An unmanned aerial vehicle group cooperative suppression method and system based on a distributed antenna array, an electronic device, and a storage medium

Abstract

The application provides a UAV group cooperative suppression method and system based on a distributed antenna array, an electronic device and a storage medium, relates to the technical field of UAV group cooperative suppression and anti-interference control, and the UAV is provided with an air pressure sensor array, which is used for collecting and processing the pressure of the airflow washed by the rotor, so that the airflow pressure distribution information is obtained. The information is used for vortex field calculation and processing of the fluid motion state, and vortex field information containing a disturbance area is generated. Based on the vortex field information, the phase of the antenna array element is dynamically adjusted and processed, the physical deformation of the array is compensated, and the compensation result is output. The result is used for cooperative phase correction processing of the beam pointing of the distributed antenna array, and the beam phase compensation amount is generated. Finally, based on the compensation amount, the UAV group transmission signal is cooperatively regulated and controlled, and the anti-disturbance suppression beam pointing to the target is generated. The method can realize continuous directional suppression of a moving target in a strong wind disturbance environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cooperative suppression and anti-jamming control of UAV groups, and in particular to a method and system for cooperative suppression of UAV groups based on a distributed antenna array, an electronic device, and a storage medium. BACKGROUND

[0002] In the scenario of continuous suppression of low-altitude UAV groups in a strong wind disturbance environment, the problem of beam pointing misalignment caused by physical deformation of the array due to strong airflow needs to be solved. This scenario requires the UAV group to maintain the ability to direct the suppression of moving targets on the ground under strong wind conditions. The core requirement is to compensate for array deformation and stabilize the multi-aircraft beam, avoiding the response lag of traditional pure algorithm correction.

[0003] The current mainstream solution uses distributed adaptive beamforming technology to generate beam weight vectors through feedback signals from the receiving end, dynamically adjusting the transmission phase of each UAV to maintain beam pointing. This solution uses angle of arrival estimation and space-time filtering algorithms to optimize beam synthesis directivity under total power constraints, attempting to offset the array drift error caused by wind disturbance.

[0004] However, this solution has a fundamental flaw: it relies solely on electromagnetic signal feedback for software layer phase correction and cannot perceive the physical structure deformation caused by the direct action of airflow on the UAV body. Dynamic deformation at the hardware level is not included in the compensation closed loop, resulting in beam pointing correction lagging behind actual physical state changes. In the low-altitude scenario of strong wind turbulence, suppression efficiency decreases, and multi-aircraft cooperative stability deteriorates rapidly with increasing disturbance intensity. SUMMARY

[0005] The present application aims to provide a method and system for cooperative suppression of UAV groups based on a distributed antenna array, an electronic device, and a storage medium to solve the problem of relying on software layer phase correction while ignoring airflow-induced array physical deformation in the prior art.

[0006] To solve the above technical problems, in a first aspect, the present application provides a method for cooperative suppression of UAV groups based on a distributed antenna array, comprising:

[0007] Based on the air pressure sensor array carried by the UAV, the pressure of the downwash flow of the UAV rotor is collected and processed to obtain airflow pressure distribution information;

[0008] Using the airflow pressure distribution information, the motion state of the downwash flow of the UAV rotor is calculated and processed using a vortex field to generate vortex field information containing a disturbance region;

[0009] Based on the vortex field information, the phase of the UAV antenna array element is dynamically adjusted to compensate for the physical deformation of the array, and the array physical deformation compensation result is obtained;

[0010] The array physical deformation compensation result is used for cooperative phase correction processing of beam pointing of the distributed antenna array, to obtain a beam phase compensation amount;

[0011] Based on the beam phase compensation amount, a cooperative regulation processing is performed on the unmanned aerial vehicle group transmission signal to generate a target-directed anti-disturbance suppression beam.

[0012] Optionally, based on the vortex field information, a dynamic adjustment processing is performed on the unmanned aerial vehicle antenna array element phase to compensate for the array physical deformation, to obtain an array physical deformation compensation result, including:

[0013] Based on the vortex field information, a vortex core positioning processing is performed on the disturbance area of the vortex field, to obtain a vortex core position;

[0014] The vortex core position is used for phase offset amount calculation processing of the element space distribution of the distributed antenna array, to generate a core area phase offset amount;

[0015] Based on the core area phase offset amount, a shift mode construction processing is performed on the inter-element phase relationship of the distributed antenna array, to obtain a spatial phase shift mode;

[0016] The spatial phase shift mode is used for anti-phase compensation processing of the tunable phase element of the distributed antenna array, to obtain an array element phase dynamic adjustment result;

[0017] Based on the array element phase dynamic adjustment result, a physical deformation calibration processing is performed on the state of the distributed antenna array after phase adjustment, to generate an array physical deformation compensation result.

[0018] Optionally, the airflow pressure distribution information is used for vortex field calculation processing of the motion state of the downwash fluid of the unmanned aerial vehicle rotor, to generate vortex field information containing a disturbance area, including:

[0019] Based on the airflow pressure distribution information, a pressure gradient calculation processing is performed on the surface of the downwash fluid of the unmanned aerial vehicle rotor, to obtain a pressure gradient vector;

[0020] The pressure gradient vector is used for vorticity calculation processing of the fluid motion rotation intensity of the downwash fluid of the unmanned aerial vehicle rotor, to generate an instantaneous vorticity distribution;

[0021] Based on the instantaneous vorticity distribution, an instantaneous vortex identification processing is performed on the high-vorticity concentration area of the vortex field, to obtain an instantaneous vortex core position;

[0022] The instantaneous vortex core position is used for spatial aggregation processing of the vortex trajectory of the vortex field within a continuous time window, to generate a stable vortex spatial distribution mode;

[0023] Based on the stable vortex space distribution mode, the region exceeding the vorticity threshold of the vortex field is marked with strong disturbance processing to generate vortex field information containing the disturbed region.

[0024] Optionally, the beam pointing of the distributed antenna array is subjected to cooperative phase correction processing using the array physical deformation compensation result to obtain a beam phase compensation amount, including:

[0025] Based on the array physical deformation compensation result, the geometric deviation of the distributed antenna array is subjected to distributed characteristic calculation processing to obtain an array geometric deviation distribution;

[0026] The phase deviation of the unmanned aerial vehicle antenna array element is subjected to independent compensation amount calculation processing using the array geometric deviation distribution to generate a single-machine phase compensation amount;

[0027] Based on the single-machine phase compensation amount, the multi-machine phase cooperative relationship of the unmanned aerial vehicle antenna array element phase is subjected to correction relationship construction processing to generate a multi-machine cooperative correction relationship;

[0028] The pointing of the beam of the distributed antenna array is subjected to joint phase correction processing using the multi-machine cooperative correction relationship to obtain a cooperative phase dynamic correction result;

[0029] Based on the cooperative phase dynamic correction result, the compensated beam phase is subjected to compensation amount integration processing to generate a beam phase compensation amount.

[0030] Optionally, the tunable phase unit of the distributed antenna array is subjected to inverse compensation processing using the spatial phase offset mode to obtain an array element phase dynamic adjustment result, including:

[0031] Based on the spatial phase offset mode, the offset direction of the unmanned aerial vehicle antenna array element phase is subjected to compensation direction determination processing to generate a compensation direction vector;

[0032] The tunable unit phase adjustment value of the unmanned aerial vehicle antenna array element phase is subjected to inverse vector value calculation processing using the compensation direction vector to generate a phase inverse adjustment amount;

[0033] Based on the phase inverse adjustment amount, the resonant characteristic of the tunable unit of the unmanned aerial vehicle antenna array element phase is subjected to resonant parameter adjustment processing to obtain a resonant parameter dynamic update result;

[0034] The inter-element phase consistency of the unmanned aerial vehicle antenna array element phase is subjected to dynamic balance processing using the resonant parameter dynamic update result to generate a phase balance state;

[0035] Based on the phase balance state, a dynamic adjustment confirmation process is performed on the compensated phase of the unmanned aerial vehicle antenna array element, and an array element phase dynamic adjustment result is generated.

[0036] Optionally, using the multi-machine cooperative correction relationship, a joint phase correction process is performed on the pointing of the distributed antenna array beam to obtain a cooperative phase dynamic correction result, including:

[0037] Based on the multi-machine cooperative correction relationship, a joint correction direction calculation process is performed on the multi-machine beam pointing deviation of the distributed antenna array to generate a joint correction direction;

[0038] Using the joint correction direction, a dynamic amplitude allocation process is performed on the phase cooperative adjustment requirement to generate a phase cooperative adjustment amount;

[0039] Based on the phase cooperative adjustment amount, a phase response process is performed on the tunable phase unit of the distributed antenna array to generate a phase response parameter;

[0040] Using the phase response parameter, a synchronization compensation process is performed on the element phase of the distributed antenna array to obtain a phase synchronization compensation result;

[0041] Based on the phase synchronization compensation result, a dynamic correction confirmation process is performed on the multi-machine phase cooperative state of the distributed antenna array to generate a cooperative phase dynamic correction result.

