A GaN phased array antenna control method and system for multi-band cooperative interference

Abstract

The present invention relates to the field of electronic information technology, and in particular to a GaN phased array antenna control method and system for multi-band collaborative interference. The method comprises extracting key parameters of electromagnetic signals and generating a collaborative interference strategy combination; mapping frequency band optimization weights to the dynamic operating mode of the GaN power amplifier unit, and adjusting the radiation field characteristics of the reconfigurable dipole array according to the power allocation parameters to construct a composite beamforming architecture; performing phase weighting and spatial multiplexing on the interference signals of each frequency band based on the composite beamforming architecture to generate a multi-beam interference cluster; collecting the thermodynamic state data of the GaN power amplifier module during the multi-beam interference cluster generation process in real time, and regulating the heat dissipation parameters of the liquid cooling system according to the thermodynamic state data. The method realizes the intelligent coordination and precise pointing of multi-band interference signals, improves the interference coverage and energy utilization, and forms a high-efficiency interference system integrating electromagnetic perception, multi-beam coordination and thermal management.

Description

Technical Field

[0001] The present invention relates to the field of electronic information technology, and in particular to a method and system for controlling a gallium nitride phased array antenna with multi-band cooperative interference. Background Art

[0002] In modern electronic warfare environments, with the rapid development of radar and communication systems toward multi-band and adaptive capabilities, traditional single-band jamming methods are no longer sufficient to counter complex electromagnetic threats. Existing jamming systems commonly suffer from limited frequency coverage, slow beam reconfiguration, and low multi-target jamming effectiveness. They perform particularly poorly against agile signals such as frequency hopping and spread spectrum. While gallium nitride (GaN) devices offer the advantage of high power density, they face performance degradation due to heat accumulation when operating in multi-band coordination. For phased array antennas, existing technologies often employ fixed-band designs or mechanical tuning, making it difficult to achieve millisecond-level dynamic multi-band beam reconfiguration and lacking a coordinated optimization mechanism for power and thermal management. When generating jamming strategies, traditional methods typically process signals in each frequency band independently, neglecting the coordinated scheduling of time-frequency-space resources, resulting in low jamming energy utilization. Furthermore, existing thermal management systems, which often rely on passive cooling or current-sharing cooling, are unable to adapt to the uneven thermal load of GaN power amplifier modules under dynamic power distribution. Therefore, there is an urgent need to develop a phased array jamming system that integrates broadband sensing, multi-beam coordination, and thermal-electric joint control to solve key technical problems such as dynamic resource allocation, three-dimensional beam isolation, and high-power thermal management in multi-band jamming. Summary of the Invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a GaN phased array antenna control method and system for multi-band collaborative interference.

[0004] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is:

[0005] A first aspect of the present invention discloses a GaN phased array antenna control method for multi-band cooperative interference, comprising the following steps:

[0006] Acquire electromagnetic signals in the target airspace in real time, extract key parameters of the electromagnetic signals, and generate a collaborative jamming strategy combination including beam pointing, power allocation parameters, and frequency band optimization weights;

[0007] The frequency band optimization weights are mapped to the dynamic operating mode of the GaN power amplifier unit, and the radiation pattern characteristics of the reconfigurable dipole array are adjusted according to the power allocation parameters to construct a composite beamforming architecture that matches the target frequency band;

[0008] Based on the composite beamforming architecture, phase weighting and spatial multiplexing are performed on the interference signals of each frequency band to generate a multi-beam interference cluster with three-dimensional isolation characteristics of time, frequency and space;

[0009] Thermodynamic state data of the gallium nitride power amplifier module during the multi-beam interference cluster generation process is collected in real time, and the heat dissipation parameters of the liquid cooling system are regulated according to the thermodynamic state data.

[0010] Preferably, the electromagnetic signal of the target airspace is acquired in real time, and the key parameters of the electromagnetic signal are extracted to generate a collaborative interference strategy combination including beam pointing, power allocation parameters and frequency band optimization weights, specifically:

[0011] Performing feature extraction processing on the electromagnetic signal to obtain signal strength, spectrum occupancy and pulse parameter dynamic change characteristics;

[0012] Performing weighted aggregation on the signal strength, spectrum occupancy, and pulse parameter dynamic change characteristics to generate a fusion feature matrix including a frequency band conflict index, a signal aggregation degree, and a pulse overlap factor, wherein the pulse overlap factor represents the time domain overlap probability of interference signals in different frequency bands;

[0013] Based on the frequency band conflict index and pulse overlap factor in the fusion feature matrix, a greedy algorithm is used to dynamically select the frequency band combination with the best interference effectiveness, and determine the beam pointing deflection compensation and power allocation weight for each frequency band. The beam pointing deflection compensation is jointly corrected by the signal aggregation degree and the dynamic change characteristics of the pulse parameters.

[0014] Combining the frequency band optimization weight and the power allocation weight, a cooperative interference strategy combination including beam pointing deflection compensation, frequency band dwell time and power time slot modulation is generated.

[0015] Preferably, the frequency band optimization weight and the power allocation weight are combined to generate a cooperative interference strategy combination including the beam pointing deflection compensation amount, frequency band dwell time and power time slot modulation, specifically:

[0016] Dynamically normalize the frequency band preference weights and power allocation weights to generate a joint optimization weight matrix. The joint optimization weight for each frequency band is obtained by logarithmically compressing the product of the standard weight of the frequency band and the power allocation weight. If the compressed value is lower than a preset threshold, the frequency band is excluded from the current interference strategy combination.

[0017] Based on the joint optimization weight matrix, the initial deflection compensation of the beam pointing in each frequency band is initialized and corrected based on the real-time electromagnetic environment disturbance coefficient of the target airspace. If the disturbance coefficient exceeds the adaptive threshold, the gradient descent method is used to iteratively optimize the deflection compensation until the beam alignment accuracy requirements are met.

[0018] A weighted round-robin algorithm is used to allocate the dwell time of each frequency band based on the joint optimization weight matrix and the beam pointing deflection compensation. If the joint optimization weight of a frequency band is higher than the preset contention threshold, its dwell time is preferentially extended and the occupation time of the low-weight frequency band is shortened.

[0019] Dynamically divide power time slots based on frequency band dwell time and beam pointing deflection compensation. A nonlinear programming algorithm is used to optimize the power allocation ratio of each time slot. If the interference efficiency gain of a time slot falls below a preset efficiency threshold, a power reallocation mechanism is triggered to readjust the transmit power of that time slot to match the current electromagnetic environment requirements.

[0020] The beam pointing deflection compensation amount, frequency band dwell time and power allocation ratio are integrated to generate a final collaborative interference strategy combination.

[0021] Preferably, the frequency band optimization weight is mapped to the dynamic operating mode of the gallium nitride power amplifier unit, and the radiation pattern characteristics of the reconfigurable dipole array are adjusted according to the power allocation parameters to construct a composite beamforming architecture that matches the target frequency band, specifically:

[0022] Generating a driving bias voltage of the GaN power amplifier unit at a plurality of preset working time nodes according to the cooperative interference strategy combination, and generating a driving bias voltage curve of the GaN power amplifier unit using a piecewise linear interpolation algorithm; and analyzing the overlap between the driving bias voltage curve and a reference bias voltage curve;

[0023] If the overlap is not greater than a preset overlap threshold, dynamically modifying the slope and intercept parameters of the driving bias voltage curve based on the frequency band optimization weights in the cooperative interference strategy combination to generate a power amplifier dynamic operating parameter set that matches the real-time electromagnetic environment; and defining a thermal coupling compensation factor between each power amplifier unit based on the power amplifier dynamic operating parameter set;

[0024] Combining the power allocation parameters with the power amplifier dynamic operating parameter set, the equivalent electrical length of the dipole arm is corrected in real time through a distributed microstrip tuning circuit, and the thermal coupling compensation factor is introduced to perform cross-unit compensation;

[0025] During the compensation process, until the array standing wave ratio exceeds the tolerance threshold, a gradient feedback mechanism is introduced to adjust the matching topology of the tuning circuit to generate an impedance optimization matrix for the radiating unit.

[0026] The impedance optimization matrix and the power amplifier dynamic operating parameter set are jointly calculated. The phase control amount is differentially corrected according to the beam pointing deflection compensation amount and the inter-unit decoupling parameters, and the amplitude control amount is time-domain weighted according to the power time slot modulation parameters and the thermal coupling compensation factor. The final output is a composite beamforming architecture with thermal-electrical-frequency joint compensation characteristics.

