CN111881609B - Configuration method and device for stealth parameters of plasma material - Google Patents
Configuration method and device for stealth parameters of plasma material Download PDFInfo
- Publication number
- CN111881609B CN111881609B CN202010761646.7A CN202010761646A CN111881609B CN 111881609 B CN111881609 B CN 111881609B CN 202010761646 A CN202010761646 A CN 202010761646A CN 111881609 B CN111881609 B CN 111881609B
- Authority
- CN
- China
- Prior art keywords
- stealth
- plasma
- value
- plasma material
- parameter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000000463 material Substances 0.000 title claims abstract description 79
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 52
- 230000002068 genetic effect Effects 0.000 claims abstract description 51
- 239000010410 layer Substances 0.000 claims abstract description 41
- 238000005457 optimization Methods 0.000 claims abstract description 24
- 239000002356 single layer Substances 0.000 claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims abstract description 20
- 230000008569 process Effects 0.000 claims abstract description 14
- 230000005540 biological transmission Effects 0.000 claims abstract description 11
- 230000009191 jumping Effects 0.000 claims abstract description 8
- 239000013598 vector Substances 0.000 claims description 33
- 230000005684 electric field Effects 0.000 claims description 29
- 238000002310 reflectometry Methods 0.000 claims description 9
- 230000035772 mutation Effects 0.000 claims description 7
- 239000006185 dispersion Substances 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 5
- 230000035699 permeability Effects 0.000 claims description 5
- 238000013213 extrapolation Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 45
- 238000005516 engineering process Methods 0.000 description 6
- 238000013461 design Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000004590 computer program Methods 0.000 description 3
- 238000010521 absorption reaction Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 239000011229 interlayer Substances 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 238000004141 dimensional analysis Methods 0.000 description 1
- 230000008034 disappearance Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000007723 transport mechanism Effects 0.000 description 1
- 238000009827 uniform distribution Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Biophysics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Biology (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Genetics & Genomics (AREA)
- Data Mining & Analysis (AREA)
- Physiology (AREA)
- Geometry (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Computational Linguistics (AREA)
- Computer Hardware Design (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Plasma Technology (AREA)
Abstract
The invention discloses a configuration method and a device of a stealth parameter of a plasma material, wherein the method comprises the following steps: constructing a calculation model of a single-layer plasma material layer, and initializing a plasma material stealth parameter according to the transmission reflection characteristic of the plasma material; optimizing stealth parameters of a single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm; and jumping out of the genetic algorithm optimization circulation process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth. The invention can realize the rapid selection setting of parameters when the plasma frequency point is stealth.
Description
Technical Field
The invention relates to the technical field of material absorption and shielding, in particular to a method and a device for configuring stealth parameters of a plasma material.
Background
Compared with stealth technologies such as materials, shapes and the like, the plasma stealth technology has the unique advantages of high absorptivity, wave absorption frequency bandwidth, good stealth effect, simplicity and convenience in use, capability of controlling plasma generation and disappearance at any time by switching, and the like, and has been widely paid attention to scientific researchers in all countries of the world. With the deep research of plasma stealth technology, the technology is gradually applied to the aspects of plasma stealth device design and military target stealth. Because of the complexity of the plasma stealth mechanism, it is very difficult to optimally design multiple parameters of the plasma.
Therefore, a new method for fast and efficient plasma frequency point stealth parameter design is needed.
Disclosure of Invention
The invention aims to provide a configuration method and a device for a plasma material stealth parameter, which can realize rapid selection and setting of the parameter when a plasma frequency point is stealth.
The invention discloses a configuration method of a stealth parameter of a plasma material, which comprises the following steps:
constructing a calculation model of a single-layer plasma material layer, and initializing a plasma material stealth parameter according to the transmission reflection characteristic of the plasma material;
optimizing stealth parameters of a single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm;
and jumping out of the genetic algorithm optimization circulation process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth.
Preferably, initializing the plasma material stealth parameters based on the transmission reflection characteristics of the plasma material comprises:
the Maxwell's equation and constitutive equation set for a non-magnetized plasma medium are expressed as follows:
wherein, V is a gradient operator,is the electric field component, +.>Is a magnetic field component>Is the polarized current density omega p Representing the plasma frequency, v is the electron impact frequency, ε 0 Is the dielectric constant in vacuum, mu 0 For permeability in vacuum, the plasma material stealth parameter includes ω p V and plasma layer thickness d, construction parameter vector p= [ ω ] p ,ν,d]The initial parameter values are randomly selected based on the range of each parameter.
