CN113630197A - Antenna phase adjustment method, antenna phase adjustment device, storage medium and electronic equipment - Google Patents
Antenna phase adjustment method, antenna phase adjustment device, storage medium and electronic equipment Download PDFInfo
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Abstract
The present disclosure provides a method, an apparatus, a storage medium, and an electronic device for adjusting a phase of an antenna, the method including: acquiring measured phase characterization information of an antenna; inputting the measured phase representation information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the measured phase representation information; the control voltage is applied to each phased element of the phased array in the antenna based on the control voltage adjustment matrix. According to the method, the preset adjusting model is trained, the operation amount and the operation time are saved, the non-linear operation capability of the deep learning model can be directly used for determining the corresponding control voltage based on the obtained actually-measured phase characterization information, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset, the initial phase error caused by the manufacturing process can be just offset, the working performance of the antenna can be further improved, and the better antenna optimization effect can be achieved.
Description
Technical Field
The present disclosure relates to the field of antenna technologies, and in particular, to a method and an apparatus for adjusting a phase of an antenna, a storage medium, and an electronic device.
Background
The antenna adjusts the beam phase through a Liquid crystal phased array voltage control system (LCPA), thereby realizing the performance adjustment of the antenna. Fig. 1 is a schematic diagram of the use principle of the LCPA voltage control system, in which a liquid crystal layer is sandwiched between upper and lower substrates of a phase shifter, and a bias voltage is applied between an upper substrate unit printed circuit and a lower substrate metal ground, so that the magnitude of an electric field between the upper and lower substrates can be changed, the arrangement direction of liquid crystal molecules in a region corresponding to each unit patch is changed, the dielectric constant of the liquid crystal layer is further changed, and the phase delay of beam propagation is changed, thereby realizing modulation of the beam phase, and each unit patch is equivalent to a phase control unit. Fig. 2 shows a fitting curve (also referred to as V-phi curve) between the control voltage (V) and the phase (phi) of the LCPA voltage control system, which is a non-linear curve and cannot be completely matched with an actual device due to factors such as electric field edge effect and process manufacturing error.
In practical engineering application, due to problems of manufacturing processes and the like, inconsistency among the phased units in the phased array can cause a random initial phase to exist when the antenna is not regulated, and the performance of the antenna is affected. However, in the case that the fitted V-phi curve is not completely matched with the actual device, how to apply the voltage to each phase control unit in the LCPA to achieve the optimal performance of the antenna becomes a problem to be solved urgently. In the prior art, calculation can be performed through an algorithm based on iterative solution, such as a pattern search algorithm or a gradient descent algorithm, but the algorithm has many iteration times and a low convergence rate, and meanwhile, the convergence result depends on control of environmental noise of a test site, so that the accuracy of the convergence result is low, and the optimization efficiency and the optimization effect of the antenna are seriously affected.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide a method and an apparatus for adjusting a phase of an antenna, a storage medium, and an electronic device, so as to solve the problems of low optimization efficiency and poor optimization effect of the antenna in the antenna optimization process in the prior art.
The embodiment of the disclosure adopts the following technical scheme: a phase adjustment method of an antenna comprises the following steps: acquiring actually measured phase characterization information of an antenna, wherein the actually measured phase characterization information is the phase characterization information of the antenna under the condition that a control voltage is not applied; inputting the actually measured phase representation information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the actually measured phase representation information; applying control voltages to individual phased elements of a phased array in the antenna based on the control voltage adjustment matrix, wherein one control voltage in the control voltage adjustment matrix is used to control one of the phased elements in the phased array.
In some embodiments, the measured phase characterizing information comprises at least: an actual far-field pattern of the antenna or a phase function representing the actual far-field pattern.
In some embodiments, the preset tuning model is trained based on the following steps: determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna; randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix; training a preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until a loss function of the preset adjusting model determined based on the phase adjusting function meets a preset condition.
In some embodiments, the determining a default phase adjustment function based on the at least one sample antenna comprises: determining a voltage phase curve for each of the sample antennas; an average of all of the voltage phase curves is determined, and the default phase adjustment function is determined to characterize the curve of the average of all of the voltage phase curves.