[0042] Optionally, based on the core area phase offset amount, an offset mode construction process is performed on the inter-element phase relationship of the distributed antenna array to obtain a spatial phase offset mode, including:

[0043] Based on the core area phase offset amount, a dominant offset identification process is performed on the array area phase offset of the distributed antenna array to generate a dominant phase offset amount;

[0044] Using the dominant phase offset amount, an offset transfer calculation process is performed on the adjacent array element phase relationship of the distributed antenna array to generate an inter-element phase transfer relationship;

[0045] Based on the inter-element phase transfer relationship, a smooth transition process is performed on the partition boundary phase continuity of the distributed antenna array to generate a boundary smooth phase distribution;

[0046] Using the boundary smooth phase distribution, a spatial mode integration process is performed on the global element phase offset of the distributed antenna array to generate an initial spatial phase offset mode;

[0047] Based on the initial spatial phase offset mode, an abnormal correction process is performed on the mode phase mutation area of the distributed antenna array to generate a spatial phase offset mode.

[0048] In a second aspect, the present application provides a UAV swarm cooperative suppression system based on a distributed antenna array, comprising:

[0049] a pressure acquisition module configured to acquire and process pressure of the downwash fluid of the UAV rotor based on an air pressure sensor array carried by the UAV, to obtain airflow pressure distribution information;

[0050] a vortex calculation module configured to calculate and process a vortex field of the downwash fluid of the UAV rotor based on the airflow pressure distribution information, to generate vortex field information containing a disturbance region;

[0051] a phase compensation module configured to dynamically adjust and process phases of the UAV antenna array elements based on the vortex field information to compensate for physical deformation of the array, to obtain an array physical deformation compensation result;

[0052] a beam correction module configured to perform cooperative phase correction processing on beam pointing of the distributed antenna array based on the array physical deformation compensation result, to obtain a beam phase compensation amount;

[0053] a cooperative suppression module configured to perform cooperative regulation processing on the UAV swarm transmission signal based on the beam phase compensation amount, to generate a disturbance-resistant suppression beam pointing at a target.

[0054] In a third aspect, the present application provides an electronic device, comprising:

[0055] a memory configured to store a computer program;

[0056] a processor configured to implement the steps of the UAV swarm cooperative suppression method based on a distributed antenna array as described in the first aspect above when executing the computer program.

[0057] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executable by a processor to implement the steps of the UAV swarm cooperative suppression method based on a distributed antenna array as described in the first aspect above.

[0058] The unmanned aerial vehicle group cooperative suppression method based on a distributed antenna array provided in the application obtains airflow pressure distribution information by collecting and processing the pressure of the downwash fluid of the unmanned aerial vehicle rotor based on the air pressure sensor array carried by the unmanned aerial vehicle; the motion state of the downwash fluid of the unmanned aerial vehicle rotor is calculated and processed by vortex field using the airflow pressure distribution information, and vortex field information containing a disturbance region is generated; the phase of the unmanned aerial vehicle antenna array element is dynamically adjusted and processed based on the vortex field information to compensate for the physical deformation of the array, and an array physical deformation compensation result is obtained; the beam pointing of the distributed antenna array is cooperatively phase-corrected using the array physical deformation compensation result, and a beam phase compensation amount is obtained; the unmanned aerial vehicle group transmission signal is cooperatively regulated and controlled based on the beam phase compensation amount, and a disturbance-resistant suppression beam pointing at a target is generated.

[0059] The technical scheme provided in the application has the following beneficial effects:

[0060] By collecting the pressure distribution of the downwash fluid of the rotor, the physical characteristics of the airflow disturbance source are perceived; the pressure information is converted into vortex field characteristics, and the spatial distribution of the strong disturbance region is accurately located; the antenna phase is dynamically adjusted based on the vortex characteristics, and the physical deformation of the array caused by the airflow is directly offset; the deformation compensation result is used to cooperatively correct the beam pointing of multiple machines, and the phase consistency of the distributed array is maintained; finally, a disturbance-resistant directional suppression beam is generated to ensure the continuous and stable interference on the moving target in a strong wind environment.

[0061] Further, the vortex core is located based on the vortex field information, the phase offset amount is calculated in combination with the spatial distribution of the array, the phase offset mode between units is constructed, the phase of the array element is dynamically adjusted through the adjustable unit reverse compensation, and finally the physical deformation compensation result is calibrated and generated. This process converts the fluid disturbance characteristics into hardware-level phase compensation actions, eliminates the geometric distortion of the array within a response period of hundreds of milliseconds, avoids the hysteresis of traditional signal feedback correction, and improves the stability of the beam pointing. BRIEF DESCRIPTION OF DRAWINGS

[0062] In order to more clearly illustrate the technical schemes of the embodiments of the application or the prior art, the drawings needed to be used in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creating any inventive labor.

[0063] Figure 1 A flowchart of a method for cooperative suppression of an unmanned aerial vehicle group based on a distributed antenna array is provided for the embodiments of the application.

[0064] Figure 2 A schematic diagram of the deformation compensation process of the unmanned aerial vehicle antenna array is provided for the embodiments of the application.

[0065] Figure 3 A flow chart of vortex field calculation of downwash flow of a rotor of a UAV is provided for an embodiment of the present application.

[0066] Figure 4 A structural schematic diagram of a UAV swarm cooperative suppression system based on a distributed antenna array is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0067] Research finds that in the UAV swarm cooperative suppression task in a strong wind environment, the existing technology relies on electromagnetic signal feedback to adjust the antenna phase, but ignores a fundamental problem: strong airflow will directly distort the physical structure of the UAV antenna, like strong wind bending the skeleton of a kite, causing flight out of control. This pure software correction is like adjusting the tension of the kite string by observing the kite swing, which cannot perceive the actual bending degree of the skeleton, resulting in that the beam pointing correction is always slow by half a beat - when a strong wind strikes, the antenna physical deformation has already occurred, and the software optimization is still chasing the invalid array state.

[0068] To solve the above problem, the present application proposes a UAV swarm cooperative suppression based on a distributed antenna array. Specifically, the airflow impact position under the rotor is captured through an air pressure sensor, the airflow data is converted into a vortex distribution map, and the strong wind vortex core causing the antenna deformation is accurately locked; then the adjustable metamaterial layer covering the fuselage is driven to bend in real time in the opposite direction, to offset the distortion of the airflow to the antenna from the physical level; finally, the beam direction is calibrated in cooperation with multiple machines to ensure that the suppression signal continuously locks the target. This method first takes the airflow physical disturbance into the compensation closed loop, and from the root source, suppresses the hardware deformation, so that the UAV swarm can still maintain the beam pointing accuracy under the eight-level strong wind, and the response speed is improved compared with the traditional scheme, so that the moving target has no place to hide in the bad weather.

[0069] In order to enable personnel in the technical field to better understand the present application scheme, the present application will be further described in detail below in combination with the drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0070] The core of the present application is to provide a UAV swarm cooperative suppression method based on a distributed antenna array, and a flowchart of a specific embodiment of the method is shown in Figure 1 The method comprises:

[0071] S101, based on the air pressure sensor array carried by the UAV, pressure acquisition and processing of the downwash flow of the rotor of the UAV is performed to obtain airflow pressure distribution information;

[0072] In this step, the airflow pressure distribution information refers to the spatial distribution characteristics of the pressure values formed by the airflow impacting the fluid surface below the unmanned aerial vehicle rotor;

[0073] The pressure acquisition and processing refers to the process of continuously acquiring fluid surface pressure data through an array of air pressure sensors and spatially integrating the data.

[0074] In the embodiments of the present application, first, a high-sensitivity air pressure sensor array is deployed in a grid pattern directly below the rotor to capture pressure values at each position point on the fluid surface; second, the discrete pressure values collected by the sensor nodes are interpolated and reconstructed according to the spatial topological relationship to generate a continuous two-dimensional pressure distribution map; then, adaptive filtering technology is used to eliminate pressure fluctuation noise caused by rotor mechanical vibration and retain the pressure signal under the action of pure airflow; finally, stable and reliable airflow pressure distribution information is output for use by downstream analysis.

[0075] In one actual case, during a coastal strong wind environment mission, the unmanned aerial vehicle group encountered a sudden lateral gust, and the sensor array below the left front rotor detected an abnormally high pressure area of 3.5 pascals. After spatial reconstruction, a left-leaning pressure distribution map was formed, clearly marking the high-pressure core area as the main impact position of the airflow.

[0076] S102, using the airflow pressure distribution information, vortex field calculation and processing are performed on the motion state of the fluid washed by the rotor below the unmanned aerial vehicle to generate vortex field information containing a disturbance region;

[0077] In this step, the vortex field information refers to the spatial distribution state of the rotating vortex formed by the fluid under the action of the rotor shear;

[0078] The vortex field calculation and processing refers to the analysis process of converting pressure distribution data into fluid rotational motion characteristics.