Preferably, optimizing the stealth parameters of the single-layer plasma material layer required to achieve the stealth purpose at different frequency points by adopting a genetic algorithm comprises:
setting the number of individuals composing the genetic algorithm population as Np and the individuals as parameter omega p The parameter vector p formed when v and d take different values i ＝[ω p ,ν,d] i I=1, 2,3 … … Np, the population is a population p consisting of all individuals (1,2,3……Np) ；
The cost function of the genetic algorithm is set as:
F cost ＝C+RCS(f)
wherein C is a constant, and RCS (f) is the RCS value at frequency point f;
when analyzing a single plasma material layer, the RCS value is replaced by the reflectivity RF value of the single plasma material layer at the f frequency point, and then the cost function becomes:
F cost ＝C+RF(f)
the parameter vector is p= [ omega ] by a time domain finite difference method p ,ν,d]Calculating a single plasma material layer of the antenna to obtain RCS values or RF values corresponding to different frequency points;
carrying the cost function into a cost function formula to realize the calculation of the cost function; obtaining cost function values of single-layer plasma material layers with different frequency points;
population updating is achieved through updating operation of a genetic algorithm.
Preferably, the updating operation includes one or more of: selection operation, mutation operation and crossover operation.
Preferably, the population updating by the selection operation of the genetic algorithm comprises:
inverting the cost function values of the single-layer plasma material layers with different frequency points to obtain a fitness value corresponding to the ith individual:
fitvalue(i)＝1/F cost (i)
calculating to obtain the total value of the fitness values corresponding to all individuals:
wherein Np is the number of individuals;
calculating to obtain a selection probability value of the ith individual:
selection_value(i)＝fitvalue(i)/fitvalue_total
where i=1, 2,3.
Preferably, the population updating by the mutation operation of the genetic algorithm comprises:
the variant forms of real number coding are:
pop m+1 (i,:)＝pop m (i,:)+λ m ·rand·pop m (i,:)
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration m As a coefficient of variation, rand is a random number between (-1, 1).
Preferably, the population update by crossover operation of the genetic algorithm comprises:
the interleaving operation for the randomly selected i-th and j-th individual (i, j) parameter vectors is:
pop m+1 (i,:)＝pop m (i,:)+λ c ·(pop m (i,:)-pop m (j,:))
pop m+1 (j,:)＝pop m (j,:)+λ c ·(pop m (j,:)-pop m (i,:))
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration c Is a crossover coefficient.
Preferably, the preset determination condition is: optimizing the iteration step number to reach a set maximum step value or cost function F cost The value is less than the set threshold.
In a second aspect, the present invention further provides a device for configuring a stealth parameter of a plasma material, including:
the initialization module is arranged to construct a calculation model of a single plasma material layer, and initializes the stealth parameters of the plasma material according to the transmission and reflection characteristics of the plasma material;
the iteration module is used for optimizing stealth parameters of the single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm;
the configuration module is set to jump out of the genetic algorithm optimization circulation process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth.
Preferably, the configuration module is arranged in the following wayOptimizing the iteration step number to reach a set maximum step value or cost function F cost And when the value is smaller than the set threshold value, jumping out of the genetic algorithm to optimize the circulation process.
Compared with the prior art, the invention has the following advantages:
the invention solves the problem of parameter selection setting in the plasma frequency point stealth requirement. The invention utilizes genetic algorithm to determine the stealth parameters of the plasma frequency points, firstly establishes a calculation model and sets the parameter variation range, and respectively initializes the plasma parameter vectors; then changing a plurality of plasma parameters into vectors to be optimized, applying the corresponding plasma parameter vectors to a calculation model, designing different cost functions according to different stealth requirements, obtaining a cost function required by updating iteration of a genetic algorithm by using a time domain finite difference method, and updating an individual optimal value and a population optimal value through iteration of the genetic algorithm; and finally, obtaining the optimal value of the final population by the optimization cycle of the judgment condition jump-out genetic algorithm, namely the corresponding parameter value for hiding the plasma frequency point. The method can quickly realize the selection setting of parameters in the process of stealth of the plasma frequency points, and is used for target stealth design.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate and do not limit the invention.
FIG. 1 is a flow chart of a method for configuring stealth parameters of a plasma material according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a computing model structure according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a configuration device for plasma material stealth parameters according to an embodiment of the present invention;
FIG. 4 is a block diagram of a computing device according to another embodiment of the present application;
FIG. 5 is a block diagram of a computer readable storage medium according to another embodiment of the present application;
FIG. 6 is a graph of reflectivity of a target at a frequency point according to another embodiment of the present application;
fig. 7 is a graph of cost function versus iteration step according to another embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions. Also, while a logical order is depicted in the flowchart, in some cases, the steps depicted or described may be performed in a different order than presented herein.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a method for configuring stealth parameters of a plasma material, including:
s101, constructing a calculation model of a single-layer plasma material layer, and initializing plasma material stealth parameters according to the transmission and reflection characteristics of the plasma material;
s102, optimizing stealth parameters of a single-layer plasma material layer which is required to achieve stealth purposes at different frequency points by adopting a genetic algorithm;
and S103, jumping out of the genetic algorithm optimization cycle process according to a preset judgment condition to obtain a corresponding parameter value of plasma frequency point stealth.