[0027] Preferably, based on the composite beamforming architecture, phase weighting and spatial multiplexing are performed on the interference signals of each frequency band to generate a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics, specifically:

[0028] Based on the composite beamforming architecture, the carrier phase noise characteristics of the interference signal in each frequency band are extracted, and an asymmetric phase compensation algorithm is used to generate phase weighting coefficients with frequency band differences.

[0029] Performing a complex domain dot multiplication operation on the phase weighting coefficient and the amplitude control variable in the composite beamforming architecture to generate a phase-optimized beam cluster with frequency-band adaptive phase compensation characteristics;

[0030] The phase-optimized beam cluster is input into the asymmetric MIMO beam synthesizer, which outputs a multiplexed beam group with spatial isolation characteristics based on the electromagnetic environment scattering characteristics of the target space.

[0031] For each sub-beam in the multiplexed beam group, combined with the frequency band dwell time and power time slot modulation parameters of its corresponding frequency band, time-frequency interleaving coding technology is used to allocate the beam transmission timing, and a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics is obtained.

[0032] Preferably, the phase-optimized beam cluster is input into the asymmetric MIMO beam synthesizer, and a multiplexed beam group with spatial isolation characteristics is output according to the electromagnetic environment scattering characteristics of the target spatial domain, specifically:

[0033] Based on the phase-optimized beam cluster, the multipath scattering intensity distribution in the target space is extracted through the spatial spectrum estimation method, and the electromagnetic environment scattering matrix containing the scatterer azimuth and Doppler spread characteristics is generated;

[0034] Perform spatial convolution operations on the electromagnetic environment scattering matrix and the phase-optimized beam cluster to obtain the energy coupling between the beams. If the coupling is greater than the preset isolation threshold, the beam pattern optimization flag is triggered to generate a set of beam pairs that need to be isolated.

[0035] For the set of beam pairs that need to be isolated, the subspace projection algorithm is used to orthogonalize the original beam weight vector. The orthogonalized weight vector is then combined with the phase-optimized beam cluster through a complex domain dot multiplication operation to form a pre-processed beam group with spatial nulling.

[0036] The preprocessed beam group is input into the MIMO beam synthesizer, and the polarization dimension of the transmit beam is optimized using the channel reciprocity principle. When it is detected that the cross-polarization isolation does not meet the requirements, a polarization rotation compensation factor is superimposed, and finally a multiplexed beam group with spatial-polarization dual-dimensional isolation characteristics is output.

[0037] Preferably, the thermodynamic state data of the gallium nitride power amplifier module during the multi-beam interference cluster generation process is collected in real time, and the heat dissipation parameters of the liquid cooling system are regulated according to the thermodynamic state data, specifically:

[0038] The distributed temperature sensor array is used to collect temperature data of each preset node in the GaN power amplifier module, substrate heat flux density, and coolant flow rate;

[0039] Calculating the local temperature rise rate of each preset location node based on the temperature data; if the local temperature rise rate of a preset location node exceeds a safety threshold, it is marked as a high temperature risk node;

[0040] Perform spatial convolution operation on the substrate heat flux density and coolant flow rate of the high temperature risk node to obtain the heat accumulation effect coefficient;

[0041] According to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted through the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized. A liquid cooling system control instruction set is generated to implement directional enhanced heat dissipation for high-temperature risk nodes.

[0042] Preferably, according to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted by the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized to generate a liquid cooling system control instruction set, specifically:

[0043] Compare the heat accumulation effect coefficient of each high-temperature risk node with the preset heat dissipation threshold. When the heat accumulation effect coefficient of a node exceeds the preset heat dissipation threshold, mark the corresponding heat dissipation flow channel as a first-level priority control path;

[0044] Based on the heat accumulation effect coefficient, combined with fluid dynamics analysis, the heat flow vector field of the high-temperature risk node is obtained. The heat flux density gradient is extracted and coupled with the heat accumulation effect coefficient for normalization and weighting. Then, the connectivity is corrected in combination with the microchannel topology structure to generate a heat conduction priority matrix for controlling coolant distribution.

[0045] The heat conduction priority matrix is input into the microfluidic valve controller, and the flow distribution weight of each branch is analyzed using the fluid mechanics equivalent impedance model. If the impedance value of the first-level priority control path exceeds the critical value, the laminar flow acceleration mode is triggered, and the initial flow control parameter set is generated through proportional-integral regulation.

[0046] Based on the initial flow control parameter set, the change in the contact thermal resistance of the radiator fins is monitored in real time. When the thermal resistance increment is detected to be greater than the allowable fluctuation range, the piezoelectric ceramic micro-displacement mechanism is activated to adjust the fin contact pressure. The optimal thermal conductivity compensation value is determined in combination with the heat accumulation effect coefficient to form the optimized thermal resistance coefficient of the fin-substrate interface.

[0047] The flow control parameter set is coupled with the thermal resistance optimization coefficient. First, a pulsed flow enhancement factor is superimposed on the first-level priority control path. Then, a three-dimensional control instruction set including valve opening timing, fin pressure level and coolant flow rate is generated according to the gradient distribution characteristics of the heat conduction priority matrix to achieve directional heat sink control of high-temperature risk nodes.

[0048] A second aspect of the present invention discloses a GaN phased array antenna control system for multi-band cooperative interference, which is applied to any of the above-mentioned GaN phased array antenna control methods and steps, including:

[0049] The broadband dynamic spectrum sensing module uses a multi-band electromagnetic scanning unit to support continuous frequency coverage from 1.5 to 6 GHz. It has a real-time spectrum scanning period of ≤10ms and interference signal parameter extraction functions, and dynamically generates collaborative interference strategies including beam pointing and power spectrum density.

[0050] The reconfigurable antenna array module, based on distributed GaN power amplifier units driving a reconfigurable dipole array, achieves single-unit gain ≥8dBi and switchable omnidirectional mode with 360° coverage and directional mode with beamwidth ≤15°. The integrated MEMS tunable filter bank controls the standing wave ratio ≤1.5.

[0051] Multi-beam cooperative interference generation module, used to generate multi-band interference clusters with spatial isolation ≥30dB, and achieve beam pointing error ≤0.5° and suppression distance ≥3km based on FPGA phase synchronization control;

[0052] The thermal management module directly bonds the GaN power amplifier chip through a three-dimensional stacked microchannel liquid cooling structure, achieving a heat dissipation power density ≥800W / cm². Combined with a thermal sensor network, it controls the chip junction temperature fluctuation to ≤±2°C.

[0053] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: the present invention realizes the intelligent coordination and precise pointing of multi-band interference signals, improves the interference coverage range and energy utilization rate; at the same time, through real-time regulation of thermodynamic state, ensures the stability of equipment under high-power operation, and forms an efficient interference system integrating electromagnetic perception, multi-beam coordination and thermal management. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying any creative work, they can also obtain drawings of other embodiments based on these drawings.

[0055] Figure 1This is a flow chart of the first method of the gallium nitride phased array antenna control method;

[0056] Figure 2 This is a flow chart of the second method of the gallium nitride phased array antenna control method;

[0057] Figure 3 This is the system block diagram of the GaN phased array antenna control system. DETAILED DESCRIPTION

[0058] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0059] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0060] like Figure 1 As shown, the first aspect of the present invention discloses a GaN phased array antenna control method for multi-band cooperative interference, comprising the following steps:

[0061] S102. Acquire electromagnetic signals in the target airspace in real time, extract key parameters of the electromagnetic signals, and generate a collaborative interference strategy combination including beam pointing, power allocation parameters, and frequency band optimization weights;

[0062] S104: Mapping the frequency band optimization weight to the dynamic operating mode of the GaN power amplifier unit, and adjusting the radiation pattern characteristics of the reconfigurable dipole array according to the power allocation parameter to construct a composite beamforming architecture that matches the target frequency band;

[0063] S106. Performing phase weighting and spatial multiplexing on interference signals in each frequency band based on the composite beamforming architecture to generate a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics;

[0064] S108 . Collecting in real time the thermodynamic state data of the gallium nitride power amplifier module during the multi-beam interference cluster generation process, and regulating the heat dissipation parameters of the liquid cooling system according to the thermodynamic state data.

