An antenna aperture parameter self-adaptive regulation method and device based on environment cognition

Abstract

The application discloses an antenna aperture parameter self-adaptive regulation and control device and method based on environment cognition, and the device comprises an antenna module, a power amplifier module, an ADC module, a DBF module and a self-adaptive regulation and control module; the antenna module is used for receiving electromagnetic signals; the power amplifier module is connected with the antenna module and the ADC module respectively, and is used for performing power amplification processing on the received electromagnetic signals to obtain amplified signals; the ADC module is used for performing digital sampling processing on the amplified signals to obtain digital signals; the DBF module is connected with the ADC module and the self-adaptive regulation and control module respectively, and is used for performing beam forming processing on the digital signals to obtain beam forming signals; and the self-adaptive regulation and control module is used for performing self-adaptive adjustment on the beam forming signals to obtain adjusted signals, so that the effect of self-adaptive regulation and control on the antenna aperture parameters of the device is realized.

Description

Technical Field

[0001] This invention relates to the fields of radar technology, intelligent sensing and intelligent antenna technology, and specifically to an adaptive control method and device for antenna aperture parameters based on environmental cognition. Background Technology

[0002] Traditional RF array apertures use an analog phased array system, and the aperture parameters need to be preset, lacking the ability to optimize and adjust according to changes in the environment and hardware status. Traditional aperture tuning uses an open-loop control strategy, which queries and sets the pre-stored tuning state from a table based on the current operating frequency band or simple sensor signals. This results in an inability to respond in real time to changes in the electromagnetic environment caused by unpredictable factors such as user interaction, thus limiting the tuning accuracy and adaptability. Summary of the Invention

[0003] This invention primarily addresses the problem of how to respond in real time to changes in the electromagnetic environment caused by unpredictable factors such as user interaction, thereby improving the spatial accuracy and adaptability of tuned antennas. This invention discloses an adaptive control method and device for antenna aperture parameters based on environmental awareness.

[0004] In a first aspect, the present invention discloses an adaptive control device for antenna aperture parameters based on environmental cognition, comprising: an antenna module, a power amplifier module, an ADC module, a DBF module, and an adaptive control module; The antenna module is used to receive electromagnetic signals; The power amplifier module is connected to the antenna module and the ADC module respectively, and is used to amplify the power of the received electromagnetic signal to obtain an amplified signal. The ADC module is used to perform digital sampling processing on the amplified signal to obtain a digital signal; The DBF module is connected to the ADC module and the adaptive control module respectively, and is used to perform beamforming processing on the digital signal to obtain a beamforming signal. The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal, so as to achieve the effect of adaptive control of the antenna aperture parameters of the device.

[0005] The antenna module includes: a dielectric substrate, an impedance transformation line, a Double-Y balun structure, a dipole antenna element, and a frequency selective surface; The dielectric substrate includes a top dielectric substrate and a bottom dielectric substrate; both the top dielectric substrate and the bottom dielectric substrate have rectangular slots, and the rectangular slots of the top dielectric substrate and the bottom dielectric substrate are orthogonally arranged to achieve a dual-polarization structure. The top layer dielectric plate is disposed above the bottom layer dielectric plate; The impedance transformation line is disposed on the top dielectric substrate, and the two ends of the impedance transformation line are respectively connected to the Double-Y balun structure and the ADC module. The impedance transformation line is used to achieve impedance matching of the antenna module; The Double-Y balun structure is connected to the impedance transformation line and the butterfly-shaped tightly coupled dipole antenna element, respectively. The surface of the dipole antenna element is provided with a frequency selective surface; The dipole antenna element is used to receive electromagnetic waves in space; The frequency selection surface is used to allow electromagnetic waves within a preset frequency band to pass through, thereby achieving a bandpass filtering effect.

[0006] The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal, including: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

[0007] A second aspect of this invention discloses an adaptive control method for antenna aperture parameters based on environmental awareness, implemented using the aforementioned adaptive control device for antenna aperture parameters based on environmental awareness, comprising: Electromagnetic signals are received using the antenna module. The received electromagnetic signal is amplified using the power amplifier module to obtain an amplified signal. The amplified signal is digitally sampled using the ADC module to obtain a digital signal. Using the DBF module, beamforming is performed on the digital signal to obtain a beamformed signal; The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal.