In the embodiment of the present invention, step S101 includes initializing plasma material stealth parameters according to transmission and reflection characteristics of the plasma material:
the Maxwell's equation and constitutive equation set for a non-magnetized plasma medium are expressed as follows:
wherein, V is a gradient operator,is the electric field component, +.>Is a magnetic field component>Is the polarized current density omega p Representing the plasma frequency, v is the electron impact frequency, ε 0 Is the dielectric constant in vacuum, mu 0 For permeability in vacuum, the plasma material stealth parameter includes ω p V, v and plasma layer thickness d, construction parameter vector p= [ ω ] p ,ν,d]The initial parameter values are randomly selected based on the range of each parameter.
The schematic structure of the single-layer plasma computing model is shown in fig. 2, and the plasma is positioned in an interlayer of the target shell and the outer wave-transparent shell and is usually positioned at the key stealth part of the target so as to achieve the target stealth effect. The outer wave-transmitting shell is set to have high wave-transmitting rate, and the embodiment of the invention can calculate without considering electromagnetic wave-transmitting rate of the outer wave-transmitting shellThe effect of wave propagation, d, is the monolayer plasma thickness. Parameter vector p= [ ω ] p ,ν,d]During initialization, parameter values are randomly selected in a range according to different parameter ranges.
In the embodiment of the present invention, step S102 of optimizing stealth parameters of a single-layer plasma material layer required to achieve stealth at different frequency points by adopting a genetic algorithm includes:
setting the number of individuals composing the genetic algorithm population as Np and the individuals as parameter omega p The parameter vector p formed when v and d take different values i ＝[ω p ,ν,d] i I=1, 2,3 … … Np, the population is a population p consisting of all individuals (1,2,3……Np) ；
The cost function of the genetic algorithm is set as:
F cost ＝C+RCS(f)
wherein C is a constant, and RCS (f) is the RCS value at frequency point f;
when analyzing a single plasma material layer, the RCS value is replaced by the reflectivity RF value of the single plasma material layer at the f frequency point, and then the cost function becomes:
F cost ＝C+RF(f)
the parameter vector is p= [ omega ] by a time domain finite difference method p ,ν,d]Calculating a single plasma material layer of the antenna to obtain RCS values or RF values corresponding to different frequency points;
carrying the cost function into a cost function formula to realize the calculation of the cost function; obtaining cost function values of single-layer plasma material layers with different frequency points;
population updating is achieved through updating operation of a genetic algorithm.
The time domain finite difference solving process comprises:
the magnetic field components H in the x, y and z directions can be obtained by carrying out differential dispersion on the Maxwell's equation of the non-magnetized plasma medium and the first equation in the constitutive relation equation set respectively x ,H y ,H z Iterative expression:
wherein the superscript n represents the iteration time step, the subscripts i, j, k represent the coordinate positions of the electric field and the magnetic field components in the x, y and z directions in space respectively, and Deltax, deltay and Deltaz are the space step sizes in the x, y and z directions in space respectively, deltat is the time step size and E x ,E y ,E z Is the electric field component in x, y and z directions in space.
The electric field components E in the x, y and z directions can be obtained by carrying out differential dispersion on the Maxwell's equation of the non-magnetized plasma medium and the second equation in the constitutive relation equation set respectively x ,E y ,E z Iterative expression:
wherein J x ,J y ,J z Is the current density component in the x, y, z direction in space.
The current density components J in the x, y and z directions can be obtained by carrying out differential dispersion on the Maxwell's equation of the non-magnetized plasma medium and the third equation in the constitutive relation equation set respectively x ,J y ,J z Iterative expression:
and obtaining the corresponding electric field component value at the observation point through time step iteration updating according to the obtained electric field, magnetic field and current density iteration formula. The RCS values of different frequency points can be obtained by performing Fourier transform (FFT) on the near-field extrapolation of the electric field component. The RF values of different frequency points can be obtained by calculating the ratio of the incident electric field to the reflected electric field at the observation point and then performing FFT conversion. In the embodiment of the invention, the parameter optimization problem of maximum RCS reduction is realized at the frequency point f for realizing the target. The optimization solution is a minimization problem of the cost function value, and the minimum cost function individual corresponds to the optimal individual of the population. In the embodiment of the invention, the RCS value at the frequency point f is replaced by the reflectivity RF value, so that the cost function becomes:
F cost ＝C+RF(f)
where C is a constant used to make the cost function value positive, c=100 is chosen here, considering that the value of RF is not less than-100 dB. Different parameter vectors p= [ omega ] are paired by a time domain finite difference method p ,ν,d]The corresponding RCS or RF is obtained by calculation, and then the RCS or RF is carried into a cost function formula to realize the calculation of the cost function.
After the cost function value of each individual in the population is obtained, the population update can be realized through the operations of selection, variation, crossover and the like of a genetic algorithm.
In an embodiment of the present invention, the update operation includes one or more of the following: selection operation, mutation operation and crossover operation.
In the embodiment of the invention, the population updating through the selection operation of the genetic algorithm comprises the following steps:
inverting the cost function values of the single-layer plasma material layers with different frequency points to obtain a fitness value corresponding to the ith individual:
fitvalue(i)＝1/F cost (i)
calculating to obtain the total value of the fitness values corresponding to all individuals:
wherein Np is the number of frequency bins;
calculating to obtain a selection probability value of the ith individual:
selection_value(i)＝fitvalue(i)/fitvalue_total
where i=1, 2,3.
