CN113642197B - Spectral analysis-based super-surface construction method - Google Patents
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Abstract
The invention discloses a super-surface construction method based on spectral analysis, which comprises the steps of obtaining incident beam information, and determining incident surface electromagnetic field distribution data according to the incident beam information; acquiring target beam information, and determining the electromagnetic field distribution data of the emergent surface according to the target beam information; and constructing the super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data. According to the invention, the electromagnetic field distribution conditions of the incident surface and the emergent surface of the super surface are determined by analyzing the incident beam and the target beam. Because the electromagnetic field distribution is closely related to the structural characteristics of the super surface, the structural characteristics of the super surface can be determined based on the respective electromagnetic field distribution conditions of the incident surface and the emergent surface, and further the construction of the super surface is realized. The method does not need to perform simulation optimization, and solves the problem that in the prior art, when the super surface is constructed, commercial software is adopted to perform simulation optimization on each structural unit on the super surface, so that a large amount of calculation cost and time cost are consumed.
Description
Technical Field
The invention relates to the technical field of optical devices, in particular to a spectral analysis-based super-surface construction method.
Background
In recent years, the super-surface made of artificial material has been widely noticed in academia and industry for about 20 years due to its low profile, light weight, and easy installation, and has made great progress and development. The super surface/super lens can realize the functions of multi-feed source multi-beam, single-feed source multi-beam and the like in a mode of modulating the surface phase. Since the function of each structural unit on the super surface is different, the physical parameters of each structural unit are also different, and therefore, the construction of the non-uniform super surface is a difficult problem in the scientific research and technological field. In the prior art, each structural unit on the super surface is usually optimized by simulation by using commercial software to complete the construction of the super surface, so that a large amount of calculation cost and time cost are consumed in the construction process.
Thus, there is still a need for improvement and development of the prior art.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method for constructing a super-surface based on spectral analysis, aiming at solving the problem that a large amount of computation cost and time cost are consumed due to the fact that a commercial software is adopted to perform simulation optimization on each structural unit on the super-surface when the super-surface is constructed in the prior art.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a method for constructing a super-surface based on spectral analysis, where the method includes:
acquiring incident beam information, and determining incident surface electromagnetic field distribution data according to the incident beam information;
acquiring target beam information, and determining the electromagnetic field distribution data of an emergent surface according to the target beam information;
and constructing the super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data.
In one embodiment, the determining incident surface electromagnetic field distribution data from the incident beam information comprises:
determining the angular spectrum domain electromagnetic field distribution data of the incident wave beam according to the incident wave beam information;
and determining the electromagnetic field distribution data of the incidence surface according to the electromagnetic field distribution data of the angular spectrum domain.
In one embodiment, the determining the angular spectrum domain electromagnetic field distribution data of the incident beam according to the incident beam information includes:
determining first spatial domain electromagnetic field distribution data corresponding to a source field according to the incident beam information, wherein the source field is used for transmitting the incident beam;
and converting the first spatial domain electromagnetic field distribution data into an angular spectrum domain through Fourier transform to obtain the angular spectrum domain electromagnetic field distribution data.
In one embodiment, the determining the incident plane electromagnetic field distribution data from the angular spectral domain electromagnetic field distribution data includes:
and carrying out phase accumulation on the electromagnetic field distribution data of the angular spectrum domain to obtain the electromagnetic field distribution data of the incidence plane.
In one embodiment, the determining of the exit surface electromagnetic field distribution data from the target beam information comprises:
determining second space domain electromagnetic field distribution data corresponding to a target far field according to the target beam information, wherein the target far field is a space where a target beam is located;
and performing Fourier inverse transformation on the second spatial domain electromagnetic field distribution data to obtain the emergent surface electromagnetic field distribution data.
In one embodiment, the performing an inverse fourier transform on the second spatial domain electromagnetic field distribution data to obtain the exit surface electromagnetic field distribution data includes:
converting the second spatial domain electromagnetic field distribution data into a Cartesian coordinate system to obtain Cartesian electromagnetic field distribution data;
carrying out inverse Fourier transform on the Cartesian electromagnetic field distribution data to obtain initial electromagnetic field distribution data;
and carrying out iterative calculation on the initial electromagnetic field distribution data to obtain the emergent surface electromagnetic field distribution data.
In one embodiment, the iteratively calculating the initial electromagnetic field distribution data to obtain the electromagnetic field distribution data of the exit surface includes:
fixing the amplitude of the initial electromagnetic field distribution data to a preset amplitude, and performing iterative calculation on the phase of the initial electromagnetic field distribution data to obtain the electromagnetic field distribution data of the emergent surface.
In one embodiment, the super-surface includes a plurality of structural units, and the constructing the super-surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data includes:
determining target physical parameters corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
determining a target structure parameter corresponding to each structural unit according to the target physical parameter corresponding to each structural unit;
and constructing the super surface according to the target structure parameters respectively corresponding to the plurality of structural units.