In some embodiments, the loss function is used to characterize at least one of the following antenna performance parameters: the gain of a main beam in a far-field directional diagram of the antenna, the ratio of a main lobe and a side lobe in the far-field directional diagram of the antenna and the directivity coefficient.
In some embodiments, the preset condition includes at least one of: the value of the loss function is minimal; the value of the loss function is less than a preset threshold.
An embodiment of the present disclosure further provides a phase adjustment apparatus for an antenna, including: the antenna phase detection device comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring actually-measured phase characterization information of an antenna, and the actually-measured phase characterization information is phase characterization information of the antenna under the condition that a control voltage is not applied; the processing module is used for inputting the actually measured phase representation information into a preset adjusting model so as to obtain a control voltage adjusting matrix output by the preset adjusting model according to the actually measured phase representation information; a tuning module to apply control voltages to individual phased elements of a phased array in the antenna based on the control voltage tuning matrix, wherein one control voltage in the control voltage tuning matrix is used to control one of the phased elements in the phased array.
In some embodiments, further comprising: a training module for training the preset adjustment model based on the steps of: determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna; randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix; training a preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until a loss function of the preset adjusting model determined based on the phase adjusting function meets a preset condition.
Embodiments of the present disclosure also provide a storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of the above-mentioned phase adjustment method of the antenna.
An embodiment of the present disclosure further provides an electronic device, which at least includes a memory and a processor, where the memory stores a computer program thereon, and the processor implements the steps of the above-mentioned antenna phase adjustment method when executing the computer program on the memory.
The beneficial effects of this disclosed embodiment lie in: through training the preset adjusting model, the operation amount and the operation time are saved, through the nonlinear operation capability of the deep learning model, the corresponding control voltage can be determined directly based on the obtained actually-measured phase characterization information, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset by the initial phase error caused by the manufacturing process, the working performance of the antenna is further improved, and the better antenna optimization effect is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present disclosure, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram illustrating a principle of using an LCPA voltage control system in the related art;
FIG. 2 is a graph of a fit between control voltage and phase for an LCPA voltage control system of the related art;
fig. 3 is a flowchart of a phase adjustment method for an antenna according to a first embodiment of the present disclosure;
FIG. 4 is a schematic diagram illustrating a training procedure of a preset tuning model according to a first embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a phase adjustment apparatus of an antenna according to a second embodiment of the present disclosure;
fig. 6 is another schematic structural diagram of a phase adjustment apparatus of an antenna according to a second embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device in a fourth embodiment of the present disclosure.
Detailed Description
Various aspects and features of the disclosure are described herein with reference to the drawings.
It will be understood that various modifications may be made to the embodiments of the present application. Accordingly, the foregoing description should not be construed as limiting, but merely as exemplifications of embodiments. Other modifications will occur to those skilled in the art within the scope and spirit of the disclosure.
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and, together with a general description of the disclosure given above, and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.
These and other characteristics of the present disclosure will become apparent from the following description of preferred forms of embodiment, given as non-limiting examples, with reference to the attached drawings.
It should also be understood that, although the present disclosure has been described with reference to some specific examples, a person of skill in the art shall certainly be able to achieve many other equivalent forms of the disclosure, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present disclosure will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present disclosure are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various forms. Well-known and/or repeated functions and structures have not been described in detail so as not to obscure the present disclosure with unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriately detailed structure.
The specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the disclosure.
The antenna adjusts the beam phase through the LCPA, thereby realizing the performance adjustment of the antenna. The LCPA voltage control system is a nonlinear system, and a V-phi curve corresponding to a phase adjusting function B (V) is also nonlinear. In the related technology, a V-phi curve is obtained by actually measuring a V-phi scatter diagram of each unit in the LCPA and performing function fitting, then the V-phi curve is written into a control MCU in a table form, and table lookup is performed according to phase shift requirements to configure control voltage, so that phase adjustment of antenna beams is realized. However, in practical engineering applications, the operation performance of the LCPA voltage control system is interfered by various factors, such as electric field edge effect, process manufacturing error (uniformity error of glass substrate, uniformity error of electrode), and the like. The combined effect of these physical processes results in the V-phi curve of the LCPA being obtained that does not fit exactly with the actual device.
