CN205039261U - Tax shape device of array antenna and array antenna directional diagram - Google Patents

Abstract

The utility model discloses a tax shape device of array antenna and array antenna directional diagram overcomes present array antenna and composes the low scheduling problem of degree of fitting when appearing. The device includes: the input acquires the directional diagram of each array element of array antenna under the coupling condition, the population generater is according to the directional diagram random generation initial population of each array element under the coupling condition, the selector is for every the individual account sufficiency value among the initial population to select gambling rim plate tactics or elite selection policy according to the sufficiency value, the regeneration optimizer, according to gambling rim plate tactics or the elite selection policy that the selector was selected, the cooperation sufficiency selects regeneration individual to it generates new individuality to optimize the individuality of regenerating, the output accords with the optimum directional diagram of predetermineeing output array antenna when finishing the rule. The utility model discloses a beam coverage of X wave band antenna array is wideer, and the practicality is better.

Description

The size enlargement apparatus of array antenna and array aerial direction figure

Technical field

The utility model relates to communication antenna technical field, particularly relates to the size enlargement apparatus of a kind of array antenna and array aerial direction figure.

Background technology

Along with microwave communication in modern age, the fast development of satellite communication and space technology, the requirement of current social to communication system is more and more higher, especially user for the beamwidth of the directional diagram of antenna and accuracy more and more higher.These require that for Antenna Design and research and development are very large tests.

The directional diagram of antenna can reflect the radiation characteristic of antenna.Generally, antenna pattern can represent the power of antennas irradiate electromagnetic ripple or the field intensity distribution pattern in space all directions.When array aerial direction figure synthesizes, first provide the target direction figure that design needs, recycle amplitude and phase place that suitable algorithm calculates the optimal solution of each antenna element figuration target direction figure.Finally, according to these group data as excitation, the target shape needed for array aerial direction figure figuration can being become.

An outstanding algorithm becomes extremely important to designing a efficient, that directional diagram accuracy is high array antenna.Classical genetic algorithm is through being usually used in the compounding design of antenna pattern.And the fitness of genetic algorithm has reacted the fitting degree of compound direction figure and target direction figure, fitness is higher, the amplitude that algorithm calculates and phase value more accurate, the degree of fitting of directional diagram is higher.Otherwise the fitness of genetic algorithm is lower, then the accuracy applying amplitude that this genetic algorithm calculates and phase value is also lower, shows that the degree of fitting of directional diagram is lower.

The main flow that classical genetic algorithm solves Array Antenna Synthesis produces initial population first randomly.Then, the above random initial population produced is substituted into the expression formula preset, calculates array direction function.Itself and corresponding target direction figure are done difference, and according to the importance of different directions to the other weighting of the difference of gained, get difference on different directions in each individuality absolute value and, then get the fitness value that inverse obtains each individuality.According to single selection strategy (such as roulette wheel dish method or elitist selection), fitness is coordinated to select regeneration individual.Regeneration individuality is intersected, the gene of population genetic previous generation of future generation can be made.According to certain crossover probability and crossover algorithm, generate new individuality.In order to avoid inbreeding, be absorbed in local optimum, according to certain mutation probability and mutation algorithm, the individuality generated in intersection makes a variation, and again generates new individuality.Finally, judge whether to reach stop condition, such as whether reach maximum genetic algebra or whether fitness value reaches preset requirement.If meet stop condition, export optimum value, otherwise, return and recalculate individual fitness value, until reach stop condition.

In the genetic algorithm of classics, when roulette wheel dish method selection opertor acts on colony, the diversity of colony's gene can be protected; but can not ensure that the performance of offspring is always better than former generation; the evolution of colony there will be repeatedly, and even temporary transient setback delays convergence of algorithm speed.Elitist selection can ensure that the performance of offspring is not worse than former generation, energy convergence speedup speed, but may occur premature problem.So the genetic algorithm of classics is when solving array antenna figuration problem, general fitness is below 0.07, and the fitting degree of target direction figure and compound direction figure and secondary lobe size can not allow designer's satisfaction completely.