[0079] In the embodiments of the present application, first, the pressure gradient vector field is generated by calculating the pressure change rate between adjacent sensor units based on the pressure distribution map to represent the airflow direction; second, the gradient vector is converted into an instantaneous vorticity intensity distribution through the fluid kinematic vorticity calculation formula; then, the vorticity intensity threshold is set to automatically identify high-vorticity aggregation areas and accurately locate the three-dimensional coordinates of the vortex core; finally, the vortex core motion trajectory within the last ten sampling periods is aggregated to output vortex field information containing the coordinates of the strong disturbance region.

[0080] In the aforementioned case, the gradient vector of the high-pressure area of the left front rotor points to the right side of the belly, and the vorticity analysis shows that a clockwise vortex with a strength of 15 radians per second is formed at this location, and the trajectory aggregation confirms that the vortex core continues to move in the direction of array element No. 3.

[0081] S103, based on the vortex field information, dynamic adjustment processing is performed on the phase of the unmanned aerial vehicle antenna array elements to compensate for the physical deformation of the array, and the array physical deformation compensation result is obtained;

[0082] In this step, the array physical deformation compensation result refers to the calibration state after eliminating the distortion of the antenna structure caused by the airflow;

[0083] The dynamic adjustment process refers to the operation process of driving the tunable hardware to correct the phase deviation.

[0084] In the embodiments of the present application, first, the vortex core position coordinates are extracted according to the vortex field information, and the phase deviation angles of each antenna array element are calculated; second, a spatial transmission model of the phase deviation between array elements is established, and the phase correlation rule of adjacent elements is derived; then, a reverse compensation voltage is applied to the tunable phase element, the dielectric constant of the dielectric substrate is changed through the piezoelectric effect, and a reverse electromagnetic wave is generated to offset the deformation phase difference; finally, the array flatness after compensation is verified by a laser interferometer, and the physical deformation calibration state data is output.

[0085] Continuing the above case, for the vortex threat, it is calculated that the third array element needs to compensate for a phase of twenty degrees, and after the metamaterial reflective layer applies a reverse voltage of five volts, the laser detection confirms that the array surface flatness is restored to an error range of one hundred microns.

[0086] S104, using the array physical deformation compensation result, performing a cooperative phase correction process on the beam pointing of the distributed antenna array to obtain a beam phase compensation amount;

[0087] In this step, the beam phase compensation amount refers to the set of phase adjustment parameters required for cooperative correction of the beam pointing of the distributed antenna.

[0088] The cooperative phase correction process refers to the control process of coordinating the phases of multiple machines to realize spatial synchronization of the beam.

[0089] In the embodiments of the present application, first, the residual position deviation of each array element is analyzed based on the deformation compensation result, and a geometric deformation distribution map is established; second, the single-machine phase compensation amount of each unmanned aerial vehicle is independently calculated according to the beam synthesis principle; then, the compensation amount data of each machine is exchanged through wireless ad hoc networking to construct a multi-machine phase cooperative constraint relationship matrix; finally, a distributed consistency algorithm is used to dynamically adjust the transmission phase of all unmanned aerial vehicles to realize dynamic convergence of the pointing error of the beam main lobe.

[0090] Continuing the above case, the phase compensation amount of the third machine is broadcast to the cluster through the wireless link, and the master machine coordinates the synchronous adjustment of the transmission phase of the remaining four unmanned aerial vehicles, and the ground monitoring station confirms that the pointing angle deviation of the five-machine beam is reduced to within zero point five degrees.

[0091] S105, based on the beam phase compensation amount, performing a cooperative regulation process on the unmanned aerial vehicle group transmission signal to generate a disturbance suppression beam pointing to the target.

[0092] In this step, the disturbance suppression beam refers to a directional high-energy electromagnetic beam generated after resisting the airflow interference;

[0093] The cooperative regulation processing refers to an operation process of integrating multiple signals to generate a spatial focused beam.

[0094] In the embodiments of the present application, first, the beam phase compensation amount is decomposed into carrier frequency, initial phase angle and amplitude parameters of each unmanned aerial vehicle; second, the Beidou timing module is used to align the multi-vehicle signal transmission time reference; then, the power amplifier is controlled to adjust the output power of the radio frequency signal according to the compensation parameters; finally, the principle of electromagnetic wave space interference is used to make the multiple signals coherently superimposed at the target position to form a high-intensity directional beam.

[0095] Continuing the above case, five unmanned aerial vehicles synchronously transmit 800 megahertz radio frequency signals according to the compensation parameters, and the target vehicle receiver detects that the signal-to-interference ratio decreases by 15 decibels, and the command platform confirms that the suppression beam continuously covers the moving target.

[0096] In summary, S101 to S105 capture the rotor airflow pressure distribution through the air pressure sensor array, accurately calculate the fluid vortex disturbance characteristics; based on the vortex position, the antenna phase is dynamically adjusted by the metamaterial reflection layer to offset the array deformation from the physical layer; then, through the distributed cooperative algorithm, the multi-vehicle beam pointing is corrected, and finally, the directional suppression beam resistant to strong wind interference is generated. The full-closed-loop solution of "fluid disturbance perception, hardware compensation, and cluster cooperative control" is formed, which completely overcomes the hysteresis defect of traditional technology relying on electromagnetic feedback, and provides reliable technical support for the continuous suppression task of unmanned aerial vehicle cluster in severe weather environment.

[0097] Optionally, as shown in Figure 2 S103 can specifically include the following steps:

[0098] In order to solve the problem of beam misalignment caused by physical deformation of the unmanned aerial vehicle array under strong wind disturbance, in some embodiments, according to S103, based on the vortex field information, the phase of the unmanned aerial vehicle antenna array element is dynamically adjusted to compensate for the physical deformation of the array, and the array physical deformation compensation result is obtained, including:

[0099] S201, based on the vortex field information, vortex core positioning processing is performed on the disturbance area of the vortex field, and the vortex core position is obtained;

[0100] In S201, the vortex core position refers to the spatial coordinates of the center point of the fluid rotating motion;

[0101] The vortex core positioning processing refers to the operation of identifying the vortex intensity peak area and determining its geometric center.

[0102] In the embodiment of the application, firstly, three-dimensional vortex distribution data in the vortex field information is analyzed, and vortex intensity values of each space unit are extracted; secondly, vortex field gradient change trends are scanned along three orthogonal directions, and gradient vector convergence regions are marked; then, adjacent convergence regions are merged into candidate vortex core regions through a spatial clustering algorithm; and finally, candidate region geometric centroid coordinates are calculated, and a dominant vortex core position is output.

[0103] In S202, the core region phase shift amount refers to a set of phase angle amounts that need to be compensated by an antenna array element corresponding to the vortex core.

[0104] In S202, the core region phase shift amount refers to a set of phase angle amounts that need to be compensated by an antenna array element corresponding to the vortex core.

[0105] The phase shift amount calculation processing refers to an operation of establishing a mapping relationship between fluid disturbance and electromagnetic wave phase deviation.

[0106] In the embodiment of the application, firstly, a three-dimensional space projection model of the vortex core position and the antenna array element is constructed, and the Euclidean distance of each array element to the vortex core is calculated; secondly, according to the proportional relationship between the fluid mechanics pressure gradient and the electromagnetic wave path difference, the signal propagation time delay difference caused by the distance change is derived; then, the time delay difference is converted into a phase lag angle according to the carrier frequency; and finally, a phase shift amount distribution radiating outward from the vortex core is generated.

[0107] In S203, the spatial phase shift mode refers to a set of spatial transmission rules of phase compensation amounts between array elements.

[0108] In S203, the spatial phase shift mode refers to a set of spatial transmission rules of phase compensation amounts between array elements.

[0109] The offset mode construction processing refers to an operation of establishing a phase adjustment amount associated topology network.

[0110] In the embodiment of the application, firstly, spatial correlation coefficients of phase shift amounts of adjacent array elements are analyzed, and a high-correlation element group is identified; secondly, a phase deviation transmission path model is established based on the array geometry configuration, and a path weight coefficient is defined; then, a minimum energy transmission equation under path constraints is solved; and finally, a global element phase cooperative adjustment rule matrix is generated.

[0111] In S204, the array element phase dynamic adjustment result refers to a phase state of an antenna element after hardware compensation.

[0112] In S204, the array element phase dynamic adjustment result refers to a phase state of an antenna element after hardware compensation.

[0113] The reverse compensation processing refers to an operation of driving a tunable material to generate a reverse wave front.

[0114] In the embodiments of the present application, first, the phase adjustment rule is converted into a piezoelectric control voltage signal; second, a reverse bias voltage is applied to the ferroelectric dielectric layer of the tunable unit; then, the dielectric lattice structure is changed through the inverse piezoelectric effect to regulate the spatial distribution of the dielectric constant; finally, a compensation electromagnetic wave opposite to the phase of the deformed wave front is formed on the surface of the dielectric substrate.