[0065] Preferably, the electromagnetic signal of the target airspace is acquired in real time, and the key parameters of the electromagnetic signal are extracted to generate a collaborative interference strategy combination including beam pointing, power allocation parameters and frequency band optimization weights, such as Figure 2 As shown, specifically:

[0066] S202, performing feature extraction processing on the electromagnetic signal to obtain signal strength, spectrum occupancy and pulse parameter dynamic change characteristics;

[0067] S204. Perform weighted aggregation on the signal strength, spectrum occupancy, and pulse parameter dynamic change characteristics to generate a fusion feature matrix including a frequency band conflict index, a signal aggregation degree, and a pulse overlap factor, wherein the pulse overlap factor represents the time domain overlap probability of interference signals in different frequency bands;

[0068] S206. Based on the frequency band conflict index and pulse overlap factor in the fusion feature matrix, a greedy algorithm is used to dynamically select the frequency band combination with the best interference efficiency, and the beam pointing deflection compensation and power allocation weight of each frequency band are determined. The beam pointing deflection compensation is jointly corrected by the signal aggregation degree and the dynamic change characteristics of the pulse parameters.

[0069] S208. Combining the frequency band optimization weight and the power allocation weight, a coordinated interference strategy combination including a beam pointing deflection compensation amount, a frequency band dwell time, and a power time slot modulation is generated.

[0070] It should be noted that in the dynamic screening process, first, based on the frequency band conflict index and pulse overlap factor in the fusion feature matrix, a greedy algorithm is used to successively select the candidate frequency bands with the highest current interference efficiency: the frequency bands with a conflict index higher than the threshold and a pulse overlap factor lower than the preset value are preferentially screened as the initial combination; then, the azimuth concentration of the interference signal in the target airspace is determined according to the signal aggregation degree, and the beam pointing deflection compensation amount of each frequency band is weightedly corrected in combination with dynamic characteristics such as the pulse repetition interval and the pulse width change rate. The compensation amount is determined by the product of the signal aggregation ratio and the pulse characteristic change rate; finally, according to the comprehensive score of the conflict index and pulse overlap factor of each frequency band, the power weight is proportionally allocated to ensure that high-conflict, low-overlap frequency bands obtain higher power priority, forming a dynamically optimized frequency band interference strategy.

[0071] Preferably, the frequency band optimization weight and the power allocation weight are combined to generate a cooperative interference strategy combination including the beam pointing deflection compensation amount, frequency band dwell time and power time slot modulation, specifically:

[0072] Dynamically normalize the frequency band preference weights and power allocation weights to generate a joint optimization weight matrix. The joint optimization weight for each frequency band is obtained by logarithmically compressing the product of the standard weight of the frequency band and the power allocation weight. If the compressed value is lower than a preset threshold, the frequency band is excluded from the current interference strategy combination.

[0073] Based on the joint optimization weight matrix, the initial deflection compensation of the beam pointing in each frequency band is initialized and corrected based on the real-time electromagnetic environment disturbance coefficient of the target airspace. If the disturbance coefficient exceeds the adaptive threshold, the gradient descent method is used to iteratively optimize the deflection compensation until the beam alignment accuracy requirements are met.

[0074] It should be noted that, based on a joint optimization weight matrix, an initial beam deflection compensation is assigned to each frequency band (higher-weighted frequency bands receive greater compensation). Simultaneously, the electromagnetic environment disturbance coefficient (such as signal strength fluctuations and multipath interference) in the target airspace is monitored in real time. When the disturbance coefficient exceeds a preset threshold, a gradient descent optimization algorithm is initiated. By calculating the error gradient between the current beam pointing direction and the target direction, the deflection compensation for each frequency band is gradually adjusted (with each adjustment decreasing as the error decreases) until the required beam pointing accuracy is achieved (e.g., an error angle of less than 0.5 degrees). During this process, adjustments to the high-frequency band weight channel are prioritized, and the iteration step size is dynamically updated based on the real-time disturbance conditions to ensure rapid convergence to the optimal beam pointing.

[0075] A weighted round-robin algorithm is used to allocate the dwell time of each frequency band based on the joint optimization weight matrix and the beam pointing deflection compensation. If the joint optimization weight of a frequency band is higher than the preset contention threshold, its dwell time is preferentially extended and the occupation time of the low-weight frequency band is shortened.

[0076] It should be noted that when allocating frequency band dwell time, the system ranks each band according to its weight in the joint optimization weight matrix and uses a weighted round-robin scheduling mechanism to allocate initial dwell time proportionally. When a frequency band's weight exceeds a contention threshold (e.g., 0.7), a priority adjustment mechanism is automatically triggered. The dwell time for that band is dynamically increased by the proportion exceeding the threshold (e.g., the dwell time increases by 15% for every 0.1 increase in weight above the threshold). Furthermore, the dwell time for lower-weighted bands (e.g., bands with a weight below 0.3) is proportionally reduced. Fine-tuning is also performed based on the calculated beam deflection compensation, with appropriate time margins added to bands with larger deflection compensations to ensure stable beam alignment. This entire allocation process is executed in real time, ensuring that high-weighted bands consistently receive at least 70% of their effective interference time.

[0077] Dynamically divide power time slots based on frequency band dwell time and beam pointing deflection compensation. A nonlinear programming algorithm is used to optimize the power allocation ratio of each time slot. If the interference efficiency gain of a time slot falls below a preset efficiency threshold, a power reallocation mechanism is triggered to readjust the transmit power of that time slot to match the current electromagnetic environment requirements.

[0078] The beam pointing deflection compensation amount, frequency band dwell time and power allocation ratio are integrated to generate a final collaborative interference strategy combination.

[0079] It should be noted that during the power allocation phase, the system divides the total transmission period into dynamic time slots based on the dwell time and beam steering compensation allocated to each frequency band. Using a nonlinear programming algorithm, the system calculates the optimal power allocation for each time slot, with the goal of maximizing interference effectiveness (high-weighted frequency bands receive more power resources). When real-time monitoring indicates that the interference effectiveness of a particular time slot falls below a threshold, power reallocation is immediately initiated: the power in that time slot is automatically reduced by 10%-30% and dynamically allocated to adjacent time slots with higher effectiveness. Ultimately, the system integrates beam steering parameters (e.g., +3.2° deflection at 2.4 GHz), frequency band dwell time (e.g., 65% at 5.8 GHz), and optimized power allocation (e.g., 60 W allocated to the 5.8 GHz time slot) to generate a complete interference strategy encompassing all three parameters of time, frequency, and space. This strategy is continuously optimized through closed-loop feedback.

[0080] In a preferred embodiment of the present invention, in an electronic countermeasure scenario against an enemy dual-frequency hopping radar (e.g., operating in the 2.4 GHz and 5.8 GHz bands), the system first captures electromagnetic signals in the target airspace in real time through a broadband receiving channel. For example, the measured signal strength in the 2.4 GHz band is -65 dBm, with a spectrum occupancy of 82% and a pulse repetition interval of 20 μs; the signal strength in the 5.8 GHz band is -58 dBm, with a spectrum occupancy of 95% and a pulse repetition interval of 15 μs. The signal features of the two bands are weighted and aggregated to generate a fused feature matrix, with a band conflict index of 0.73 (preset threshold 0.6) and a pulse overlap factor of 0.45. A greedy algorithm is used to select the two bands as the interference combination, resulting in a beam deflection offset of +3.2° and a power weight of 0.4 for the 2.4 GHz band, and a deflection offset of -1.8° and a power weight of 0.6 for the 5.8 GHz band. Dynamic normalization generates a joint optimization weight matrix (with a preset threshold of 0.15). When the electromagnetic disturbance coefficient exceeds the threshold (e.g., a measured value of 0.85 > 0.7), the 5.8GHz deflection compensation is iteratively corrected to -2.1° using a gradient descent method. The resulting collaborative strategy: 35% dwell time at 2.4GHz, 40W power slot allocation, and 65% dwell time at 5.8GHz, 60W power slot allocation, forming an adaptive jamming solution for dual-band frequency-hopping signals.

[0081] In summary, the present invention dynamically generates the optimal interference strategy by extracting signal features in real time and integrating parameters such as frequency band conflict and signal aggregation. It can adapt to complex electromagnetic environments, intelligently screen high-efficiency interference bands, accurately allocate beam pointing and power resources, and achieve rapid optimization configuration of multi-band collaborative interference, thereby improving interference efficiency and resource utilization.