And in current Antenna Design, the coverage of common cosecant square expansion wave beam is generally below 55 °, and the coverage of wave beam is comparatively limited, has been difficult to meet more and more higher communication requirement.

Utility model content

The problem that when technical problem to be solved in the utility model is to overcome array antenna figuration in prior art, degree of fitting is low and antenna beam coverage is limited.

The utility model provide firstly a kind of size enlargement apparatus of array aerial direction figure, comprising: input, obtains the directional diagram of each array element of array antenna under coupling condition; Population maker, according to the directional diagram stochastic generation initial population of each array element under described coupling condition; Selector, for each individuality in described initial population calculates fitness value, and selects roulette wheel dish strategy or elitist selection strategy according to described fitness value; Regeneration optimizer, the roulette wheel dish strategy selected by described selector or elitist selection strategy, coordinate fitness to select regeneration individual, and be optimized described regeneration individuality, generate new individuality; Output, exports the optimal direction figure of described array antenna when meeting default end rules.

Wherein, this device also comprises: feedback controller, when described individuality does not newly meet described default end rules, recalculates instruction to described selector feedback; Described selector according to described in recalculate instruction and recalculate described fitness value.

Wherein, described selector comprises: computing unit, calculates described fitness value; Selected cell, when described fitness value is less than or equal to fitness threshold value, selects roulette wheel dish strategy, otherwise selects elitist selection strategy.

The utility model additionally provides a kind of array antenna, comprise: be spaced the multiple array-element antenna of distance for half-wavelength, each array-element antenna described comprises rectangular element antenna and connected feeder line, and described feeder line is connected with the narrow limit of rectangular element antenna by feedback point.

Wherein, the quantity of described array-element antenna is 10,14,16 or 20.

Wherein, described feeder line is the octagon with two groups of parallel edges.

Wherein, the selected cosecant of each array-element antenna of a described array antenna square expansion wave beam is target direction figure.

Compared with prior art, the utility model has benefited from the accurate figuration of modified model self-adapted genetic algorithm, and antenna pattern wave cover width can reach 65 °.The beam coverage of X-wave band autenna battle array of the present utility model is wider, and practicality is better, has very superior application prospect in aircraft navigation detection.

Other features and advantages of the utility model will be set forth in the following description, and, partly become apparent from specification, or understand by implementing the technical solution of the utility model.The purpose of this utility model and other advantages realize by structure specifically noted in specification, claims and accompanying drawing and/or flow process and obtain.

Accompanying drawing explanation

Accompanying drawing is used to provide the further understanding to the technical solution of the utility model or prior art, and forms a part for specification.Wherein, accompanying drawing and the embodiment of the present utility model of expressing the utility model embodiment are used from explanation the technical solution of the utility model, but do not form the restriction to technical solutions of the utility model.

Fig. 1 is the schematic flow sheet of the shaping method of the array aerial direction figure of the utility model embodiment.

Fig. 2 is the array antenna schematic diagram of the utility model embodiment.

Fig. 3 is the structural representation of array-element antenna in the array antenna of the utility model embodiment.

Fig. 4 is the band diagram of array-element antenna in the array antenna of the utility model embodiment.

Fig. 5 is the directional diagram of array element under coupling condition in the utility model embodiment.

Fig. 6 is the structural representation of the array antenna size enlargement apparatus of the utility model embodiment.

Fig. 7 is the array antenna size enlargement apparatus of the utility model embodiment fitness value figure when adopting modified model self-adapted genetic algorithm when high fitness threshold value.

Fig. 8 is the array antenna size enlargement apparatus of the utility model embodiment fitness value figure when adopting modified model self-adapted genetic algorithm when low fitness threshold value.

Fig. 9 is the array antenna size enlargement apparatus of the utility model embodiment fitness value figure when not adopting elitist selection strategy during using modified self-adapted genetic algorithm.

Figure 10 is fitness value figure when adopting classical genetic algorithm.