Due to the problems of the manufacturing process and the like, the phase control units in the LCPA may have uneven thickness, and at this time, when the antenna is not regulated, an initial phase error exists, which affects the performance of the antenna, so the LCPA needs to be optimized to counteract the effect of the initial phase error on the performance of the antenna, so that the antenna can exert the optimal performance.
Since LCPA is unable to build a mathematical analytic model of the pressure control system, it is necessary to design and use a model-free optimization algorithm that does not rely on a mathematical model of the system in the optimization system for processing. Common LCPA voltage control system optimization algorithms include: pattern search algorithm, gradient descent algorithm. Both algorithms are optimization algorithms based on iterative solution. (1) The pattern search method changes the value of each control signal variable during each iteration, so that the updated variable steps in a direction that increases system performance. When changing the values of all variables does not result in a system performance increase, the above process is repeated with the step size reduced by half until the step size is sufficiently small. The iteration times of the algorithm are usually 1000-2000 times, the convergence speed of the algorithm is low, and the optimization time of the antenna is seriously influenced. (2) In each iteration process of the gradient descent method, the values of all control signal variables are changed simultaneously, so that the updated control signals step along the gradient descent direction of the original signals. Until the phase shift performance reaches a set convergence value. The iteration times of the algorithm are more than 80 times; meanwhile, the nonlinear solution is not accurate enough, and the calculation amount is multiplied when large-scale array calculation is carried out.
In order to solve the above problems in the prior art, a first embodiment of the present disclosure provides a phase adjustment method for an antenna, which is mainly used in a phase adjustment process of an antenna with an LCPA, and a flowchart thereof is shown in fig. 3, and mainly includes steps S10 to S30:
and S10, acquiring the actually measured phase characterization information of the antenna.
Because the liquid crystal layer thickness is uneven between each phase control unit in the LCPA of the antenna possibly caused by the manufacturing process, the dielectric constants of the liquid crystal layer parts corresponding to each phase control unit are different, so that the beam emitted by the antenna has an initial phase under the condition that no control voltage is applied, and the data obtained by acquiring the actually measured phase representation information of the antenna reflects the difference between each phase control unit. The purpose of this embodiment is how to quickly determine the control voltage for each phase control unit, so that the phase adjustment performed by the phase control unit after applying the control voltage can cancel out the initial phase error caused by the process problem.
In some embodiments, the measured phase characterization information may be an actual far-field pattern corresponding to the antenna or a phase function representing the actual far-field pattern
Other parameters for characterizing the phase situation, such as the field strength value in the normal direction, may also be used, where θ and
for representing the beam offset angles, i.e., azimuth and elevation angles, from the antenna in the horizontal and vertical directions.
And S20, inputting the measured phase characterization information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the measured phase characterization information.
The preset adjustment model in this embodiment is a deep learning model, which can be obtained by training any neural network model, for example, a VGG network at 16/19 layer, a google lenet network at 22 layer, or the like, and can also design the number of network layers and structure by itself, which is not limited in this embodiment. Specifically, the implementation of the preset adjustment model in this embodiment may be equivalent to solving an optimization problem, and the core of the method is to define a phase shift performance evaluation index J, where J is a function related to the control voltage adjustment matrix, that is, a specific value of the control voltage adjustment matrix has an influence on J, and the purpose of the preset adjustment model is to solve the control voltage adjustment matrix that minimizes the value of J. At this time, when the control voltage adjusting matrix output by the preset adjusting model is applied to each phase control unit of the antenna LCPA, the phase adjustment performed by the phase control unit can be used for offsetting the initial phase error generated by the process problem and realizing the optimization of the antenna performance.