[0082] Preferably, the frequency band optimization weight is mapped to the dynamic operating mode of the gallium nitride power amplifier unit, and the radiation pattern characteristics of the reconfigurable dipole array are adjusted according to the power allocation parameters to construct a composite beamforming architecture that matches the target frequency band, specifically:

[0083] Generating a driving bias voltage of the GaN power amplifier unit at a plurality of preset working time nodes according to the cooperative interference strategy combination, and generating a driving bias voltage curve of the GaN power amplifier unit using a piecewise linear interpolation algorithm; and analyzing the overlap between the driving bias voltage curve and a reference bias voltage curve;

[0084] It should be noted that the system sets the driving bias voltage for the GaN power amplifier unit at key time nodes based on the dwell time and power allocation parameters for each frequency band in the coordinated interference strategy. The specific steps are: first, extract the power time slot information for each frequency band in the strategy (for example, the 2.4GHz band allocates 40W of power during the 5-20ms period). Then, based on a preset power-voltage mapping table, the initial bias voltage values for the corresponding time nodes are determined (for example, 28V for the 5ms node and 30V for the 15ms node). Next, the voltage values are weighted and modified based on the frequency band's preferred weight (with an appropriate increase in voltage margin for high-weighted frequency bands). Ultimately, a sequence of driving bias voltage nodes is generated that is strictly synchronized with the operating time of each frequency band, providing reference parameters for the subsequent generation of continuous driving voltage curves. Throughout this process, the system monitors the status of the power amplifier unit in real time to ensure that the voltage parameters remain consistent with the dynamic interference strategy.

[0085] If the overlap is not greater than a preset overlap threshold, dynamically modifying the slope and intercept parameters of the driving bias voltage curve based on the frequency band optimization weights in the cooperative interference strategy combination to generate a power amplifier dynamic operating parameter set that matches the real-time electromagnetic environment; and defining a thermal coupling compensation factor between each power amplifier unit based on the power amplifier dynamic operating parameter set;

[0086] It should be noted that when the generated drive bias voltage curve detects that the overlap with the reference curve falls below a preset threshold (e.g., 85%), the system automatically initiates a dynamic correction mechanism. First, the slope of the voltage curve is proportionally adjusted based on the preferred weight ratio of each frequency band in the collaborative interference strategy (e.g., 60% for 5.8GHz). Simultaneously, the curve intercept parameter is compensated and corrected based on real-time electromagnetic environment parameters (e.g., signal strength fluctuations). The corrected parameter set contains the optimal operating voltage, adjustment slope, and compensation amount for each power amplifier unit. Based on this, the system calculates the thermal influence coefficient between adjacent power amplifier units. Combining the unit spacing and operating temperature difference, it generates a thermal coupling compensation factor (e.g., an adjustment factor in the range of 0.5-1.2) to offset thermal interference, ensuring thermal stability when multiple power amplifiers operate in coordination.

[0087] Combining the power allocation parameters with the power amplifier dynamic operating parameter set, the equivalent electrical length of the dipole arm is corrected in real time through a distributed microstrip tuning circuit, and the thermal coupling compensation factor is introduced to perform cross-unit compensation;

[0088] During the compensation process, until the array standing wave ratio exceeds the tolerance threshold, a gradient feedback mechanism is introduced to adjust the matching topology of the tuning circuit to generate an impedance optimization matrix for the radiating unit.

[0089] It should be noted that, based on the power allocation parameters and the dynamic operating parameters of the power amplifier, the system first automatically adjusts the physical length of the dipole radiating arms through a distributed microstrip tuning circuit (for example, shortening the dipole arms for the 5.8 GHz band from 12 mm to 11.3 mm) to match the equivalent electrical length requirement of the current operating frequency band. Simultaneously, a calculated thermal coupling compensation factor (e.g., 0.8) is injected into the compensation network between adjacent elements to offset performance drift caused by power amplifier heating. During this process, the array's standing wave ratio (SWR) is monitored in real time. If the SWR exceeds a preset tolerance (e.g., 1.5), a gradient feedback mechanism is immediately activated. Based on the deviation between the current SWR and the target value, the tuning circuit's matching structure is dynamically adjusted (e.g., increasing the shunt capacitor to 1.2 pF or changing the microstrip line length). After multiple iterations of optimization, the system ultimately outputs an impedance optimization matrix that achieves optimal matching for the entire array, ensuring maximum radiation efficiency.

[0090] The impedance optimization matrix and the power amplifier dynamic operating parameter set are jointly calculated. The phase control amount is differentially corrected according to the beam pointing deflection compensation amount and the inter-unit decoupling parameters, and the amplitude control amount is time-domain weighted according to the power time slot modulation parameters and the thermal coupling compensation factor. The final output is a composite beamforming architecture with thermal-electrical-frequency joint compensation characteristics.

[0091] In a preferred embodiment of the present invention, in an electronic jamming scenario targeting an enemy dual-frequency hopping radar (2.4GHz / 5.8GHz), the system sets the driving bias voltage nodes for the GaN power amplifier units corresponding to the two frequency bands (28V@5ms, 30V@15ms for the 2.4GHz node; 32V@5ms, 34V@15ms for the 5.8GHz node) based on a generated coordinated jamming strategy (35% dwell, 40W power for the 2.4GHz node; 32V@5ms, 34V@15ms for the 5.8GHz node). After generating a driving curve using piecewise linear interpolation, the system checks that its overlap with the baseline curve (preset 30V±5%) is 78% (below the threshold of 85%). The system then dynamically adjusts the slope (from 0.4V / ms to 0.45V / ms) and intercept (from 27.8V to 28.2V) based on the frequency band preference weight (5.8GHz weight 0.6), generating a dynamic operating parameter set. Based on the spacing between adjacent power amplifier units (0.5λ) and the real-time temperature gradient (ΔT = 7°C), a thermal coupling compensation factor of 0.8 was defined. Subsequently, a microstrip tuning circuit was used to shorten the 5.8GHz dipole arm length from 12mm to 11.3mm (equivalent electrical length correction), and the compensation factor was injected to offset the thermal coupling effect. When the array standing wave ratio (SWR) increased to 1.8 (with a tolerance of 1.5), the gradient feedback mechanism automatically adjusted the tuning circuit topology, increasing the parallel capacitance to 1.2pF, thus forming an impedance optimization matrix. The final joint calculation outputs: a 2.4GHz phase adjustment of +0.3° (originally +3.2°) with an amplitude weighting factor of 0.92, and a 5.8GHz phase adjustment of -2.4° (originally -2.1°) with an amplitude weighting factor of 1.08. This formed a composite beamforming architecture, which, combined with the aforementioned interference strategy in a closed-loop manner, achieved stable dual-band beam coverage.

[0092] In summary, the present invention dynamically optimizes the power amplifier bias curve and thermal coupling compensation, combined with real-time adjustment of impedance matching, to achieve precise adaptation of multi-band power distribution and radiation field pattern, suppress the influence of thermal effects on beam pointing, improve the array standing wave ratio stability and beamforming accuracy, and ensure the spatial coverage quality and energy concentration of the composite interference beam in complex electromagnetic environments.

[0093] Preferably, based on the composite beamforming architecture, phase weighting and spatial multiplexing are performed on the interference signals of each frequency band to generate a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics, specifically:

[0094] Based on the composite beamforming architecture, the carrier phase noise characteristics of the interference signal in each frequency band are extracted, and an asymmetric phase compensation algorithm is used to generate phase weighting coefficients with frequency band differences.

[0095] It should be noted that the phase jitter characteristics of signals in each frequency band (such as 2.3GHz and 5.6GHz) are measured in real time through a high-precision phase detection circuit to obtain their phase noise distribution characteristics. Then, an asymmetric phase compensation algorithm is used to calculate the corresponding compensation parameters based on the differences in phase noise in each frequency band (such as better phase stability in the low-frequency band and greater jitter in the high-frequency band). A larger compensation weight is given to the frequency band with greater phase jitter (5.6GHz), while a smaller compensation is used for the relatively stable frequency band (2.3GHz). Finally, a phase weighting coefficient that matches the characteristics of each frequency band is generated, where the high-frequency band coefficient contains a larger phase compensation angle and amplitude adjustment factor, ensuring that the signals in each frequency band can achieve optimal phase consistency after weighting.

[0096] Performing a complex domain dot multiplication operation on the phase weighting coefficient and the amplitude control variable in the composite beamforming architecture to generate a phase-optimized beam cluster with frequency-band adaptive phase compensation characteristics;

[0097] The phase-optimized beam cluster is input into the asymmetric MIMO beam synthesizer, which outputs a multiplexed beam group with spatial isolation characteristics based on the electromagnetic environment scattering characteristics of the target space.