[0115] S205, based on the array element phase dynamic adjustment result, performing physical deformation calibration processing on the state of the distributed antenna array after phase adjustment to generate an array physical deformation compensation result.

[0116] In S205, the physical deformation calibration processing refers to an operation of verifying the recovery accuracy of the array geometric structure.

[0117] In the embodiments of the present application, first, a millimeter wave reference test signal is transmitted to irradiate the array surface; second, an interference fringe image formed by array reflection is received; then, the spatial distribution characteristics of the fringe distortion area are analyzed; finally, a deformation elimination verification conclusion and a residual error distribution map are output.

[0118] The following is a specific example:

[0119] In a strong wind environment of the Gobi Desert, the unmanned aerial vehicle cluster encounters a persistent lateral wind shear. First, the right rear rotor area is locked by analyzing the vortex field, and the vortex core is accurately positioned at a specific height above the fourth array element; then, it is calculated that the vortex causes the fourth array element to produce a significant phase lag, and the adjacent array elements appear a gradient attenuation associated offset; then, a phase transfer model is established to confirm that the offset spreads along a specific path of the array; then, a reverse voltage is applied to the metamaterial layer to generate a compensation wave front to offset the deformation; finally, after transmitting the test beam, the interference image shows that the reflected wave front of the array surface is uniformly distributed, and the laser range finder confirms that the flatness error is below the working threshold.

[0120] In summary, S201 to S205 convert the fluid mechanics characteristics into electromagnetic phase compensation parameters by capturing the vortex core position; based on the array spatial topology, a phase coordination rule between units is established; a tunable dielectric is driven to generate a reverse wave front to offset the physical deformation; finally, the geometric structure recovery state is output through interference verification. A closed-loop control chain from environmental disturbance perception to hardware compensation verification is formed, which breaks through the lagging limitation of traditional technology relying on electromagnetic feedback, and provides key technical support for the continuous operation of the unmanned aerial vehicle cluster in severe weather conditions.

[0121] Optionally, as shown in Figure 3 S102 can specifically include the following steps:

[0122] To accurately capture the source of air flow disturbance to drive subsequent hardware compensation, in some embodiments, according to S102, the air flow pressure distribution information is used to perform vortex field calculation processing on the motion state of the downwash flow of the unmanned aerial vehicle rotor, to generate vortex field information containing a disturbance area, including:

[0123] S301, based on the air flow pressure distribution information, performing pressure gradient calculation processing on the surface of the downwash flow of the unmanned aerial vehicle rotor to obtain a pressure gradient vector;

[0124] In S301, the pressure gradient vector refers to the direction and amplitude feature vector of the pressure change between adjacent sensor units on the surface of the fluid;

[0125] The pressure gradient calculation processing refers to the process of establishing a vectorized representation of the pressure space difference.

[0126] In the embodiments of the present application, first, the original pressure values collected by the discrete distributed sensor nodes are loaded into a three-dimensional space grid model, and a pressure distribution surface is constructed according to the node latitude and longitude coordinates; second, the central difference method is used to calculate the first-order partial derivative values of the surface grid in the east-west and north-south directions point by point, to obtain the pressure change rate components; then, the two-direction change rate components are combined to form a two-dimensional gradient vector to determine the pressure change direction and intensity at each position; finally, an adaptive sliding window filter is used to eliminate the high-frequency fluctuation components caused by rotor mechanical vibration, retain the steady-state gradient characteristics dominated by the air flow, and output a spatially continuous pressure gradient vector field.

[0127] S302, using the pressure gradient vector to perform vorticity calculation processing on the rotational intensity of the fluid motion of the downwash flow of the unmanned aerial vehicle rotor, to generate an instantaneous vorticity distribution;

[0128] In S302, the instantaneous vorticity distribution refers to the spatial field distribution characteristics of the rotation angular velocity of the fluid clusters;

[0129] The vorticity calculation processing refers to the process of converting the pressure gradient into a rotational mechanical parameter through fluid dynamics equations.

[0130] In the embodiments of the present application, first, a Navier-Stokes dynamics correlation model of the pressure gradient vector and the fluid velocity field is established, and the differential conversion relationship between the gradient field and the rotational motion is defined; second, the vorticity component of the velocity field is solved in the three-dimensional spatial domain, and the pressure gradient integral is converted into the rotation angular velocity value through Green's formula; then, the Laplace smoothing algorithm is used to correct the spatial continuity of the discrete vorticity values to eliminate sudden points caused by calculation noise; finally, the angular velocity value is mapped to the spatial grid nodes to generate a global instantaneous vorticity intensity distribution map.

[0131] S303, based on the instantaneous vorticity distribution, performing instantaneous vortex identification processing on the high-vorticity concentrated area of the vortex field to obtain an instantaneous vortex core position;

[0132] In S303, the instantaneous vortex core position refers to the spatial coordinates of the rotating vortex center point.

[0133] The instantaneous vortex identification processing is an operation of specifying the geometric center of the local vorticity extreme region.

[0134] In the embodiments of the present application, first, an adaptive double-threshold segmentation algorithm is used to extract a significant high-vorticity region based on global statistical features of the vorticity field; second, a morphological closing operation is used to connect spatially adjacent high-vorticity units and fill local holes to form a continuous region; third, the weighted centroid coordinates of the vorticity intensity of each connected region are calculated, and a spatial weighted average is performed with the vorticity value as the weight factor; and finally, the three-dimensional position coordinates of the vortex core are determined in combination with the height sensor data, and the spatial positioning result of the dominant vortex core is output.

[0135] S304, using the instantaneous vortex core position, spatial aggregation processing is performed on the vortex trajectory of the vortex field in a continuous time window to generate a stable vortex spatial distribution pattern;

[0136] In S304, the stable vortex spatial distribution pattern refers to a set of vortex motion rules after random disturbances are eliminated.

[0137] The spatial aggregation processing refers to an operation of integrating time-series trajectories to form spatial probability features.

[0138] In the embodiments of the present application, first, the vortex core position moving path is tracked in a continuous time sequence, and three-dimensional coordinate data at each sampling time is recorded; second, a Kalman filter algorithm is used to eliminate trajectory jitter caused by measurement noise and predict the actual motion trajectory; third, a polynomial curve fitting is used to establish a vortex core movement trend model, and a prediction value of the position at a future time is calculated; and finally, a vortex spatial distribution probability density map based on a Gaussian mixture model is constructed to represent the stable motion law.

[0139] S305, based on the stable vortex spatial distribution pattern, a strong disturbance marking processing is performed on a region exceeding the vorticity threshold of the vortex field to generate vortex field information containing the disturbed region.

[0140] In S305, the strong disturbance marking processing refers to an operation of identifying a high-risk vortex region according to a threat level.

[0141] In the embodiments of the present application, first, a vorticity safety threshold model trained by a historical flight database is loaded, which integrates wind speed, altitude, and aircraft configuration parameters; second, the spatial probability density in the stable distribution pattern is weighted and fused with the vorticity intensity to generate a comprehensive threat coefficient matrix; third, the spatial grid unit with a threat coefficient exceeding a dynamic threshold is marked as a high-risk disturbance area; and finally, the high-risk area boundary coordinates, core position, and threat level are encapsulated as a structured vortex field information data packet.

[0142] The following is a specific example:

[0143] In a coastal gust environment real combat task, the UAV cluster encountered intermittent sea and land wind alternation. First, the left rotor below the air pressure sensor array detected a strip-shaped high pressure area, and the gradient calculation found that there was a continuous pressure mutation zone in the direction of the belly, and the gradient vector showed that the airflow converged to the tail; the vorticity calculation revealed that the area formed a clockwise vortex of fifteen radians per second, and the vortex core was identified to be stably located three meters above the side of the second array element; the vortex core was observed to move along a parabolic trajectory to the tail for ten consecutive sampling periods, and the Kalman filter and curve fitting confirmed that it continued to affect the third to fifth array element areas; finally, according to the fusion threat coefficient model, the area was labeled as a third-level strong disturbance area, and the vortex field information containing boundary coordinates and core position was output.

[0144] In summary, S301 to 305 establish a fluid motion trend model through spatial analysis of pressure gradient vectors, realizing accurate conversion of pressure data to rotational vorticity fields; capture instantaneous vortex cores based on morphological and weighted centroid positioning techniques, and construct stable motion patterns using time series filtering and curve fitting; use a dynamic threat coefficient model to calibrate strong disturbance areas and generate vortex field information that can drive hardware compensation. Form a full-chain processing capability from raw pressure sensing to intelligent disturbance identification, breaking through the technical bottleneck of traditional methods for transient airflow response lag, providing high-precision spatial reference for feedforward compensation of array physical deformation.