In the embodiment of the invention, the cost function F is to be solved cost When the selection operation is performed by adopting the wheel disc method, the selection operation is required when the individual selection probability is obtained, and the cost function is inverted to obtain the fitness value.
In the embodiment of the invention, the implementation of population updating through mutation operation of a genetic algorithm comprises the following steps:
the variant forms of real number coding are:
pop m+1 (i,:)＝pop m (i,:)+λ m ·rand·pop m (i,:)
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration m As a coefficient of variation, rand is a random number between (-1, 1).
In the embodiment of the invention, the population updating through the cross operation of the genetic algorithm comprises the following steps:
the interleaving operation for the randomly selected i-th and j-th individual (i, j) parameter vectors is:
pop m+1 (i,:)＝pop m (i,:)+λ c ·(pop m (i,:)-pop m (j,:))
pop m+1 (j,:)＝pop m (j,:)+λ c ·(pop m (j,:)-pop m (i,:))
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration c Is a crossover coefficient.
In the embodiment of the invention, the preset judging conditions are as follows: optimizing the iteration steps to a set maximum step value or costFunction F cost The value is less than the set threshold.
In the embodiment of the invention, the cost function F cost After the minimum value is obtained, the loop is jumped out, and operations such as selection are not performed. The operations such as selection and the like are to continuously update the parameter vector value in each loop iteration, obtain the parameter vector meeting the requirement after the preset judging condition is jumped out of the loop, and correspond to the cost function F at the moment cost The minimum value is obtained.
Example two
As shown in fig. 3, a device for configuring stealth parameters of a plasma material is characterized by comprising:
the initialization module is arranged to construct a calculation model of a single plasma material layer, and initializes the stealth parameters of the plasma material according to the transmission and reflection characteristics of the plasma material;
the iteration module is used for optimizing stealth parameters of the single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm;
the configuration module is set to jump out of the genetic algorithm optimization circulation process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth.
In the embodiment of the invention, the configuration module optimizes the iteration step number to reach the set maximum step value or cost function F cost And when the value is smaller than the set threshold value, jumping out of the genetic algorithm to optimize the circulation process.
Example III
The present embodiments also provide a computing device, referring to fig. 4, comprising a memory 1120, a processor 1110 and a computer program stored in said memory 1120 and executable by said processor 1110, the computer program being stored in a space 1130 for program code in the memory 1120, which computer program, when being executed by the processor 1110, is adapted to carry out any of the method steps 1131 according to the present invention.
Embodiments of the present application also provide a computer-readable storage medium. Referring to fig. 5, the computer-readable storage medium includes a storage unit for program code, the storage unit being provided with a program 1131' for performing the method steps according to the present invention, the program being executed by a processor.
Example IV
The embodiment of the invention describes a plasma frequency point stealth parameter design process based on a genetic algorithm:
1. and (5) establishing a calculation model and initializing a parameter vector.
The schematic structure of the plasma computing model is shown in fig. 2, and the plasma is positioned in an interlayer of the target shell and the outer wave-transparent shell and is usually positioned at the key stealth part of the target so as to achieve the target stealth effect. Assuming that the outer wave-transmitting shell has high wave-transmitting rate, the influence of the outer wave-transmitting shell on electromagnetic wave propagation can be ignored in simulation calculation, and d is the thickness of the plasma.
The Maxwell's equation and constitutive equation set for a non-magnetized plasma medium can be written as follows:
wherein, V is a gradient operator,is the electric field component, +.>Is a magnetic field component>Is the polarized current density omega p Representing the plasma frequency, v is the electron impact frequency，ε 0 Is the dielectric constant in vacuum, mu 0 For permeability in vacuum, the plasma material stealth includes ω p V, and d, the construction parameter vector p= [ ω ] p ,ν,d]The initial parameter values are randomly selected based on the range of each parameter.
2. Cost function calculation and population updating.
The parameter optimization problem of achieving maximum RCS reduction at frequency point f in order to achieve the goal. The cost function of the optimization algorithm may be set to:
F cost ＝C+RCS(f)
the optimization solution is to solve the problem of minimizing the cost function value, and the minimum cost function individual corresponds to the optimal individual of the population. If for the one-dimensional analysis case the RCS value at the f-frequency point can be replaced with the reflectivity RF value, the cost function becomes:
F cost ＝C+RF(f)
where C is a constant used to make the cost function value positive, c=100 is chosen here, considering that the value of RF is not less than-100 dB. Different parameter vectors p= [ omega ] are paired by a time domain finite difference method p ,ν,d]The corresponding RCS or RF is obtained by calculation, and then the RCS or RF is carried into a cost function formula to realize the calculation of the cost function.