[0008] The adaptive adjustment of the beamforming signal using the adaptive control module to obtain the adjusted signal includes: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

[0009] The signal correction model, constructed based on the received electromagnetic signal and beamforming signal, includes: Using the antenna module, a preset standard signal is received; The preset standard signal is input into the radio frequency link consisting of a power amplifier module, an ADC module, and a DBF module in sequence to obtain the output signal of the DBF module and the output signal of the power amplifier module. A DBF correction model is constructed by performing a DBF correction model on the standard signal and the output signal of the DBF module to obtain the DBF correction model; A nonlinear suppression model is constructed for the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model. Based on the DBF correction model and the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0010] The signal correction model constructed based on the DBF correction model and the radio frequency nonlinear suppression model includes: Use the input terminal of the DBF correction model as the input terminal of the signal correction model; The output of the radio frequency nonlinear suppression model is used as the output of the signal correction model; By connecting the output of the DBF correction model and the input of the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0011] The step of constructing a DBF correction model from the standard signal and the DBF module output signal to obtain the DBF correction model includes: The preset standard signal is sequentially input to the antenna module at multiple different incident angles to obtain the DBF module output signal at each incident angle; A directional response sample set is constructed using the DBF module output signals at all incident angles; the directional response sample set includes the DBF module output signals at all incident angles. Based on the aforementioned directional response sample set, a spatial domain error cost function is constructed. , The expression is: , in: This represents the total number of sampling directions. They represent the first The elevation and azimuth angles of each incident direction; Let be the ideal array manifold vector, representing the weighted response that should be in this direction under ideal conditions; For the DBF module output signal in the k-th direction, This represents the number of antenna elements. The digital beamforming correction weight matrix is ​​the solution to be found. Number of output beam channels; The DBF correction model is obtained by solving the spatial domain error cost function.

[0012] A third aspect of the present invention discloses an adaptive control device for antenna aperture parameters based on environmental cognition, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the adaptive control method for antenna aperture parameters based on environmental awareness.

[0013] In a fourth aspect of this invention, a computer-readable storage medium is disclosed, wherein the computer-readable storage medium stores computer instructions, which, when invoked by a computer, are used to execute the aforementioned adaptive control method for antenna aperture parameters based on environmental awareness.

[0014] A fifth aspect of the present invention discloses an information data processing terminal, which is used to implement the aforementioned adaptive control method for antenna aperture parameters based on environmental cognition.

[0015] The beneficial effects of this invention are as follows: This invention proposes an aperture adaptive control method that adapts to unfamiliar environments and unknown object waveforms, enabling it to adaptively control and nonlinearly equalize and optimize according to changes in the environment and hardware status. In time-varying and complex environments, it achieves optimal suppression of background noise and optimal radio frequency compatibility through beamforming, sidelobe nulling, and frequency domain adaptive filtering, avoiding mutual interference between the sidelobe radiation power and the frequency usage of other devices when high-power interference occurs.

[0016] The dielectric substrate in the antenna module consists of a top dielectric substrate and a bottom dielectric substrate, which play a crucial role in realizing the dual-polarization structure. Both the top and bottom dielectric substrates have rectangular slots, and these slots are orthogonally arranged. This orthogonal arrangement is the core principle behind the dual-polarization structure. In electromagnetism, polarization refers to the orientation of an electric field vector in space. The dual-polarization structure can simultaneously support the transmission or reception of signals with two different polarizations, such as horizontal and vertical polarization, or ±45° polarization. When electromagnetic waves are incident on this orthogonally arranged dielectric substrate, the different orientations of the rectangular slots result in different responses to electromagnetic waves with different polarization directions. For horizontally polarized electromagnetic waves, the rectangular slots of the top dielectric substrate may have a specific coupling effect, while the orthogonal rectangular slots of the bottom dielectric substrate couple vertically polarized electromagnetic waves. In this way, the coordinated operation of the top and bottom dielectric substrates enables effective processing of electromagnetic waves with different polarization directions, thereby realizing a dual-polarization structure. This greatly improves the antenna's signal transmission and reception capabilities, allowing it to work better in complex communication environments. Simultaneously, it can transmit or receive signals with different polarization characteristics, increasing communication capacity and reliability.