[0145] To overcome the problem of beam mismatch caused by physical deformation in multi-machine cooperation, in some embodiments, according to S104, the array physical deformation compensation result is used for cooperative phase correction processing of the beam pointing of the distributed antenna array, to obtain a beam phase compensation amount, including:

[0146] S401, based on the array physical deformation compensation result, the geometric deviation of the distributed antenna array is calculated and processed based on the distribution characteristics, to obtain an array geometric deviation distribution;

[0147] In S401, the array geometric deviation distribution refers to a set of topological features that quantitatively describe the spatial displacement of the array elements and their propagation rules;

[0148] The distribution characteristic calculation and processing refers to an operation of extracting spatial correlation patterns from deformation data.

[0149] In the embodiment of the application, first, displacement correction vector components of each array element in the three-dimensional Cartesian coordinate system in the deformation compensation result are extracted; second, a continuous displacement field function model of the array surface is constructed by using a thin plate spline interpolation algorithm, and a spatial displacement distribution is fitted by a radial basis function; then, a gradient change rate is obtained by calculating a first-order partial derivative of the displacement field function in the X and Y planes, and a curvature distribution feature is obtained by solving a second-order partial derivative; finally, a geometric deviation distribution heat map with a spatial propagation path is generated by fusing a gradient direction vector and a curvature intensity scalar.

[0150] In S402, the single-machine phase compensation quantity refers to a complete set of single-machine full-array phase correction parameters.

[0151] In S402, the single-machine phase compensation quantity refers to a complete set of single-machine full-array phase correction parameters.

[0152] The independent compensation quantity calculation processing refers to a mapping and conversion process of geometric deformation to electromagnetic phase parameters.

[0153] In the embodiment of the application, first, a mapping relationship between an array displacement vector and an electromagnetic wave path difference is established based on a geometric optics ray tracing model, and a signal propagation path increment is calculated by three-dimensional space projection; second, the path increment is converted into a phase lag angle according to a carrier frequency characteristic, and a phase angle that each array element needs to compensate is calculated by using a wavelength and phase conversion formula; then, a signal transmission topology structure of an array feed network is analyzed, and a transfer characteristic of phase compensation in a feed link is analyzed; finally, an array element level compensation instruction set containing amplitude and phase parameters is generated.

[0154] In S403, the multi-machine phase collaborative correction relationship refers to a constraint library defining a multi-unmanned aerial vehicle phase parameter linkage rule.

[0155] In S403, the multi-machine phase collaborative correction relationship refers to a constraint library defining a multi-unmanned aerial vehicle phase parameter linkage rule.

[0156] The correction relationship construction processing refers to an operation of establishing a machine group level phase collaboration framework.

[0157] In the embodiment of the application, first, time division multiplexing wireless channel is used to exchange each machine phase compensation quantity data set; second, a spatial correlation analysis method is used to calculate a phase coupling coefficient between machines, and a symmetric matrix reflecting a phase interference intensity is constructed; then, a constrained quadratic programming problem is constructed by taking minimization of a main lobe width of a beam synthesis pattern as an objective function; finally, a multi-machine phase weight correlation rule library satisfying a beam focusing condition is obtained by solving.

[0158] S404, performing joint phase correction processing on the pointing of the beams of the distributed antenna array by using the multi-machine cooperative correction relationship, to obtain a cooperative phase dynamic correction result;

[0159] In S404, the cooperative phase dynamic correction result refers to the convergence state after the multi-machine joint phase adjustment.

[0160] The joint phase correction processing refers to the operation of coordinating the multi-machine to implement compensation synchronously.

[0161] In the embodiments of the present application, first, the cooperative rule base is parsed into a time division phase control instruction sequence executable by each machine; second, the Beidou satellite timing system and the PTP precise clock protocol are used to realize microsecond-level instruction execution time synchronization; then, the liquid crystal tunable unit is driven to adjust the birefringence according to the instruction sequence, and the optical properties of the medium substrate are changed by electrically controlling the molecular orientation; finally, a closed-loop feedback mechanism is used to collect the phase of each array element radiation field, and the multi-machine phase convergence state is verified.

[0162] S405, based on the cooperative phase dynamic correction result, performing compensation amount integration processing on the corrected beam phase to generate a beam phase compensation amount.

[0163] In S405, the compensation amount integration processing refers to the operation of optimizing, verifying and packaging the final phase parameters.

[0164] In the embodiments of the present application, first, the actual radiation phase distribution of each array element is obtained by scanning with a near-field probe array; second, a residual cloud map of the target phase model and the measured value is constructed to identify the systematic deviation area; then, the conjugate gradient optimization algorithm is used to iteratively adjust the compensation parameters; finally, the beam control parameter set verified by the far-field pattern is packaged.

[0165] The following is a specific example:

[0166] In a certain cross-sea strong wind environment operation task, five unmanned aerial vehicle clusters encountered non-uniform airflow impact. First, the displacement of the array element of the first machine is parsed from the deformation compensation data, and the displacement vector points upward; the second machine belly array element has a sinking displacement; the third to fifth machines present a gradient tilt deformation. By constructing a displacement field model through a thin plate spline algorithm, it is found that the deformation propagates in a corrugated shape along the wing span. In the independent compensation stage, according to the twenty-four gigahertz carrier characteristics, the three millimeter sinking displacement of the second machine is converted into a twelve degree phase lag. In the cooperative construction stage, the five machine data are exchanged through the wireless network, and the spatial correlation analysis reveals that the phase coupling coefficient of the third and fourth machines reaches zero point nine. In the joint correction stage, the Beidou system is used to realize three hundred microsecond-level synchronization of the five machines, and the liquid crystal unit is driven to adjust the birefringence to generate a compensation wavefront. Finally, the near-field scanning shows that the residual error is less than three degrees, and the far-field test confirms that the beam main lobe focusing performance meets the standard.

[0167] In summary, S401 to S405 accurately capture the deformation space propagation rule by geometric displacement field modeling, establish a deterministic mapping link from mechanical deformation to electromagnetic parameters; build a multi-machine phase coupling constraint system, crack the beam splitting problem caused by independent compensation of distributed systems; achieve joint regulation of multiple units by using nanosecond-level time synchronization technology; and finally output high-reliability beam control parameters through near-far field joint verification. Form a "deformation feature extraction, electromagnetic parameter conversion, cluster collaborative optimization, joint execution verification" technical closed loop, which fundamentally solves the beam instability problem of distributed arrays in strong wind environment and realizes the sustained and accurate coverage capability of the suppressed beam in severe weather conditions.

[0168] To achieve accurate hardware compensation for phase shift caused by air flow disturbance, according to S204, in some embodiments, the spatial phase shift pattern is used to perform inverse compensation processing on the tunable phase units of the distributed antenna array, and the array element phase dynamic adjustment result is obtained, including:

[0169] S501, based on the spatial phase shift pattern, compensating direction determination processing is performed on the shift direction of the unmanned aerial vehicle antenna array element phase to generate a compensation direction vector;

[0170] In S501, the compensation direction vector refers to the dominant change trend vector feature of the phase deviation extracted from the spatial phase shift pattern in three-dimensional space;

[0171] The compensation direction determination processing refers to the operation of identifying the maximum phase shift trend direction through spatial pattern analysis.

[0172] In the embodiments of the present application, first, covariance matrix calculation is performed on the three-dimensional data set of the spatial phase shift pattern to solve the eigenvalues and eigenvectors thereof; second, the eigenvector corresponding to the maximum eigenvalue is selected as the dominant shift direction reference axis; third, the eigenvector is decomposed into an azimuth angle component and a pitch angle component; fourth, the direction cosine component is calculated through the conversion formula from the spherical coordinate system to the rectangular coordinate system; and finally, the direction cosine is unit vectorized to generate a standardized compensation direction vector, which accurately represents the main direction of the phase shift that needs to be compensated.

[0173] S502, using the compensation direction vector, inverse vector value calculation processing is performed on the tunable unit phase adjustment value of the unmanned aerial vehicle antenna array element phase to generate a phase inverse adjustment value;

[0174] In S502, the phase inverse adjustment value refers to a set of compensation control parameters that need to be applied to offset the original phase shift;

[0175] The inverse vector value calculation processing refers to the operation of deriving inverse control parameters according to the compensation direction.

[0176] In the embodiments of the present application, first, a projection conversion model of the compensation direction vector and the local coordinate system of each array element is established, and the projection component of the vector on the array element plane is calculated; second, the pre-stored phase and voltage response characteristic curve is queried to obtain the basic compensation coefficient corresponding to the projection component; then, the optimal compensation step is calculated through a dynamic programming algorithm combined with the transient response characteristic of the tunable unit and the historical compensation record; finally, the reverse adjustment parameter package containing the voltage amplitude, action duration and change slope is generated by synthesizing the basic coefficient and the compensation step.

[0177] S503, based on the phase reverse adjustment amount, performing resonance parameter adjustment processing on the tunable unit resonance characteristic of the unmanned aerial vehicle antenna array element phase to obtain a resonance parameter dynamic update result;

[0178] In S503, the resonance parameter dynamic update result refers to the electromagnetic response state of the dielectric characteristic change of the tunable unit;

[0179] The resonance parameter adjustment processing refers to the operation of driving the hardware medium to realize electromagnetic characteristic reconstruction.