[0098] For each sub-beam in the multiplexed beam group, combined with the frequency band dwell time and power time slot modulation parameters of its corresponding frequency band, time-frequency interleaving coding technology is used to allocate the beam transmission timing, and a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics is obtained.

[0099] Among them, time-frequency interleaving coding technology refers to a scheduling method that achieves isolated arrangement of multi-beam signals in the two-dimensional time-frequency space by staggered allocation of the transmission timing and frequency resources of signals in different frequency bands, setting protection intervals in the time domain, and maintaining interval bandwidth in the frequency domain, thereby avoiding mutual interference.

[0100] It's important to note that the system intelligently schedules each sub-beam within a multiplexed beam group. First, the system divides the basic transmit time slots based on the preset dwell times for each frequency band (e.g., 20ms for S-band and 30ms for C-band). The energy density of each time slot is then determined based on the power-slot modulation parameters (e.g., 40W for S-band and 60W for C-band). Time-frequency interleaving (TFI) is used to stagger the transmission timing of sub-beams in different frequency bands—high-band, high-power time slots alternate with low-band time slots, while maintaining a 10ms guard interval. Furthermore, spatial isolation is ensured through spatial pointing differences (e.g., a 22° difference in beam azimuth angle). This ultimately creates a three-dimensional, isolated interference beam cluster with time-staggered, frequency-separated, and spatially independent pointing directions. The system monitors isolation in each dimension in real time and dynamically adjusts the transmission timing and power ratio to maximize interference effectiveness.

[0101] Preferably, the phase-optimized beam cluster is input into the asymmetric MIMO beam synthesizer, and a multiplexed beam group with spatial isolation characteristics is output according to the electromagnetic environment scattering characteristics of the target spatial domain, specifically:

[0102] Based on the phase-optimized beam cluster, the multipath scattering intensity distribution in the target space is extracted through the spatial spectrum estimation method, and the electromagnetic environment scattering matrix containing the scatterer azimuth and Doppler spread characteristics is generated;

[0103] It should be noted that the system first performs a spatial scan of the phase-optimized beam cluster, receiving multipath reflection signals from the target airspace via the array antenna. Spatial spectrum estimation techniques (such as the MUSIC algorithm) are used to analyze the spatial arrival angle distribution of the received signals and extract the azimuth information of each scatterer (e.g., the presence of a strong scatterer at 35°). Doppler shift analysis is also used to capture the dynamic characteristics of the scatterers (e.g., the ±500Hz frequency deviation caused by a moving target). Parameters such as azimuth, Doppler shift, and signal strength are integrated into a two-dimensional matrix, where row vectors represent different azimuth angles (5° intervals) and column vectors contain the Doppler spread and scattering intensity at the corresponding angles (e.g., a 35° azimuth corresponds to a scattering intensity of -65dBm and a Doppler spread of 300Hz). This ultimately generates a scattering matrix that comprehensively characterizes the electromagnetic environment.

[0104] Perform spatial convolution operations on the electromagnetic environment scattering matrix and the phase-optimized beam cluster to obtain the energy coupling between the beams. If the coupling is greater than the preset isolation threshold, the beam pattern optimization flag is triggered to generate a set of beam pairs that need to be isolated.

[0105] It's important to note that when the coupling degree of a beam pair is detected to exceed a preset isolation threshold (e.g., 0.6), the system automatically marks that beam pair for optimization, generating an isolation set containing all highly coupled beam pairs. The system then records the coupling azimuth and coupling strength for each marked beam pair, which serve as input parameters for subsequent beam pattern optimization. This entire process is executed in a real-time loop, ensuring continuous monitoring of coupling status in dynamic electromagnetic environments.

[0106] For the set of beam pairs that need to be isolated, the subspace projection algorithm is used to orthogonalize the original beam weight vector. The orthogonalized weight vector is then combined with the phase-optimized beam cluster through a complex domain dot multiplication operation to form a pre-processed beam group with spatial nulling.

[0107] It should be noted that for highly coupled beam pairs that require isolation (such as beams A and B), the system first constructs an orthogonalized subspace based on the beam coupling orientation (e.g., 35°) using a subspace projection algorithm. The original beam weight vectors are projected onto this subspace to generate a new set of orthogonal weight vectors (e.g., beam A weight vector rotated 15°, beam B rotated -10°). These orthogonalized weight vectors are then multiplied in the complex domain with the original phase-optimized beam cluster (real part multiplication adjusts amplitude, imaginary part multiplication adjusts phase). This creates a radiation null exceeding 25dB in the coupling orientation (35°) while maintaining the beam characteristics in other directions. In the final output preprocessed beam set, the previously interfering beam pairs achieve significant energy isolation in the specified direction, while the other beams maintain their original radiation characteristics, achieving spatially selective suppression.

[0108] The preprocessed beam group is input into the MIMO beam synthesizer, and the polarization dimension of the transmit beam is optimized using the channel reciprocity principle. When it is detected that the cross-polarization isolation does not meet the requirements, a polarization rotation compensation factor is superimposed, and finally a multiplexed beam group with spatial-polarization dual-dimensional isolation characteristics is output.

[0109] It should be noted that after the system inputs the preprocessed beam group into the MIMO beamformer, it first analyzes the polarization characteristics of the receiving end feedback based on the principle of channel reciprocity and independently optimizes the polarization state of each sub-beam. When the cross-polarization component of a beam (such as the vertical component in a horizontally polarized beam) is detected to exceed a threshold (such as -15dB), a polarization rotation compensation factor (such as a 12° polarization rotation angle) is automatically calculated and added, and the cross-polarization component is suppressed by adjusting the excitation phase difference of the antenna elements. At the same time, the optimized spatial nulling characteristics are maintained unchanged. The final output is a two-dimensional isolated beam group with both spatial directional isolation (such as a 35° directional null) and polarization orthogonality (main / cross-polarization isolation >20dB), effectively isolating beams in different frequency bands in both spatial and polarization dimensions.

[0110] In a preferred embodiment of the present invention, in an electronic warfare scenario against a dual-band radar (e.g., operating in the S-band at 2.3 GHz and the C-band at 5.6 GHz), the system first extracts the phase noise characteristics of the two-band signals (e.g., phase jitter ±8° in the S-band and ±12° in the C-band) from a composite beamforming architecture. An asymmetric compensation algorithm is then used to generate differentiated phase weighting coefficients (0.92e^(j15°) in the S-band and 0.88e^(j22°) in the C-band). These coefficients are complex-multiplied by the amplitude control factor (0.95 in the S-band and 1.05 in the C-band) to form a phase-optimized beam cluster. During MIMO beamformer processing, the spatial spectrum indicates that the 5.6 GHz beam exhibits strong multipath scattering at 35° (e.g., the scattering matrix indicates an energy coupling of 0.75, exceeding the isolation threshold of 0.6). Therefore, the beam weight vectors for the two bands are orthogonalized to form a null with a depth of ≥25 dB at 35°. During the polarization optimization phase, the C-band cross-polarization isolation was detected to be only 12dB (required ≥15dB). This was increased to 17dB by adding an 18° polarization rotation compensation factor. The resulting multiplexed beamset uses a 20ms dwell / 40W power slot encoding for the S-band beam and a 30ms / 60W power slot encoding for the C-band. The two beams are interleaved in the time domain, with a 3.3GHz frequency interval and a 22° spatial pointing difference, achieving three-dimensional interference isolation.

[0111] To sum up, in order to solve the technical problems of mutual interference between beams and low energy utilization of multi-band interference signals in a complex electromagnetic environment, the present invention realizes adaptive isolation of multi-band interference signals in the time domain, frequency domain and spatial domain by performing phase compensation and spatial-polarization two-dimensional isolation processing, reduces energy coupling between beams, improves the spatial pointing accuracy and energy concentration of interference signals, and further enhances the interference effectiveness through polarization optimization, thereby forming an efficient interference beam cluster with three-dimensional isolation characteristics.