When model training is actually performed, the training step of the preset adjusting model can be performed offline, so that the operation time is further saved, and the operation amount during actual antenna optimization is reduced. Specifically, the training steps of the preset tuning model are shown in fig. 4, and mainly include steps S21 to S23:
s21, a default phase adjustment function is determined based on the at least one sample antenna.
The sample antenna can be an antenna to be optimized or other antennas produced in the same batch with the antenna to be optimized, and in order to improve the universality of the preset adjustment model under the common condition, a large number of antennas in different batches can be selected when the sample antenna is selected, so that the preset adjustment model obtained by final training can achieve a good optimization effect when any antenna is optimized. The phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna, and the default phase adjustment function is the phase adjustment function b (v) which can meet the requirements of all sample antennas, that is, all sample antennas can use the same phase adjustment function b (v) to determine the control voltage when performing phase adjustment. Note that the LCPA array size and dimensions are the same in all sample antennas.
Specifically, when a default phase adjustment function is determined, a voltage phase curve (namely a V-phi curve) of each sample antenna needs to be determined, in the process of determining the V-phi curve of each sample antenna, a V-phi scatter diagram of each sample antenna can be obtained through actual measurement, and then the V-phi curve is obtained through an interpolation fitting mode; during actual measurement, the voltage value can be controlled to perform gradient change in a 0.25V step size in an interval of 0-18V in the ground determining process of the scatter diagram, a corresponding phase value is obtained, and in the fitting process, the pchip interpolation function can be selected as the interpolation function, and the interpolation interval is 10 mV. After the V-phi curves of each sample antenna are determined, all the obtained V-phi curves are averaged to obtain an average processing result, and a default phase adjustment function b (V) is determined to characterize the curves of the value processing results of all the voltage phase curves. Further, the specific mode of the averaging process may be an averaging process, a moving average process, or the like, or may be another mode for performing the averaging process, and the embodiment is not limited.
For example, let the control voltage adjust matrix be
The ideal phase matrix generated after applying the voltage matrix V can be expressed as:
in combination with voltage control system errors caused by the combination of electric field edge effects, process manufacturing errors and the like, the actual phase matrix will be expressed as: phiBB (v) + S, where S is a M × N dimensional noise matrix, and its specific error distribution characteristics can be adjusted according to the noise type, for example, when S is additive white gaussian noise, there is
σn 2Is the noise variance.
And S22, randomly generating a preset number of initial phase error matrixes, and determining theoretical phase characterization information corresponding to each initial phase error matrix.
Initial phase error matrix phirandFor characterizing non-uniformities between individual phased-units due to process non-uniformities, i.e.Initial phase errors caused by manufacturing process problems among the phase control units of different antennas are simulated, and the initial phase errors can be randomly generated in a large quantity through simulation software such as MATLAB. After the initial phase error matrixes of the preset number are generated, because the initial phase error matrixes cannot be directly measured in actual operation, the initial phase error matrixes can be sequentially used as theoretical phase representation information of initial phase conditions of all phase control units in the antenna, such as directional diagrams and field intensity values in normal directions and the like, to determine the corresponding directional diagrams and field intensity values in the normal directions
And pass through
Indicating the initial phase error condition of the phase control unit.
When actually determining the phase characterization information corresponding to each initial phase error matrix, the receiving unit is usually installed at a fixed position near the antenna, but because of the same position difference between the phased units in the LCPA phased array, the distances between the receiving unit and each phased unit are also different, and further the inherent phase difference Φ between the units is caused0Is generated. In particular,. phi0This can be represented by the following matrix:
wherein the content of the first and second substances,
it is to be noted that the inherent phase difference Φ involved in the present embodiment0The cancellation can be directly performed by other methods specifically for performing the inherent phase difference cancellation, which have been disclosed in the prior art, and the embodiment does not disclose how to perform the cancellation on the inherent phase difference.
In determining the initial phase error matrix phirandCorresponding theoretical phase characterization information
In the present embodiment, the actual measurement phase characterization information of each initial phase matrix may be actually measured by the receiving unit as the phase characterization information required for training, but since the training sample has a large magnitude under a normal condition, and the actual measurement needs to consume a large amount of time, the theoretical phase characterization information corresponding to the initial phase matrix is calculated by the following formula:
and S23, training the preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until the loss function of the preset adjusting model determined based on the phase adjusting function meets the preset condition.