Embodiment

Describe execution mode of the present utility model in detail below with reference to drawings and Examples, to the utility model, how application technology means solve technical problem whereby, and the implementation procedure reaching relevant art effect can fully understand and implement according to this.Each feature in the utility model embodiment and embodiment, can be combined with each other under prerequisite of not conflicting mutually, the technical scheme formed is all within protection range of the present utility model.

In addition, the step that the method for the utility model embodiment shown by accompanying drawing comprises, can perform in the computer system of such as one group of computer executable instructions.Further, although the method for the utility model embodiment has embodied the certain logical order of the technical solution of the utility model when performing in shown flow chart, typically, this logical order has been only limitted to by the embodiment shown by this flow chart.In other embodiments of the present utility model, the logical order of the technical solution of the utility model also can be different from mode shown in the drawings to realize.

As shown in Figure 1, the shaping method of array aerial direction figure of the present utility model, mainly comprises the steps.

Step S110, determines the linear array antenna be made up of N number of array element, obtains the directional diagram of each array element of array antenna under coupling condition.

Step S120, according to the directional diagram of each array element under coupling condition, produces initial population randomly.Wherein, initial population adopts binary system to represent.

Step S130, for each individuality in initial population calculates fitness value, and selects roulette wheel dish strategy or elitist selection strategy according to fitness value.

Particularly, that the initial population produced at random is substituted into expression formula computing array directivity function, and respective direction figure and target direction figure is asked poor, according to the importance of different directions to the other weighting of difference, get the absolute value of difference on different directions in each individuality and sue for peace, then getting inverse and obtain fitness value.

The calculation expression of fitness fit is as follows:

$fit=\frac{1}{weight\left({\mathrm{\θ}}_i\right)\×diff\left({\mathrm{\θ}}_i\right)},-180\≤{\mathrm{\θ}}_i\≤180$

Wherein, the weight of weight corresponding to each point, diff is the absolute error of each point and target direction figure in composite diagram.

$weight\left({\mathrm{\θ}}_i\right)=\left\{\begin{array}{cc}{a}_1,& 1\≤i\≤114\\ a_2,& 115\≤i\≤168\\ a_3,& 169\≤i\≤179\\ a_4,& 180\≤i\≤240\\ a_5,& 241\≤i\≤360\end{array}\right.$

Wherein, θ is the angle value in antenna pattern, and scope is at 0 °-360 °, and i has 5 kinds of values here, by 360 ° points in order to 5 sections, adds five sections of corresponding weights a respectively, and the object of weighted value is in order to figuration more accurately.

Step S140, according to selected roulette wheel dish strategy or elitist selection strategy, coordinates fitness to select regeneration individual, and is optimized described regeneration individuality, generate new individuality.

Judge fitness value with the selection strategy that roulette wheel dish is selected and elitist selection combines, when maximum adaptation angle value is less than or equal to fitness threshold value, adopts roulette wheel dish method to select regeneration individual, do not introduce elitism strategy, protect the diversity of population gene.And when maximum adaptation angle value is higher than fitness threshold value, introduces elitism strategy and carry out convergence speedup speed, select regeneration individual.When regeneration individuality is optimized, first carry out cross processing according to the crossover probability preset and crossover algorithm, and then according to the mutation probability preset and mutation algorithm, variation process is carried out to the individuality that intersection obtains, generates new individuality.The good gene of population of future generation hereditary previous generation well can be enable like this.

In roulette wheel dish selection course, at evolution mid-early stage and later stage of evolution, select different crossover probabilities and mutation probability respectively, while contributing to convergence speedup like this, avoid being absorbed in local optimum as far as possible.

Particularly, in roulette wheel dish selection course, judge that fitness value compares with the evolution mid-early stage threshold value preset further.This evolution threshold value in period can be used for distinguishing the current early stage still middle and later periods being in evolution.If fitness value is less than default evolution threshold value in period, then think when evolution is also in early days; If fitness value is greater than default evolution threshold value in period, then think when evolution is also in the middle and later periods.

Early stage for evolution, adopt following expression to carry out crossover and mutation respectively:

pc1＝pc1+(pc0-0.5)/NG

pm1＝pm1-(0.4-pm0)/NG

Wherein, pc0 is initial crossover probability, and pm0 is initial mutation probability, and NG is maximum genetic algebra, and pc1 is the crossover probability of linear change, and pm1 is the mutation probability of linear change.