[0112] Preferably, the thermodynamic state data of the gallium nitride power amplifier module during the multi-beam interference cluster generation process is collected in real time, and the heat dissipation parameters of the liquid cooling system are regulated according to the thermodynamic state data, specifically:

[0113] The distributed temperature sensor array is used to collect temperature data of each preset node in the GaN power amplifier module, substrate heat flux density, and coolant flow rate;

[0114] Calculating the local temperature rise rate of each preset location node based on the temperature data; if the local temperature rise rate of a preset location node exceeds a safety threshold, it is marked as a high temperature risk node;

[0115] Perform spatial convolution operation on the substrate heat flux density and coolant flow rate of the high temperature risk node to obtain the heat accumulation effect coefficient;

[0116] According to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted through the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized. A liquid cooling system control instruction set is generated to implement directional enhanced heat dissipation for high-temperature risk nodes.

[0117] Preferably, according to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted by the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized to generate a liquid cooling system control instruction set, specifically:

[0118] Compare the heat accumulation effect coefficient of each high-temperature risk node with the preset heat dissipation threshold. When the heat accumulation effect coefficient of a node exceeds the preset heat dissipation threshold, mark the corresponding heat dissipation flow channel as a first-level priority control path;

[0119] Based on the heat accumulation effect coefficient, combined with fluid dynamics analysis, the heat flow vector field of the high-temperature risk node is obtained. The heat flux density gradient is extracted and coupled with the heat accumulation effect coefficient for normalization and weighting. Then, the connectivity is corrected in combination with the microchannel topology structure to generate a heat conduction priority matrix for controlling coolant distribution.

[0120] It should be noted that, first, based on the heat accumulation effect coefficient (e.g., 1.8) at the high-temperature risk node, fluid dynamics simulation analysis is used to determine the heat flux vector distribution in that area, identifying the direction and intensity of heat flux concentration (e.g., a vortex-shaped heat flux with a maximum heat flux density of 8 W / cm²). Heat flux gradient data (e.g., an X-direction gradient of 0.5 W / cm³) is then extracted and weighted (the heat flux gradient accounts for 60% and the heat accumulation coefficient accounts for 40%) to obtain a preliminary heat conduction priority score. This score is then modified based on the topological structural parameters of the microfluidic network (e.g., branch connectivity and number of bends). Complex branches with multiple bends have their priority scores reduced by 20%, while straight branches have their scores increased by 15%. Finally, a heat conduction priority matrix is generated, containing each branch's priority score (e.g., a score of 0.85 for branch B) and recommended flow adjustment ratios, providing a quantitative basis for the precise control of the subsequent liquid cooling system. This entire process is updated at preset intervals (e.g., 5 seconds) to adapt to changes in the heat distribution in real time.

[0121] The heat conduction priority matrix is input into the microfluidic valve controller, and the flow distribution weight of each branch is analyzed using the fluid mechanics equivalent impedance model. If the impedance value of the first-level priority control path exceeds the critical value, the laminar flow acceleration mode is triggered, and the initial flow control parameter set is generated through proportional-integral regulation.

[0122] It's important to note that after inputting the heat transfer priority matrix into the microfluidic valve controller, the system first calculates the flow resistance characteristics of each cooling branch using a fluid dynamics equivalent impedance model (for example, the impedance of first-priority branch B is 0.8 Pa·s / m³). If the impedance of a branch exceeds a critical value (0.6 Pa·s / m³), the system automatically activates laminar acceleration mode. Based on the current impedance excess (33%), the system dynamically calculates flow control parameters using a proportional-integral control algorithm. This algorithm initially increases the base flow rate by the excess percentage (for example, from 0.5 m / s to 0.8 m / s). It then fine-tunes the flow rate by accumulating historical errors using the integral term (adding an additional 0.1 m / s compensation). This ultimately generates an initial flow control parameter set, including the target flow rate (0.9 m / s), adjustment duration (3 seconds), and acceleration (0.3 m / s²). This parameter set is then distributed in real time to the intelligent valve actuator in the corresponding branch, establishing a baseline for subsequent refined flow control.

[0123] Based on the initial flow control parameter set, the change in the contact thermal resistance of the radiator fins is monitored in real time. When the thermal resistance increment is detected to be greater than the allowable fluctuation range, the piezoelectric ceramic micro-displacement mechanism is activated to adjust the fin contact pressure. The optimal thermal conductivity compensation value is determined in combination with the heat accumulation effect coefficient to form the optimized thermal resistance coefficient of the fin-substrate interface.

[0124] The flow control parameter set is coupled with the thermal resistance optimization coefficient. First, a pulsed flow enhancement factor is superimposed on the first-level priority control path. Then, a three-dimensional control instruction set including valve opening timing, fin pressure level and coolant flow rate is generated according to the gradient distribution characteristics of the heat conduction priority matrix to achieve directional heat sink control of high-temperature risk nodes.

[0125] It should be noted that the system couples the flow control parameter set (such as the target flow rate of 0.9m / s) with the thermal resistance optimization coefficient (such as the compensation value of 0.85 corresponding to a 15% reduction in interface thermal resistance). The specific steps are as follows: superimposing a pulsed flow enhancement on the first-level priority branch (such as branch B) (periodic fluctuations of ±0.2m / s within the initial 2 seconds to destroy the thermal boundary layer); at the same time, analyzing the gradient distribution of the heat conduction priority matrix, generating an incremental valve opening curve (0-80% linear opening) for high-gradient areas (such as branches with a score > 0.8), matching the corresponding fin pressure level (such as level III 8N pressure); and finally integrating to form a three-dimensional control instruction - branch B is accelerated by 0.3m / s² to 1.1m / s within 0-3 seconds, synchronously triggering a step-by-step increase in fin pressure (5N→8N), and the valve executes an 80% opening hold mode. Through the synergistic effect of time-domain pulses, spatial pressure and flow field velocity, directional heat sink control is achieved within 10 seconds at high-temperature nodes (such as the 98°C area).

[0126] In a preferred embodiment of the present invention, during a dual-band radar (2.4GHz / 5.8GHz) electronic jamming mission, while the system was performing high-power multi-beam jamming (40W for 20ms in the 2.4GHz beam and 60W for 30ms in the 5.8GHz beam), distributed temperature sensors detected a local hotspot in the 5.8GHz power amplifier unit area: the temperature at node A reached 98°C (safety threshold 95°C), the temperature rise rate was 15°C / s (threshold 10°C / s), the substrate heat flux density was 8W / cm², and the coolant flow rate was 0.5m / s. A spatial convolution operation yielded a heat accumulation coefficient of 1.8 (preset threshold 1.2) at this node, prompting the system to immediately designate it as a first-level priority control path. Fluid dynamics analysis revealed a vortex-like distribution of the heat flux vector field in this area, and calculation of the heat conduction priority matrix indicated that the impedance of branch B exceeded the specified value (0.8Pa·s / m³ > critical value 0.6), triggering the laminar acceleration mode and increasing the flow rate to 1.2m / s. At the same time, the piezoelectric ceramic micro-displacement mechanism increases the contact pressure of the heat sink fins from 5N to 8N, reducing the interfacial thermal resistance by 15%. This ultimately generates a three-dimensional control command: 80% valve opening (pulsed opening) for branch B, fin pressure level III, and a coolant flow rate of 1.2m / s. Within 10 seconds, the temperature of node A drops to 88°C, ensuring stable operation of the 5.8GHz power amplifier module under continuous high-power interference.

[0127] In summary, to address the technical issues of local overheating and low heat dissipation efficiency caused by uneven heat distribution in GaN power amplifier modules in multi-beam interference scenarios, the present invention uses a dynamic control mechanism driven by thermodynamic state data to identify high-temperature risk areas in real time and quantify the heat accumulation effect. Through the coordinated control of fluid path optimization and contact thermal resistance compensation, it achieves precise positioning and directional heat dissipation of hotspots, improves the heat dissipation response speed and temperature uniformity under high-power conditions, and ensures the thermal stability and reliability of GaN power amplifier modules in complex interference tasks.

[0128] In this embodiment, the gallium nitride phased array antenna control method may further include the following steps:

[0129] The random number generator is triggered by the quantum vacuum fluctuation effect to generate a quantum random number sequence with true random characteristics, and the sequence is divided into multiple quantum random number segments according to preset grouping rules;

[0130] Hash mapping is performed between the carrier frequency of the interference signal in each frequency band and the quantum random number segment to generate the initial phase hopping sequence corresponding to each frequency band;

[0131] By utilizing the quantum correlation characteristics of entangled photon pairs, the entangled phase synchronization factor is obtained through Bell state measurement. This factor is convolved with the initial phase jump sequence to generate a multi-band joint phase jump matrix with quantum correlation characteristics.

