal stability deteriorates slightly (e.g., S=0.4, K≈0.75), the adjustment range is relatively gentle to avoid system over-response; while when the signal changes drastically (e.g., S=0.6, K≈1.64), the adjustment coefficient increases significantly, driving subsequent circuits to generate larger impedance and phase adjustments, thereby quickly compensating for the effects of signal changes. The final adaptive adjustment coefficient K will serve as the core input parameter for subsequent lookup of the impedance-phase joint adjustment mapping table.

[0045] The initial impedance adjustment amount of the matching slot and the reference phase compensation value of the reflecting oscillator are obtained by querying the preset impedance-phase joint adjustment mapping table according to the adaptive adjustment coefficient. It should be noted that the impedance-phase joint adjustment mapping table stores the initial impedance adjustment of the matching slots and the reference phase compensation value of the reflecting oscillator required for rapid system performance recovery under different disturbance levels. The purpose of consulting this table is to provide a fast, coarse-tuning baseline parameter, avoiding optimization from scratch and thus shortening the response time.

[0046] The frequency drift is weighted by the initial impedance adjustment to generate an impedance correction factor; simultaneously, the signal strength change rate is convolved with the reference phase compensation value to obtain the phase adjustment. The digital control code for the matching slot is obtained by querying the preset variable capacitor control code table according to the impedance correction factor; and the phase offset instruction set required for the reflecting oscillator is determined according to the phase adjustment amount. The impedance-phase joint adjustment mapping table is a two-dimensional lookup table pre-stored in the system memory. It uses the adaptive adjustment coefficient as the input index and directly outputs the corresponding initial impedance adjustment amount and reference phase compensation value to achieve rapid coordinated control of antenna impedance matching and beam pointing.

[0047] Digital control code is loaded into the variable capacitor array of the matching slot through a digital control circuit, while a phase offset instruction set is applied to the reflector array through a phase controller. Finally, the voltage standing wave ratio and main lobe width of the antenna system are monitored in real time. When the rate of change of the main lobe width exceeds the tolerance value, the signal stability index is recalculated and a new adjustment cycle is started.

[0048] It should be noted that the adjustment effect is verified by real-time monitoring of the voltage standing wave ratio (VSWR) and the main lobe width of the radiation pattern at the antenna port. VSWR is used to assess the impedance matching status, and the main lobe width is used to assess the beam focusing degree. When the rate of change of the main lobe width is detected to be greater than a tolerance value (e.g., greater than 5% / s), it indicates that the adjustment may not have fully kept up with the target changes or introduced new distortions. The system immediately recalculates the signal stability index and starts a new adjustment cycle, thus forming a continuous, closed-loop adaptive optimization process. This ensures that the antenna system remains dynamically in the optimal countermeasure state against the target UAV throughout the entire countermeasure process.

[0049] The multimode antenna also includes an antenna structure, which adopts a multilayer composite substrate design. The substrate includes an upper first panel and a lower second panel. An active element is disposed on the first panel, and a first reflector is disposed on the second panel. The active element and the first reflector are connected by metal vias. Above the active element, multiple directional elements are disposed along the width of the first panel to enhance the antenna directivity. A second reflector is added below the first reflector to optimize the signal reflection path. A microstrip line is disposed in the middle of the first reflector for feeding, and matching slots are disposed on both sides of the microstrip line. By adjusting the size and shape of the matching slots, the antenna bandwidth is increased.

[0050] This embodiment also includes: Based on the frequency domain feature vector and protocol type of the UAV signal output by the environmental perception module, and combined with the real-time collected environmental multipath scattering parameters, an electromagnetic propagation digital twin model is constructed. The current antenna system's reflection unit excitation scheme and bias voltage optimization sequence are input into the electromagnetic propagation digital twin model to perform multi-dimensional countermeasure strategy simulation analysis, and to deduce the signal polarization synthesis process and bit error rate change trajectory of the UAV communication link under different phase gradient and impedance matching combinations. Extract the Doppler feature variation index and adaptive modulation switching response of the communication link from the simulation results to generate a channel degradation feature set; When the rate of change of any feature in the channel degradation feature set exceeds the preset agile countermeasure threshold, the corresponding countermeasure strategy is determined to be effective, and its phase gradient distribution and impedance matching parameters are recorded as the preferred strategy vector. The phase offset command set and matching slot admittance adjustment parameters of the oscillator unit are generated by reverse calculation based on the optimized strategy vector; The phase offset command set of the oscillator element and the admittance adjustment parameters of the matching slot are loaded into the physical antenna system to perform directional interference, and the interference effectiveness factor is continuously verified through the electromagnetic propagation digital twin model until the preset suppression index is reached.