[0017] This invention effectively suppresses various interferences and significantly optimizes anti-interference capabilities by constructing a signal correction model. During communication, the presence of interference signals can severely affect communication quality and even lead to communication interruptions. Traditional anti-interference methods often fail to comprehensively consider various interference factors, resulting in unsatisfactory effects. The device of this invention, through in-depth analysis of received electromagnetic signals and beamforming signals, constructs a DBF correction model and a radio frequency nonlinear suppression model, thereby obtaining a signal correction model. The DBF correction model can accurately correct signals at different incident angles, compensating for errors caused by changes in the signal incident angle, improving beamforming accuracy, and thus enhancing the reception capability of useful signals while suppressing interference signals. The radio frequency nonlinear suppression model can effectively suppress the nonlinear distortion generated by the power amplifier module, reducing the resulting interference. In satellite communication, signals are easily interfered with by natural factors such as solar storms. The device of this invention can effectively suppress interference signals through the signal correction model, ensuring normal satellite communication and improving the survivability and reliability of the communication system in complex interference environments. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention; Figure 2 This is a schematic diagram of the antenna module of the present invention. Detailed Implementation

[0019] To better understand the content of this invention, an embodiment is provided here.

[0020] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention. Figure 2 This is a schematic diagram of the antenna module of the present invention.

[0021] In a first aspect, the present invention discloses an adaptive control device for antenna aperture parameters based on environmental cognition, comprising: an antenna module, a power amplifier module, an ADC module, a DBF module, and an adaptive control module; The antenna module is used to receive electromagnetic signals; The power amplifier module is connected to the antenna module and the ADC module respectively, and is used to amplify the power of the received electromagnetic signal to obtain an amplified signal. The ADC module is used to perform digital sampling processing on the amplified signal to obtain a digital signal; The DBF module is connected to the ADC module and the adaptive control module respectively, and is used to perform beamforming processing on the digital signal to obtain a beamforming signal. The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal, so as to achieve the effect of adaptive control of the antenna aperture parameters of the device.

[0022] The antenna module includes: a dielectric substrate, an impedance transformation line, a Double-Y balun structure, a butterfly-shaped tightly coupled dipole antenna element, and a frequency selective surface; The dielectric substrate includes a top dielectric substrate and a bottom dielectric substrate; both the top dielectric substrate and the bottom dielectric substrate have rectangular slots, and the rectangular slots of the top dielectric substrate and the bottom dielectric substrate are orthogonally arranged to achieve a dual-polarization structure. The top layer dielectric plate is disposed above the bottom layer dielectric plate; The impedance transformation line is disposed on the top dielectric substrate, and the two ends of the impedance transformation line are respectively connected to the Double-Y balun structure and the ADC module. The impedance transformation line is used to achieve impedance matching of the antenna module; The Double-Y balun structure is connected to the impedance transformation line and the butterfly-shaped tightly coupled dipole antenna element, respectively. The surface of the butterfly-shaped tightly coupled dipole antenna element is provided with a frequency selective surface; The butterfly-shaped tightly coupled dipole antenna element is used to receive electromagnetic waves in space; The frequency selection surface is used to allow electromagnetic waves within a preset frequency band to pass through, thereby achieving a bandpass filtering effect.

[0023] Impedance matching lines are positioned on the top dielectric substrate, connecting to the Double-Y balun structure and the ADC module at both ends. Their primary function is to achieve impedance matching for the antenna module. Impedance matching is a crucial concept in radio frequency (RF) circuits. If impedance is mismatched, signal reflection occurs during transmission, leading to energy loss and reduced communication quality. The impedance matching line acts as a bridge, adjusting its impedance characteristics to achieve good impedance matching between the antenna module and subsequent circuitry (such as the ADC module), ensuring efficient signal transmission and reducing signal reflection and energy loss. The Double-Y balun structure is connected to the impedance matching line and the butterfly-shaped tightly coupled dipole antenna element. It is a balun, primarily used to convert unbalanced signals to balanced signals and vice versa. In antenna systems, this conversion is significant for reducing electromagnetic interference, improving system efficiency, and optimizing impedance matching. For example, it can convert single-ended signals into differential signals, helping to suppress common-mode noise and enhance the overall performance of the RF circuit. The butterfly-shaped tightly coupled dipole antenna element has a frequency-selective surface on its surface for receiving electromagnetic waves in space. Its unique shape and structural design give it excellent electromagnetic wave reception capabilities, effectively capturing electromagnetic signals from the surrounding environment. The frequency selective surface allows electromagnetic waves within a preset frequency band to pass through, achieving a bandpass filtering effect. It acts like a frequency filter, allowing only specific frequency bands of electromagnetic waves to pass while blocking other frequency bands. This effectively reduces the intrusion of external interference signals, improves the antenna's reception quality of target signals, ensures the antenna can accurately receive signals in the required frequency band even in complex electromagnetic environments, and enhances the reliability and stability of communication.

