CN106357316A - Beam forming method and device of array antenna - Google Patents

Abstract

The invention relates to a beam forming method and a beam forming device of an array antenna. The method comprises the following steps: generating a particle swarm according to the preset population size, and initializing the parameters of the particle swarm; calculating the fitness value of each particle in the particle swarm according to a preset fitness function determined according to the required beam, wherein the optimal solution of the problem of the fitness function is the amplitude and phase value required by the beam; with the particle swarm as a parent particle swarm, adopting an immune algorithm for the parent particle swarm according to the fitness values of the particles to obtain a next-generation particle swarm of the parent particle swarm; updating the optimal value of the particles and the optimal solution of the problem according to the preset rules; judging whether the preset maximum iteration number is up; and if so, determining the phase and signal amplitude of each array element according to the optimal solution of the problem, and forming to obtain the required beam of the array antenna. In combination with the particle swarm algorithm and the immune algorithm, the search speed can be effectively increased, the efficiency is high, and the formed antennae beam meets the requirements.

Description

The beam form-endowing method of array antenna and device

Technical field

The present invention relates to communication technical field, more particularly to a kind of beam form-endowing method of array antenna and device.

Background technology

In the various fields such as radar, radio communication, wave beam forming is a kind of Signal Pretreatment skill based on aerial array Art, wave beam forming pass through adjust aerial array in each array element weight coefficient produce have directivity wave beam such that it is able to Obtain obvious array gain.Control phase place and the signal amplitude of each array element by beamformer, obtain required wave beam.

This is a multidimensional nonlinear optimization problem.It is well suited for solving such complexity based on the evolution algorithmic of group intelligence Nonlinear optimal problem, and these algorithms have clear concept, program simple the features such as.The evolution of conventional group intelligence is calculated Method has particle cluster algorithm.In particle cluster algorithm, the potential solution of each optimization problem is one " particle " in search space, and grain The position of son is exactly the solution of required problem.All of particle has a fitness value being determined by optimised function, and Each particle also has the direction that a speed determines that they circle in the air and distance.Particle cluster algorithm initializes a group random particles first (RANDOM SOLUTION), is flown with certain speed in search space, then finds optimal solution by iteration.In each iteration, Particle updates oneself by following the tracks of two extreme values, and first is exactly the optimal solution that particle itself is found, and another extreme value is The optimal solution that whole population is found at present.

Particle cluster algorithm has the characteristics that algorithm is simple, easily realizes, search speed is fast, institute's containing parameter is less.But it is basic Particle cluster algorithm have the too fast, Premature Convergence of convergence, hunting zone less, the problems such as easily converge to local extremum, therefore, Determine that using particle cluster algorithm the time needed for the parameters such as phase place and the signal amplitude of the wave beam of array antenna is long, efficiency is low.

Content of the invention

Based on this it is necessary to provide a kind of beam form-endowing method of array antenna and device, can quickly determine array sky The phase place of the wave beam of line and signal amplitude.

A kind of beam form-endowing method of array antenna, comprising:

Produce population according to pre-setting population scale, and initialize each parameter of population；Described parameter includes: grain The original position of son and initial velocity；

According to pre-setting, the suitable of each particle in described population is calculated according to the fitness function that required wave beam determines Answer angle value；The optimal solution of the problem of described fitness function is the amplitude and phase value needed for synthesis object beam；

Using described population as parent population, according to the fitness value of described particle, described parent particle is mined massively With immune algorithm, obtain the population of future generation of described parent population；Described immune algorithm includes clone, high frequency closedown and choosing Select operation；

Optimal value according to preset rules more new particle and the optimal solution of problem, wherein, the optimal value of particle and problem Optimal solution determines, described preset rules are according to the position of particle:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, i.e. i-th particle warp in population The desired positions gone through,For its corresponding adaptive value degree；For the optimal solution of problem, i.e. all particle warps in population The desired positions gone through,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is Iterationses；

Judge whether to reach default maximum iteration time；

If so, phase place and the signal amplitude of each array element are then determined according to the optimal solution of problem, figuration obtains required array sky The wave beam of line.

In one embodiment, described using described population as parent population, according to the fitness value of described particle, Immune algorithm is adopted to described parent population, the step obtaining the population of future generation of described parent population includes:

According to the fitness value of described particle, particle is carried out with the filial generation particle that clone operations obtain described particle；Described The number that particle is cloned is proportionate with the fitness value of described particle；

Described filial generation particle is carried out with high frequency closedown operation and obtains Variant progeny particle；

Calculate the fitness value of described variation particle according to described fitness function, and form from parent and Variant progeny The larger particle of n1 adaptive value is selected, with the n-n1 new particle composition population of future generation randomly generating in set.

In one embodiment, if judging not reaching default maximum iteration time, the speed of more new particle and position； And the fitness value according to fitness function and each particle in the speed of the particle updating, position calculation population of future generation.