In one embodiment, the determining the target physical parameter corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the exit surface electromagnetic field distribution data includes:
determining initial physical parameters corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
and determining an optimization target, and performing iterative calculation on the initial physical parameters corresponding to each structural unit according to the optimization target to obtain target physical parameters corresponding to each structural unit.
In one embodiment, the determining an initial physical parameter corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the exit surface electromagnetic field distribution data includes:
determining a transmission matrix according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
and determining initial physical parameters corresponding to each structural unit according to the transmission matrix.
In one embodiment, the optimization objective includes a plurality of optimization objectives, and the iteratively calculating the initial physical parameter corresponding to each structural unit according to the optimization objectives includes:
inputting the initial physical parameters corresponding to each structural unit into a multi-objective optimization algorithm corresponding to a plurality of optimization targets;
and performing iterative calculation on the initial physical parameters corresponding to each structural unit through the multi-objective optimization algorithm.
In one embodiment, the determining the target structural parameter corresponding to each structural unit according to the target physical parameter corresponding to each structural unit includes:
inputting the target physical parameters corresponding to each structural unit into a parameter extraction optimization algorithm;
and outputting the target structure parameters corresponding to each structural unit through the parameter extraction optimization algorithm.
In a second aspect, an embodiment of the present invention further provides a super-surface construction system based on spectral analysis, where the system includes:
the incident surface calculation module is used for acquiring incident beam information and determining incident surface electromagnetic field distribution data according to the incident beam information;
the exit surface calculation module is used for acquiring target beam information and determining exit surface electromagnetic field distribution data according to the target beam information;
and the super surface construction module is used for constructing a super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data.
In a third aspect, an embodiment of the present invention further provides a super-surface, where the super-surface is constructed by using any one of the above-mentioned spectrum analysis-based super-surface construction methods.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a plurality of instructions are stored, wherein the instructions are adapted to be loaded and executed by a processor to implement any of the steps of the spectral analysis-based super-surface construction method described above.
The invention has the beneficial effects that: according to the embodiment of the invention, incident beam information is acquired, and incident surface electromagnetic field distribution data is determined according to the incident beam information; acquiring target beam information, and determining the electromagnetic field distribution data of the emergent surface according to the target beam information; and constructing the super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data. According to the invention, the electromagnetic field distribution conditions of the incident surface and the emergent surface of the super surface are determined by analyzing the incident beam and the target beam. Because the electromagnetic field distribution is closely related to the structural characteristics of the super surface, the structural characteristics of the super surface can be determined based on the respective electromagnetic field distribution conditions of the incident surface and the emergent surface, and further the construction of the super surface is realized. The method does not need to perform simulation optimization, and solves the problem that in the prior art, when the super surface is constructed, commercial software is adopted to perform simulation optimization on each structural unit on the super surface, so that a large amount of calculation cost and time cost are consumed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for constructing a super-surface based on spectral analysis according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of the relationship between the source field, the super-surface, and the far-field provided by an embodiment of the present invention.
Fig. 3 is a schematic diagram of fourier optics provided by an embodiment of the invention.
FIG. 4 is a schematic diagram of obtaining a phase distribution of a super-surface/super-lens ideal exit surface by using a limiting amplitude G-S algorithm according to an embodiment of the present invention.
FIG. 5 is a complete flow chart of the method for constructing a super-surface based on spectral analysis according to the embodiment of the present invention.
FIG. 6 is a schematic diagram of the working principle of the super-surface provided by the embodiment of the invention.
FIG. 7 is a diagram illustrating the results of a multi-objective optimization algorithm provided by an embodiment of the present invention.
Fig. 8 is a schematic diagram of a pareto improvement provided by an embodiment of the present invention.
FIG. 9 is a block diagram of the interior of a super-surface construction system based on spectral analysis according to an embodiment of the present invention.
Fig. 10 is a functional block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.
In recent years, the super-surface made of artificial material has been widely noticed in academia and industry for about 20 years due to its low profile, light weight, and easy installation, and has made great progress and development. The super surface/super lens can realize the functions of multi-feed source multi-beam, single-feed source multi-beam and the like in a mode of modulating the surface phase. Since the function of each structural unit on the super surface is different, the physical parameters of each structural unit are also different, and therefore, the construction of the non-uniform super surface is a difficult problem in the scientific research and technological field. In the prior art, each structural unit on the super surface is usually optimized by simulation by using commercial software to complete the construction of the super surface, so that a large amount of calculation cost and time cost are consumed in the construction process.
Aiming at the defects in the prior art, the invention provides a super-surface construction method based on spectral analysis, which comprises the steps of obtaining incident beam information and determining incident surface electromagnetic field distribution data according to the incident beam information; acquiring target beam information, and determining the electromagnetic field distribution data of an emergent surface according to the target beam information; and constructing the super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data. Because the superlens is mainly used for modulating electromagnetic waves, the electromagnetic field distribution conditions of the incident surface and the emergent surface of the super surface are determined by analyzing the incident beam and the target beam. Because the electromagnetic field distribution is closely related to the structural characteristics of the super surface, the structural characteristics of the super surface can be determined based on the respective electromagnetic field distribution conditions of the incident surface and the emergent surface, and further the construction of the super surface is realized. The method does not need to perform simulation optimization, and solves the problem that in the prior art, when the super surface is constructed, commercial software is adopted to perform simulation optimization on each structural unit on the super surface, so that a large amount of calculation cost and time cost are consumed.