After the cost function value of each individual in the population is obtained, the population update can be realized through the operations of selection, variation, crossover and the like of a genetic algorithm. The genetic algorithm specifically comprises the following steps:
(1) And selecting operation. Since the inversion problem is to be solved as the minimum problem of the cost function Fcost, the following modifications are needed when the individual selection probabilities are required when the selection operation is performed by adopting the roulette method:
inverting the individual cost function value to obtain an individual fitness value:
fitvalue(i)＝1/F cost (i)
calculating the total value of all individual fitness values:
calculating to obtain the selection probability value of the individual:
selection_value(i)＝fitvalue(i)/fitvalue_total
wherein i=1, 2,3. Representing individuals in the population. The three steps can ensure that smaller Fcost has larger probability of being selected.
(2) Mutation operation: the variant forms of real number encoding herein are:
pop m+1 (i,:)＝pop m (i,:)+λ m ·rand·pop m (i,:)
wherein pop is m (i) a parameter vector representing the ith population of individuals in the mth optimization iteration, lambda m As a coefficient of variation, rand is a random number between (-1, 1).
(3) Crossover operation: the interleaving operation herein for two real number encoded individual (i, j) parameter vectors randomly selected is:
pop m+1 (i,:)＝pop m (i,:)+λ c ·(pop m (i,:)-pop m (j,:))
pop m+1 (j,:)＝pop m (j,:)+λ c ·(pop m (j,:)-pop m (i,:))
wherein lambda is c Is a crossover coefficient.
3. And selecting the value of the stealth parameter of the plasma frequency point.
And (3) obtaining a final population optimal value by the optimization cycle of the judgment condition jump-out genetic algorithm, namely a corresponding parameter value for hiding the plasma frequency point.
The embodiment of the invention optimizes the plasma parameter omega when electromagnetic waves at the outer boundary of the plasma structure are vertically incident (theta=0°) p The spatial distribution is the lowest reflectivity that can be achieved at the frequency point f=6 GHz in both the case of a uniform distribution and a linear distribution (non-uniform). Fig. 6 and fig. 7 respectively show a reflectivity map and a change map of a cost function value with the number of iteration steps, which correspond to the result of the optimization parameter when the stealth performance at the outer boundary of the target structure is optimal, at the frequency point f=6ghz. As can be seen from fig. 6 and 7, non-The plasma parameters obtained by uniform and uniform plasma optimization can realize the RF less than or equal to-50 dB at the frequency point of f=6 GHz, and the plasma has good stealth performance.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
Claims (8)
1. The configuration method of the stealth parameters of the plasma material is characterized by comprising the following steps:
constructing a calculation model of a single-layer plasma material layer, and initializing a plasma material stealth parameter according to the transmission reflection characteristic of the plasma material;
optimizing stealth parameters of a single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm;
jumping out of the genetic algorithm optimization cycle process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth;
initializing plasma material stealth parameters according to the transmission reflection characteristics of the plasma material includes:
the Maxwell's equation and constitutive equation set for a non-magnetized plasma medium are expressed as follows:
wherein,is a gradient operator, < >>Is the electric field component, +.>Is a magnetic field component>Is the polarized current density omega p Representing plasmaThe bulk frequency, v is the electron collision frequency, ε 0 Is the dielectric constant in vacuum, mu 0 For permeability in vacuum, the plasma material stealth parameter includes ω p V and plasma layer thickness d, construction parameter vector +.>Randomly selecting an initial parameter value according to the range of each parameter; the optimization of stealth parameters of a single-layer plasma material layer requiring stealth at different frequency points by adopting a genetic algorithm comprises the following steps:
setting the number of individuals composing the genetic algorithm population as Np and the individuals as parameter omega p The parameter vector p formed when v and d take different values i ＝[ω p ,ν,d] i I=1, 2,3 … … Np, the population is a population p consisting of all individuals (1,2,3……Np) ；
The cost function of the genetic algorithm is set as:
F cost ＝C+RCS(f)
wherein C is a constant, and RCS (f) is the RCS value at frequency point f;
when analyzing a single plasma material layer, the RCS value is replaced by the reflectivity RF value of the single plasma material layer at the f frequency point, and then the cost function becomes:
F cost ＝C+RF(f)
the parameter vector is p= [ omega ] by a time domain finite difference method p ,ν,d]Calculating a single plasma material layer of the antenna to obtain RCS values or RF values corresponding to different frequency points; said RF value is not less than-100 dB, and said C is used to make the cost function value positive;
carrying the cost function into a cost function formula to realize the calculation of the cost function; obtaining cost function values of single-layer plasma material layers with different frequency points;
realizing population updating through updating operation of a genetic algorithm;
the solving process of the time domain finite difference method comprises the following steps:
performing difference on the first equation in the Maxwell's equation and constitutive relation equation set of the non-magnetized plasma mediumSeparating the dispersion to obtain magnetic field components H in x, y and z directions x ,H y ,H z Iterative expression:
wherein the superscript n represents the iteration time step, the subscripts i, j, k represent the coordinate positions of the electric field and the magnetic field components in the x, y and z directions in space respectively, and Deltax, deltay and Deltaz are the space step sizes in the x, y and z directions in space respectively, deltat is the time step size and E x ,E y ,E z Is the electric field component in the x, y and z directions in space;
carrying out differential dispersion on a Maxwell's equation of a non-magnetized plasma medium and a second equation in a constitutive relation equation set to respectively obtain electric field components E in x, y and z directions x ,E y ,E z Iterative expression:
wherein J x ,J y ,J z Is the current density component in the x, y and z directions in space;
differential discretization is carried out on a Maxwell's equation of a non-magnetized plasma medium and a third equation in a constitutive relation equation set to respectively obtain current density components J in x, y and z directions x ,J y ,J z Iterative expression:
obtaining corresponding electric field component values at the observation points through time step iteration updating according to the obtained electric field, magnetic field and current density iteration formulas; obtaining RCS values of different frequency points through near-far field extrapolation of the electric field component and Fourier transform (FFT); and calculating the ratio of the incident electric field to the reflected electric field at the observation point, and performing FFT (fast Fourier transform) to obtain RF (radio frequency) values of different frequency points.