[0180] In the embodiments of the present application, first, the reverse adjustment parameter package is parsed into a differential voltage control time sequence signal; second, a time sequence voltage is applied to the transparent electrode of the liquid crystal tunable unit to form a spatial gradient electric field distribution; then the liquid crystal molecules are driven to rotate by the electric field force to change the spatial distribution of their birefringence; finally, the unit scattering parameters are monitored by a vector network analyzer, and the parameter update state is confirmed according to the resonance frequency offset and the quality factor change.

[0181] S504, using the resonance parameter dynamic update result, performing dynamic balance processing on the inter-element phase consistency of the unmanned aerial vehicle antenna array element phase to generate a phase balance state;

[0182] In S504, the phase balance state refers to the cooperative stable state after the phase difference between the array elements is eliminated;

[0183] The dynamic balance processing refers to a closed-loop adjustment operation for maintaining the phase cooperation of multiple units.

[0184] In the embodiments of the present application, first, the instantaneous phase difference of adjacent elements is collected by a near-field coupling probe; second, a transfer function model of the phase difference and voltage correction is constructed; then, the voltage fine adjustment amount is dynamically calculated by using a digital PID controller; again, a frequency traction mechanism between elements is established by using a distributed phase-locked loop technology; finally, when the phase difference of all elements is stable within the set threshold, a balance verification signal is output.

[0185] S505, based on the phase balance state, performing dynamic adjustment confirmation processing on the compensated unmanned aerial vehicle antenna array element phase to generate an array element phase dynamic adjustment result.

[0186] In S505, the dynamic adjustment confirmation processing refers to an operation of verifying the compensation effect through a test signal.

[0187] In the embodiments of the present application, first, a linear frequency modulation test signal covers the working frequency band; second, the array surface reflection signal is collected through a receiving probe array; then, a comparison heat map of the phase distribution before and after compensation is generated by a digital signal processor; then, the improvement degree of the phase distribution uniformity is quantified by principal component analysis; finally, an adjustment result authentication report containing the phase standard deviation and peak shift is output.

[0188] The following is a specific example:

[0189] In a certain strong wind environment real-time measurement task on a Gobi desert, the UAV cluster encountered a sudden lateral wind shear. First, the spatial phase shift pattern was analyzed to find that the maximum shift direction was thirty degrees in the nose-up direction, and the standardized compensation direction vector was extracted by principal component analysis; in the inverse vector value calculation stage, the vector was projected into the local coordinate system of the third array element, and the adjustment parameter package that needs to apply a negative step voltage was generated by combining historical compensation data; during the resonant parameter adjustment, a twelve-volt starting voltage was applied to the liquid crystal cell electrode, and the resonant frequency moved three hundred megahertz to a lower frequency at a slope of zero point five volts per millisecond; during the dynamic balance stage, it was detected that there was a phase difference in the fourth adjacent unit, and the phase difference was adjusted to zero by a PID controller; finally, a two to thirty-two hertz sweep signal was transmitted, and the phase distribution graph showed that the array consistency was improved to the standard level, and the system generated an adjustment compliance authentication.

[0190] To sum up, S501 to S505 accurately capture the dominant direction of phase shift by spatial pattern analysis to generate a compensation vector, calculate the optimal inverse control parameters based on projection conversion and dynamic programming; achieve dielectric property reconstruction by electric field regulation of liquid crystal molecule orientation; maintain the phase consistency between units by closed-loop feedback and phase-locked technology; finally, verify the compensation effect by sweep test and phase distribution analysis. Form a complete technical closed loop of "direction recognition, parameter calculation, hardware reconstruction, collaborative balance, effect authentication", break through the response speed and precision limitations of traditional phase correction, and realize the high-precision phase self-compensation ability of hundreds of milliseconds in complex airflow environment.

[0191] In order to solve the problem of beam pointing misalignment caused by response delay of distributed array in multi-machine cooperation, in some embodiments, according to S404, the pointing direction of the beam of the distributed antenna array is jointly phase-corrected based on the multi-machine cooperative correction relationship, and the cooperative phase dynamic correction result is obtained, including:

[0192] S601, based on the multi-machine cooperative correction relationship, a joint correction direction calculation process is performed on the multi-machine beam pointing deviation of the distributed antenna array to generate a joint correction direction;

[0193] In S601, the joint correction direction refers to a collaborative adjustment dominant vector of cluster beam pointing error in a three-dimensional space;

[0194] The joint correction direction calculation processing refers to an operation of generating a global optimal adjustment reference by fusing multiple machine error data.

[0195] In the embodiments of the present application, first, the inter-machine phase coupling strength matrix in the collaborative correction relationship database and the independent pointing deviation data of each machine are analyzed; second, an optimization function with the maximum beam synthesis directional diagram main lobe gain as the target is constructed, which includes three constraint conditions of azimuth deviation, elevation deviation and phase coupling weight; then, a quasi-Newton iterative algorithm with constraints is used to solve the gradient field of the target function; then, the principal axis direction of the gradient field is extracted through eigenvalue decomposition; finally, the principal axis direction is converted into a three-dimensional unit direction vector containing azimuth cosine and elevation cosine, to generate a spatial reference vector guiding the collaborative adjustment of multiple machines.

[0196] S602, using the joint correction direction, performing dynamic amplitude allocation processing on the phase collaborative adjustment requirement to generate a phase collaborative adjustment amount;

[0197] In S602, the phase collaborative adjustment amount refers to a collaborative allocation scheme of phase compensation parameters of each unmanned aerial vehicle.

[0198] The dynamic amplitude allocation processing refers to an operation of dynamically allocating adjustment resources according to spatial positions and threat levels.

[0199] In the embodiments of the present application, first, a rotation transformation model of the joint direction vector and the local coordinate system of each machine is established, and the projection component of the direction vector in the reference system of each machine is calculated; second, the projection weight coefficient is calculated according to the spatial geometric position of the unmanned aerial vehicle relative to the target; then, the threat level evaluation matrix is constructed by fusing airflow disturbance monitoring data; then, the threat level is converted into a resource allocation priority through a fuzzy decision algorithm; finally, the projection weight and the priority coefficient are subjected to tensor product operation to generate a parameter set of phase adjustment amplitude, action time and change rate of each unmanned aerial vehicle.

[0200] S603, based on the phase collaborative adjustment amount, performing phase response processing on the tunable phase units of the distributed antenna array to generate a phase response parameter;

[0201] In S603, the phase response parameter refers to the electromagnetic response state of the tunable unit to the control instruction.

[0202] The phase response processing refers to an operation of driving hardware to perform electromagnetic characteristic reconstruction.

[0203] In the embodiment of the application, first, the phase adjustment parameter package is parsed into a voltage control waveform timing signal, including a rising edge slope, a steady-state amplitude and a duration; second, a timing voltage waveform is applied to the interdigital electrodes of the liquid crystal tunable unit to form a spatial gradient electric field in the dielectric layer; then the orientation rotation of the liquid crystal molecules is driven by the electric field force to change the spatial distribution of the birefringence; finally, the scattering parameter matrix is collected by a vector network analyzer, the resonance frequency shift, bandwidth change and quality factor fluctuation characteristics are analyzed, and an electromagnetic response state report is generated.

[0204] S604, using the phase response parameter, synchronously compensating the unit phase of the distributed antenna array to obtain a phase synchronization compensation result;

[0205] In S604, the phase synchronization compensation result refers to the convergence state of the phase matching between multiple machine units.

[0206] The synchronous compensation processing refers to a closed-loop adjustment operation to realize the spatiotemporal consistency of the cluster phase.

[0207] In the embodiment of the application, first, the instantaneous phase distribution of the radiation field of each machine is collected by a near-field probe array; second, a phase difference rate differential equation between adjacent units is constructed; then, a distributed consensus algorithm is used to calculate the compensation voltage fine adjustment amount of each machine; then, the fine adjustment instruction execution timing is coordinated through a high-precision clock synchronization network; finally, when the time integral value of the phase difference between all units converges to a set tolerance band, a phase lock completion signal is output.

[0208] S605, based on the phase synchronization compensation result, dynamically correcting and confirming the multi-machine phase coordination state of the distributed antenna array to generate a coordinated phase dynamic correction result.

[0209] In S605, the dynamic correction and confirmation processing refers to an operation of verifying the coordination effect through spatial scanning and signal analysis.

[0210] In the embodiment of the application, first, a step frequency sweep test signal is transmitted to cover the working frequency band; second, a spatial signal intensity distribution is collected by a distributed receiver array; then, a compressed sensing algorithm is used to reconstruct a three-dimensional beam pattern; then, main lobe pointing angle accuracy, sidelobe suppression ratio and beam width characteristic parameters are extracted; finally, a correction result authentication report containing spatial focusing performance indicators is output.