As shown in fig. 1, the method comprises the steps of:
step S100, obtaining incident beam information, and determining incident surface electromagnetic field distribution data according to the incident beam information.
In particular, an incident beam refers to a beam emerging from a source field, which is also determined since the nature of the source field is known. The objective of this embodiment is to construct a super-surface, through which an incident beam emitted from a source field is modulated, and make the modulated emergent beam meet a preset condition when reaching a target far field. Because the incident beam information can reflect the relevant characteristics of the incident beam, the state of the incident beam when reaching the super-surface incident surface can be calculated based on the incident beam information, and the electromagnetic field distribution condition of the incident surface is further determined, namely the electromagnetic field distribution data of the incident surface is obtained.
In one implementation, the step S100 specifically includes the following steps:
step S101, determining the angular spectrum domain electromagnetic field distribution data of the incident wave beam according to the incident wave beam information;
and S102, determining the electromagnetic field distribution data of the incidence surface according to the electromagnetic field distribution data of the angular spectrum domain.
Because there is usually a certain spatial distance between the source field and the super-surface, the incident beam will pass through a transmission distance after being emitted from the source field and reach the incident surface of the super-surface. Therefore, in this embodiment, the initial state of the incident beam when the incident beam exits from the source field needs to be determined first, and then the state of the incident beam when the incident beam reaches the super-surface incident plane after passing through the transmission distance is calculated, so as to determine the electromagnetic field distribution condition of the incident plane. Since the angular spectrum electromagnetic field distribution data can reflect the energy distribution of the incident beam propagating in each direction after the incident beam is emitted from the source field, that is, the angular spectrum electromagnetic field distribution data can visually decompose the incident beam into plane waves propagating in each direction (as shown in fig. 3), in this embodiment, the angular spectrum electromagnetic field distribution data is determined according to the incident beam information, and then the state of the plane waves in each direction reaching the super-surface incident surface is calculated according to the angular spectrum electromagnetic field distribution data, so as to determine the electromagnetic field distribution condition of the incident surface, thereby obtaining the incident surface electromagnetic field distribution data.
In one implementation, the step S101 specifically includes the following steps:
step S1011, determining first spatial domain electromagnetic field distribution data corresponding to a source field according to the incident beam information, wherein the source field is used for emitting the incident beam;
step S1012, transforming the first spatial domain electromagnetic field distribution data into an angular spectrum domain through fourier transform, so as to obtain the angular spectrum domain electromagnetic field distribution data.
Specifically, as shown in fig. 2, since both the source field and the incident beam are known and determined, the relevant characteristic information of the incident beam, i.e., the incident beam information, is also determined. Therefore, the electromagnetic field distribution corresponding to the spatial domain where the source field is located can be determined based on the incident beam information, and the first spatial domain electromagnetic field distribution data can be obtained. Because the Fourier components of the incident wave beams at different spatial frequencies can be regarded as plane waves propagating along different directions, the electromagnetic field distribution of a spatial domain can be converted into the electromagnetic field distribution of an angular spectrum domain through Fourier transform, and then the electromagnetic field distribution data of the angular spectrum domain can be obtained.
For example, as shown in fig. 3, knowing that the original point plane (z = 0) has a spatial field distribution of E (x, y,0), the spatial field distribution can be converted into an angular spectrum domain through spectrum transformation, so as to obtain an angular spectrum field distribution E (kx, ky,0) corresponding to the original point plane, where the conversion formula is as follows:
in an implementation manner, the step S102 specifically includes the following steps:
and S1021, carrying out phase accumulation on the electromagnetic field distribution data of the angular spectrum domain to obtain the electromagnetic field distribution data of the incidence plane.
Specifically, since a certain transmission distance exists between the source field of the transmission beam and the super-surface, the phase of the incident beam will change to a certain extent when the incident beam reaches the super-surface incidence plane through the transmission distance after being emitted from the source field. Therefore, the present embodiment obtains the incident surface electromagnetic field distribution data by phase-integrating the plane waves in the respective propagation directions decomposed based on the incident beam.
For example, as shown in fig. 3, the plane z 'is a super-surface incident plane, and when the electromagnetic field distribution of the space where the plane z = z' (i.e. the incident plane electromagnetic field distribution) is required to be obtained, the phase accumulation is realized by the following formula, and the incident plane electromagnetic field distribution is solved:
wherein,
、
the wave numbers of the electromagnetic wave along the x-direction and the y-direction respectively,
to limit the function, ensure
. Shift term
The phase accumulation of the electromagnetic wave in the propagation process is characterized.