[0132] The multi-band joint phase jump matrix is input into the quantized interference modulator, and the phase jump information is encoded into the carrier signal of each frequency band through the quantum tunneling effect, forming a quantized interference waveform with non-local correlation characteristics;

[0133] Based on the principle of quantum non-cloning, quantum fingerprint features are implanted in the waveform, so that the interference signals in each frequency band exhibit unpredictable phase mutations in the time domain and maintain quantum correlation in the frequency domain, and finally output a quantized interference codebook with anti-reverse analysis characteristics.

[0134] Among them, the quantum random number segment serves as the basic random source throughout the entire processing process, the entangled phase synchronization factor ensures the spatiotemporal correlation of multi-band hopping, and the quantum fingerprint feature provides the ultimate anti-cracking protection. The three form a progressive quantum protection system.

[0135] In this embodiment, to address the technical issues of traditional electronic jamming signals, such as strong predictability, poor multi-band coordination, and susceptibility to reverse engineering, this embodiment utilizes quantum true randomness to ensure the unpredictability of jamming signals, achieves non-local correlation of multi-band phase jumps through quantum entanglement, and combines quantum fingerprint features to form non-replicable jamming signatures. Ultimately, a jamming codebook with inherent quantum randomness, cross-band correlation, and anti-cracking properties is generated, thereby enhancing the concealment and anti-jamming capabilities in electronic countermeasures.

[0136] In this embodiment, the gallium nitride phased array antenna control method may further include the following steps:

[0137] The frequency band preference weights of each frequency band are converted into binary coding sequences, and adapter fragments are added to both ends of the sequence according to preset rules to form an artificial DNA single chain, where the weight values of different frequency bands correspond to specific base arrangement and combination patterns;

[0138] Based on DNA origami technology, a molecular reaction network with parallel computing capabilities was constructed, and the encoded DNA single strand was injected into the reaction system as an input signal.

[0139] During the strand displacement reaction, complementary DNA probe sequences are designed to specifically bind to the input strand, where the probe concentration gradient reflects the interference efficiency index of each frequency band. When the input strand and the probe undergo displacement reaction, a displacement product chain with a fluorescent label is generated.

[0140] A fluorescence intensity detection device was used to monitor the displacement reaction rates of different weight combinations in real time, and a mapping relationship between the reaction kinetic parameters and the quality of the interference strategy was established. The DNA chain combination corresponding to the peak displacement rate represented the Pareto front solution.

[0141] By using high-throughput sequencing technology to decode the base sequence of the dominant DNA chain, the optimal distribution ratio of the frequency band weights is reversely analyzed, and the interference strategy solution set that meets multi-objective optimization is output, completing the reverse conversion from biomolecular computing to electromagnetic interference strategy.

[0142] It should be noted that to address the technical issues of low computational efficiency and difficulty in quickly obtaining Pareto optimal solutions in traditional algorithms for optimizing multi-band interference strategies, this embodiment leverages the high parallelism and specificity of DNA strand displacement reactions to rapidly optimize multi-target interference strategies, improving the efficiency of solving frequency band weight allocation schemes in complex electromagnetic environments. At the same time, the inherent characteristics of biomolecular computing ensure the global optimality of the output solution set, providing an efficient optimization method for dynamic interference decision-making.

[0143] like Figure 3 As shown, the second aspect of the present invention discloses a GaN phased array antenna control system for multi-band cooperative interference, which is applied to any of the above-mentioned GaN phased array antenna control methods and steps, including:

[0144] Wideband dynamic spectrum sensing module 1 uses a multi-band electromagnetic scanning unit to support continuous frequency coverage of 1.5-6GHz. It has a real-time spectrum scanning period of ≤10ms and interference signal parameter extraction function, and dynamically generates collaborative interference strategies including beam pointing and power spectrum density.

[0145] Reconfigurable antenna array module 2, based on distributed gallium nitride power amplifier units driving a reconfigurable dipole array, achieves single-unit gain ≥ 8dBi and switchable omnidirectional mode 360° coverage and directional mode beamwidth ≤ 15°. The integrated MEMS tunable filter bank controls the standing wave ratio ≤ 1.5;

[0146] Multi-beam cooperative interference generation module 3 is used to generate multi-band interference clusters with spatial isolation ≥30dB, and achieve beam pointing error ≤0.5° and suppression distance ≥3km based on FPGA phase synchronization control;

[0147] Thermal management module 4 directly bonds the GaN power amplifier chip through a three-dimensional stacked microchannel liquid cooling structure, achieving a heat dissipation power density of ≥800W / cm². Combined with a thermal sensor network, it controls the chip junction temperature fluctuation to ≤±2°C.

[0148] The above are only specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A GaN phased array antenna control method for multi-band cooperative interference, characterized in that: The following steps are involved: Acquire electromagnetic signals in the target airspace in real time, extract key parameters of the electromagnetic signals, and generate a collaborative jamming strategy combination including beam pointing, power allocation parameters, and frequency band optimization weights; The frequency band optimization weights are mapped to the dynamic operating mode of the GaN power amplifier unit, and the radiation pattern characteristics of the reconfigurable dipole array are adjusted according to the power allocation parameters to construct a composite beamforming architecture that matches the target frequency band; Based on the composite beamforming architecture, phase weighting and spatial multiplexing are performed on the interference signals of each frequency band to generate a multi-beam interference cluster with three-dimensional isolation characteristics of time, frequency and space; collecting thermodynamic state data of the gallium nitride power amplifier module in real time during the multi-beam interference cluster generation process, and regulating the heat dissipation parameters of the liquid cooling system according to the thermodynamic state data; The electromagnetic signal of the target airspace is acquired in real time, and the key parameters of the electromagnetic signal are extracted to generate a collaborative interference strategy combination including beam pointing, power allocation parameters and frequency band optimization weights, specifically: Performing feature extraction processing on the electromagnetic signal to obtain signal strength, spectrum occupancy and pulse parameter dynamic change characteristics; Performing weighted aggregation on the signal strength, spectrum occupancy, and pulse parameter dynamic change characteristics to generate a fusion feature matrix including a frequency band conflict index, a signal aggregation degree, and a pulse overlap factor, wherein the pulse overlap factor represents the time domain overlap probability of interference signals in different frequency bands; Based on the frequency band conflict index and pulse overlap factor in the fusion feature matrix, a greedy algorithm is used to dynamically select the frequency band combination with the best interference effectiveness, and determine the beam pointing deflection compensation and power allocation weight for each frequency band. The beam pointing deflection compensation is jointly corrected by the signal aggregation degree and the dynamic change characteristics of the pulse parameters. Combining the frequency band optimization weight and the power allocation weight, a coordinated interference strategy combination including beam pointing deflection compensation, frequency band dwell time, and power time slot modulation is generated. Among them, the frequency band optimization weight and power allocation weight are combined to generate a cooperative interference strategy combination including beam pointing deflection compensation, frequency band dwell time and power time slot modulation, specifically: Dynamically normalize the frequency band preference weights and power allocation weights to generate a joint optimization weight matrix. The joint optimization weight for each frequency band is obtained by logarithmically compressing the product of the standard weight of the frequency band and the power allocation weight. If the compressed value is lower than a preset threshold, the frequency band is excluded from the current interference strategy combination. Based on the joint optimization weight matrix, the initial deflection compensation of the beam pointing in each frequency band is initialized and corrected based on the real-time electromagnetic environment disturbance coefficient of the target airspace. If the disturbance coefficient exceeds the adaptive threshold, the gradient descent method is used to iteratively optimize the deflection compensation until the beam alignment accuracy requirements are met. A weighted round-robin algorithm is used to allocate the dwell time of each frequency band based on the joint optimization weight matrix and the beam pointing deflection compensation. If the joint optimization weight of a frequency band is higher than the preset contention threshold, its dwell time is preferentially extended and the occupation time of the low-weight frequency band is shortened. Dynamically divide power time slots based on frequency band dwell time and beam pointing deflection compensation. A nonlinear programming algorithm is used to optimize the power allocation ratio of each time slot. If the interference efficiency gain of a time slot falls below a preset efficiency threshold, a power reallocation mechanism is triggered to readjust the transmit power of that time slot to match the current electromagnetic environment requirements. The beam pointing deflection compensation amount, frequency band dwell time and power allocation ratio are integrated to generate a final collaborative interference strategy combination.