In evolution mid-early stage, pc1 is greater than pm1 and contributes to convergence speedup.

For evolving mid-term, following expression is adopted to carry out crossover and mutation respectively:

pc2＝1/(1+exp(-10/fiy))-0.1

pm2＝0.2/(5*(1+exp(1/fiy)))

Wherein, pc2 and the crossover probability for adaptive change, pm2 is the mutation probability of adaptive change.

In evolution mid-term, pc2 is less than pm2 and helps avoid and be absorbed in local optimum.

Step S150, when meeting default end rules, the optimal direction figure of output array antenna.When new individuality does not meet default end rules, recalculate fitness value, return step S130 and proceed.

As shown in Figure 2, give the array antenna schematic diagram be made up of 16 array-element antenna in the utility model embodiment, each array-element antenna interval d is each other the length of 9GHz half-wavelength, and such as half-wavelength is 16.667mm.Further, as shown in Figure 3, each array-element antenna comprises again rectangular element antenna and connected feeder line, and described feeder line is connected with the narrow limit of rectangular element antenna by feedback point, and described feeding line portion is the octagon with two groups of parallel edges.Dielectric-slab adopts has certain thickness Rogers 5880 material.During array shaped aerial figuration, if the ability of the more figurations of number of arrays is stronger, optionally, described array antenna can also adopt the array-element antenna number of other number, such as 10, or 14, or 20.

For the array antenna be made up of 16 array-element antenna, optimize the S of each array-element antenna good respectively ₁₁parameter, obtains good frequency bandwidth, and frequency band range is 8.5GHz ~ 9.8GHz, and centre frequency is 9.05GHz, gives the band diagram of array-element antenna as shown in Figure 4.Further, determine the directional diagram that described 16 array-element antenna are respective under coupling condition, give the directional diagram of an example array element under coupling condition as shown in Figure 5.Wherein, S ₁₁for input reflection coefficient, namely input return loss.Because antenna has related to the frequency range of high frequency, high-frequency band can relate to the problem of coupling, mates the reflection that bad words will produce input energy, thus affects the problems such as the input power deficiency of whole equipment, input reflection coefficient S ₁₁what react is exactly problems.

As shown in Figure 6, give a kind of size enlargement apparatus of array aerial direction figure, comprise input 610, population maker 620, selector 630, regeneration optimizer 640 and output 650.

Input 610, obtains the directional diagram under the coupling condition of each array element of array antenna.

Population maker 620, is connected with input 610, according to the directional diagram of each array element under this coupling condition, generates initial population randomly.Wherein, described initial population can adopt binary system to represent.

Selector 630, is connected with population maker 620, is that each individuality in initial population calculates fitness value, and the comparative result preset according to fitness value and fitness, selection roulette wheel dish strategy or elitist selection strategy.

Regeneration optimizer 640, is connected with selector 630, the roulette wheel dish strategy selected by selector 630 or elitist selection strategy, coordinates fitness to select regeneration individual, and carries out crossover and mutation optimization to regeneration individuality, generate new individuality.

Judge fitness value with the selection strategy that roulette wheel dish is selected and elitist selection combines, when maximum adaptation angle value is less than or equal to fitness threshold value, adopts roulette wheel dish method to select regeneration individual, do not introduce elitism strategy, protect the diversity of population gene.And when maximum adaptation angle value is higher than fitness threshold value, introduces elitism strategy and carry out convergence speedup speed, select regeneration individual.When regeneration individuality is optimized, first carry out cross processing according to the crossover probability preset and crossover algorithm, and then according to the mutation probability preset and mutation algorithm, variation process is carried out to the individuality that intersection obtains, generates new individuality.The good gene of population of future generation hereditary previous generation well can be enable like this.

In roulette wheel dish selection course, at evolution mid-early stage and later stage of evolution, select different crossover probabilities and mutation probability respectively, while contributing to convergence speedup like this, avoid being absorbed in local optimum as far as possible.

Particularly, in roulette wheel dish selection course, judge that fitness value compares with the evolution mid-early stage threshold value preset further.This evolution threshold value in period can be used for distinguishing the current early stage still middle and later periods being in evolution.If fitness value is less than default evolution threshold value in period, then think when evolution is also in early days; If fitness value is greater than default evolution mid-early stage threshold value, then think when evolution is also in the middle and later periods.

Early stage for evolution, adopt following expression to carry out crossover and mutation respectively:

pc1＝pc1+(pc0-0.5)/NG

pm1＝pm1-(0.4-pm0)/NG

Wherein, pc1 is the crossover probability of linear change, and pm1 is the mutation probability of linear change.

In evolution mid-early stage, pc1 is greater than pm1 and contributes to convergence speedup.

For evolving mid-term, following expression is adopted to carry out crossover and mutation respectively:

pc2＝1/(1+exp(-10/fiy))-0.1

pm2＝0.2/(5*(1+exp(1/fiy)))

$fiy=\frac{E\left(fitness\right)+1}{\sqrt{D\left(fitness\right)}}$

Wherein, pc2 and the crossover probability for adaptive change, pm2 is the mutation probability of adaptive change.E (fitness) is fitness average, and D (fitness) is fitness variance.In evolution mid-term, pc2 is less than pm2 and helps avoid and be absorbed in local optimum.

Output 650, is connected with regeneration optimizer 640, exports the optimal direction figure of described array antenna when meeting default end rules.Wherein, this default end rules is such as that whether the genetic algebra of cross and variation reaches maximum genetic algebra or fitness value reaches requirement.

The size enlargement apparatus of the utility model embodiment, also comprises feedback controller.Controller, when new individuality does not meet described default end rules, recalculates instruction to selector 630 feedback.Selector 630, according to recalculating instruction, recalculates fitness value, and then carries out policy selection according to the fitness value recalculated.

Selector 630 comprises computing unit and selected cell.Computing unit calculates fitness value.Particularly, that the initial population produced at random by described population maker 620 substitutes into expression formula computing array directivity function, difference is done with target direction figure, and according to the importance of different directions to the other weighting of difference, get different directions difference in each individuality absolute value and, then get inverse and obtain fitness value.The fitness value that selected cell calculates fitness computing unit and fitness threshold value compare, if gained fitness value is less than or equal to fitness threshold value, selects to adopt roulette wheel dish strategy, if gained fitness value is greater than fitness threshold value, select elitist selection strategy.

Regeneration optimizer 640 comprises regeneration unit, cross unit and variation unit.Regeneration unit coordinates fitness to select regeneration individual according to roulette wheel dish strategy or elitist selection strategy.Cross unit is connected with regeneration unit, carries out cross processing, according to certain crossover probability and crossover algorithm, generate new individuality to regeneration individuality; The gene of population genetic previous generation of future generation can be made like this.Variation unit is connected with cross unit, carries out variation process, generate new individuality, to avoid inbreeding, be absorbed in local optimum the individuality after intersecting according to certain mutation probability and mutation algorithm.

Application example:

First, a selected cosecant square expansion wave beam is target direction figure, and the specific targets of target direction figure are :-3dB width range is 0 °-12 °,-10dB beamwidth is 65 °, wave cover is 65 °, and frequency band range is 8.5GHz ~ 9.8GHz, and centre frequency is 9.05GHz.

As shown in Figure 2, give the array antenna comprising 16 array-element antenna, the interval d of each array-element antenna is the half-wavelength 16.667mm of 9.05GHz, array-element antenna in array antenna comprises rectangular element antenna and connected feeder line, as shown in Figure 3, the length L=12.6mm of the rectangular element antenna of micro-band, width W=9.45mm, and the width w presenting some position can be determined ₁=7.2975mm.Further, feeder line is the octagon with two groups of parallel edges, and illustrated dimension is respectively total length L ₁=15.96mm, overall width w ₃=6.93mm, the feedback connected with rectangular element point width w ₂=0.42mm, away from the parallel opposite end width w of rectangular element ₄=1.302mm, width is w ₃the length L of=6.93mm part ₂=11.34mm, described w ₃and w ₄the trapezoidal height L formed ₃=2.31mm.Dielectric-slab adopts Rogers 5880, and thickness is 1.575mm.

Optimize the S of each array-element antenna good ₁₁parameter, obtains good frequency bandwidth, and frequency band range is 8.5GHz ~ 9.8GHz, and centre frequency is 9.05GHz, as shown in Figure 4, to give in array antenna an example of 16 array-element antenna directional diagram respective under coupling condition.The directional diagram of each array-element antenna obtained above is substituted into the size enlargement apparatus shown in the Fig. 6 applying modified model self-adapted genetic algorithm and the shaping method shown in Fig. 1 processes, calculate each ideal adaptation angle value, the calculation expression of fitness fit is as follows:

$fit=\frac{1}{weight\left({\mathrm{\θ}}_i\right)\×diff\left({\mathrm{\θ}}_i\right)},-180\≤{\mathrm{\θ}}_i\≤180$

Wherein, the weight of weight corresponding to each point, diff is the absolute error of each point of composite diagram and required direction figure.

$weight\left({\mathrm{\θ}}_i\right)=\left\{\begin{array}{c}{a}_1,1\≤i\≤114\\ a_2,115\≤i\≤168\\ a_3,169\≤i\≤179\\ a_4,180\≤i\≤240\\ a_5,241\≤i\≤360\end{array}\right.$

Wherein, θ is the angle value in antenna pattern, and scope is at 0 °-360 °, and i has 5 kinds of values here, by 360 ° points in order to 5 sections, adds five sections of corresponding weights a respectively, and the object of weighted value is in order to figuration more accurately.

Adopt the flow process shown in Fig. 1 to carry out figuration to the directional diagram of 9.05GHz center frequency point, the amplitude and the phase place that array antenna figuration are become optimal solution needed for target direction figure can be calculated.

In the shaping method flow process applying modified model self-adapted genetic algorithm, population scale is set to 300, and amplitude coding figure place is 7, and phase code figure place is 9, and genetic algebra is 2000.

The advantage of carrying out array antenna figuration of using modified adaptive algorithm is shown below by four block graphics Comparative result.

First be adopt modified model self-adapted genetic algorithm to set a higher threshold (0.065) and the fitness having elite's retention strategy to obtain and compound direction figure, as shown in Figure 7, result display fitness is more than 0.09, and compound direction figure figuration is perfect, it is fine that secondary lobe suppresses, and lobe width can reach 65 °.Then under equal conditions change high threshold values into low valve valve (0.05), observed result, as shown in Figure 8, now fitness is about 0.07, and compound direction figure figuration is also not ideal enough.Then, under equal conditions removed by elite's retention strategy, observed result, as shown in Figure 9, now fitness is about 0.05, and compound direction figure figuration is then more undesirable.Finally, adopt the fitness value and antenna compound direction figure that obtain during classical genetic algorithm, as shown in Figure 10, fitness can only reach about 0.06, and obviously, secondary lobe is larger in the main lobe shake of compound direction figure.

This shows, compared with classical genetic algorithm, introduce modified model self-adapted genetic algorithm and carry out figuration operation, arrange and elite's retention strategy owing to adding threshold values, figuration precision for antenna improves a lot, and also can obtain our target broad beam directional diagram.

The utility model, on the basis of roulette wheel dish method, proposes a kind of selection strategy combined with the selection of roulette wheel dish and elitist selection and carries out genetic manipulation.When maximum adaptation angle value is lower than threshold value, selects by roulette wheel dish method, do not introduce elitism strategy, protection population gene diversity.And when maximum adaptation angle value is higher than threshold value, in algorithm, introduce elitism strategy, convergence speedup speed.The fitness value that traditional genetic algorithm calculates, when solving array antenna figuration problem, can be risen to more than 0.09 from less than 0.07, improve a lot to the fitting degree tool of directional diagram by modified model self-adapted genetic algorithm.

The cosecant square wave beam based on follow-on self-adapted genetic algorithm research and design, the parameter of target direction figure is-3dB width range is 0 °-12 °, and-10dB beamwidth is 65 °, and wave cover is 65 °, frequency band range is 8.5GHz ~ 9.8GHz, and centre frequency is 9.05GHz.Have benefited from the accurate figuration of modified model self-adapted genetic algorithm, make antenna pattern wave cover width can reach 65 °, the beam coverage of the X-wave band autenna battle array of the design is wider, and practicality is better, has very superior application prospect in aircraft navigation detection.

For the problem such as in prior art, during array antenna figuration the low and antenna beam coverage of degree of fitting is limited; the utility model carries out genetic manipulation with the selection strategy that roulette wheel dish is selected and elitist selection combines; when maximum adaptation angle value is less than or equal to fitness threshold value; adopt roulette wheel dish method to carry out selecting and not introducing elitism strategy, protect the diversity of population gene.When maximum adaptation angle value is higher than threshold value, introduces elitism strategy and select, accelerate convergence rate.For obtaining larger antenna pattern wave cover width, the utility model devises rectangular patch array antenna, can meet the figuration of cosecant square expansion wave beam.In the utility model embodiment, a selected cosecant square expansion wave beam is target direction figure, the specific targets of target direction figure are :-3dB width range is 0 °-12 °, and-10dB beamwidth is 65 °, and wave cover is 65 °, frequency band range is 8.5GHz ~ 9.8GHz, and centre frequency is 9.05GHz.

Those skilled in the art should be understood that, each part of the device that above-mentioned the utility model embodiment provides, and each step in method, they can concentrate on single calculation element, or are distributed on network that multiple calculation element forms.Alternatively, they can realize with the executable program code of calculation element.Thus, they can be stored and be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the utility model is not restricted to any specific hardware and software combination.

Although the execution mode disclosed by the utility model is as above, the execution mode that described content only adopts for ease of understanding technical solutions of the utility model, and be not used to limit the utility model.Those of skill in the art belonging to any the utility model; under the prerequisite not departing from the spirit and scope disclosed by the utility model; any amendment and change can be carried out in the form implemented and details; but scope of patent protection of the present utility model, the scope that still must define with appending claims is as the criterion.

Claims (7)

1. a size enlargement apparatus for array aerial direction figure, is characterized in that, comprising:

Input, obtains the directional diagram of each array element of array antenna under coupling condition;

Population maker, according to the directional diagram stochastic generation initial population of each array element under described coupling condition;

Selector, for each individuality in described initial population calculates fitness value, and selects roulette wheel dish strategy or elitist selection strategy according to described fitness value;

Regeneration optimizer, the roulette wheel dish strategy selected by described selector or elitist selection strategy, coordinate fitness to select regeneration individual, and be optimized described regeneration individuality, generate new individuality;

Output, exports the optimal direction figure of described array antenna when meeting default end rules.

2. size enlargement apparatus according to claim 1, is characterized in that, this device also comprises:

Feedback controller, when described individuality does not newly meet described default end rules, recalculates instruction to described selector feedback;

Described selector according to described in recalculate instruction and recalculate described fitness value.

3. size enlargement apparatus according to claim 1, is characterized in that, described selector comprises:

Computing unit, calculates described fitness value;

Selected cell, when described fitness value is less than or equal to fitness threshold value, selects roulette wheel dish strategy, otherwise selects elitist selection strategy.

4. an array antenna, is characterized in that, comprising:

Be spaced the multiple array-element antenna of distance for half-wavelength, each array-element antenna described comprises rectangular element antenna and connected feeder line, and described feeder line is connected with the narrow limit of rectangular element antenna by feedback point.

5. array antenna according to claim 4, is characterized in that, the quantity of described array-element antenna is 10,14,16 or 20.

6. array antenna according to claim 4, is characterized in that, described feeder line is the octagon with two groups of parallel edges.

7. array antenna as claimed in claim 4, is characterized in that, the selected cosecant of an each array-element antenna square expansion wave beam for described array antenna is target direction figure.