As shown in fig. 1, the method further comprises the steps of:
and S200, acquiring target beam information, and determining the electromagnetic field distribution data of the emergent surface according to the target beam information.
Specifically, the target beam information is determined based on the modulation task, and can reflect a state required to be presented when the emergent beam modulated by the super-surface reaches a target far field, so that the state of the beam emitted from the emergent surface of the super-surface can be calculated according to the target beam information, the electromagnetic field distribution condition of the emergent surface is obtained, and the electromagnetic field distribution data of the emergent surface is obtained.
In an implementation manner, the step S200 specifically includes the following steps:
step S201, determining second space domain electromagnetic field distribution data corresponding to a target far field according to the target beam information, wherein the target far field is a space where a target beam is located;
step S202, performing Fourier inverse transformation on the second spatial domain electromagnetic field distribution data to obtain the emergent surface electromagnetic field distribution data.
Specifically, since the target beam information may reflect the state of the beam existing within the target far field, the electromagnetic field distribution of the space in which the target far field is located, that is, the second spatial domain electromagnetic field distribution data may be determined based on the target beam information. In order to reversely calculate the state of the beam emitted from the emitting surface of the super-surface from the target far field, in this embodiment, inverse fourier transform needs to be performed on the second spatial domain electromagnetic field distribution data, so as to obtain the initial state of the beam emitted from the emitting surface of the super-surface, and determine the electromagnetic field distribution condition of the emitting surface, that is, the electromagnetic field distribution data of the emitting surface.
In an implementation manner, the step S202 specifically includes the following steps:
step S2021, converting the second spatial domain electromagnetic field distribution data into a Cartesian coordinate system to obtain Cartesian electromagnetic field distribution data;
step S2022, performing inverse Fourier transform on the Cartesian electromagnetic field distribution data to obtain initial electromagnetic field distribution data;
step S2023, performing iterative computation on the initial electromagnetic field distribution data to obtain the emergent surface electromagnetic field distribution data.
Specifically, in order to solve the initial state of the beam when the beam exits from the exit surface of the super-surface, in this embodiment, first, the electromagnetic field distribution of the space where the target far field is located needs to be converted into the electromagnetic field distribution in the cartesian coordinate system to obtain cartesian electromagnetic field distribution data, so that the problem to be solved is converted into a function solution problem. And then carrying out Fourier inverse transformation on the Cartesian electromagnetic field distribution data to obtain initial electromagnetic field distribution data, carrying out iterative optimization on the initial electromagnetic field distribution data until the initial electromagnetic field distribution data meet the electromagnetic field distribution condition of an emergent face corresponding to a target remote place, and obtaining the electromagnetic field distribution data of the emergent face after the iteration is finished.
In an implementation manner, the step S2023 specifically includes the following steps:
step S20231, fixing the amplitude of the initial electromagnetic field distribution data to a preset amplitude, and performing iterative computation on the phase of the initial electromagnetic field distribution data to obtain electromagnetic field distribution data of the exit surface.
For the design of the array surface of the emitting surface of the super surface, controlling the change of the amplitude and the phase at the same time is too complicated, and in order to reduce the calculation overhead, the embodiment adopts an iterative algorithm for limiting the amplitude, that is, the amplitude of the initial electromagnetic field distribution data is fixed, and only the phase is subjected to iterative calculation until the initial electromagnetic field distribution data converges to the ideal phase, so as to obtain the electromagnetic field distribution data of the emitting surface. The preset amplitude may be set according to the modulation task, for example, the preset amplitude may be set according to the amplitude distribution that propagates from the source field to the incident surface without loss.
Specifically, the iterative algorithm for limiting the amplitude adopted in this embodiment is an amplitude limitation optimization scheme of the Gerchberg-Saxton algorithm, and for easy understanding, this embodiment provides a step flow of this algorithm:
1. the desired far field pattern is transformed to a cartesian coordinate system.
2. And (4) performing Fourier inverse transformation on the directional diagram in the Cartesian coordinate system to a near field.
3. And replacing the amplitude distribution of the near field with the amplitude distribution of the feed source propagating to the incident plane under the condition of no damage.
4. The fourier transform is the far field produced by the replaced near field distribution. And the amplitude of the far field is replaced with the amplitude of the desired far field.
5. Repeating the steps 2-4 until convergence.
For example, as shown in fig. 4, it is first determined that the target is to obtain an elliptical far-field distribution, then the electromagnetic field amplitude distribution of the exit surface of the super-surface is forced to be gaussian, and through iterative computation, the radiation and phase distribution of the exit surface satisfying the target far-field is finally obtained.
In one implementation, in addition to the optimization iterative algorithm, a non-iterative algorithm such as Direct Amplitude Encoding (Direct Amplitude Encoding) may be used for the processing of the inverse fourier transform from the far field to the exit surface.
As shown in fig. 1, the method further comprises the steps of:
and S300, constructing a super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data.