[0024] The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal, including: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

[0025] The signal correction model, constructed based on the received electromagnetic signal and beamforming signal, includes: Using the antenna module, a preset standard signal is received; The preset standard signal is input into the radio frequency link consisting of a power amplifier module, an ADC module, and a DBF module in sequence to obtain the output signal of the DBF module and the output signal of the power amplifier module. A DBF correction model is constructed by performing a DBF correction model on the standard signal and the output signal of the DBF module to obtain the DBF correction model; A nonlinear suppression model is constructed for the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model. Based on the DBF correction model and the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0026] The signal correction model constructed based on the DBF correction model and the radio frequency nonlinear suppression model includes: Use the input terminal of the DBF correction model as the input terminal of the signal correction model; The output of the radio frequency nonlinear suppression model is used as the output of the signal correction model; By connecting the output of the DBF correction model and the input of the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0027] The step of constructing a DBF correction model from the standard signal and the DBF module output signal to obtain the DBF correction model includes: The preset standard signal is sequentially input to the antenna module at multiple different incident angles to obtain the DBF module output signal at each incident angle; A directional response sample set is constructed using the DBF module output signals at all incident angles; the directional response sample set includes the DBF module output signals at all incident angles. Based on the aforementioned directional response sample set, a spatial domain error cost function is constructed. , The expression is: , in: This represents the total number of sampling directions. They represent the first The elevation and azimuth angles of each incident direction; Let be the ideal array manifold vector, representing the weighted response that should be in this direction under ideal conditions; For the DBF module output signal in the k-th direction, This represents the number of antenna elements. The digital beamforming correction weight matrix is ​​the solution to be found. Number of output beam channels; The DBF correction model is obtained by solving the spatial domain error cost function.

[0028] Solving the spatial domain error cost function to obtain the DBF correction model includes: The error cost function is minimized using an iterative gradient descent approach. The update rules are as follows: in Step size factor The number of iterations, the gradient term Calculated using numerical difference or automatic differentiation methods; When the change in cost function between two consecutive iterations is less than a preset threshold, or when the maximum number of iterations is reached, the iteration stops, and the final result is obtained. As the DBF corrected weight matrix; Establish a two-dimensional lookup table structure based on the incident direction. Use the index key to store the corresponding corrected weight vector. ,in ; The DBF correction model consists of a lookup table and an online interpolation module. It is used to dynamically call and generate corrected beamforming coefficients based on the estimated signal arrival direction during real-time operation. The corrected beamforming coefficients are multiplied with the output signal of the DBF module to obtain an intermediate signal. The online interpolation module is then used to interpolate the intermediate signal to obtain the output signal of the DBF correction model.

[0029] The nonlinear suppression model is constructed by applying a nonlinear suppression model to the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model, including: Obtain the amplification factor A of the power amplifier module; Multiplying the standard signal by the amplification factor A yields the amplified standard signal; Using the amplified standard signal as the output and the output signal of the power amplifier module as the input, a function is fitted to the input and output to obtain the first suppression model. A second suppression model is obtained by performing power amplification nonlinearity modeling on the standard signal and the output signal of the power amplifier module. The first and second suppression models are fused together to obtain the radio frequency nonlinear suppression model.

[0030] The function fitting can be performed using a multinomial loss function fitting method; The second suppression model is obtained by performing power amplification nonlinearity modeling on the standard signal and the output signal of the power amplifier module, including: A set of single-frequency sinusoidal signals with different power levels are used as standard signals and input to the power amplifier module. The amplitude of the input signals is recorded. With the corresponding output signal amplitude and the phase shift of the input and output signals ,in , This represents the number of test points; Construct the input-output amplitude response curve and phase distortion curve, and express them as functional relationships: in, Describe the gain compression characteristics. Describe the AM-PM conversion effect; Constructing inverse nonlinear mapping functions in the digital domain and Specifically, this is achieved through piecewise polynomial fitting: Input signal amplitude range Divided into Each subinterval; within each subinterval, for and By performing piecewise polynomial fitting and solving separately, we obtain... and The solution value; based on and The solution value is obtained, and the corresponding inverse function is obtained. and ; Based on inverse function and The second suppression model is constructed, and its expression is: , in, Let x be the output of the second suppression model and x be the input. This represents the phase of the input quantity x; Within each sub-interval, for and By performing piecewise polynomial fitting and solving separately, we obtain... and The solution values ​​include: Within each subinterval, a third-order polynomial approximation method is used to construct the function to be solved. Its expression is: in Let be the target input amplitude after predistortion, and be the output of the function to be solved. Let be the desired output amplitude, be the input to the function to be solved, and be the coefficients. Determined by minimizing the sum of squared local residuals; right The solution value is obtained by constructing a piecewise linear function, the expression of which is: , , Let be the phase offset between the input and output signals of the j-th sub-interval; The nonlinear modeling of the power amplification is implemented by the piecewise inverse function, phase compensation lookup table and dynamic predistortion kernel method, and is deployed before the ADC module or digital front end to perform predistortion processing on the input signal to compensate for the nonlinear distortion in the power amplification process.