[0051] It should be noted that the environmental perception module continuously scans the airspace, and its output UAV signal frequency domain feature vector (such as center frequency and bandwidth) and identified protocol types (such as Wi-Fi, image transmission, and remote control protocols) can provide the electromagnetic fingerprint of the target object for the digital twin. Simultaneously, multipath scattering parameters (such as delay spread and angle spread) in the environment are collected in real time through an auxiliary receiving channel, thereby constructing a high-fidelity electromagnetic propagation digital twin model. Subsequently, the reflection unit excitation scheme (controlling beam shape) and bias voltage optimization sequence (controlling the operating point of active devices) to be used in the current antenna system are input into this digital twin model for multi-dimensional countermeasure strategy simulation analysis. That is, multiple different phase gradient (controlling beam pointing) and impedance matching (affecting energy transmission efficiency) combination strategies are simulated in parallel in virtual space. Through simulation, the signal polarization synthesis process (how to combat interference) and its bit error rate change trajectory (communication quality degradation trend) of the UAV communication link under each strategy can be known in advance. Furthermore, from a large number of simulation results, key indicators that profoundly reflect the impact on the robustness of the communication link are extracted: the Doppler characteristic variation index (characterizing whether the signal characteristic changes caused by UAV maneuvers are aggravated by interference) and the adaptive modulation switching response (characterizing the behavior of the UAV being forced to slow down or switch coding modes to resist interference), thus constituting the channel degradation feature set. A preset agile countermeasure threshold (e.g., 0.5) is set as a decision threshold. When the rate of change of any feature in the channel degradation feature set exceeds this threshold (e.g., the bit error rate shows a sharp jump rather than a slow increase in the simulation), the corresponding countermeasure strategy is determined to be an efficient and agile effective strategy, and the phase gradient distribution and impedance matching parameters that generate this effect are immediately recorded and encapsulated into a preferred strategy vector. Then, based on this preferred strategy vector, a set of phase offset instructions for the oscillator elements (specifically controlling the phase of each antenna element) and matching slot admittance adjustment parameters (specifically adjusting the component values ​​of the impedance matching network) that can actually be executed by the physical antenna system are generated. Finally, the above instructions and parameters are loaded into the physical antenna system to execute directional interference. At the same time, the electromagnetic propagation digital twin model continuously receives state feedback from the physical system and verifies the interference effectiveness factor (such as the interference-to-signal ratio of the interference signal to the target signal) until the preset suppression index is reached (such as the complete interruption of drone communication), thereby ensuring the reliability and continuity of the countermeasure effect, thus improving the success rate and overall effectiveness of the countermeasure system and effectively dealing with the adaptive anti-interference behavior of intelligent drones.

[0052] This embodiment also includes: Based on the UAV communication protocol features (including protocol type and frequency domain feature vector) parsed by the environmental perception module, the polarization state parameters hidden in the UAV signal waveform are extracted to generate target polarization fingerprint features containing elliptic polarizability and polarization principal axis direction. The target polarization fingerprint features are compared and analyzed with the current polarization state parameters obtained by real-time sampling through the antenna receiving port, and the polarization mismatch index is calculated. When the polarization mismatch index exceeds the tolerance threshold, a dielectric constant tensor adjustment parameter is generated based on the difference in polarization principal axis directions between the two, and the equivalent dielectric properties of the beamforming network are changed by reconstructing the orientation distribution of liquid crystal molecules. Synchronous drive reconfigurable magnetoelectric dipole units perform spatial phase reorganization to generate cross-polarization components that are conjugate-matched with the rotational characteristics of the target signal; The polarization alignment rate of the backscattered signal is monitored in real time. When the polarization alignment rate reaches the maximum correlation value, the current polarization control parameters are locked to achieve synergistic enhancement of polarization diversity gain and spatial polarization filtering.