[0211] The following is a specific example:

[0212] In a cross-sea strong wind confrontation mission, a cluster composed of four unmanned aerial vehicles (UAVs) performs continuous suppression on a moving target. First, a joint calibration direction of an azimuth angle of 62 degrees and a pitch angle of 8 degrees is parsed from a cooperative calibration relationship database; in a dynamic allocation stage, the third UAV is given the maximum adjustment weight according to its threat state at the main wind port; in a phase response processing stage, an 18-volt peak voltage is applied to the liquid crystal unit of the third UAV, and it is monitored that the resonant frequency migrates to a high frequency of 450 megahertz; in a synchronization compensation stage, the four UAVs complete phase matching within 500 microseconds through a consensus algorithm, and the maximum phase difference between the signal display units is less than 3 degrees; finally, the direction pattern reconstructed by step frequency scanning shows that the main lobe pointing accuracy reaches 0.2 degrees, the sidelobe suppression is better than 25 decibels, and the system generates a cooperative calibration standard certification.

[0213] To sum up, S601 to S605 establish a global cooperative reference through joint calibration direction calculation, realize resource optimization allocation based on threat perception dynamic allocation; drive the tunable medium to complete electromagnetic property reconstruction, and realize accurate phase matching of multiple machines through a distributed consensus mechanism; finally, the spatial scanning verifies the performance of the beam spatial focusing. A full-closed-loop technology chain of "reference establishment, resource allocation, hardware reconstruction, cooperative locking, and effect verification" is formed, which breaks through the beam splitting defect caused by asynchronous response of traditional distributed systems, and realizes the ability of microsecond-level multi-machine beam spatial synchronization control in a complex electromagnetic environment.

[0214] In order to accurately construct the phase cooperative relationship between array units to realize efficient hardware compensation, in some embodiments, according to S203, based on the core area phase offset, a phase relationship offset mode construction process between units of the distributed antenna array is performed to obtain a spatial phase offset mode, including:

[0215] S701, based on the core area phase offset, a dominant offset identification process of the array area phase offset of the distributed antenna array is performed to generate a dominant phase offset;

[0216] In S701, the dominant phase offset refers to a set of key unit phase offset parameters with global influence identified from the core area phase offset;

[0217] The dominant offset identification process is an operation of specifying a dominant phase disturbance source.

[0218] In the embodiments of the present application, first, the core area phase offset is subjected to spatial density clustering analysis, and a high-density offset unit cluster is identified through a density peak detection algorithm; second, the variance contribution rate of the offset of each unit cluster is calculated to analyze its influence weight on the global phase distribution; third, a unit cluster with a contribution rate exceeding a preset judgment condition is selected as a dominant offset source; finally, the phase offset angle and spatial coordinate information of all units in the dominant offset source are extracted to generate a structured dominant phase offset data set.

[0219] S702, offset transfer calculation processing is performed on the adjacent array unit phase relationship of the distributed antenna array using the dominant phase offset, to generate an inter-unit phase transfer relationship;

[0220] In S702, the inter-unit phase transfer relationship refers to a mathematical model quantitatively describing the propagation rule of the phase offset of adjacent units;

[0221] The offset transfer calculation processing refers to the operation of establishing a phase disturbance space diffusion model.

[0222] In the embodiments of the present application, first, a three-dimensional space adjacency topology network graph of the array units is constructed, and the geometric distance and orientation relationship between units are labeled; second, a phase offset transfer differential equation is established based on the elastic wave propagation similarity principle, and a transfer coefficient of the offset decay with distance is defined; third, the dominant phase offset is input as a boundary condition into the transfer equation for finite element discretization solution; and finally, the phase coupling strength matrix and transfer direction vector set between adjacent units are obtained.

[0223] S703, based on the inter-unit phase transfer relationship, smooth transition processing is performed on the partition boundary phase continuity of the distributed antenna array to generate a boundary smooth phase distribution;

[0224] In S703, the boundary smooth phase distribution refers to a continuous phase field distribution that eliminates phase jumps at the partition junction;

[0225] The smooth transition processing refers to an operation that realizes high-order continuity of the phase field.

[0226] In the embodiments of the present application, first, the phase value mutation point of the partition boundary unit is detected, and the gradient discontinuity position is located; second, a transition surface control grid is constructed using a bicubic spline interpolation algorithm, and a transition control point is inserted in the mutation area; third, the transition surface morphology is optimized based on the minimum curvature energy functional, to ensure the continuity of the first derivative; and finally, the boundary smooth phase distribution field that satisfies the second-order differentiable condition is generated through surface parameterization mapping.

[0227] S704, using the boundary smooth phase distribution, spatial mode integration processing is performed on the global unit phase offset of the distributed antenna array to generate an initial spatial phase offset mode;

[0228] In S704, the initial spatial phase offset mode refers to a preliminary continuous distribution model of the global phase offset;

[0229] The spatial mode integration processing refers to an operation of constructing a global unified phase field.

[0230] In the embodiments of the present application, firstly, the boundary smooth phase distribution is taken as the Dirichlet boundary condition; secondly, a phase field harmonic functional is constructed based on the variational principle, and a gradient square integral minimization target is defined; then, the Euler and Lagrange equations are discretized and solved by using the finite difference method; finally, the global steady-state phase distribution solution is obtained by using the multi-grid iteration algorithm, and an initial spatial phase shift pattern matrix is generated.

[0231] In S705, the abnormal correction processing of the mode phase jump region of the distributed antenna array is performed based on the initial spatial phase shift pattern, and a spatial phase shift pattern is generated.

[0232] In S705, the abnormal correction processing refers to an operation of eliminating local singularity of the phase field and ensuring physical realizability.

[0233] In the embodiments of the present application, firstly, the Sobel operator is used to detect the phase gradient jump region in the initial pattern; secondly, an anisotropic diffusion algorithm is applied for adaptive smoothing, and the edge features are retained along the phase contour direction; then, the local unit phase value is adjusted through topological optimization to meet the super material processing constraint condition; finally, the phase distribution physical rationality is verified by using the Lorenz curve fitting, and the spatial phase shift pattern that can drive the compensation hardware is output.

[0234] The following is a specific example:

[0235] In a certain coastal strong wind environment measurement task, the unmanned aerial vehicle array detects that there is a significant phase shift in the third array element region. Firstly, the third unit cluster is identified as the dominant shift source by density clustering, and the variance contribution rate exceeds the determination threshold; secondly, a transfer model is established according to the array topology, and it is solved that the fifth unit needs to be compensated; then, the phase jump is detected at the boundary of the second and fourth partitions, and a transition surface is constructed by using the cubic spline interpolation to realize smooth connection; then, the global continuous phase field is generated by using the variational principle; finally, the gradient jump is found in the seventh unit region, and the spatial phase shift pattern that meets the compensation requirements of the liquid crystal tuning unit is output after the distortion is eliminated by the anisotropic diffusion.

[0236] In summary, S701 to S705 accurately locate the key disturbance nodes through the dominant shift source, establish a phase space diffusion model based on the physical transfer law, realize seamless transition at the partition boundary by using high-order continuous surface technology, construct a global unified phase field based on the variational principle, and finally ensure the physical realizability of the pattern through adaptive smoothing and topological optimization. A complete technical chain of "core positioning, spatial transmission, boundary fusion, global integration, and abnormal optimization" is formed, which breaks through the local limitations of traditional phase modeling and provides a high-precision spatial phase reference for hardware-level compensation.

[0237] Figure 4A structural schematic diagram of a specific embodiment of a kind of unmanned aerial vehicle group cooperative suppression system based on distributed antenna array provided for the embodiment of the present application, refer to Figure 4 The system can include:

[0238] A pressure acquisition module 41 is used for acquiring and processing the pressure of the downwash fluid of the unmanned aerial vehicle rotor based on the air pressure sensor array carried by the unmanned aerial vehicle, to obtain air flow pressure distribution information;

[0239] A vortex calculation module 42 is used for calculating and processing the vortex field of the motion state of the downwash fluid of the unmanned aerial vehicle rotor based on the air flow pressure distribution information, to generate vortex field information containing a disturbance region;

[0240] A phase compensation module 43 is used for dynamically adjusting and processing the phase of the unmanned aerial vehicle antenna array element based on the vortex field information to compensate for the physical deformation of the array, to obtain an array physical deformation compensation result;

[0241] A beam correction module 44 is used for performing cooperative phase correction processing on the beam pointing of the distributed antenna array using the array physical deformation compensation result, to obtain a beam phase compensation amount;

[0242] A cooperative suppression module 45 is used for performing cooperative regulation processing on the unmanned aerial vehicle group transmission signal based on the beam phase compensation amount, to generate a disturbance-resistant suppression beam pointing to the target.

[0243] The unmanned aerial vehicle group cooperative suppression system based on distributed antenna array of the embodiment of the present application is used to implement the aforementioned unmanned aerial vehicle group cooperative suppression method based on distributed antenna array, so the specific embodiments in the unmanned aerial vehicle group cooperative suppression system based on distributed antenna array can refer to the embodiment part of the unmanned aerial vehicle group cooperative suppression method based on distributed antenna array in the foregoing, and the specific embodiments can refer to the description of the corresponding embodiment part, which will not be described here.