[0031] The step of fusing the first suppression model and the second suppression model to obtain the radio frequency nonlinear suppression model includes: The amplified standard signal is used as the output. The output signal of the power amplifier module is used as the input, and then input into the first suppression model and the second suppression model respectively to obtain the corresponding output signal. The output signals of the first and second suppression models are compared with the amplified standard signal to calculate the difference and obtain the corresponding weight values. Using the weight values ​​of the first and second suppression models, a weighted sum is performed on the first and second suppression models to obtain the radio frequency nonlinear suppression model.

[0032] The step of using the weight values ​​of the first suppression model and the second suppression model to perform a weighted summation of the first suppression model and the second suppression model involves multiplying the weight value of the first suppression model with the first suppression model to obtain a first result, multiplying the weight value of the second suppression model with the second suppression model to obtain a second result, and multiplying the first result and the second result to obtain the radio frequency nonlinear suppression model.

[0033] The difference calculation includes: The output signal of the first suppression model or the second suppression model is discretely sampled with the amplified standard signal to obtain the model output sequence and the standard sequence, respectively. The difference sequence is obtained by subtracting the output sequence of the model from the standard sequence. Statistical calculations were performed on the differential sequences to obtain the median, mode, and kurtosis. The second-order central moments and second-order raw moments are calculated on the differential sequences to obtain the second-order central moments and second-order raw moments; The median, mode, kurtosis, second central moment, and second origin moment are fused and calculated to obtain the corresponding weight values.

[0034] The expression for the fusion calculation is: , in, Indicates the weight value. express function, Let represent the median, mode, kurtosis, second central moment, and second raw moment, respectively.

[0035] A second aspect of this invention discloses an adaptive control method for antenna aperture parameters based on environmental awareness, implemented using the adaptive control device for antenna aperture parameters based on environmental awareness, comprising: Electromagnetic signals are received using the antenna module. The power amplifier module is used to amplify the received electromagnetic signal to obtain an amplified signal. The amplified signal is digitally sampled using the ADC module to obtain a digital signal. Using the DBF module, beamforming is performed on the digital signal to obtain a beamformed signal; The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal.

[0036] The process of adaptively adjusting the beamforming signal using the adaptive control module to obtain the adjusted signal includes: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

[0037] The signal correction model, constructed based on the received electromagnetic signal and beamforming signal, includes: Using the antenna module, a preset standard signal is received; The preset standard signal is input into the radio frequency link consisting of a power amplifier module, an ADC module, and a DBF module in sequence to obtain the output signal of the DBF module and the output signal of the power amplifier module. A DBF correction model is constructed by performing a DBF correction model on the standard signal and the output signal of the DBF module to obtain the DBF correction model; A nonlinear suppression model is constructed for the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model. Based on the DBF correction model and the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0038] The signal correction model constructed based on the DBF correction model and the radio frequency nonlinear suppression model includes: Use the input terminal of the DBF correction model as the input terminal of the signal correction model; The output of the radio frequency nonlinear suppression model is used as the output of the signal correction model; By connecting the output of the DBF correction model and the input of the radio frequency nonlinear suppression model, a signal correction model is constructed.

[0039] The step of constructing a DBF correction model from the standard signal and the DBF module output signal to obtain the DBF correction model includes: The preset standard signal is sequentially input to the antenna module at multiple different incident angles to obtain the DBF module output signal at each incident angle; A directional response sample set is constructed using the DBF module output signals at all incident angles; the directional response sample set includes the DBF module output signals at all incident angles. Based on the aforementioned directional response sample set, a spatial domain error cost function is constructed. , The expression is: , in: This represents the total number of sampling directions. They represent the first The elevation and azimuth angles of each incident direction; Let be the ideal array manifold vector, representing the weighted response that should be in this direction under ideal conditions; The DBF module outputs a signal in the k-th direction. This represents the number of antenna elements. The digital beamforming correction weight matrix is ​​the solution to be found. Number of output beam channels; The DBF correction model is obtained by solving the spatial domain error cost function.