[0053] It should be noted that the UAV communication protocol features (including protocol type and frequency domain feature vector) parsed by the environmental perception module are used to extract the implicit polarization state parameters in the signal waveform, generating target polarization fingerprint features containing elliptic polarizability and polarization principal axis direction, thereby accurately identifying the polarization characteristics of the target. The acquired target polarization fingerprint features are compared and analyzed with the current polarization state parameters obtained in real time through the antenna receiving port. By calculating Euclidean distance or cosine of the included angle, the polarization mismatch index is quantified. When this index exceeds a preset tolerance threshold (the value range is usually set to 0.1 to 0.5, preferably 0.3), it indicates that the current polarization matching state can no longer meet the requirements for efficient countermeasures. At this time, a corresponding dielectric constant tensor adjustment parameter is generated according to the difference between the target and the current polarization principal axis direction. By applying a specific sequence of control voltages, the orientation distribution of liquid crystal molecules in the liquid crystal polarization control layer is reconstructed, thereby changing the equivalent dielectric properties of the beamforming network and realizing the dynamic reconstruction of the substrate's electromagnetic properties. Simultaneously, the reconfigurable magnetoelectric dipole unit is driven to perform precise spatial phase reconfiguration. By adjusting the feed phase relationship of each radiating unit, a cross-polarization component that is perfectly conjugate-matched to the azimuth characteristics of the target signal is generated, forming a polarization-matched beam pattern. During implementation, the polarization alignment rate of the UAV backscattered signal is monitored in real time. When the ratio reaches the maximum correlation value, the current polarization control parameters are immediately locked, ultimately achieving synergistic enhancement of polarization diversity gain and spatial polarization filtering, improving the transmission efficiency and interference effect of the countermeasure signal.

[0054] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0055] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0056] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0057] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0058] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0059] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A broadband multimode antenna suitable for UAV countermeasure scenarios, characterized in that, It includes an environmental perception and frequency band scanning module, a mode adaptive selection module, a reflection path optimization module, a multi-mode collaborative enhancement module, and a feedback adjustment module; The environmental perception and frequency band scanning module scans the electromagnetic environment in real time, detects the communication frequency band characteristics of the UAV in the target airspace, and identifies the communication protocol type. The mode adaptive selection module adjusts the electromagnetic response parameters of the open resonant ring unit according to the detected UAV communication characteristics, so that the antenna system can adaptively switch between omnidirectional search mode and directional enhancement mode. The reflection path optimization module controls the signal reflection path of the reflector based on the current operating mode, and optimizes the radiation directivity and bandwidth coverage of the antenna by combining the impedance adjustment of the matching slot. In directional mode, the multi-mode collaborative enhancement module coordinates the electromagnetic coupling between the directional oscillator and the open resonant ring unit to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. The feedback adjustment module adjusts the matching slot parameters and reflector phase of the antenna system according to the real-time changes in the UAV signal to maintain the optimal countermeasure effect.

2. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that, Real-time scanning of the electromagnetic environment detects the communication frequency band characteristics of UAVs within the target airspace and identifies the communication protocol type, specifically: The target spatial domain is continuously sensed by a broadband receiving front-end to obtain raw spectrum data; the raw spectrum data is preprocessed and subjected to fast Fourier transform to generate frequency domain feature vectors. Based on the frequency domain feature vector, the center frequency, bandwidth, and amplitude features of the signal peak are extracted; The center frequency is matched with a preset drone frequency band knowledge base to identify potential drone signals; The potential UAV signal is demodulated and analyzed to obtain the modulation index, symbol rate and time-domain pulse characteristics; The time-domain pulse features are matched with the protocol fingerprint feature library using the spectral correlation density function. When the matching degree exceeds the preset matching degree threshold, it is determined to be a specific UAV communication protocol type. Finally, the identification result containing frequency band features and protocol type is output.

3. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that, Based on the detected UAV communication characteristics, the electromagnetic response parameters of the open-loop resonator are adjusted to enable the antenna system to adaptively switch between omnidirectional search mode and directional enhancement mode. Specifically: The system queries the pre-defined protocol-mode mapping database based on the protocol type to obtain the initial mode priority parameters corresponding to the protocol; at the same time, it extracts the corresponding frequency band sensitivity factor based on the frequency band range where the center frequency point is located. The initial mode priority parameter and the frequency band sensitivity factor are input into the mode decision matrix and weighted to obtain the mode fitness score. The pattern fitness score is compared with a preset threshold value. When the pattern fitness score is lower than the preset threshold value, an omnidirectional search pattern identifier is generated. When the pattern fitness score is equal to or higher than the preset threshold value, a directional enhancement pattern identifier is generated. The pattern identifier includes a pattern type code, a pattern confidence index, and a frequency band adaptation coefficient. The pattern confidence index is obtained by normalizing the difference between the pattern fitness score and a preset threshold value, and the frequency band adaptation coefficient is derived from the weighted calculation result of the frequency band sensitivity factor.

4. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that, Based on the current operating mode, the signal reflection path of the reflector is controlled, and the antenna's radiation directivity and bandwidth coverage are optimized by combining the impedance adjustment of the matching slot. Specifically: The initial phase offset vector of each reflecting oscillator is obtained by querying the preset radiation mode-phase mapping table according to the mode type code. The reflection path compensation factor is determined based on the frequency band adaptation coefficient. The initial phase offset vector is weighted and calculated with the reflection path compensation factor to generate a reflection unit excitation scheme containing the amplitude and phase parameters of each reflection unit. The phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit, and the corresponding phase offset is applied to each reflector to form the phase gradient required for beamforming. Meanwhile, based on the frequency band adaptation coefficient, the impedance-frequency band correspondence database is queried to obtain the initial impedance matching parameters of the matching slot, and the impedance correction is calculated in combination with the reflection path compensation factor to obtain the final impedance adjustment value. Based on the final impedance adjustment value, the capacitance value of the variable capacitor element in the matching slot is adjusted by the digital control circuit to achieve the tuning of the impedance matching network. Finally, the optimization effect of radiation directivity and frequency band coverage was verified by monitoring the voltage standing wave ratio characteristics of the antenna input port.

5. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 4, characterized in that, The phase offset to be applied to each reflector is determined according to the excitation scheme of the reflector unit, and the corresponding phase offset is applied to each reflector to form the phase gradient required for beamforming, specifically as follows: Extract the target phase parameters of each reflecting oscillator in the excitation scheme of the reflecting unit, compare the target phase parameters with the current phase state, and calculate the original phase offset difference; The phase offset difference is corrected by amplitude weighting based on the amplitude parameters of the reflection unit to generate the phase offset of each oscillator. The phase offset is converted into control code for a programmable phase shifter array, wherein the generation of the control code requires combining the phase quantization step and calibration lookup table of the phase shifter; The control code is sent to the phase shifter array drive circuit through the serial peripheral interface, and the corresponding phase offset is applied to each reflecting oscillator to form the required wavefront phase distribution.

6. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that, In directional mode, the electromagnetic coupling between the guiding oscillator and the open resonant ring unit is coordinated to enhance the signal strength in the target direction while suppressing electromagnetic noise in the interference frequency band. Specifically: Based on the frequency band adaptation coefficient and mode confidence index in the received mode identifier, the preset coupling parameter configuration library is queried to obtain the initial phase offset of the oscillator unit and the reference bias voltage of the open resonator. Based on the frequency band adaptation coefficient and the reference bias voltage, the gradient descent optimization algorithm is used to calculate the optimal bias voltage adjustment for each resonant ring unit, generating an optimized bias voltage sequence. Based on the initial phase offset and the bias voltage optimization sequence, the phase compensation value directed to the oscillator is calculated by phase weighting, where the phase weighting needs to be combined with the oscillator spacing factor and the frequency-wavelength ratio parameter. The phase compensation value is converted into a digital phase control word and sent to the digital phase shifter array that guides the oscillator via a serial interface. The bias voltage optimization sequence is converted into an analog voltage signal and then loaded onto the varactor diodes of each open-loop resonant ring via a digital-to-analog converter. Based on real-time monitored forward gain and sidelobe level data, the electromagnetic coupling efficiency index is calculated, and the bias voltage optimization sequence and phase compensation value are iteratively optimized according to the electromagnetic coupling efficiency index to achieve adaptive closed-loop control of electromagnetic coupling parameters.

7. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 6, characterized in that, Based on real-time monitored radiation pattern forward gain and sidelobe level data, the electromagnetic coupling effectiveness index is calculated, and the bias voltage optimization sequence and phase compensation value are iteratively optimized according to the electromagnetic coupling effectiveness index, specifically as follows: The ratio of forward gain to sidelobe level is calculated as an electromagnetic coupling effectiveness index. The electromagnetic coupling effectiveness index is input into the Lyapunov exponential prediction model. By solving the eigenvalues ​​of the Jacobian matrix of the system state equation, the system stability prediction index is calculated. The system stability prediction index is compared with the preset stability threshold. When the system stability prediction index is greater than the preset stability threshold, an optimization step size adjustment coefficient is generated. The bias voltage optimization sequence is subjected to gradient descent operation based on the optimization step size adjustment coefficient to generate a set of bias voltage correction values. Simultaneously, the system stability prediction index is convolved with the phase compensation value to obtain the phase compensation correction factor; Based on the bias voltage correction set and the phase compensation correction factor, a weighted fusion algorithm is used to generate a new bias voltage optimization sequence and phase compensation value; After applying the new parameter set to the antenna system, the radiation pattern data is reacquired and the Lyapunov exponential rate of change is calculated. The iteration stops when the rate of change is less than the convergence threshold; otherwise, the optimization process continues with the new parameter set as input.

8. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that, Based on the real-time changes in the UAV signal, the matching slot parameters and the phase of the reflecting element of the antenna system are adjusted to maintain the optimal countermeasure effect, specifically as follows: Real-time monitoring of the intensity change rate and frequency drift of UAV signals yields signal stability indices. The signal stability index is compared with a preset threshold, and an adaptive adjustment coefficient is generated when the preset threshold is exceeded. The initial impedance adjustment amount of the matching slot and the reference phase compensation value of the reflecting oscillator are obtained by querying the preset impedance-phase joint adjustment mapping table according to the adaptive adjustment coefficient. The frequency drift is weighted by the initial impedance adjustment to generate an impedance correction factor. Simultaneously, the signal strength change rate is convolved with the reference phase compensation value to obtain the phase adjustment amount; The digital control code for the matching slot is obtained by querying the preset variable capacitor control code table according to the impedance correction factor; and the phase offset instruction set required for the reflecting oscillator is determined according to the phase adjustment amount. Digital control code is loaded into the variable capacitor array of the matching slot through a digital control circuit, while a phase offset instruction set is applied to the reflector array through a phase controller. Finally, the voltage standing wave ratio and main lobe width of the antenna system are monitored in real time. When the rate of change of the main lobe width exceeds the tolerance value, the signal stability index is recalculated and a new adjustment cycle is started.

9. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 1, characterized in that: It also includes an antenna structure, which adopts a multi-layer composite substrate design. The substrate includes an upper first panel and a lower second panel. An active vibrator is disposed on the first panel, and a first reflector is disposed on the second panel. The active vibrator and the first reflector are connected by metal vias.

10. A broadband multimode antenna suitable for UAV countermeasure scenarios according to claim 9, characterized in that: Above the active element, multiple guiding elements are arranged along the width of the first panel to enhance the antenna directivity. A second reflecting element is added below the first reflecting element to optimize the signal reflection path. A microstrip line is arranged in the middle of the first reflecting element for power feeding. Matching slots are arranged on both sides of the microstrip line. By adjusting the size and shape of the matching slots, the antenna bandwidth is increased.

Images