2. The configuration method according to claim 1, wherein the update operation comprises one or more of the following: selection operation, mutation operation and crossover operation.
3. The configuration method according to claim 2, wherein the population update by the selection operation of the genetic algorithm comprises:
inverting the cost function values of the single-layer plasma material layers with different frequency points to obtain a fitness value corresponding to the ith individual:
fitvalue(i)＝1/F cost (i)
calculating to obtain the total value of the fitness values corresponding to all individuals:
wherein Np is the number of individuals;
calculating to obtain a selection probability value of the ith individual:
selection_value(i)＝fitvalue(i)/fitvalue_total
where i=1, 2,3.
4. The configuration method according to claim 2, wherein the population update by the mutation operation of the genetic algorithm includes:
the variant forms of real number coding are:
pop m+1 (i,:)＝pop m (i,:)+λ m ·rand·pop m (i,:)
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration m As a coefficient of variation, rand is a random number between (-1, 1).
5. The configuration method according to claim 2, wherein the population update by the crossover operation of the genetic algorithm comprises:
the interleaving operation for the randomly selected i-th and j-th individual (i, j) parameter vectors is:
pop m+1 (i,:)＝pop m (i,:)+λ c ·(pop m (i,:)-pop m (j,:))
pop m+1 (j,:)＝pop m (j,:)+λ c ·(pop m (j,:)-pop m (i,:))
wherein pop is m (i) parameter vector, lambda representing the i-th individual in the mth optimization iteration c Is a crossover coefficient.
6. The configuration method according to claim 1, wherein the preset determination condition is: optimizing the iteration step number to reach a set maximum step value or cost function F cost The value is less than the set threshold.
7. A device for configuring stealth parameters of a plasma material, comprising:
the initialization module is arranged to construct a calculation model of a single plasma material layer, and initializes the stealth parameters of the plasma material according to the transmission and reflection characteristics of the plasma material;
the iteration module is used for optimizing stealth parameters of the single-layer plasma material layer which is required to achieve stealth at different frequency points by adopting a genetic algorithm;
the configuration module is used for jumping out of the genetic algorithm optimization cycle process according to preset judging conditions to obtain corresponding parameter values of plasma frequency point stealth;
initializing the stealth parameters of the plasma material according to the transmission and reflection characteristics of the plasma material comprises:
the Maxwell's equation and constitutive equation set for a non-magnetized plasma medium are expressed as follows:
wherein,is a gradient operator, < >>Is the electric field component, +.>Is a magnetic field component>Is the polarized current density omega p Representing the plasma frequency, v is the electron impact frequency, ε 0 Is the dielectric constant in vacuum, mu 0 For permeability in vacuum, the plasma material stealth parameter includes ω p V and plasma layer thickness d, construction parameter vector p= [ ω ] p ,ν,d]Randomly selecting an initial parameter value according to the range of each parameter;
the genetic algorithm is used for optimizing stealth parameters of a single-layer plasma material layer which is required to achieve stealth purposes at different frequency points, and the method comprises the following steps:
setting the number of individuals composing the genetic algorithm population as Np and the individuals as parameter omega p The parameter vector p formed when v and d take different values i ＝[ω p ,ν,d] i I=1, 2,3 … … Np, the population is a population p consisting of all individuals (1,2,3……Np) ；
The cost function of the genetic algorithm is set as:
F cost ＝C+RCS(f)
wherein C is a constant, and RCS (f) is the RCS value at frequency point f;
when analyzing a single plasma material layer, the RCS value is replaced by the reflectivity RF value of the single plasma material layer at the f frequency point, and then the cost function becomes:
F cost ＝C+RF(f)
the parameter vector is p= [ omega ] by a time domain finite difference method p ,ν,d]Calculating a single plasma material layer of the antenna to obtain RCS values or RF values corresponding to different frequency points; said RF value is not less than-100 dB, and said C is used to make the cost function value positive;
carrying the cost function into a cost function formula to realize the calculation of the cost function; obtaining cost function values of single-layer plasma material layers with different frequency points;
realizing population updating through updating operation of a genetic algorithm;
the solving process of the time domain finite difference method comprises the following steps:
carrying out differential discretization on a Maxwell's equation of a non-magnetized plasma medium and a first equation in a constitutive relation equation set to respectively obtain magnetic field components H in x, y and z directions x ,H y ,H z Iterative expression:
wherein the superscript n represents the iteration time step, the subscripts i, j, k represent the coordinate positions of the electric field and the magnetic field components in the x, y and z directions in space respectively, and Deltax, deltay and Deltaz are the space step sizes in the x, y and z directions in space respectively, deltat is the time step size and E x ,E y ,E z Is the electric field component in the x, y and z directions in space;
carrying out differential dispersion on a Maxwell's equation of a non-magnetized plasma medium and a second equation in a constitutive relation equation set to respectively obtain electric field components E in x, y and z directions x ,E y ,E z Iterative expression:
wherein J x ,J y ,J z Is the current density component in the x, y and z directions in space;
differential between Maxwell's equation and the third equation in the constitutive equation set for non-magnetized plasma mediaDiscrete to obtain current density components J in x, y and z directions x ,J y ,J z Iterative expression:
obtaining corresponding electric field component values at the observation points through time step iteration updating according to the obtained electric field, magnetic field and current density iteration formulas; the RCS values of different frequency points are obtained through the near-far field extrapolation of the electric field components and the Fourier transform (FFT); and calculating the ratio of the incident electric field to the reflected electric field at the observation point, and performing FFT (fast Fourier transform) to obtain RF (radio frequency) values of different frequency points.
8. The configuration device according to claim 7, wherein the configuration module is configured to optimize the number of iterative steps to a set maximum step value or cost function F cost And when the value is smaller than the set threshold value, jumping out of the genetic algorithm to optimize the circulation process.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010761646.7A CN111881609B (en) | 2020-07-31 | 2020-07-31 | Configuration method and device for stealth parameters of plasma material |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010761646.7A CN111881609B (en) | 2020-07-31 | 2020-07-31 | Configuration method and device for stealth parameters of plasma material |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111881609A CN111881609A (en) | 2020-11-03 |
| CN111881609B true CN111881609B (en) | 2024-02-02 |
Family
ID=73204997
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010761646.7A Active CN111881609B (en) | 2020-07-31 | 2020-07-31 | Configuration method and device for stealth parameters of plasma material |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111881609B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112711874B (en) * | 2020-12-17 | 2023-05-12 | 北京环境特性研究所 | Method and device for selecting radar wave-absorbing parameters of wide frequency band of plasma coating target |
| CN112926248B (en) * | 2021-03-11 | 2023-05-09 | 北京环境特性研究所 | Plasma photonic crystal structure design method |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105549031A (en) * | 2015-12-31 | 2016-05-04 | 武汉大学 | Ionosphere propagation time delay time domain value calculating method of satellite signals |
| CN106410425A (en) * | 2016-12-06 | 2017-02-15 | 复旦大学 | Ultra-wideband full polarization full-angle rotating parabolic gradient electromagnetic stealth super-surface and design method thereof |
| CN107644140A (en) * | 2017-10-11 | 2018-01-30 | 上海无线电设备研究所 | A kind of plasma material design method |
| CN107958105A (en) * | 2017-11-09 | 2018-04-24 | 上海无线电设备研究所 | A kind of method reflected using plasma-coated reduction electromagnetic wave in metal surface |
| CN108170950A (en) * | 2017-12-27 | 2018-06-15 | 电子科技大学 | Multilayer Frequency-Selective Surfaces absorbing material modeling optimization method based on neural network |
| CN109740238A (en) * | 2018-12-28 | 2019-05-10 | 哈尔滨工业大学 | A kind of structural optimization method and preparation method thereof of the wideband Meta Materials wave-absorber based on topological optimization |
| CN110311223A (en) * | 2019-07-25 | 2019-10-08 | 哈尔滨工业大学 | Signal enhancing type Plasma Stealth antenna windows |
| CN111430903A (en) * | 2020-04-01 | 2020-07-17 | 中国人民解放军空军工程大学 | Radiation scattering integrated low-RCS antenna housing and design method thereof |
-
2020
- 2020-07-31 CN CN202010761646.7A patent/CN111881609B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105549031A (en) * | 2015-12-31 | 2016-05-04 | 武汉大学 | Ionosphere propagation time delay time domain value calculating method of satellite signals |