[0040] The spatial domain error cost function formula constructed in this invention can accurately evaluate the error between the DBF module output signal and the ideal signal. By considering multiple factors such as the total number of sampling directions, the elevation and azimuth angles of different incident directions, the ideal array manifold vector, and the DBF module output signal, it comprehensively measures the degree of difference between the actual output signal and the ideal signal. This formula provides an accurate basis for constructing the DBF correction model, enabling us to adjust the digital beamforming correction weight matrix in a targeted manner according to the magnitude and distribution of the error, thereby improving the accuracy of beamforming, enhancing the signal directionality and gain, effectively suppressing interference signals, and improving the performance of the communication system.

[0041] Solving the spatial domain error cost function to obtain the DBF correction model includes: The error cost function is minimized using an iterative gradient descent approach. The update rules are as follows: in Step size factor For the number of iterations, the gradient term Calculated using numerical difference or automatic differentiation methods; When the change in cost function between two consecutive iterations is less than a preset threshold, or when the maximum number of iterations is reached, the iteration stops, and the final result is obtained. As the DBF corrected weight matrix; Establish a two-dimensional lookup table structure based on the incident direction. Use the index key to store the corresponding corrected weight vector. ,in ; The DBF correction model consists of a lookup table and an online interpolation module. It is used to dynamically call and generate corrected beamforming coefficients based on the estimated signal arrival direction during real-time operation. The corrected beamforming coefficients are multiplied with the output signal of the DBF module to obtain an intermediate signal. The online interpolation module is then used to interpolate the intermediate signal to obtain the output signal of the DBF correction model.

[0042] The nonlinear suppression model is constructed by applying a nonlinear suppression model to the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model, including: Obtain the amplification factor A of the power amplifier module; Multiplying the standard signal by the amplification factor A yields the amplified standard signal; Using the amplified standard signal as the output and the output signal of the power amplifier module as the input, a function is fitted to the input and output to obtain the first suppression model. A second suppression model is obtained by performing power amplification nonlinearity modeling on the standard signal and the output signal of the power amplifier module. The first and second suppression models are fused together to obtain the radio frequency nonlinear suppression model.

[0043] The function fitting can be performed using a multinomial loss function fitting method; The second suppression model is obtained by performing power amplification nonlinearity modeling on the standard signal and the output signal of the power amplifier module, including: A set of single-frequency sinusoidal signals with different power levels are used as standard signals and input to the power amplifier module. The amplitude of the input signals is recorded. With the corresponding output signal amplitude and the phase shift of the input and output signals ,in , This represents the number of test points; Construct the input-output amplitude response curve and phase distortion curve, and express them as functional relationships: in, Describe the gain compression characteristics. Describe the AM-PM conversion effect; Constructing inverse nonlinear mapping functions in the digital domain and Specifically, this is achieved through piecewise polynomial fitting: Input signal amplitude range Divided into Each subinterval; within each subinterval, for and By performing piecewise polynomial fitting and solving separately, we obtain... and The solution value; based on and The solution value is obtained, and the corresponding inverse function is obtained. and ; Based on inverse function and The second suppression model is constructed, and its expression is: , in, Let x be the output of the second suppression model and x be the input. This represents the phase of the input quantity x; Within each sub-interval, for and By performing piecewise polynomial fitting and solving separately, we obtain... and The solution values ​​include: Within each subinterval, a third-order polynomial approximation method is used to construct the function to be solved. Its expression is: in Let be the target input amplitude after predistortion, and be the output of the function to be solved. Let be the desired output amplitude, be the input to the function to be solved, and be the coefficients. Determined by minimizing the sum of squared local residuals; right The solution value is obtained by constructing a piecewise linear function, the expression of which is: , , Let be the phase offset between the input and output signals of the j-th sub-interval; The nonlinear modeling of the power amplification is implemented by the piecewise inverse function, phase compensation lookup table and dynamic predistortion kernel method, and is deployed before the ADC module or digital front end to perform predistortion processing on the input signal to compensate for the nonlinear distortion in the power amplification process.

[0044] The step of fusing the first suppression model and the second suppression model to obtain the radio frequency nonlinear suppression model includes: The amplified standard signal is used as the output. The output signal of the power amplifier module is used as the input, and then input into the first suppression model and the second suppression model respectively to obtain the corresponding output signal. The output signals of the first and second suppression models are compared with the amplified standard signal to calculate the difference and obtain the corresponding weight values. Using the weight values ​​of the first and second suppression models, a weighted sum is performed on the first and second suppression models to obtain the radio frequency nonlinear suppression model.

[0045] The step of using the weight values ​​of the first suppression model and the second suppression model to perform a weighted summation of the first suppression model and the second suppression model involves multiplying the weight value of the first suppression model with the first suppression model to obtain a first result, multiplying the weight value of the second suppression model with the second suppression model to obtain a second result, and multiplying the first result and the second result to obtain the radio frequency nonlinear suppression model.

[0046] The difference calculation includes: The output signal of the first suppression model or the second suppression model is discretely sampled with the amplified standard signal to obtain the model output sequence and the standard sequence, respectively. The difference sequence is obtained by subtracting the output sequence of the model from the standard sequence. Statistical calculations were performed on the differential sequences to obtain the median, mode, and kurtosis. The second-order central moments and second-order raw moments are calculated on the differential sequences to obtain the second-order central moments and second-order raw moments; The median, mode, kurtosis, second central moment, and second origin moment are fused and calculated to obtain the corresponding weight values.

[0047] The expression for the fusion calculation is: , in, Indicates the weight value. express function, Let represent the median, mode, kurtosis, second central moment, and second raw moment, respectively.

[0048] The construction of the RF nonlinearity suppression model involves multiple formulas that model and suppress the nonlinear distortion of the power amplifier from different perspectives. By obtaining the amplification coefficient of the power amplifier module, amplifying the standard signal, and then employing a series of operations including multinomial loss function fitting and power amplification nonlinearity modeling, the first and second suppression models were obtained. These models consider the nonlinear characteristics of the power amplifier from different aspects, such as gain compression characteristics and AM-PM conversion effects. Through the construction and analysis of the input-output amplitude response curve and phase distortion curve, as well as the construction of the inverse nonlinear mapping function, the nonlinear distortion in the power amplification process is effectively offset. By fusing these models and comprehensively considering the influence of multiple factors on the signal, the linearity of the signal is further improved, signal distortion is reduced, and thus communication quality is improved, enabling the communication system to operate stably in more complex environments.

[0049] In the calculation expressions of this invention, the variables involved have all been dimensionless before calculation.

[0050] In all embodiments of the present invention, the values ​​of the independent variables in the input of all computational expressions or mathematical functions meet the reasonable requirements of the input range of the computational expressions or mathematical functions, and can ensure that the computational expressions or mathematical functions can be calculated smoothly without violating physical laws or mathematical rules.

[0051] A third aspect of the present invention discloses an adaptive control device for antenna aperture parameters based on environmental cognition, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the adaptive control method for antenna aperture parameters based on environmental awareness.

[0052] In a fourth aspect of this invention, a computer-readable storage medium is disclosed, wherein the computer-readable storage medium stores computer instructions, which, when invoked by a computer, are used to execute the aforementioned adaptive control method for antenna aperture parameters based on environmental awareness.

[0053] A fifth aspect of the present invention discloses an information data processing terminal, which is used to implement the aforementioned adaptive control method for antenna aperture parameters based on environmental cognition.

[0054] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. An adaptive control device for antenna aperture parameters based on environmental cognition, characterized in that, include: Antenna module, power amplifier module, ADC module, DBF module, and adaptive control module; The antenna module is used to receive electromagnetic signals; The power amplifier module is connected to the antenna module and the ADC module respectively, and is used to amplify the power of the received electromagnetic signal to obtain an amplified signal. The ADC module is used to perform digital sampling processing on the amplified signal to obtain a digital signal; The DBF module is connected to the ADC module and the adaptive control module respectively, and is used to perform beamforming processing on the digital signal to obtain a beamforming signal. The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal.