2. The GaN phased array antenna control method for multi-band cooperative interference according to claim 1, characterized in that: The frequency band optimization weights are mapped to the dynamic operating mode of the GaN power amplifier unit, and the radiation pattern characteristics of the reconfigurable dipole array are adjusted according to the power allocation parameters to construct a composite beamforming architecture that matches the target frequency band. Specifically, Generating a driving bias voltage of the GaN power amplifier unit at a plurality of preset working time nodes according to the cooperative interference strategy combination, and generating a driving bias voltage curve of the GaN power amplifier unit using a piecewise linear interpolation algorithm; and analyzing the overlap between the driving bias voltage curve and a reference bias voltage curve; If the overlap is not greater than a preset overlap threshold, dynamically modifying the slope and intercept parameters of the driving bias voltage curve based on the frequency band optimization weights in the cooperative interference strategy combination to generate a power amplifier dynamic operating parameter set that matches the real-time electromagnetic environment; and defining a thermal coupling compensation factor between each power amplifier unit based on the power amplifier dynamic operating parameter set; Combining the power allocation parameters with the power amplifier dynamic operating parameter set, the equivalent electrical length of the dipole arm is corrected in real time through a distributed microstrip tuning circuit, and the thermal coupling compensation factor is introduced to perform cross-unit compensation; During the compensation process, until the array standing wave ratio exceeds the tolerance threshold, a gradient feedback mechanism is introduced to adjust the matching topology of the tuning circuit to generate an impedance optimization matrix for the radiating unit. The impedance optimization matrix and the power amplifier dynamic operating parameter set are jointly calculated. The phase control amount is differentially corrected according to the beam pointing deflection compensation amount and the inter-unit decoupling parameters, and the amplitude control amount is time-domain weighted according to the power time slot modulation parameters and the thermal coupling compensation factor. The final output is a composite beamforming architecture with thermal-electrical-frequency joint compensation characteristics.

3. The GaN phased array antenna control method for multi-band cooperative interference according to claim 1, characterized in that: Based on the composite beamforming architecture, phase weighting and spatial multiplexing are performed on the interference signals in each frequency band to generate a multi-beam interference cluster with three-dimensional isolation characteristics of time, frequency and space. Specifically: Based on the composite beamforming architecture, the carrier phase noise characteristics of the interference signal in each frequency band are extracted, and an asymmetric phase compensation algorithm is used to generate phase weighting coefficients with frequency band differences. Performing a complex domain dot multiplication operation on the phase weighting coefficient and the amplitude control variable in the composite beamforming architecture to generate a phase-optimized beam cluster with frequency-band adaptive phase compensation characteristics; The phase-optimized beam cluster is input into the asymmetric MIMO beam synthesizer, which outputs a multiplexed beam group with spatial isolation characteristics based on the electromagnetic environment scattering characteristics of the target space. For each sub-beam in the multiplexed beam group, combined with the frequency band dwell time and power time slot modulation parameters of its corresponding frequency band, time-frequency interleaving coding technology is used to allocate the beam transmission timing, and a multi-beam interference cluster with time-frequency-space three-dimensional isolation characteristics is obtained.

4. The GaN phased array antenna control method for multi-band cooperative interference according to claim 3, characterized in that: The phase-optimized beam cluster is input into the asymmetric MIMO beamformer, which outputs a multiplexed beam group with spatial isolation characteristics based on the electromagnetic environment scattering characteristics of the target space. Specifically: Based on the phase-optimized beam cluster, the multipath scattering intensity distribution in the target space is extracted through the spatial spectrum estimation method, and the electromagnetic environment scattering matrix containing the scatterer azimuth and Doppler spread characteristics is generated; Perform spatial convolution operations on the electromagnetic environment scattering matrix and the phase-optimized beam cluster to obtain the energy coupling between the beams. If the coupling is greater than the preset isolation threshold, the beam pattern optimization flag is triggered to generate a set of beam pairs that need to be isolated. For the set of beam pairs that need to be isolated, the subspace projection algorithm is used to orthogonalize the original beam weight vector. The orthogonalized weight vector is then combined with the phase-optimized beam cluster through a complex domain dot multiplication operation to form a pre-processed beam group with spatial nulling. The preprocessed beam group is input into the MIMO beam synthesizer, and the polarization dimension of the transmit beam is optimized using the channel reciprocity principle. When it is detected that the cross-polarization isolation does not meet the requirements, a polarization rotation compensation factor is superimposed, and finally a multiplexed beam group with spatial-polarization dual-dimensional isolation characteristics is output.

5. The GaN phased array antenna control method for multi-band cooperative interference according to claim 1, characterized in that: The thermodynamic state data of the GaN power amplifier module during the multi-beam interference cluster generation process is collected in real time, and the heat dissipation parameters of the liquid cooling system are regulated according to the thermodynamic state data, specifically: The distributed temperature sensor array is used to collect temperature data of each preset node in the GaN power amplifier module, substrate heat flux density, and coolant flow rate; Calculating the local temperature rise rate of each preset location node based on the temperature data; if the local temperature rise rate of a preset location node exceeds a safety threshold, it is marked as a high temperature risk node; Perform spatial convolution operation on the substrate heat flux density and coolant flow rate of the high temperature risk node to obtain the heat accumulation effect coefficient; According to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted through the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized. A liquid cooling system control instruction set is generated to implement directional enhanced heat dissipation for high-temperature risk nodes.

6. The GaN phased array antenna control method for multi-band cooperative interference according to claim 5, characterized in that: According to the heat accumulation effect coefficient, the flow distribution priority of the coolant path is adjusted through the microchannel valve controller, and the heat conduction efficiency of the radiator fins is optimized to generate a liquid cooling system control instruction set, specifically: Compare the heat accumulation effect coefficient of each high-temperature risk node with the preset heat dissipation threshold. When the heat accumulation effect coefficient of a node exceeds the preset heat dissipation threshold, mark the corresponding heat dissipation flow channel as a first-level priority control path; Based on the heat accumulation effect coefficient, combined with fluid dynamics analysis, the heat flow vector field of the high-temperature risk node is obtained. The heat flux density gradient is extracted and coupled with the heat accumulation effect coefficient for normalization and weighting. Then, the connectivity is corrected in combination with the microchannel topology structure to generate a heat conduction priority matrix for controlling coolant distribution. The heat conduction priority matrix is input into the microfluidic valve controller, and the flow distribution weight of each branch is analyzed using a fluid mechanics equivalent impedance model; If the impedance value of the first-level priority control path is higher than the critical value, the laminar acceleration mode is triggered, and the initial flow control parameter set is generated through proportional-integral regulation; Based on the initial flow control parameter set, the change in the contact thermal resistance of the radiator fins is monitored in real time. When the thermal resistance increment is detected to be greater than the allowable fluctuation range, the piezoelectric ceramic micro-displacement mechanism is activated to adjust the fin contact pressure. The optimal thermal conductivity compensation value is determined in combination with the heat accumulation effect coefficient to form the optimized thermal resistance coefficient of the fin-substrate interface. The flow control parameter set is coupled with the thermal resistance optimization coefficient. First, a pulsed flow enhancement factor is superimposed on the first-level priority control path. Then, a three-dimensional control instruction set including valve opening timing, fin pressure level and coolant flow rate is generated according to the gradient distribution characteristics of the heat conduction priority matrix to achieve directional heat sink control of high-temperature risk nodes.

7. A GaN phased array antenna control system with multi-band cooperative interference, applied to the GaN phased array antenna control method according to any one of claims 1 to 6, characterized in that: include: The broadband dynamic spectrum sensing module uses a multi-band electromagnetic scanning unit to support continuous frequency coverage from 1.5 to 6 GHz. It has a real-time spectrum scanning period of ≤10ms and interference signal parameter extraction functions, and dynamically generates collaborative interference strategies including beam pointing and power spectrum density. The reconfigurable antenna array module, based on distributed GaN power amplifier units driving a reconfigurable dipole array, achieves unit gain ≥8dBi and switchable omnidirectional mode with 360° coverage and directional mode with beamwidth ≤15°. The integrated MEMS tunable filter bank controls the standing wave ratio to ≤1.

5. Multi-beam cooperative interference generation module, used to generate multi-band interference clusters with spatial isolation ≥30dB, and achieve beam pointing error ≤0.5° and suppression distance ≥3km based on FPGA phase synchronization control; The thermal management module directly bonds the GaN power amplifier chip through a three-dimensional stacked microchannel liquid cooling structure, achieving a heat dissipation power density ≥800W / cm². Combined with a thermal sensor network, it controls the chip junction temperature fluctuation to ≤±2°C.

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