Specifically, the objective of this embodiment is to forward analyze the propagation process of the incident beam from the known source field to the incident surface of the super-surface, calculate the electromagnetic field distribution data of the incident surface, and determine the wavefront design of the incident surface of the super-surface; and through reversely analyzing the backward propagation process of the target beam from the target far field to the emergent surface of the super surface, calculating the electromagnetic field distribution data of the emergent surface, and determining the design of the array surface of the emergent surface of the super surface. And finally, constructing a super surface capable of completing a modulation task according to the deduced array surface design of the incident surface and the emergent surface. After the construction is finished, the incident beam is transmitted to the super surface from the source field, is emitted after being modulated by the super surface and is transmitted to a target far field, and then the target beam can be obtained.
In one implementation, the super-surface includes a plurality of structural units, and the step S300 specifically includes the following steps:
step S301, determining target physical parameters corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
step S302, determining a target structure parameter corresponding to each structural unit according to the target physical parameter corresponding to each structural unit;
step S303, constructing the super surface according to the target structure parameters respectively corresponding to the plurality of structural units.
The super surface is an ultrathin two-dimensional array plane and consists of a plurality of structural units, and the scattering characteristic of each unit is the superposition of all incident wave responses, in other words, the emergent wave of the super surface emergent surface is the convolution of the incident wave and the structural response. In order to reduce the computational overhead, the present embodiment splits the super-surface construction task into the construction task of each structural unit, where the construction task of each structural unit mainly includes determining the corresponding physical parameter and structural parameter. And for each structural unit, determining a corresponding target physical parameter, and solving the corresponding target structural parameter by taking the target physical parameter as a guide. And finally, constructing the super surface capable of finishing the modulation task according to the target structure parameters corresponding to all the structure units.
In one implementation, the step S301 specifically includes the following steps:
step S3011, determining initial physical parameters corresponding to each structural unit according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
and S3012, determining an optimization target, and performing iterative computation on the initial physical parameters corresponding to each structural unit according to the optimization target to obtain target physical parameters corresponding to each structural unit.
Specifically, the present embodiment mainly adopts an iterative optimization manner to determine the target physical parameters of each structural unit. Before iterative computation, however, initial physical parameters need to be set for each structural unit by using the estimated incident surface electromagnetic field distribution data and emergent surface electromagnetic field distribution data, and then iterative optimization is performed based on the initial physical parameters. Moreover, because blind optimization is time-consuming and the results of different optimization target iterations are different, it is necessary to determine an optimization target, for example, the optimization target may be loss, or goodness of fit, or efficiency, and then perform iterative computation on the initial physical parameters of each structural unit based on the determined optimization target until the ideal physical parameters of each structural unit, that is, the target physical parameters, are iterated.
In one implementation manner, the step S3011 specifically includes the following steps:
step S30111, determining a transmission matrix according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
step S30112, determining an initial physical parameter corresponding to each structural unit according to the transmission matrix.
The present embodiment mainly uses a transmission matrix method to determine the initial physical parameters of each structural unit. Specifically, the super-surface is equivalent to a transmission medium, and a transmission matrix for reflecting the mapping relation of electromagnetic fields of the front space and the rear space of the super-surface can be determined according to the deduced electromagnetic field distribution data of the incident surface and the electromagnetic field distribution data of the emergent surface. Based on the transmission matrix, the projection/reflection response of each structural unit to all angular spectral components of the incident beam in the periodic environment can be solved, so as to set initial physical parameters for each structural unit.
The transmission matrix method requires each structure unit to be regarded as a discrete volume tensor (
、
、
And
). Wherein,
in order to be the dielectric tensor,
is a magnetic-medium tensor which is a magnetic-medium tensor,
for the electromagnetic mutual-coupling conductivity tensor to be,
is the magnetic-electric mutual coupling conductivity tensor.
Knowing the body tensor and the plane waves incident in various directions, the additive response of each artificial unit to the incident field can be efficiently calculated by using a transmission matrix method. The specific implementation process of the transmission matrix method is as follows:
1. and (3) analytically calculating the transmission/reflection response of each structural unit to all angular spectrum components of the incident wave under the periodic environment by using a transmission matrix method.
2. And carrying out Fourier inverse transformation on the field of the angular spectrum domain, and converting the field into the electromagnetic field distribution of a space domain.
3. And extracting the corresponding spatial field intensity and phase of the position of each structural unit in the non-periodic wavefront environment.
4. These discrete electromagnetic field distributions are combined according to a non-periodic wavefront distribution to generate the final transmissive/reflective spatial field.
In one implementation, the optimization objective includes a plurality of optimization objectives, and the step S3012 specifically includes the following steps:
step S30121, inputting the initial physical parameters corresponding to each structural unit into a multi-objective optimization algorithm corresponding to a plurality of optimization objectives;
and S30122, performing iterative calculation on the initial physical parameters corresponding to each structural unit through the multi-objective optimization algorithm.