2. The adaptive antenna aperture parameter control device based on environmental cognition as described in claim 1, characterized in that, The antenna module includes: a dielectric substrate, an impedance transformation line, a Double-Y balun structure, a dipole antenna element, and a frequency selective surface; The dielectric substrate includes a top dielectric substrate and a bottom dielectric substrate; both the top dielectric substrate and the bottom dielectric substrate have rectangular slots, and the rectangular slots of the top dielectric substrate and the bottom dielectric substrate are orthogonally arranged to achieve a dual-polarization structure. The top layer dielectric plate is disposed above the bottom layer dielectric plate; The impedance transformation line is disposed on the top dielectric substrate, and the two ends of the impedance transformation line are respectively connected to the Double-Y balun structure and the ADC module. The impedance transformation line is used to achieve impedance matching of the antenna module; The Double-Y balun structure is connected to the impedance transformation line and the butterfly-shaped tightly coupled dipole antenna element, respectively. The surface of the dipole antenna element is provided with a frequency selective surface; The dipole antenna element is used to receive electromagnetic waves in space; The frequency selection surface is used to allow electromagnetic waves within a preset frequency band to pass through, thereby achieving a bandpass filtering effect.

3. The adaptive control device for antenna aperture parameters based on environmental cognition as described in claim 2, characterized in that, The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal, including: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

4. An adaptive control method for antenna aperture parameters based on environmental cognition, characterized in that, This is achieved using the adaptive antenna aperture parameter control device based on environmental awareness as described in any one of claims 1 to 3, comprising: Electromagnetic signals are received using the antenna module. The received electromagnetic signal is amplified using the power amplifier module to obtain an amplified signal. The amplified signal is digitally sampled using the ADC module to obtain a digital signal. Using the DBF module, beamforming is performed on the digital signal to obtain a beamformed signal; The adaptive control module is used to adaptively adjust the beamforming signal to obtain the adjusted signal.

5. The adaptive control method for antenna aperture parameters based on environmental cognition as described in claim 4, characterized in that, The adaptive adjustment of the beamforming signal using the adaptive control module to obtain the adjusted signal includes: A signal correction model is constructed based on the received electromagnetic signal and beamforming signal; The beamforming signal is processed using the signal correction model to obtain the adjusted signal.

6. The adaptive control method for antenna aperture parameters based on environmental cognition as described in claim 5, characterized in that, The signal correction model, constructed based on the received electromagnetic signal and beamforming signal, includes: Using the antenna module, a preset standard signal is received; The preset standard signal is input into the radio frequency link consisting of a power amplifier module, an ADC module, and a DBF module in sequence to obtain the output signal of the DBF module and the output signal of the power amplifier module. A DBF correction model is constructed by performing a DBF correction model on the standard signal and the output signal of the DBF module to obtain the DBF correction model; A nonlinear suppression model is constructed for the standard signal and the output signal of the power amplifier module to obtain the radio frequency nonlinear suppression model. Based on the DBF correction model and the radio frequency nonlinear suppression model, a signal correction model is constructed.

7. The adaptive control method for antenna aperture parameters based on environmental cognition as described in claim 6, characterized in that, The signal correction model constructed based on the DBF correction model and the radio frequency nonlinear suppression model includes: Use the input terminal of the DBF correction model as the input terminal of the signal correction model; The output of the radio frequency nonlinear suppression model is used as the output of the signal correction model; By connecting the output of the DBF correction model and the input of the radio frequency nonlinear suppression model, a signal correction model is constructed.

8. The adaptive control method for antenna aperture parameters based on environmental cognition as described in claim 6, characterized in that, The step of constructing a DBF correction model from the standard signal and the DBF module output signal to obtain the DBF correction model includes: The preset standard signal is sequentially input to the antenna module at multiple different incident angles to obtain the DBF module output signal at each incident angle; A directional response sample set is constructed using the DBF module output signals at all incident angles; the directional response sample set includes the DBF module output signals at all incident angles. Based on the aforementioned directional response sample set, a spatial domain error cost function is constructed. , The expression is: ， in: This represents the total number of sampling directions. They represent the first The elevation and azimuth angles of each incident direction; Let be the ideal array manifold vector, representing the weighted response that should be in this direction under ideal conditions; The DBF module outputs a signal in the k-th direction. This represents the number of antenna elements. The digital beamforming correction weight matrix is ​​the one to be solved. Number of output beam channels; The DBF correction model is obtained by solving the spatial domain error cost function.

9. An adaptive control device for antenna aperture parameters based on environmental cognition, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the adaptive control method for antenna aperture parameters based on environmental awareness as described in any one of claims 4 to 8.

10. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the adaptive control method for antenna aperture parameters based on environmental cognition as described in any one of claims 4 to 8.

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