The theoretical phase characterization information obtained in the step S22
As the network input of the preset regulation model, the form of the input data can be selected as follows:
i.e. the input data may be equivalent to a total of 2 pixels
To ensure that the input data of the neural network is real, wherein N isθIs composed of
The number of sampling points in the theta direction,
is composed of
In that
Number of sampling points in the direction.
When training is actually carried out, the loss function of the adjusting model is preset to be used as the termination condition of the model training. Specifically, it may be set that when the loss function meets a preset condition, the training of the model is deemed to be completed. When the loss function meets the preset condition, the parameter values in the current model network can be stored to form a trained preset adjusting model, so that the trained parameter values can be directly used for controlling the output of the voltage adjusting matrix when the preset adjusting model is used subsequently. It should be noted that the parameter values in the model network may include various model network parameters such as the number of network layers, the number of nodes, and the weight values, and the specific parameter types and numbers included in the model network may be adjusted according to different neural network models used, which is not limited herein; the specific training optimization mode of the parameter values of each parameter is related to the training logic inside the network model, and the embodiment does not limit the specific training mode, as long as the expected training effect can be achieved.
In this embodiment, when the loss function is selected, the antenna performance is mainly used as an index, for example, the loss function is at least used for characterizing one of the following antenna performance parameters: the gain of the main beam in the far-field pattern of the antenna, the ratio of the main lobe to the side lobe in the far-field pattern of the antenna, and the directivity coefficient may also be other parameters used for characterizing the performance of the antenna, and this embodiment is not particularly limited. The control voltage regulating matrix output by the preset regulating model can meet the requirement on the antenna performance parameter by limiting the certain antenna performance parameter as a loss function.
For example, in some embodiments, the objective of the final optimization is to maximize the directivity coefficient D, and the design of the loss function may refer to the calculation formula of D for the main beam
In terms of:
at this time, the formula for correspondingly setting the loss function is as follows:
at this time, if it is necessary to ensure the maximum value of D, the preset condition is set to make the loss function
At the minimum, wherein,
for control voltage regulation matrices requiring presetting of the output of the regulation model, i.e. in which the control voltage regulation matrix is
Time, loss function
And minimum. Will be provided with
The measured phase characterization information formed by the antenna after being applied to each phase control unit is:
at this time, the process of the present invention,
the calculated phase situation should exactly match
Cancel each other out, or sum of both approaches zero infinitely, making the corresponding calculated
The directivity factor of (2) is largest.
It should be appreciated that when the antenna performance parameter targeted for optimization changes, the corresponding loss function formula also changes, e.g., when the antenna performance parameter is selected to be the maximum gain of the main beam in the far-field pattern
Or
Wherein the content of the first and second substances,
for calibrated far-field patterns, it can be determined by simulation, e.g.
Or may be obtained by actual measurement.
Due to the fact that the selected optimization targets are different and the corresponding loss functions are different, when the preset condition is set, the value of the loss function can be set to be the minimum, a threshold value can be preset, when the value of the loss function is smaller than the preset threshold value, the loss function is determined to meet the preset condition, the adaptability of the termination condition is improved, and the training times and the training time are reduced to a certain extent.
In addition, in some embodiments, the trained preset adjustment model can be tested through test data, whether the preset adjustment model meets the actual requirement or not is judged according to the test result, the preset adjustment model is stored under the condition that the requirement is met, and if the preset adjustment model cannot meet the requirement, the preset adjustment model can be adjusted through a mode of modifying the model structure, adjusting the number of model layers, the number of nodes or other model parameters and is based on the mode that the model structure is modified, the number of model layers is adjusted, the number of nodes or other model parametersSteps S21 to S23 perform retraining of the model. The test data may also be obtained through simulation, the actual requirement may be a specific requirement for the antenna performance, and the embodiment does not limit the specific content, as long as the control voltage adjustment matrix output by the preset adjustment model is ensured
After being applied to the phase control element of the antenna, the antenna actually exhibits a performance that meets the requirements.