Specifically, when the super-surface size is large, the number of corresponding structural units is large, blind optimization is time-consuming, and in order to improve the efficiency and effect of optimization, a plurality of optimization targets are predetermined in the embodiment, a multi-objective optimization algorithm is determined based on the optimization targets, and the initial physical parameters of each structural unit are iteratively optimized through the multi-objective optimization algorithm.
In one implementation manner, an incident beam is taken as a direct incident beam, and the initial physical parameter corresponding to each structural unit is iteratively calculated through the multi-objective optimization algorithm to obtain a target physical parameter corresponding to each structural unit, specifically:
1. according to the incident beam information and the emergent beam information corresponding to the straight incident beam, determining initial volume tensor parameter distribution data (namely initial physical parameters) corresponding to each structural unit;
2. inputting the initial volume tensor parameter distribution data corresponding to each structural unit into the Multi-Objective Optimization Algorithm (Multi-Objective Optimization Algorithm);
3. determining Pareto improvement edges (Pareto Front) corresponding to a plurality of optimization objectives through the multi-objective optimization algorithm;
4. and determining the tensor parameter distribution data (namely target physical parameters) of the target body corresponding to each structural unit according to the pareto improvement edges.
Specifically, the multi-objective optimization algorithm is completed only after the multi-objective optimization algorithm is converged near the preset threshold, and fig. 7 shows an iteration result of the multi-objective optimization algorithm. In addition, the multi-objective optimization algorithm has a plurality of optimization objectives, namely a plurality of cost functions:
wherein
For the calculated radio-electromagnetic field amplitude phase of the ith structural unit,
is the ideal electromagnetic field amplitude phase of the ith structural unit. FIG. 8 illustrates pareto improvement edges formed based on multiple optimization objectives, from which a designer may determine a selection advantage according to design needs.
In an implementation manner, the step S302 specifically includes the following steps:
step S3021, inputting the target physical parameters corresponding to each structural unit into a parameter-extracting optimization algorithm;
and step S3022, outputting the target structure parameters corresponding to each structural unit through the parameter extraction optimization algorithm.
Specifically, the parameter extraction optimization algorithm in this embodiment is a comprehensive algorithm, which includes a parameter extraction algorithm and an optimization algorithm. After the target physical parameters of each structural unit are determined, the structural parameters corresponding to the target physical parameters of each structural unit can be solved through a parameter extraction optimization algorithm, and the target structural parameters of each structural unit are obtained (as shown in fig. 5). And then determining the artificial structural units meeting the requirements from the existing mature structure for constructing the super surface. Since the variation of the physical equivalent parameter corresponding to the variation of the artificial structure parameter generally has a trend corresponding to the variation of the artificial structure parameter, the above process does not consume too much computing resources.
For example, taking the three-layer structure shown in fig. 6 as an example, by changing the parameters of the patch structure of each layer, such as the size of the patch, the size of the gap, etc., it is possible to achieve a high transmission efficiency for the incident electromagnetic wave and a wide range of phase changes, i.e., changes in physical parameters, and thus this structure can be determined to be used as an implementation of a non-uniform wavefront, i.e., a super-surface. Since the variation of the structural parameters and physical parameters of each layer of patches has trend, when designing the super surface, once the physical parameters of each layer of patches are determined, the corresponding structural parameters can be deduced.
The invention has the advantages that:
1. the invention provides a comprehensive algorithm based on a Fourier optical method, an equivalent parameter generation method, a parameter extraction method, a transmission matrix method and a multi-objective optimization algorithm, and a super-surface transmission array/reflection array is systematically modeled and optimized from a feed source to a far field, so that the aim of intelligent design is fulfilled.
2. The method adopted by the invention is an analytical method or a semi-analytical method, and the operation speed is greatly increased when the array surface is designed, so that the aim of high-efficiency design is fulfilled.
3. The present invention is a systematic approach and is therefore generic. The method can be suitable for designing the super-surface transmission array/reflection array system with different feed sources, different feed positions, different array surface positions and different far field forms, and the limitation is greatly reduced compared with the prior method.
4. When modeling is carried out, the hyper-unit is equivalent to an adult parameter, and the full-angle spectrum characteristics (transmission and reflection of incident electromagnetic waves with different angles and different polarizations) of the hyper-unit are analyzed by a transmission matrix method, so that the interaction characteristics of the hyper-unit and the electromagnetic field are fully considered, and further, the error is reduced in the design stage.
5. In the invention, a multi-objective optimization algorithm is adopted during fitting optimization, so that the compromise relationship among indexes of the super-surface reflection array/transmission array can be quantitatively analyzed.
6. According to the method, when Fourier transform from a far field to a near field is carried out, an iterative algorithm for limiting the amplitude is adopted, so that the amplitude and phase distribution of the required surface on the emergent surface are more accurately evaluated.
Based on the above embodiment, the present invention further provides a super-surface construction system based on spectral analysis, as shown in fig. 9, the system includes:
the incident plane calculation module 01 is used for acquiring incident beam information and determining incident plane electromagnetic field distribution data according to the incident beam information;
the exit surface calculation module 02 is used for acquiring target beam information and determining exit surface electromagnetic field distribution data according to the target beam information;
and the super-surface constructing module 03 is configured to construct a super-surface according to the incident surface electromagnetic field distribution data and the exit surface electromagnetic field distribution data.
Based on the above embodiments, the present invention further provides a super-surface, wherein the super-surface is constructed by using the super-surface construction method based on spectral analysis according to any of the above embodiments.
Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 10. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a method of super-surface construction based on spectral analysis. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.
It will be understood by those skilled in the art that the block diagram of fig. 10 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.
In one implementation, one or more programs are stored in a memory of the terminal and configured to be executed by one or more processors include instructions for performing a method of spectral analysis-based super-surface construction.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses a super-surface construction method, a super-surface construction system, a super-surface, a beam modulation method and a storage medium based on spectral analysis, wherein the method comprises the steps of obtaining incident beam information and determining incident surface electromagnetic field distribution data according to the incident beam information; acquiring target beam information, and determining the electromagnetic field distribution data of an emergent surface according to the target beam information; and constructing the super surface according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data. Because the superlens is mainly used for modulating electromagnetic waves, the electromagnetic field distribution conditions of the incident surface and the emergent surface of the super surface are determined by analyzing the incident beam and the target beam. Because the electromagnetic field distribution is closely related to the structural characteristics of the super surface, the structural characteristics of the super surface can be determined based on the respective electromagnetic field distribution conditions of the incident surface and the emergent surface, and further the construction of the super surface is realized. The method does not need to perform simulation optimization, and solves the problem that in the prior art, when the super surface is constructed, commercial software is adopted to perform simulation optimization on each structural unit on the super surface, so that a large amount of calculation cost and time cost are consumed.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (4)
1. A method of spectral analysis-based super-surface construction, the method comprising:
acquiring incident beam information;
determining first spatial domain electromagnetic field distribution data corresponding to a source field according to the incident beam information, wherein the source field is used for transmitting the incident beam;
converting the first spatial domain electromagnetic field distribution data into an angular spectrum domain through Fourier transform to obtain the angular spectrum domain electromagnetic field distribution data;
carrying out phase accumulation on the angular spectrum domain electromagnetic field distribution data to obtain incident plane electromagnetic field distribution data;
acquiring target beam information;
determining second space domain electromagnetic field distribution data corresponding to a target far field according to the target beam information, wherein the target far field is a space where a target beam is located;
converting the second spatial domain electromagnetic field distribution data into a Cartesian coordinate system to obtain Cartesian electromagnetic field distribution data;
carrying out inverse Fourier transform on the Cartesian electromagnetic field distribution data to obtain initial electromagnetic field distribution data;
fixing the amplitude of the initial electromagnetic field distribution data to be a preset amplitude, and performing iterative calculation on the phase of the initial electromagnetic field distribution data to obtain electromagnetic field distribution data of an emergent surface;
determining a transmission matrix according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
determining initial physical parameters corresponding to each structural unit according to the transmission matrix;
determining an optimization objective, wherein the optimization objective comprises a plurality of optimization objectives;
inputting the initial physical parameters corresponding to each structural unit into a multi-objective optimization algorithm corresponding to a plurality of optimization targets; performing iterative calculation on the initial physical parameters corresponding to each structural unit through the multi-objective optimization algorithm to obtain target physical parameters corresponding to each structural unit;
inputting the target physical parameters corresponding to each structural unit into a parameter extraction optimization algorithm;
outputting a target structure parameter corresponding to each structural unit through the parameter extraction optimization algorithm;
constructing a super surface according to the target structure parameters respectively corresponding to each structural unit, wherein the super surface comprises a plurality of structural units;
fixing the amplitude of the initial electromagnetic field distribution data to a preset amplitude, and performing iterative computation on the phase of the initial electromagnetic field distribution data, wherein the iterative computation comprises the following steps:
fixing the amplitude of initial electromagnetic field distribution data by adopting an improved Gerchberg-Saxton algorithm, and performing iterative computation on the phase of the initial electromagnetic field distribution data until the initial electromagnetic field distribution data converges to an ideal phase;
the execution process of the improved Gerchberg-Saxton algorithm is as follows: transforming the required far-field directional diagram to a Cartesian coordinate system; carrying out inverse Fourier transform on a directional diagram under a Cartesian coordinate system to obtain a near field; replacing the amplitude distribution of the near field with the amplitude distribution of the feed source transmitted to the incident plane under the lossless condition; a far field resulting from the near field distribution after the fourier transform is replaced; and replacing the amplitude of the far field with the amplitude of the required far field;
the transmission matrix method takes each structural unit as a discrete volume tensor
、
、
And
wherein
in order to be the dielectric tensor,
is a magnetic-medium tensor which is a magnetic-medium tensor,
for the electromagnetic mutual-coupling conductivity tensor to be,
is a magnetic-electric mutual coupling conductivity tensor; knowing the body tensor and the plane waves incident in all directions, and calculating the summation response of each structural unit to an incident field by using a transmission matrix method; the implementation process of the transmission matrix method is as follows: analyzing and calculating the transmission/reflection response of each structural unit to all angular spectrum components of the incident wave under the periodic environment by using a transmission matrix method; carrying out Fourier inverse transformation on the field of the angular spectrum domain, and converting the field into electromagnetic field distribution of a spatial domain; extracting the corresponding spatial field intensity and phase position of each structural unit in the non-periodic array surface environment; these discrete electromagnetic field distributions are combined according to a non-periodic wavefront distribution to generate the final transmissive/reflective spatial field.