| CN106410425A (en) * | 2016-12-06 | 2017-02-15 | 复旦大学 | Ultra-wideband full polarization full-angle rotating parabolic gradient electromagnetic stealth super-surface and design method thereof |
| CN107644140A (en) * | 2017-10-11 | 2018-01-30 | 上海无线电设备研究所 | A kind of plasma material design method |
| CN107958105A (en) * | 2017-11-09 | 2018-04-24 | 上海无线电设备研究所 | A kind of method reflected using plasma-coated reduction electromagnetic wave in metal surface |
| CN108170950A (en) * | 2017-12-27 | 2018-06-15 | 电子科技大学 | Multilayer Frequency-Selective Surfaces absorbing material modeling optimization method based on neural network |
| CN109740238A (en) * | 2018-12-28 | 2019-05-10 | 哈尔滨工业大学 | A kind of structural optimization method and preparation method thereof of the wideband Meta Materials wave-absorber based on topological optimization |
| CN110311223A (en) * | 2019-07-25 | 2019-10-08 | 哈尔滨工业大学 | Signal enhancing type Plasma Stealth antenna windows |
| CN111430903A (en) * | 2020-04-01 | 2020-07-17 | 中国人民解放军空军工程大学 | Radiation scattering integrated low-RCS antenna housing and design method thereof |
Non-Patent Citations (7)
| Title |
|---|
| An E-J Collocated 3-D FDTD Model of Electromagnetic Wave Propagation in Magnetized Cold Plasma;Yaxin Yu et al.;《IEEE Transactions on Antennas and Propagation》;第58卷(第2期);第470-476页 * |
| Study and optimization on the scattering characteristic of two-dimensional metal airfoil covered with plasma using ADE-FDTD;Fei Du et al.;《Optik》;第147卷;正文第225-230页 * |
| Use of Collisional Plasma as an Optimum Lossy Dielectric for Wave Absorption in Planar Layers, Analysis, and Application;Alireza Ghayekhloo et al.;《IEEE Transactions on Plasma Science》;第42卷(第8期);正文第1999-2003页 * |
| 基于FDTD的磁化时变等离子体电磁特性研究;席阳红;《中国优秀硕士学位论文全文数据库 基础科学辑》(第10期);第A005-81页 * |
| 基于GA和DE的非均匀等离子体介质参数重构算法研究;冯雪健等;《中国传媒大学学报(自然科学版)》;第26卷(第3期);正文第34-37页 * |
| 等离子体对电磁波吸收及反射的研究及应用;宋黎浩;《中国优秀硕士学位论文全文数据库 基础科学辑》(第3期);第A005-208页 * |
| 隐身应用中等离子体参数的Nelder-Mead优化反演研究;程立等;《核聚变与等离子体物理》;第32卷(第4期);第362-365页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111881609A (en) | 2020-11-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111881609B (en) | Configuration method and device for stealth parameters of plasma material | |
| Dong et al. | Fast multi-objective optimization of multi-parameter antenna structures based on improved MOEA/D with surrogate-assisted model | |
| Fallahi et al. | Efficient procedures for the optimization of frequency selective surfaces | |
| Bose et al. | Design of an aperture-coupled microstrip antenna using a hybrid neural network | |
| Ranjan et al. | BWDO algorithm and its application in antenna array and pixelated metasurface synthesis | |
| Asi et al. | Design of multilayer microwave broadband absorbers using central force optimization | |
| de Sena et al. | Harmonic suppression using optimised hexagonal defected ground structure by genetic algorithm | |
| CN115329680A (en) | Optimization method and system for lens in Vivaldi antenna and related equipment | |
| Nouri et al. | An optimized small compact rectangular antenna with meta-material based on fast multi-objective optimization for 5G mobile communication | |
| CN112926248B (en) | Plasma photonic crystal structure design method | |
| Han et al. | Resource management of opportunistic digital array radar antenna aperture for pattern synthesis | |
| Zaki et al. | Wideband RCS reduction using three different implementations of AMC structures | |
| CN114491992B (en) | Efficient electromagnetic scattering method based on equivalent dipole moment and physical optical method | |
| KR102532758B1 (en) | Design method and storage medium storing computer programs for frequency selective surface filters | |
| Seong et al. | Study on pattern synthesis of conformal array using enhanced adaptive genetic algorithm | |
| Rasool et al. | Radiowave propagation prediction in the presence of multiple knife edges using 3D parabolic equation method | |
| Naous et al. | Machine learning-aided design of dielectric-filled slotted waveguide antennas with specified sidelobe levels | |
| CN115146544A (en) | Array antenna design method adopting knowledge and data hybrid driving | |
| Jiang et al. | Spatial transformation-enabled electromagnetic devices: from radio frequencies to optical wavelengths | |
| Yazdani‐Shavakand et al. | A fast multi‐structural tracking method for characteristic modes with the ability to identify and amend errors | |
| Abdolee et al. | Decimal genetic algorithms for null steering and sidelobe cancellation in switch beam smart antenna system | |
| CN112711874B (en) | Method and device for selecting radar wave-absorbing parameters of wide frequency band of plasma coating target | |
| Fu et al. | A novel mapping approach to design FSS‐based microwave absorbers for relaxed manufacturing tolerances | |
| CN116599811B (en) | Multi-carrier directional modulation method of time modulation antenna array | |
| Cheng et al. | Thinning and weighting of planar/conformal arrays considering mutual coupling effects |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |