Terahertz coded metasurface two-degree-of-freedom beam steering method and system

Abstract

A terahertz coded metasurface two-degree-of-freedom beam steering method and system, in the method, a mirror-symmetry metasurface unit composed of a metal double-slit resonant ring and a polytetrafluoroethylene dielectric layer is used. A two-dimensional coding matrix is optimized by a genetic algorithm, including initial population generation, fitness calculation, dynamic adjustment of crossover and mutation probability, execution of crossover and mutation operation, elite reservation strategy and iterative optimization steps, and finally the optimized coding sequence is converted into the rotation angle of the metasurface unit, realizing the accurate control of the terahertz beam. The present application is used for reducing the influence of phase quantization error, and improving the electric field intensity and the accuracy of beam pointing of the terahertz beam in the target direction.

Description

Technical Field

[0001] This application belongs to the field of beam control, and in particular relates to a terahertz-coded metasurface two-degree-of-freedom beam control method and system. Background Technology

[0002] Terahertz waves have great potential for application in future wireless communication, radar detection, and high-resolution imaging due to their advantages such as large bandwidth, high transmission rate, and high security. The key to promoting the practical application of this technology lies in how to achieve flexible and efficient control of terahertz beams.

[0003] To achieve flexible control of terahertz beams, digitally coded metasurface technology has emerged. Unlike traditional analog metasurfaces, which require a continuously changing phase response, digitally coded metasurfaces utilize arrays of discrete-phase-response superatoms. By changing the spatial arrangement of these coded units in a two-dimensional plane, the wavefront phase distribution of the incident terahertz wave can be effectively controlled, thereby achieving beamforming functions such as beam deflection, focusing, or multi-beaming. Currently, the design of coded matrices for specific beam directions is typically based on the generalized Snell's law or phase gradient theory. This involves first calculating the continuous phase distribution required to deflect the beam to the target angle, then quantizing and mapping it to the closest discrete coded state, thus achieving control over the terahertz wave radiation direction.

[0004] However, since the phase response of the coded metasurface is discrete, if the traditional analytical calculation method is used directly, unavoidable phase quantization errors will be introduced, which will make it difficult for the electric field intensity of the actual generated beam in the target direction to reach the theoretical optimal value, or even cause pointing deviation. Summary of the Invention

[0005] This application provides a terahertz coded metasurface two-degree-of-freedom beam control method and system, which is used to reduce the influence of phase quantization error and improve the electric field strength and beam pointing accuracy of the terahertz beam in the target direction.

[0006] In the first aspect, this application provides a terahertz coded metasurface two-degree-of-freedom beam control method, which sets the row and column size of the metasurface array, and randomly generates several two-dimensional coding matrices based on a 2-bit coding set containing four states, and forms an initial population from the several two-dimensional coding matrices.

[0007] Using a pre-defined terahertz far-field scattering model, the electric field intensity of each two-dimensional coding matrix in the initial population at the target elevation angle and target azimuth angle was calculated respectively.

[0008] The electric field strength value is used as the individual fitness of the corresponding two-dimensional coding matrix;

[0009] Calculate the average fitness of all individuals in the initial population to obtain the average fitness of the population;

[0010] Based on the individual fitness and the population average fitness of each two-dimensional encoding matrix, determine the crossover probability and mutation probability of each two-dimensional encoding matrix;

[0011] Based on the crossover and mutation probabilities of each two-dimensional encoding matrix, crossover and mutation operations are performed on each two-dimensional encoding matrix to obtain a set of offspring individuals;

[0012] The two-dimensional coding matrix of the top-performing individuals in the initial population based on their fitness is used as the elite individuals.

[0013] The elite individuals and their offspring are merged, and a predetermined number of two-dimensional coding matrices are selected according to the individual fitness from high to low to form a new generation population.

[0014] Determine whether the current iteration process meets the preset termination condition;

[0015] If the preset termination condition is not met, the new generation population will be used as the initial population, and the process will return to the step of calculating the electric field strength of each two-dimensional coding matrix in the initial population at the target pitch angle and the target azimuth angle.

[0016] If the preset termination condition is met, the two-dimensional coding matrix with the highest individual fitness in the new generation population is selected as the optimal coding sequence output.

[0017] According to the preset mapping rules, each encoding element in the optimal encoding sequence is converted into the rotation angle of the corresponding metasurface unit;

[0018] The corresponding metasurface unit in the terahertz-coded metasurface is rotated according to the rotation angle.

[0019] By employing the above technical solution, the two-dimensional coding matrix is ​​optimized using a genetic algorithm. Crossover and mutation probabilities are dynamically adjusted based on individual fitness, and an elite retention strategy is introduced, improving the convergence efficiency of the coding sequence. The optimized two-dimensional coding matrix can more accurately achieve beam control at the target elevation and azimuth angles. Due to the mirror-symmetric three-layer structure design, the combination of the metal double-slit resonator ring and the PTFE dielectric layer enhances the electromagnetic response of the metasurface unit. By mapping the optimal coding sequence to the rotation angle of the metasurface unit, precise control of the incident electromagnetic wave phase is achieved. This optimization method based on a genetic algorithm reduces the impact of phase quantization errors and improves the electric field strength and beam pointing accuracy of the terahertz beam in the target direction.

[0020] In conjunction with some implementations of the first aspect, in some implementations, the crossover probability and mutation probability of each two-dimensional encoding matrix are determined based on the individual fitness and the population average fitness of each two-dimensional encoding matrix, specifically including:

[0021] The default crossover probability is set to the first preset value, and the default mutation probability is set to the second preset value, where the first preset value is greater than the second preset value.

[0022] If the individual fitness of the two-dimensional coding matrix is ​​higher than the average fitness of the population, then the crossover probability is reduced to any third preset value less than the first preset value and the mutation probability is reduced to any fourth preset value less than the second preset value.

[0023] If the individual fitness of the two-dimensional coding matrix is ​​less than or equal to the average fitness of the population, then the crossover probability will remain unchanged or be increased to any fifth preset value greater than the first preset value, and the mutation probability will remain unchanged or be increased to any sixth preset value greater than the second preset value.

[0024] By adopting the above technical solution, an adaptive crossover and mutation probability adjustment strategy is used based on the relationship between individual fitness and the average fitness of the population. When an individual's fitness is higher than the average fitness of the population, the crossover and mutation probabilities are reduced to protect the characteristics of superior individuals. When an individual's fitness is lower than or equal to the average fitness of the population, the crossover and mutation probabilities are increased, increasing population diversity, reducing the probability of local optima, enhancing the algorithm's ability to find the global optimum, improving the optimization effect of the two-dimensional coding matrix, and making the obtained coding sequence closer to the ideal beam control target.

[0025] In conjunction with some implementation methods of the first aspect, in some implementation methods, the calculation formula for the preset terahertz far-field scattering model is as follows:

[0026]

[0027] In the above formula, The pitch angle, It is the azimuth angle. Let be the propagation constant. For a unit period, For the first The phase of each unit, This is the far-field function for a single unit.

[0028] By adopting the above technical solution, key parameters such as unit period, propagation constant, unit phase, and unit far-field function are considered. The phase accumulation effect of electromagnetic waves in the propagation process in space is accurately described by the complex exponential function, which improves the accuracy of far-field scattering characteristic calculation.

[0029] In conjunction with some implementation methods of the first aspect, in some implementation methods, the preset mapping rule is as follows:

[0030] The 2-bit encoding set contains four encoding states: {00, 01, 10, 11}.

[0031] The encoding state 00 corresponds to a metasurface unit rotation angle of 0°; the encoding state 01 corresponds to a metasurface unit rotation angle of 45°; the encoding state 10 corresponds to a metasurface unit rotation angle of 90°; the encoding state 11 corresponds to a metasurface unit rotation angle of 135°; the co-polarization reflection phase difference of the metasurface units corresponding to adjacent encoding states is fixed at 90°, and the phase error does not exceed 2%.

[0032] By adopting the above technical solution, the four encoding states are mapped to four rotation angles of 0°, 45°, 90° and 135°, realizing a 90° co-polarization reflection phase difference between the metasurface units corresponding to adjacent encoding states.

[0033] In conjunction with some embodiments of the first aspect, the structural parameters and material properties of the metasurface unit specifically include:

[0034] The outer radius of the metal double-slit resonant ring is 44 μm, the inner radius is 35 μm, the slit width is 8 μm, and the metal thickness is 0.4 μm.

[0035] The polytetrafluoroethylene dielectric layer has a thickness of 25 μm and a relative permittivity of 2.1 + 0.0002i;

[0036] The period length of the metasurface unit is 110 μm.

[0037] By adopting the above technical solution, the geometric dimensions of the resonant ring are matched with the terahertz wavelength, which enhances the coupling ability of the resonant ring to terahertz waves. The dielectric layer can provide a stable electromagnetic field distribution environment for the metal resonant ring, reducing the loss of electromagnetic waves during transmission. The metasurface unit period length makes the unit spacing smaller than the terahertz operating wavelength, suppressing the generation of higher-order diffraction effects.

[0038] In conjunction with some implementation methods of the first aspect, in some implementation methods, a preset terahertz far-field scattering model is used to calculate the electric field intensity of each two-dimensional coding matrix in the initial population at the target elevation angle and the target azimuth angle, respectively, specifically including:

[0039] Set a spatial interference suppression zone, which is defined by a preset pitch angle range and azimuth angle range, and the spatial interference suppression zone does not include the target pitch angle and the target azimuth angle;

[0040] Using a pre-defined terahertz far-field scattering model, the main lobe electric field intensity of each two-dimensional coding matrix at the target elevation angle and target azimuth angle, as well as the maximum side lobe electric field intensity within the space interference suppression region, are calculated respectively.

[0041] Based on the electric field strength of the main lobe and the electric field strength of the maximum side lobe, the corrected electric field strength of each two-dimensional coding matrix is ​​calculated using a preset electric field strength calculation function, and the corrected electric field strength is used as the electric field strength of the two-dimensional coding matrix at the target pitch angle and the target azimuth angle.

[0042] By adopting the above technical solution, when calculating the electric field intensity of each two-dimensional coding matrix, the electric field intensity of the main lobe in the target direction and the electric field intensity of the maximum side lobe in the suppression region are considered simultaneously, and the modified electric field intensity is used as the evaluation index. This improves the accuracy of beamforming, enhances the directional performance of metasurface beam control, strengthens the spatial selectivity of the metasurface for terahertz beams, and reduces the radiation intensity of the beam in undesired directions.

[0043] In conjunction with some implementations of the first aspect, in some implementations, the preset electric field strength calculation function is:

[0044]

[0045] In the above function, To correct the electric field strength, and These are the preset main lobe weighting coefficients and the preset side lobe suppression weighting coefficients, respectively. The magnitude of the electric field intensity on the main lobe. This represents the magnitude of the maximum sidelobe electric field intensity within the spatial interference suppression region.

[0046] By adopting the above technical solution and adjusting the ratio of the weighting coefficients, the relationship between main lobe gain and side lobe suppression is balanced, improving the flexibility of beamforming. The calculation method for the modified electric field intensity considers the energy focusing effect in the main lobe direction and the interference suppression effect in the side lobe region, improving the overall performance of the beam pattern. This weighted calculation method enhances the metasurface's spatial control capability of terahertz beams, improves the lobe characteristics of the beam pattern, and increases the energy utilization efficiency of terahertz beams during space transmission.

[0047] In a second aspect, embodiments of this application provide a system comprising: one or more processors and a memory; the memory being coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, and the one or more processors invoking the computer instructions to cause the system to perform the method as described in the first aspect and any possible implementation thereof.

[0048] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0049] Fourthly, embodiments of this application provide a computer program product that, when run on a system, causes the system to execute the method described in any possible implementation of the first aspect.

[0050] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0051] 1. This application provides a terahertz-encoded metasurface two-degree-of-freedom beam control method. It optimizes the two-dimensional encoding matrix using a genetic algorithm, dynamically adjusts crossover and mutation probabilities based on individual fitness, and introduces an elite retention strategy to improve the convergence efficiency of the encoding sequence. The optimized two-dimensional encoding matrix can more accurately achieve beam control at the target elevation and azimuth angles. Due to the mirror-symmetric three-layer structure design, the combination of the metal double-slit resonator ring and the polytetrafluoroethylene dielectric layer enhances the electromagnetic response of the metasurface unit. By mapping the optimal encoding sequence to the rotation angle of the metasurface unit, precise control of the incident electromagnetic wave phase is achieved. This genetic algorithm-based optimization method reduces the impact of phase quantization errors and improves the electric field strength and beam pointing accuracy of the terahertz beam in the target direction.

[0052] 2. This application provides a terahertz coded metasurface dual-degree-of-freedom beamforming method. When calculating the electric field intensity of each two-dimensional coding matrix, the main lobe electric field intensity in the target direction and the maximum side lobe electric field intensity in the suppression region are considered simultaneously. The modified electric field intensity is used as an evaluation index, which improves the accuracy of beamforming, improves the directional performance of metasurface beamforming, enhances the spatial selectivity of the metasurface to the terahertz beam, and reduces the radiation intensity of the beam in the undesired direction. Attached Figure Description

[0053] Figure 1 This is a schematic flowchart of a terahertz-encoded metasurface dual-degree-of-freedom beam control method in an embodiment of this application.

[0054] Figure 2 This is another flowchart illustrating a terahertz-encoded metasurface dual-degree-of-freedom beam control method in an embodiment of this application.

[0055] Figure 3 This is a schematic diagram of the physical device structure of a terahertz coded metasurface dual-degree-of-freedom beam control system provided in the embodiments of this application. Detailed Implementation

[0056] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0057] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0058] With the rapid development of 6G technology and terahertz (THz) science, the terahertz band, due to its ultra-wide bandwidth and extremely high data transmission rate, has become a key frequency band for future wireless communication and high-resolution imaging. In terahertz communication and radar systems, how to flexibly and efficiently control the direction and shape of the beam is a core issue. Current technologies typically employ traditional phased array antennas or mechanically scanned antennas to achieve beam scanning, but these devices are often bulky, costly, and complex. In recent years, coded metasurfaces, as a type of digital metamaterial, have emerged. By changing the digital coding states of the units (such as "0" and "1"), they can control the phase of electromagnetic waves, thereby achieving flexible beam control. They offer advantages such as low profile, low cost, and ease of integration.

[0059] However, as the scale of metasurface arrays increases, the number of combinations of coded sequences grows exponentially, making it extremely difficult to find the optimal coded sequence in the vast solution space that can accurately achieve dual-degree-of-freedom beam pointing at specific elevation and azimuth angles. Traditional exhaustive methods or simple optimization algorithms often involve excessive computation or are prone to getting trapped in local optima, resulting in insufficient beam pointing accuracy, excessively high sidelobe levels, and difficulty in balancing convergence speed and optimization accuracy. Furthermore, existing phase modulation methods often ignore the impact of quantization errors on the actual far-field radiation pattern. To address these technical problems, this application provides a terahertz coded metasurface dual-degree-of-freedom beam pointing method. An embodiment is described below, combined with… Figure 1 The present application describes a terahertz-encoded metasurface dual-degree-of-freedom beam control method in its embodiments:

[0060] Please see Figure 1This is a flowchart illustrating a terahertz-encoded metasurface dual-degree-of-freedom beam control method in an embodiment of this application.

[0061] S101. Set the row and column size of the metasurface array, and randomly generate several two-dimensional coding matrices based on a 2-bit coding set containing four states, and form an initial population from the several two-dimensional coding matrices.

[0062] The terahertz-encoded metasurface consists of several periodically arranged metasurface units. Each metasurface unit is a mirror-symmetric structure containing a top layer, a middle layer, and a bottom layer. The top and bottom layers are metal double-slit resonant rings, and the middle layer is a polytetrafluoroethylene (PTFE) dielectric layer. The structural parameters and material properties of the metasurface unit are as follows: the outer radius of the metal double-slit resonant ring is 44 μm, the inner radius is 35 μm, the slit width is 8 μm, and the metal thickness is 0.4 μm; the thickness of the PTFE dielectric layer is 25 μm, and the relative permittivity is 2.1 + 0.0002i; the period length of the metasurface unit is 110 μm.

[0063] The system first defines the physical size parameters of the metasurface array, namely, the number of rows and columns of metasurface units in the array. This scale determines the antenna aperture size and the upper limit of beam gain. Then, the system constructs an initial solution space based on a 2-bit coding set, which contains four discrete states {00, 01, 10, 11}, each corresponding to a different physical phase response. Based on this, the system uses a random algorithm to generate several two-dimensional coding matrices. The dimension of each matrix is ​​consistent with the defined row and column size, and each element in the matrix is ​​randomly selected from the four states. This set of generated two-dimensional coding matrices is collectively referred to as the "initial population," where each two-dimensional coding matrix represents an independent individual, i.e., a possible metasurface phase distribution scheme. In this step, the metasurface unit structure is specifically defined as a three-layer mirror-symmetric structure containing a top layer, a middle layer, and a bottom layer. The top and bottom layers consist of metal double-slit resonant rings with geometric parameters including an outer radius of 44 μm, an inner radius of 35 μm, a slit width of 8 μm, and a metal thickness of 0.4 μm. This structural design is intended to generate strong electromagnetic resonances to cover the required phase range. The middle layer is a polytetrafluoroethylene (PTFE) dielectric layer with a thickness of 25 μm and a relative permittivity of 2.1 + 0.0002i, providing stable dielectric support and impedance matching. The period length of the unit cell is fixed at 110 μm to meet the subwavelength requirements of the terahertz band. The initial population size is typically set to a preset integer value, which needs to strike a balance between computational efficiency and population diversity.

[0064] In implementing this step, the system can employ various random number generation strategies to construct the initial population. The first approach uses a pseudo-random number generator (such as the Mason rotation algorithm) to independently generate a random floating-point number between 0 and 1 for each position in each two-dimensional encoding matrix. This number is then mapped to four states: 00, 01, 10, and 11, based on the intervals [0, 0.25), [0.25, 0.5), [0.5, 0.75), and [0.75, 1.0]. This method is simple, efficient, and can quickly fill a large amount of individual data. To improve the uniformity of the initial population distribution in the solution space, the second approach uses chaotic mapping algorithms (such as Logistic mapping or Tent mapping) to generate a chaotic sequence. The system first generates a chaotic sequence and then quantizes the values ​​in the sequence into four encoded states. Because chaotic sequences are ergodic and non-repetitive, the initial population generated by this method is more evenly distributed in the encoding space, which can effectively avoid the initial population from clustering in a local region of the solution space, thus providing a better global search basis for subsequent genetic algorithm iterations.

[0065] S102. Using the preset terahertz far-field scattering model, calculate the electric field intensity of each two-dimensional coding matrix in the initial population at the target elevation angle and the target azimuth angle respectively.

[0066] Using a pre-defined terahertz far-field scattering model, the electric field intensity of each two-dimensional coding matrix in the initial population at the target elevation angle and target azimuth angle is calculated. The calculation formula for the pre-defined terahertz far-field scattering model is as follows:

[0067]

[0068] In the above formula, The pitch angle, It is the azimuth angle. Let be the propagation constant. For a unit period, For the first The phase of each unit, This represents the far-field function of a single unit. For each two-dimensional encoding matrix in the initial population, the system converts its internal encoding state into the corresponding phase distribution, and combines this with the input "target elevation angle" and "target azimuth angle" parameters, substituting them into the scattering model formula for calculation. The core of this step lies in calculating the electric field vector sum of all units in the array in a specific spatial direction (i.e., the target angle) through the superposition principle, thereby obtaining the composite electric field intensity in that direction.

[0069] To efficiently implement this computation, the system can employ parallel computing acceleration techniques based on graphics processing units (GPUs). Since the initial population contains a large number of individuals, and the electric field calculation process for each individual is independent, the system can transfer the data of each two-dimensional encoding matrix to GPU memory, using parallel kernel functions written in CUDA or OpenCL architectures to simultaneously perform matrix operations and complex number accumulations on hundreds or thousands of individuals. This approach can improve computational speed by several orders of magnitude compared to traditional CPU serial computation. Another implementation method utilizes the Fast Fourier Transform (FFT) algorithm. Since the far-field radiation pattern is essentially a Fourier transform of the aperture field distribution, the system can map the two-dimensional encoding matrix to an aperture field distribution matrix, expand the matrix dimension by zero-padding, and then perform a two-dimensional FFT operation. Although the FFT calculates the field distribution across the entire space, the values ​​at the target's elevation and azimuth angles can be directly extracted using indices. This method offers a particularly significant advantage in time complexity when processing very large-scale arrays (such as 100x100 and above).

[0070] S103. Use the electric field strength value as the individual fitness of the corresponding two-dimensional coding matrix;

[0071] After calculating the electric field strength, the system performs a fitness assignment operation. Fitness is a core indicator in genetic algorithms used to evaluate the quality of individuals, directly determining their survival probability in subsequent evolutionary processes. In this step, the system directly selects the electric field strength magnitude (or the square of the magnitude, i.e., power density) calculated in step S102 at the target elevation and azimuth angles as the individual fitness of the corresponding two-dimensional encoding matrix. This means that the encoding matrix with stronger radiated energy and more precise beam pointing in the target direction will obtain a higher fitness value. This process establishes a clear optimization guideline: finding the phase encoding distribution that maximizes the directional radiation capability in the target direction. At this point, fitness is a non-negative real number, and the system establishes a key-value pair mapping between an index and the fitness value for each individual in the population, so that subsequent steps can sort and filter them.

[0072] S104. Calculate the average fitness of all individuals in the initial population to obtain the average fitness of the population.

[0073] The system iterates through the fitness values ​​of all individuals in the current population, performs an accumulation operation, and divides the accumulated result by the total number of individuals in the population to obtain the average fitness of the population. This statistic reflects the overall quality level of the current generation of the population and serves as a baseline for subsequent adaptive parameter adjustments.

[0074] S105. Based on the individual fitness and the population average fitness of each two-dimensional coding matrix, determine the crossover probability and mutation probability of each two-dimensional coding matrix.

[0075] The system determines the crossover probability and mutation probability of each two-dimensional encoding matrix based on the individual fitness and the average fitness of the population. Specifically, this includes: setting the default crossover probability to a first preset value and the default mutation probability to a second preset value, where the first preset value is greater than the second preset value; if the individual fitness of the two-dimensional encoding matrix is ​​higher than the average fitness of the population, then the crossover probability is reduced to any third preset value less than the first preset value and the mutation probability is reduced to any fourth preset value less than the second preset value; if the individual fitness of the two-dimensional encoding matrix is ​​less than or equal to the average fitness of the population, then the crossover probability is kept unchanged or increased to any fifth preset value greater than the first preset value, and the mutation probability is kept unchanged or increased to any sixth preset value greater than the second preset value.

[0076] Based on the principles of adaptive genetic algorithms, the system dynamically assigns crossover and mutation probabilities to each individual in the population. This step involves several preset probability thresholds: a first preset value (default high crossover rate), a second preset value (default low mutation rate), a third preset value (low crossover rate), a fourth preset value (extremely low mutation rate), a fifth preset value (high crossover rate), and a sixth preset value (high mutation rate). The core of the logical judgment lies in comparing the individual's fitness with the population average fitness obtained in step S104. If the individual's fitness is higher than the average, it indicates that the individual carries a superior gene fragment. To prevent the superior pattern from being destroyed in subsequent operations, the system will reduce the individual's crossover probability to the third preset value and the mutation probability to the fourth preset value, adopting a protection strategy. Conversely, if the individual's fitness is lower than or equal to the average, it indicates that the individual is performing poorly. The system will maintain its crossover probability at the first preset value or increase it to the fifth preset value, and maintain its mutation probability at the second preset value or increase it to the sixth preset value, adopting a elimination or recombination strategy. The specific values ​​for the first preset value (default high crossover rate), the second preset value (default low mutation rate), the third preset value (low crossover rate), the fourth preset value (extremely low mutation rate), the fifth preset value (high crossover rate), and the sixth preset value (high mutation rate) are not specified here.

[0077] S106. Based on the crossover probability and mutation probability of each two-dimensional encoding matrix, perform crossover and mutation operations on each two-dimensional encoding matrix to obtain a set of offspring individuals;

[0078] Based on the probability parameters determined in step S105, the system performs crossover operations on pairs of individuals in the population and mutation operations on individual individuals. Crossover involves exchanging partial coding matrix data between two parent individuals to generate superior offspring; mutation randomly alters the coding state at certain positions in the individual's matrix to introduce new genetic diversity. For crossover, the system first generates a random number; if this number is less than the crossover probability, crossover is performed. Similarly, for mutation, if the random number is less than the mutation probability, mutation is performed. The new set of individuals generated in this process is called the "offspring set." This step is the core of the genetic algorithm in generating new solutions and directly determines the algorithm's search trajectory.

[0079] When implementing crossover operations, the system can employ single-point or multi-point crossover techniques. In the context of a two-dimensional matrix, the system can stretch the matrix into a one-dimensional vector, randomly select one or more cut points, and swap the segments of the two parent vectors after the cut points. Alternatively, the system can use block crossover, randomly selecting a rectangular region in the two-dimensional matrix and swapping all the coding elements of the two parent vectors within that region. For mutation operations, the system typically uses single-point mutation, randomly selecting a coordinate (x, y) in the matrix and randomly changing its coding state from its current value to one of the other three values ​​in the 2-bit coding set. Another mutation implementation is inversion mutation, which involves selecting a gene sequence and completely reversing its order. This method alters the arrangement structure while preserving the gene components, facilitating mutations that generate phase gradients in a specific direction.

[0080] S107. The two-dimensional coding matrix of the top-performing individuals in the initial population based on their fitness is taken as the elite individuals.

[0081] The system employs an elite preservation strategy to prevent the loss of superior genes due to the randomness of genetic operations (crossover and mutation). First, the system sorts all individuals in the initial population (or the previous generation) according to their fitness from highest to lowest. After sorting, the system selects a top-ranked number of two-dimensional encoding matrices based on a preset proportion (e.g., the top 5% or top 10%). These selected individuals are called "elite individuals." Elite individuals are directly copied and stored in a temporary elite buffer without undergoing crossover or mutation. This step ensures the monotonically convergent nature of the algorithm, meaning that the optimal solution in each generation is at least no worse than the previous generation.

[0082] S108. Merge the elite individuals and offspring individuals, and select a predetermined number of two-dimensional coding matrices according to the order of individual fitness from high to low to form a new generation population.

[0083] The system merges the elite individuals retained in step S107 with the offspring individuals generated in step S106 into the same data pool. At this point, the total number of individuals in the data pool usually exceeds the initial population size. To maintain a constant population size, the system needs to re-evaluate the fitness of all merged individuals (the fitness of elite individuals is known, but the fitness of offspring individuals needs to be recalculated or calculated during generation). Subsequently, the system rigorously selects individuals whose fitness is equal to the initial population size, in descending order. These selected individuals constitute the new generation population, used for the next iteration cycle.

[0084] S109. Determine whether the current iteration process meets the preset termination condition;

[0085] After each generation of population updates, the system needs to check whether the criteria for stopping the algorithm have been met. Preset termination conditions typically include two dimensions: first, the maximum number of iterations, i.e., whether the number of generations the algorithm has run has reached a preset upper limit (e.g., 100 or 500 generations); second, convergence accuracy, i.e., whether the fitness of the best individual has reached the expected target value, or whether the change in the average fitness of the population over several consecutive generations (e.g., 20 consecutive generations) is less than a very small threshold (i.e., stagnation). If either of these conditions is met, the system determines that the iteration has ended; otherwise, the system will continue to execute the next round of the loop.

[0086] S110, Use the new generation population as the initial population;

[0087] If the preset termination condition is not met, the new generation population is used as the initial population, and the process returns to the step of calculating the electric field strength of each two-dimensional encoding matrix in the initial population at the target elevation and azimuth angles. This is a logically recursive or loop-connected step. If step S109 determines that the termination condition is not met, the system needs to completely transfer or mark the data state of the new generation population generated in step S108 as the initial population for the next round of the cycle. This is not just data copying, but also an update of the algorithm state. Subsequently, the system control flow jumps back to step S102 (calculating electric field strength) to begin a new round of evaluation, selection, crossover, and mutation. This step ensures that the genetic algorithm is a closed-loop feedback control system, accumulating evolutionary advantages through continuous iteration.

[0088] In practical implementations, to improve memory operation efficiency, the system typically avoids large-scale data transfer (DeepCopy). Instead, it employs double buffering or pointer swapping techniques. The system pre-allocates two sufficiently large spaces in memory to store the data of the current generation and the next generation, respectively. In step S110, the system only needs to swap the pointers (Current_Ptr and Next_Ptr) pointing to these two memory regions to instantly complete the population replacement. This operation has a time complexity of O(1), saving system overhead. Another implementation method utilizes object reference updates in object-oriented programming to reassign the population objects, ensuring that the garbage collection mechanism (if applicable) correctly handles old, useless data (in the case of partial update mode).

[0089] S111. Select the two-dimensional coding matrix with the highest individual fitness in the new generation population as the optimal coding sequence output;

[0090] If the preset termination condition is met, the two-dimensional encoding matrix with the highest individual fitness in the new generation population is selected as the optimal encoding sequence output. After step S109 determines that the termination condition is met, the system performs the final output operation. The system traverses the last generation population (or directly accesses the globally historical best variable maintained throughout the iteration process) and locks the two-dimensional encoding matrix with the largest fitness value. This matrix represents the phase distribution scheme found throughout the evolutionary process that best responds to the target pitch and azimuth angles. The system extracts this matrix, marks it as the optimal encoding sequence, and outputs it to the subsequent processing module through the data interface. At this point, the output data is still a numerical matrix composed of {00, 01, 10, 11}.

[0091] In practical implementation, the system can use a simple linear scan algorithm to traverse the final population array, comparing and recording the indices of the maximum values. For ease of subsequent analysis, the system not only outputs the optimal coding sequence but also simultaneously outputs the corresponding simulation pattern data, maximum gain value, sidelobe level data, and convergence curve. Another implementation approach is to perform a local search verification before outputting the results. That is, after selecting the optimal individual, a rapid exhaustive check is performed on its surrounding coding states (e.g., randomly flipping 1-2 bits) to confirm whether they are true local extrema. Although this adds a small amount of computation, it ensures the robustness of the output results.

[0092] S112. According to the preset mapping rules, each coding element in the optimal coding sequence is converted into the rotation angle of the corresponding metasurface unit.

[0093] According to a preset mapping rule, the system converts each coded element in the optimal coded sequence into the rotation angle of the corresponding metasurface unit. The preset mapping rule is as follows: the 2-bit coded set contains four coded states {00, 01, 10, 11}; the coded state 00 corresponds to a metasurface unit rotation angle of 0°; the coded state 01 corresponds to a metasurface unit rotation angle of 45°; the coded state 10 corresponds to a metasurface unit rotation angle of 90°; and the coded state 11 corresponds to a metasurface unit rotation angle of 135°. The co-polarization reflection phase difference of the metasurface units corresponding to adjacent coded states is fixed at 90°, and the phase error does not exceed 2%.

[0094] The system receives the optimal encoding sequence output in step S111 and converts it into physical control parameters. This application utilizes the Pancharatnam-Berry (PB) phase principle (also known as geometric phase), which states that under circularly polarized wave incidence, an additional phase, twice the rotation angle, can be introduced by rotating an anisotropic metasurface unit. Pre-defined mapping rules clarify the correspondence between the 2-bit encoding and the physical rotation angle: encoding "00" maps to 0° rotation; encoding "01" maps to 45° rotation; encoding "10" maps to 90° rotation; and encoding "11" maps to 135° rotation.

[0095] In practice, the system can build a highly efficient look-up table (LUT). The system iterates through the encoding matrix, using each 2-bit binary number as an index, and directly reads the corresponding floating-point angle value from the LUT. This method is extremely fast.

[0096] S113. Rotate the corresponding metasurface unit in the terahertz-encoded metasurface according to the rotation angle.

[0097] The system drives changes in the physical structure of the terahertz-encoded metasurface based on the angle control matrix generated in step S112. If it's on actual dynamic metasurface hardware (e.g., a microfluidic, MEMS, or liquid crystal-based metasurface), the system converts the angle values ​​into corresponding driving voltages or pulse signals and sends them to the underlying actuators to drive each unit to rotate to a specified angle. If it's in the simulation design phase, the system uses scripts in electromagnetic simulation software (such as CST or HFSS) to batch modify the geometric rotation parameters of each unit in the model, completing the model reconstruction for final full-wave verification or fabrication layout export.

[0098] In practical implementation, for metasurfaces based on microelectromechanical systems (MEMS), the system outputs control voltage via a multiplexed digital-to-analog converter (DAC). An electrostatic comb driver is integrated beneath each cell, and the voltage magnitude determines the rotation angle. The system needs to refresh the control voltage of the array row by row or column by column according to a specific timing sequence. For statically fabricated metasurfaces, this step corresponds to the generation of a photomask. The system uses GDSII or DXF format to generate scripts, drawing the actual geometry of each double-slit resonant ring based on the angle matrix. Each shape is rotated by a corresponding angle relative to the local coordinate system.

[0099] In the above embodiments, the convergence efficiency of the coding sequence is improved by optimizing the two-dimensional coding matrix using a genetic algorithm, dynamically adjusting the crossover and mutation probabilities based on individual fitness, and introducing an elite retention strategy. The optimized two-dimensional coding matrix can more accurately achieve beam control at the target elevation and azimuth angles. Due to the mirror-symmetric three-layer structure design, the combination of the metal double-slit resonator ring and the polytetrafluoroethylene dielectric layer enhances the electromagnetic response of the metasurface unit. By mapping the optimal coding sequence to the rotation angle of the metasurface unit, precise control of the incident electromagnetic wave phase is achieved. This optimization method based on a genetic algorithm reduces the influence of phase quantization error and improves the electric field strength and beam pointing accuracy of the terahertz beam in the target direction.

[0100] The above embodiments described the basic process of a terahertz-encoded metasurface two-degree-of-freedom beamforming method based on a genetic algorithm. To further improve the accuracy of beamforming, especially in terms of spatial interference suppression, another terahertz-encoded metasurface two-degree-of-freedom beamforming method is introduced below. This method optimizes the calculation process of the electric field intensity by introducing the concept of a spatial interference suppression region and modifying the calculation method of the electric field intensity, thus achieving finer control of the beam pattern. The following section combines... Figure 2 Another terahertz-encoded metasurface two-degree-of-freedom beam control method in the embodiments of this application is described below:

[0101] Please see Figure 2 This is another flowchart illustrating a terahertz-encoded metasurface dual-degree-of-freedom beam control method in an embodiment of this application.

[0102] S201. Set the spatial interference suppression area;

[0103] The system sets up a spatial interference suppression region, which is defined by preset elevation and azimuth ranges, but excludes the target elevation and azimuth angles. The system first performs the definition of the spatial interference suppression region, a crucial initialization step for achieving high signal-to-noise ratio beamforming. In this step, the spatial interference suppression region refers to a specific solid angle range within the terahertz beam scanning space that the system explicitly specifies to reduce electromagnetic radiation intensity. This region typically corresponds to sensitive receiving equipment, friendly communication channels, or geographical locations where radio silence needs to be maintained. This region is jointly defined by the preset elevation and azimuth ranges, forming one or more closed regions in spherical coordinates, either rectangular or of arbitrary shape. It is important to note that the setting of the spatial interference suppression region is non-exclusive and flexible; that is, the system can simultaneously set multiple discontinuous suppression regions, and the shape of the regions is not limited to regular geometric shapes. Furthermore, to ensure the physical feasibility of beamforming and the performance of the main lobe, the system logically mandates that the spatial interference suppression region and the main beam region containing the target elevation and azimuth angles must not overlap, and there should be a non-zero angular distance between them as a transition zone. The relevant angular threshold relationship is: the absolute value of the difference between the boundary angle of the suppression region and the target angle must be greater than half of the preset beam half-power bandwidth to prevent unintended reduction in the main lobe gain. Through this step, the system transforms the originally simple beam pointing problem into a constrained optimization problem, namely, minimizing the sidelobe level in a specific region while ensuring the main lobe pointing.

[0104] In implementing this step, the system can adopt a parameter configuration method based on a human-computer interaction interface. The system provides a visual spherical coordinate scan map or a two-dimensional planar unfolded map. Operators delineate the rectangular suppression zone by inputting specific values ​​for the starting elevation angle, ending elevation angle, starting azimuth angle, and ending azimuth angle. After receiving the input, the system automatically runs a collision detection algorithm to verify whether the input area covers the target beam direction. If a collision exists, an alarm is issued and the setting is rejected. Another implementation method is adaptive setting based on environmental perception. The system connects to radar or spectrum monitoring equipment through an external interface to receive the coordinate information of interference sources or sensitive targets in the environment in real time. The internal processor converts these Cartesian coordinates into spherical coordinates relative to the center of the metasurface array and automatically calculates the required angular range based on the physical size and distance of the interference source, thereby dynamically generating a spatial interference suppression area.

[0105] S202. Using a preset terahertz far-field scattering model, calculate the main lobe electric field intensity of each two-dimensional coding matrix at the target elevation angle and target azimuth angle, as well as the maximum side lobe electric field intensity within the space interference suppression region.

[0106] After determining the suppression region, the system calls a preset terahertz far-field scattering model to perform a detailed electromagnetic performance evaluation of each individual in the population. In this step, the main lobe electric field strength specifically refers to the far-field radiation field strength modulus generated by the two-dimensional coding matrix at the predetermined target pointing (target elevation angle and target azimuth angle), which characterizes the beam gain performance. The maximum sidelobe electric field strength refers to the peak electric field strength in all radiation directions generated by the coding matrix within the spatial interference suppression region defined in step S201. This is an extremum search process aimed at finding the most severe interference point within the region. The preset terahertz far-field scattering model is consistent with the aforementioned embodiment, based on array antenna theory, and comprehensively considers element phase, array factor, and propagation constant. The system not only needs to calculate the field strength at a single point, but also needs to scan or search a continuous spatial region to capture the maximum radiated energy within that region. This step is the basis for subsequent calculations of the corrected fitness, and its calculation accuracy directly affects the final beam's interference suppression capability.

[0107] When calculating the main lobe electric field intensity, the system directly substitutes the target angle into the scattering formula to obtain the result. For calculating the maximum sidelobe electric field intensity within the space interference suppression region, the system can employ a discrete grid scanning method. First, the system discretizes the continuous pitch and azimuth angle ranges according to a preset step size (e.g., 0.5 degrees or 1 degree), generating a grid set containing several sampling points. Then, using a GPU parallel computing architecture, the system simultaneously calculates the electric field intensity of the encoding matrix at all grid points and selects the maximum value through comparison operations. This method is simple to implement and can be accelerated using matrix operations. Another implementation method is to use a gradient-based local search algorithm (such as hill climbing or Newton's method). The system randomly selects several initial seed points within the suppression region, calculates their field strength and gradient direction, and guides the search points to move in the direction of increasing field strength until convergence to a local maximum. The system then compares the values ​​of all converged points and selects the largest as the maximum sidelobe electric field intensity. This method significantly reduces the computational load compared to full grid scanning when the suppression region is large.

[0108] S203. Based on the electric field strength of the main lobe and the electric field strength of the maximum side lobe, calculate the corrected electric field strength of each two-dimensional coding matrix using a preset electric field strength calculation function, and use the corrected electric field strength as the electric field strength of the two-dimensional coding matrix at the target pitch angle and the target azimuth angle.

[0109] Based on the electric field intensity of the main lobe and the electric field intensity of the maximum side lobe, the corrected electric field intensity of each two-dimensional coding matrix is ​​calculated using a preset electric field intensity calculation function. This corrected electric field intensity is then used as the electric field intensity of the two-dimensional coding matrix at the target elevation and azimuth angles. The preset electric field intensity calculation function is as follows:

[0110]

[0111] In the above function, To correct the electric field strength, and These are the preset main lobe weighting coefficients and the preset side lobe suppression weighting coefficients, respectively. The magnitude of the electric field intensity on the main lobe. This represents the magnitude of the maximum sidelobe electric field intensity within the spatial interference suppression region.

[0112] The system directly assigns the calculated corrected electric field strength to the corresponding two-dimensional encoding matrix as its new fitness in the genetic algorithm. This means that if an encoding matrix has a strong main lobe but strong side lobes in the suppression region, its corrected score will be significantly reduced, thus eliminating it from the evolutionary process; only individuals with strong main lobes and low side lobes in the suppression region can obtain high scores and be inherited.

[0113] In the above embodiments, when calculating the electric field intensity of each two-dimensional coding matrix, the electric field intensity of the main lobe in the target direction and the electric field intensity of the maximum side lobe in the suppression region are considered simultaneously, and the modified electric field intensity is used as an evaluation index, which improves the accuracy of beamforming, improves the directional performance of metasurface beam control, enhances the spatial selectivity of the metasurface for terahertz beams, and reduces the radiation intensity of the beam in undesired directions.

[0114] The system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of a terahertz coded metasurface dual-degree-of-freedom beam control system provided in an embodiment of this application.

[0115] It should be noted that, Figure 3 The structure of the system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0116] like Figure 3 As shown, the system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0117] The following components are connected to I / O interface 305: input section 306 including a camera, infrared sensor, etc.; output section 307 including a liquid crystal display (LCD) and speakers, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0118] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0119] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0120] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0121] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of a system, cause the system to implement the methods provided in the above embodiments.

[0122] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0123] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0124] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0125] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A terahertz-encoded metasurface two-degree-of-freedom beam control method, characterized in that, The terahertz-encoded metasurface is composed of several periodically arranged metasurface units, each of which is a mirror-symmetric structure comprising a top layer, a middle layer, and a bottom layer. The top and bottom layers are metallic double-slit resonant rings, and the middle layer is a polytetrafluoroethylene dielectric layer. The method includes: Set the row and column size of the metasurface array, and randomly generate several two-dimensional coding matrices based on a 2-bit coding set containing four states, and form the several two-dimensional coding matrices into an initial population; Using a preset terahertz far-field scattering model, the electric field intensity of each two-dimensional coding matrix in the initial population at the target elevation angle and the target azimuth angle is calculated respectively. The electric field strength value is used as the individual fitness of the corresponding two-dimensional coding matrix; Calculate the average fitness of all individuals in the initial population to obtain the average fitness of the population; The crossover probability and mutation probability of each two-dimensional encoding matrix are determined based on the individual fitness of each two-dimensional encoding matrix and the average fitness of the population. Based on the crossover probability and mutation probability of each two-dimensional encoding matrix, crossover and mutation operations are performed on each two-dimensional encoding matrix to obtain a set of offspring individuals; The two-dimensional coding matrix of the top-ranked individuals in the initial population based on their fitness is used as the elite individuals. The elite individuals and the offspring individuals are merged, and a predetermined number of two-dimensional coding matrices are selected according to the individual fitness from high to low to form a new generation population. Determine whether the current iteration process meets the preset termination condition; If the preset termination condition is not met, the new generation population is used as the initial population, and the process returns to the step of calculating the electric field strength of each two-dimensional coding matrix in the initial population at the target pitch angle and the target azimuth angle. If the preset termination condition is met, the two-dimensional coding matrix with the highest fitness of the individual in the new generation population is selected as the optimal coding sequence output. According to the preset mapping rules, each coding element in the optimal coding sequence is converted into the rotation angle of the corresponding metasurface unit; Rotate the corresponding metasurface unit in the terahertz-encoded metasurface according to the rotation angle.

2. The method according to claim 1, characterized in that, The step of determining the crossover probability and mutation probability of each two-dimensional encoding matrix based on the individual fitness of each two-dimensional encoding matrix and the average fitness of the population specifically includes: The default crossover probability is set to a first preset value, and the default mutation probability is set to a second preset value, wherein the first preset value is greater than the second preset value; If the individual fitness of the two-dimensional coding matrix is ​​higher than the average fitness of the population, then the crossover probability is reduced to any third preset value less than the first preset value and the mutation probability is reduced to any fourth preset value less than the second preset value. If the individual fitness of the two-dimensional coding matrix is ​​less than or equal to the average fitness of the population, then the crossover probability remains unchanged or is increased to any fifth preset value greater than the first preset value, and the mutation probability remains unchanged or is increased to any sixth preset value greater than the second preset value.

3. The method according to claim 1, characterized in that, The calculation formula for the preset terahertz far-field scattering model is as follows: In the above formula, the The pitch angle, the The azimuth angle, the Let be the propagation constant, the For a unit period, the For the first The phase of each unit, the This is the far-field function for a single unit.

4. The method according to claim 1, characterized in that, The preset mapping rule is as follows: The 2-bit encoding set includes four encoding states: {00, 01, 10, 11}. The encoding state 00 corresponds to a metasurface unit rotation angle of 0°; the encoding state 01 corresponds to a metasurface unit rotation angle of 45°; the encoding state 10 corresponds to a metasurface unit rotation angle of 90°; the encoding state 11 corresponds to a metasurface unit rotation angle of 135°; the co-polarization reflection phase difference of metasurface units corresponding to adjacent encoding states is fixed at 90°, and the phase error does not exceed 2%.

5. The method according to claim 1, characterized in that, The structural parameters and material properties of the metasurface unit specifically include: The outer radius of the metal double-slit resonant ring is 44 μm, the inner radius is 35 μm, the slit width is 8 μm, and the metal thickness is 0.4 μm. The polytetrafluoroethylene dielectric layer has a thickness of 25 μm and a relative permittivity of 2.1 + 0.0002i. The period length of the metasurface unit is 110 μm.

6. The method according to claim 1, characterized in that, The step of using a preset terahertz far-field scattering model to calculate the electric field intensity of each two-dimensional encoding matrix in the initial population at the target elevation angle and target azimuth angle specifically includes: A spatial interference suppression zone is defined, which is limited by a preset pitch angle range and an azimuth angle range, and the spatial interference suppression zone does not include the target pitch angle and the target azimuth angle; Using the preset terahertz far-field scattering model, the main lobe electric field intensity of each of the two-dimensional coding matrices at the target pitch angle and the target azimuth angle, as well as the maximum side lobe electric field intensity in the space interference suppression region, are calculated respectively. Based on the main lobe electric field strength and the maximum side lobe electric field strength, a preset electric field strength calculation function is used to calculate the corrected electric field strength of each two-dimensional coding matrix, and the corrected electric field strength is used as the electric field strength of the two-dimensional coding matrix at the target pitch angle and the target azimuth angle.

7. The method according to claim 6, characterized in that, The preset electric field strength calculation function is: In the above function, the For the corrected electric field strength, the and stated These are preset main lobe weighting coefficients and preset side lobe suppression weighting coefficients, respectively. The magnitude of the electric field intensity of the main lobe is given by the following formula. The magnitude of the maximum sidelobe electric field intensity within the spatial interference suppression region.

8. A terahertz-coded metasurface dual-degree-of-freedom beam control system, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the system, the system performs the method as described in any one of claims 1-7.

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