Through the steps, the training of the preset adjusting model is realized, the control voltage adjusting matrix output by the preset adjusting model meets the preset condition with the minimum loss function through continuously optimizing the model parameters, and further, after the voltage corresponding to the control voltage adjusting matrix is applied to each phase control unit of the antenna, the initial phase error caused by the phase control unit manufacturing process can be eliminated, so that the antenna has better working performance.
S30, a control voltage is applied to each phased element of the phased array in the antenna based on the control voltage adjustment matrix.
Based on the actually measured phase characterization information obtained in step S10, the actually measured phase characterization information is input as input data into a preset adjustment model, so that a control voltage adjustment matrix can be obtained, and when each control voltage in the control voltage adjustment matrix is applied to a corresponding phase control unit, an initial phase error caused by a phase control unit manufacturing process can be eliminated, and the antenna has better working performance. It should be noted that the size of the control voltage adjustment matrix is the same as the size of the array formed by the phase control units in the LCPA, each element in the control voltage adjustment matrix corresponds to a unique phase control unit in the LCPA array, the position of the phase control unit in the array is the same as the position of its corresponding element in the control voltage adjustment matrix, and the value of the element is the control voltage to be applied to the corresponding phase control unit.
According to the method, the operation amount and the operation time are saved by training the preset adjusting model, the determination of the corresponding control voltage can be directly carried out based on the obtained actually-measured phase characterization information through the nonlinear operation capability of the deep learning model, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset, the initial phase error caused by the manufacturing process can be just offset, the working performance of the antenna can be further improved, and the better antenna optimization effect can be achieved.
A second embodiment of the present disclosure provides a phase adjustment apparatus for an antenna, which can be installed in an antenna having an LCPA, for implementing control voltage adjustment of each phase control unit in the LCPA. Specifically, fig. 5 shows a schematic structural diagram of a phase adjustment apparatus of an antenna, which mainly includes an obtaining module 10, a processing module 20, and an adjusting module 30, where the obtaining module 10 is configured to obtain measured phase characterization information of the antenna, where the measured phase characterization information is phase characterization information of the antenna under a condition that a control voltage is not applied to the antenna; the processing module 20 is configured to input the measured phase characterization information into a preset adjustment model to obtain a control voltage adjustment matrix output by the preset adjustment model according to the measured phase characterization information; the adjusting module 30 is configured to apply control voltages to individual phased elements of a phased array in the antenna based on a control voltage adjustment matrix, wherein one control voltage in the control voltage adjustment matrix is used to control one phased element in the phased array. Specifically, the measured phase characterization information at least includes: the actual far-field pattern of the antenna or the phase function used to represent the actual far-field pattern.
In some embodiments, as shown in fig. 6, it further includes a training module 40 on the basis of fig. 5, which is mainly used for training the preset adjustment model based on the following steps: determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna; randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix; and training the preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until the loss function of the preset adjusting model determined based on the phase adjusting function meets the preset condition.
In some embodiments, training module 40 is specifically configured to: determining a voltage phase curve for each sample antenna; the mean of all voltage phase curves is determined and a default phase adjustment function is determined to characterize the curve of the mean of all voltage phase curves.
In particular, the loss function is used to characterize at least one of the following antenna performance parameters: the gain of a main beam in a far-field directional diagram of the antenna, the ratio of a main lobe and a side lobe in the far-field directional diagram of the antenna and the directivity coefficient. In addition, the preset condition includes at least one of: the value of the loss function is minimal; the value of the loss function is smaller than the preset threshold, which condition is specifically selected as the preset condition can be set according to the actual requirement, and this embodiment is not limited.
According to the method, the operation amount and the operation time are saved by training the preset adjusting model, the determination of the corresponding control voltage can be directly carried out based on the obtained actually-measured phase characterization information through the nonlinear operation capability of the deep learning model, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset, the initial phase error caused by the manufacturing process can be just offset, the working performance of the antenna can be further improved, and the better antenna optimization effect can be achieved.
A third embodiment of the present disclosure provides a storage medium, which can be installed in any antenna with an LCPA, and is specifically a computer-readable medium, storing a computer program, and when the computer program is executed by a processor, the computer program implements the method provided in any embodiment of the present disclosure, including the following steps S31 to S33:
s31, acquiring actually measured phase characterization information of the antenna, wherein the actually measured phase characterization information is the phase characterization information of the antenna under the condition that the control voltage is not applied;
s32, inputting the measured phase representation information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the measured phase representation information;
s33, applying control voltages to the individual phased elements of the phased array in the antenna based on the control voltage adjustment matrix, wherein one control voltage in the control voltage adjustment matrix is used to control one phased element in the phased array.
Specifically, the measured phase characterization information at least includes: the actual far-field pattern of the antenna or the phase function used to represent the actual far-field pattern.
The computer program is further executed by the processor to train the preset model by: determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna; randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix; and training the preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until the loss function of the preset adjusting model determined based on the phase adjusting function meets the preset condition.
When the computer program is executed by the processor to determine the default phase adjustment function based on the at least one sample antenna, the processor is specifically configured to perform the following steps: determining a voltage phase curve for each sample antenna; the mean of all voltage phase curves is determined and a default phase adjustment function is determined to characterize the curve of the mean of all voltage phase curves.
In particular, the loss function is used to characterize at least one of the following antenna performance parameters: the gain of a main beam in a far-field directional diagram of the antenna, the ratio of a main lobe and a side lobe in the far-field directional diagram of the antenna and the directivity coefficient. In addition, the preset condition includes at least one of: the value of the loss function is minimal; the value of the loss function is smaller than the preset threshold, which condition is specifically selected as the preset condition can be set according to the actual requirement, and this embodiment is not limited.
According to the method, the operation amount and the operation time are saved by training the preset adjusting model, the determination of the corresponding control voltage can be directly carried out based on the obtained actually-measured phase characterization information through the nonlinear operation capability of the deep learning model, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset, the initial phase error caused by the manufacturing process can be just offset, the working performance of the antenna can be further improved, and the better antenna optimization effect can be achieved.
A fourth embodiment of the present disclosure provides an electronic device, which may be any antenna with an LCPA, and its schematic structure is shown in fig. 7, and includes at least a memory 100 and a processor 200, and in addition, it should include other functional modules or structural devices for implementing the original functions of the antenna. The memory 100 has a computer program stored thereon, and the processor 200 implements the method provided by any of the embodiments of the present disclosure when executing the computer program on the memory 100. Illustratively, the electronic device computer program steps are as follows S41-S43:
s41, acquiring actually measured phase characterization information of the antenna, wherein the actually measured phase characterization information is the phase characterization information of the antenna under the condition that the control voltage is not applied;
s42, inputting the measured phase representation information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the measured phase representation information;
s43, applying control voltages to the individual phased elements of the phased array in the antenna based on the control voltage adjustment matrix, wherein one control voltage in the control voltage adjustment matrix is used to control one phased element in the phased array.
Specifically, the measured phase characterization information at least includes: the actual far-field pattern of the antenna or the phase function used to represent the actual far-field pattern.
The processor also executes the following computer program to train the preset model: determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna; randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix; and training the preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until the loss function of the preset adjusting model determined based on the phase adjusting function meets the preset condition.
The processor, when executing the computer program stored on the memory for determining the default phase adjustment function based on the at least one sample antenna, is further configured to: determining a voltage phase curve for each sample antenna; the mean of all voltage phase curves is determined and a default phase adjustment function is determined to characterize the curve of the mean of all voltage phase curves.
In particular, the loss function is used to characterize at least one of the following antenna performance parameters: the gain of a main beam in a far-field directional diagram of the antenna, the ratio of a main lobe and a side lobe in the far-field directional diagram of the antenna and the directivity coefficient. In addition, the preset condition includes at least one of: the value of the loss function is minimal; the value of the loss function is smaller than the preset threshold, which condition is specifically selected as the preset condition can be set according to the actual requirement, and this embodiment is not limited.
According to the method, the operation amount and the operation time are saved by training the preset adjusting model, the determination of the corresponding control voltage can be directly carried out based on the obtained actually-measured phase characterization information through the nonlinear operation capability of the deep learning model, so that the phase change of each phase control unit of the antenna LCPA after the corresponding control voltage is input can be just offset, the initial phase error caused by the manufacturing process can be just offset, the working performance of the antenna can be further improved, and the better antenna optimization effect can be achieved.
While the present disclosure has been described in detail with reference to the embodiments, the present disclosure is not limited to the specific embodiments, and those skilled in the art can make various modifications and alterations based on the concept of the present disclosure, and the modifications and alterations should fall within the scope of the present disclosure as claimed.
Claims (10)
1. A method for adjusting a phase of an antenna, comprising:
acquiring actually measured phase characterization information of an antenna, wherein the actually measured phase characterization information is the phase characterization information of the antenna under the condition that a control voltage is not applied;
inputting the actually measured phase representation information into a preset adjusting model to obtain a control voltage adjusting matrix output by the preset adjusting model according to the actually measured phase representation information;
applying control voltages to individual phased elements of a phased array in the antenna based on the control voltage adjustment matrix, wherein one control voltage in the control voltage adjustment matrix is used to control one of the phased elements in the phased array.
2. The phase adjustment method of claim 1, wherein the measured phase characterization information comprises at least: an actual far-field pattern of the antenna or a phase function representing the actual far-field pattern.
3. The phase adjustment method according to claim 1, wherein the preset adjustment model is trained based on the following steps:
determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna;
randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix;
training a preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until a loss function of the preset adjusting model determined based on the phase adjusting function meets a preset condition.
4. The phase adjustment method of claim 3, wherein determining a default phase adjustment function based on the at least one sample antenna comprises:
determining a voltage phase curve for each of the sample antennas;
determining a mean processing result of all the voltage phase curves and determining the default phase adjustment function to characterize a curve of the mean processing result of all the voltage phase curves.
5. The phase adjustment method of claim 3, wherein the loss function is used to characterize at least one of the following antenna performance parameters: the gain of a main beam in a far-field directional diagram of the antenna, the ratio of a main lobe and a side lobe in the far-field directional diagram of the antenna and the directivity coefficient.
6. The phase adjustment method according to claim 5, wherein the preset condition comprises at least one of:
the value of the loss function is minimal;
the value of the loss function is less than a preset threshold.
7. An apparatus for adjusting a phase of an antenna, comprising:
the antenna phase detection device comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring actually-measured phase characterization information of an antenna, and the actually-measured phase characterization information is phase characterization information of the antenna under the condition that a control voltage is not applied;
the processing module is used for inputting the actually measured phase representation information into a preset adjusting model so as to obtain a control voltage adjusting matrix output by the preset adjusting model according to the actually measured phase representation information;
a tuning module to apply control voltages to individual phased elements of a phased array in the antenna based on the control voltage tuning matrix, wherein one control voltage in the control voltage tuning matrix is used to control one of the phased elements in the phased array.
8. The phase adjustment apparatus according to claim 7, further comprising:
a training module for training the preset adjustment model based on the steps of:
determining a default phase adjustment function based on at least one sample antenna, wherein the phase adjustment function is used for representing the adjustment condition of the control voltage to the phase of the sample antenna;
randomly generating a preset number of initial phase error matrixes, and determining theoretical phase representation information corresponding to each initial phase error matrix;
training a preset adjusting model based on theoretical phase characterization information corresponding to the initial phase error matrix until a loss function of the preset adjusting model determined based on the phase adjusting function meets a preset condition.
9. A storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the phase adjustment method of the antenna of any one of claims 1 to 6.
10. An electronic device comprising at least a memory, a processor, the memory having a computer program stored thereon, characterized in that the processor, when executing the computer program on the memory, implements the steps of the method of phase adjustment of an antenna according to any of claims 1 to 6.
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