[0244] The present application also provides an electronic device, comprising: a memory for storing a computer program; a processor for executing the computer program to implement the steps of the above-mentioned any one of the unmanned aerial vehicle group cooperative suppression method based on distributed antenna array.

[0245] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the above-mentioned any one of the unmanned aerial vehicle group cooperative suppression method based on distributed antenna array.

[0246] In one exemplary embodiment, the above-mentioned computer readable storage medium can include but is not limited to: U disk, read-only memory, random access memory, mobile hard disk, magnetic disk or optical disk and various computer program storage media.

[0247] An embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program realizes the steps in any of the above-mentioned embodiments of the method for suppressing a UAV group based on a distributed antenna array when executed by a processor.

[0248] Those skilled in the art will further appreciate that the units and algorithms described in connection with the examples disclosed herein can be embodied directly in hardware, in software, or in a combination of the two. For ease of understanding, descriptions of functional units and algorithms have been generally described herein in their general form without reference to the specific internal structure of the hardware or software. Whether a functional unit is implemented in hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0249] The above provides a method, system, electronic device and storage medium for suppressing a UAV group based on a distributed antenna array. The principles and implementation modes of the present application are described by applying specific examples. The above descriptions of the examples are only used to help understand the method of the present application and its core idea. It should be pointed out that, for those skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the present application.

Claims

1. A method for coordinated suppression of unmanned aerial vehicle (UAV) swarms based on a distributed antenna array, characterized in that, include: Based on the barometric pressure sensor array onboard the drone, pressure data of the downwash fluid from the drone rotor is collected and processed to obtain airflow pressure distribution information. Using the airflow pressure distribution information, the motion state of the downwash fluid of the UAV rotor is calculated and processed to generate vortex field information containing the disturbance region. Based on the eddy current field information, the phase of the UAV antenna array elements is dynamically adjusted to compensate for the physical deformation of the array, resulting in a physical deformation compensation result. This includes: locating the vortex core in the disturbance region of the eddy current field based on the eddy current field information to obtain the vortex core position; calculating the phase offset of the element spatial distribution of the distributed antenna array using the vortex core position to generate a core region phase offset; constructing an offset mode for the phase relationship between the elements of the distributed antenna array based on the core region phase offset to obtain a spatial phase offset mode; performing phase inversion compensation on the tunable phase elements of the distributed antenna array using the spatial phase offset mode to obtain a dynamic phase adjustment result for the array elements; and performing physical deformation calibration on the state of the distributed antenna array after phase adjustment based on the dynamic phase adjustment result for the array elements to generate a physical deformation compensation result for the array. Using the physical deformation compensation results of the array, the beam pointing of the distributed antenna array is subjected to coordinated phase correction processing to obtain the beam phase compensation amount; Based on the beam phase compensation amount, the signals transmitted by the UAV swarm are coordinated and processed to generate an anti-disturbance suppression beam pointing towards the target.

2. The method according to claim 1, characterized in that, Using the airflow pressure distribution information, the motion state of the downwash fluid from the UAV rotor is calculated using eddy current field analysis to generate eddy current field information including the disturbance region, including: Based on the airflow pressure distribution information, the pressure gradient of the surface of the downwash fluid from the UAV rotor is calculated to obtain the pressure gradient vector; Using the pressure gradient vector, the vorticity of the fluid motion rotation intensity of the UAV rotor underwash fluid is calculated to generate an instantaneous vorticity distribution; Based on the instantaneous vorticity distribution, instantaneous vortex identification processing is performed on the high vorticity concentration region of the vortex field to obtain the instantaneous vortex core position. Using the instantaneous vortex core position, the vortex trajectory of the vortex field within a continuous time window is spatially aggregated to generate a stable vortex spatial distribution pattern. Based on the stable vortex spatial distribution pattern, regions exceeding the vorticity threshold of the vortex field are subjected to strong disturbance marking processing to generate vortex field information containing the disturbance region.

3. The method according to claim 1, characterized in that, Using the physical deformation compensation results of the array, a coordinated phase correction process is performed on the beam pointing of the distributed antenna array to obtain the beam phase compensation amount, including: Based on the physical deformation compensation results of the array, the geometric deviation of the distributed antenna array is calculated to obtain the array geometric deviation distribution. Using the array geometric deviation distribution, the phase deviation of the UAV antenna array elements is independently calculated and processed to generate the single-unit phase compensation amount; Based on the single-machine phase compensation amount, the multi-machine phase coordination relationship of the UAV antenna array element phase is corrected and a multi-machine coordination correction relationship is generated. Using the aforementioned multi-machine cooperative correction relationship, joint phase correction processing is performed on the beam pointing of the distributed antenna array to obtain cooperative phase dynamic correction results; Based on the collaborative phase dynamic correction results, the corrected beam phase is integrated with the compensation amount to generate the beam phase compensation amount.

4. The method according to claim 1, characterized in that, Using the spatial phase offset mode, the tunable phase elements of the distributed antenna array are subjected to phase inversion compensation processing to obtain the dynamic phase adjustment results of the array elements, including: Based on the aforementioned spatial phase offset mode, the offset direction of the UAV antenna array element phase is determined by compensation direction determination processing to generate a compensation direction vector. Using the compensation direction vector, the phase adjustment value of the tunable unit of the UAV antenna array is calculated by inverse vector value to generate the phase inverse adjustment amount; Based on the phase reversal adjustment amount, the resonant parameters of the tunable unit resonant characteristics of the UAV antenna array element phase are adjusted to obtain the dynamic update result of the resonant parameters. Using the dynamic update results of the resonance parameters, the phase consistency between the elements of the UAV antenna array is dynamically balanced to generate a phase balance state. Based on the phase balance state, the phase of the UAV antenna array elements after compensation is dynamically adjusted and confirmed to generate the dynamic adjustment result of the array element phase.

5. The method according to claim 3, characterized in that, Using the aforementioned multi-machine cooperative correction relationship, joint phase correction processing is performed on the beam pointing of the distributed antenna array to obtain cooperative phase dynamic correction results, including: Based on the multi-machine cooperative correction relationship, the joint correction direction calculation is performed on the multi-machine beam pointing deviation of the distributed antenna array to generate the joint correction direction. Using the joint correction direction, the phase coordination adjustment requirement is dynamically allocated to generate the phase coordination adjustment amount; Based on the phase coordination adjustment amount, the tunable phase element of the distributed antenna array is subjected to phase response processing to generate phase response parameters; Using the phase response parameters, the phase of the unit cells of the distributed antenna array is synchronized to obtain the phase synchronization compensation result. Based on the phase synchronization compensation results, the multi-machine phase coordination state of the distributed antenna array is dynamically corrected and confirmed to generate a coordinated phase dynamic correction result.

6. The method according to claim 1, characterized in that, Based on the phase offset of the core region, the phase relationship between the elements of the distributed antenna array is processed to construct an offset mode, resulting in a spatial phase offset mode, including: Based on the phase offset of the core region, the phase offset of the array region of the distributed antenna array is subjected to dominant offset identification processing to generate dominant phase offset. Using the dominant phase offset, the phase relationship between adjacent array elements of the distributed antenna array is calculated and processed to generate the phase transfer relationship between elements; Based on the phase transfer relationship between the units, the phase continuity of the partition boundary of the distributed antenna array is smoothed to generate a smooth phase distribution at the boundary. Using the boundary smooth phase distribution, the global element phase offset of the distributed antenna array is subjected to spatial mode integration processing to generate an initial spatial phase offset mode. Based on the initial spatial phase offset mode, anomaly correction processing is performed on the mode phase change region of the distributed antenna array to generate a spatial phase offset mode.

7. A UAV swarm cooperative suppression system based on a distributed antenna array, applied to the UAV swarm cooperative suppression method based on a distributed antenna array as described in any one of claims 1-6, characterized in that, include: The pressure acquisition module is used to collect and process the pressure of the downwash fluid from the UAV rotor based on the air pressure sensor array mounted on the UAV, and obtain airflow pressure distribution information. The eddy current calculation module is used to perform eddy current field calculation processing on the motion state of the downwash fluid of the UAV rotor using the airflow pressure distribution information, and generate eddy current field information containing the disturbance region. The phase compensation module is used to dynamically adjust the phase of the UAV antenna array elements based on the eddy current field information to compensate for the physical deformation of the array and obtain the array physical deformation compensation result. The beam correction module is used to perform coordinated phase correction processing on the beam pointing of the distributed antenna array using the array physical deformation compensation results, so as to obtain the beam phase compensation amount. The collaborative suppression module is used to perform collaborative modulation and processing on the signals transmitted by the UAV swarm based on the beam phase compensation amount, and generate an anti-disturbance suppression beam pointing towards the target.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the UAV swarm cooperative suppression method based on a distributed antenna array as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the implementation of the UAV swarm cooperative suppression method based on a distributed antenna array as described in any one of claims 1 to 6.

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