2. A system for constructing a super-surface based on spectral analysis, the system comprising:
the system comprises an incident surface calculation module, a first spatial domain electromagnetic field distribution module and a second spatial domain electromagnetic field distribution module, wherein the incident surface calculation module is used for acquiring incident beam information and determining first spatial domain electromagnetic field distribution data corresponding to a source field according to the incident beam information, and the source field is used for emitting the incident beam;
converting the first spatial domain electromagnetic field distribution data into an angular spectrum domain through Fourier transform to obtain the angular spectrum domain electromagnetic field distribution data;
carrying out phase accumulation on the angular spectrum domain electromagnetic field distribution data to obtain incident plane electromagnetic field distribution data;
the exit surface calculation module is used for acquiring target beam information and determining second spatial domain electromagnetic field distribution data corresponding to a target far field according to the target beam information, wherein the target far field is a space where the target beam is located;
converting the second spatial domain electromagnetic field distribution data into a Cartesian coordinate system to obtain Cartesian electromagnetic field distribution data;
carrying out inverse Fourier transform on the Cartesian electromagnetic field distribution data to obtain initial electromagnetic field distribution data;
fixing the amplitude of the initial electromagnetic field distribution data to be a preset amplitude, and performing iterative calculation on the phase of the initial electromagnetic field distribution data to obtain electromagnetic field distribution data of an emergent surface;
the super-surface construction module is used for determining a transmission matrix according to the incident surface electromagnetic field distribution data and the emergent surface electromagnetic field distribution data;
determining initial physical parameters corresponding to each structural unit according to the transmission matrix;
determining an optimization objective, wherein the optimization objective comprises a plurality of optimization objectives;
inputting the initial physical parameters corresponding to each structural unit into a multi-objective optimization algorithm corresponding to a plurality of optimization targets; performing iterative calculation on the initial physical parameters corresponding to each structural unit through the multi-objective optimization algorithm to obtain target physical parameters corresponding to each structural unit;
inputting the target physical parameters corresponding to each structural unit into a parameter extraction optimization algorithm;
outputting a target structure parameter corresponding to each structural unit through the parameter extraction optimization algorithm;
constructing a super surface according to the target structure parameters respectively corresponding to each structural unit, wherein the super surface comprises a plurality of structural units;
fixing the amplitude of the initial electromagnetic field distribution data to a preset amplitude, and performing iterative computation on the phase of the initial electromagnetic field distribution data, wherein the iterative computation comprises the following steps:
fixing the amplitude of initial electromagnetic field distribution data by adopting an improved Gerchberg-Saxton algorithm, and performing iterative computation on the phase of the initial electromagnetic field distribution data until the initial electromagnetic field distribution data converges to an ideal phase;
the execution process of the improved Gerchberg-Saxton algorithm is as follows: transforming the required far-field directional diagram to a Cartesian coordinate system; carrying out inverse Fourier transform on a directional diagram under a Cartesian coordinate system to obtain a near field; replacing the amplitude distribution of the near field with the amplitude distribution of the feed source transmitted to the incident plane under the lossless condition; a far field resulting from the near field distribution after the fourier transform is replaced; and replacing the amplitude of the far field with the amplitude of the required far field;
the transmission matrix method takes each structural unit as a discrete volume tensor
、
、
And
wherein
in order to be the dielectric tensor,
is a magnetic-medium tensor which is a magnetic-medium tensor,
for the electromagnetic mutual-coupling conductivity tensor to be,
is a magnetic-electric mutual coupling conductivity tensor; knowing the body tensor and the plane waves incident in all directions, and calculating the summation response of each structural unit to an incident field by using a transmission matrix method; wherein the transmissionThe matrix input method is implemented as follows: analyzing and calculating the transmission/reflection response of each structural unit to all angular spectrum components of the incident wave under the periodic environment by using a transmission matrix method; carrying out Fourier inverse transformation on the field of the angular spectrum domain, and converting the field into electromagnetic field distribution of a spatial domain; extracting the corresponding spatial field intensity and phase position of each structural unit in the non-periodic array surface environment; these discrete electromagnetic field distributions are combined according to a non-periodic wavefront distribution to generate the final transmissive/reflective spatial field.
3. A super-surface, wherein the super-surface is constructed using the spectral analysis-based super-surface construction method of claim 1.
4. A computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of the spectral analysis based super-surface construction method according to claim 1.
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