In one embodiment, the number that described particle is carried out with the filial generation particle that clone operations obtain particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness of particle Value.

In one embodiment, the formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is: x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1, and 2 ..., n represent the d dimension of particle, and w is inertia weight, C1 and c2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.

A kind of beam size enlargement apparatus of array antenna, comprising: initialization module, fitness computing module, Immune computation mould Block, update module, judge module and figuration module；

Described initialization module, pre-sets population scale for basis and produces population, and initialize each of population Parameter；Described parameter includes: the original position of particle and initial velocity；

Described fitness computing module, for according to the fitness function calculating pre-setting according to the determination of required wave beam The fitness value of each particle in described population；The optimal solution of the problem of described fitness function is needed for synthesis object beam Amplitude and phase value；

Described Immune computation module, for using described population as parent population, according to the fitness of described particle Value, adopts immune algorithm to described parent population, obtains the population of future generation of described parent population；Described immune algorithm Including clone, high frequency closedown and selection operation；

Described update module, for the optimal value of the optimal value according to preset rules more new particle and population, wherein, presets Rule is:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, i.e. i-th particle warp in population The desired positions gone through,For its corresponding adaptive value degree；For the optimal solution of problem, i.e. all particle warps in population The desired positions gone through,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is Iterationses；

Described judge module, is used for judging whether to reach default maximum iteration time；

Described figuration module, for when the judged result of described judge module is for being, the optimal solution according to problem determines The phase place of each array element and signal amplitude, figuration obtains the wave beam of required array antenna.

In one embodiment, described Immune computation module includes: clone operations module, mutation operation module and selection behaviour Make module；

Described clone operations module, for the fitness value according to described particle, carries out clone operations to particle and obtains institute State the filial generation particle of particle；The number that described particle is cloned is proportionate with the fitness value of described particle；

Described mutation operation module, obtains Variant progeny particle for described filial generation particle is carried out with high frequency closedown operation；

Described selection operation module, for calculating the fitness value of described variation particle according to described fitness function, and Select the larger particle of n1 adaptive value from the set of parent and Variant progeny composition, with the n-n1 new particle randomly generating Composition population of future generation.

In one embodiment, the beam size enlargement apparatus of array antenna also include parameter update module, and described parameter updates Module, for when the judged result of described judge module is no, the speed of more new particle and position, described fitness calculates mould Tuber is according to the fitness value of fitness function and each particle in the speed of the particle updating, position calculation population of future generation.

In one embodiment, the number that described particle is carried out with the filial generation particle that clone operations obtain particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness of particle Value.

In one embodiment, the formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is:

x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1, and 2 ..., n represent the d dimension of particle, and w is inertia weight, C1 and c2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.

The beam form-endowing method of above-mentioned array antenna, by solving fitness letter using particle cluster algorithm and immune algorithm The optimal solution of the problem of number, based on particle cluster algorithm, incorporates immune algorithm wherein, multiple using the clone entering immune algorithm System, high frequency closedown, Immune Clone Selection etc. operate to improve diversity of particle swarm and convergence of algorithm speed, effectively increases feature choosing Select efficiency, so that antenna shaped-beam is met and require.

Brief description

Fig. 1 is the flow chart of the beam form-endowing method of the array antenna of an embodiment；

Fig. 2 is the array antenna schematic diagram of an embodiment；

Fig. 3 is the wave beam that the array antenna shown in Fig. 2 is obtained using the beam form-endowing method of the array antenna of the present invention Directional diagram；

Fig. 4 is that the width phase excited data of the wave beam shown in table 1 is added to the emulation directional diagram obtaining wave beam in simulation software；

Fig. 5 is the high-level schematic functional block diagram of the beam size enlargement apparatus of the array antenna of an embodiment.

Specific embodiment

As shown in figure 1, a kind of beam form-endowing method of array antenna, comprise the following steps:

S102: produce population according to pre-setting population scale, and initialize each parameter of population.

The population scale of population pre-sets, and produces the population of corresponding scale, and initializes each parameter of population. Each parameter of population includes: original position x of particle_i(t)=(x_i1, x_i2... ..., x_id), initial velocity v_i(t)=(v_i1, v_i2... ..., v_id).Wherein, each x_iT () all represents a kind of possible solution, in the present invention, by abstract for optimized variable be The position vector of particle.

S104: the suitable of each particle in population is calculated according to the fitness function that required wave beam determines according to pre-setting Answer angle value.

Determine fitness function previously according to required wave beam.Fitness function is related to the parameter of shaped-beam.Different The fitness function that wave beam requires can be different.Calculate the fitness value of each particle in population according to fitness function. The optimal solution of the problem of fitness function is the amplitude and phase value needed for synthesis object beam.Being mapped in particle cluster algorithm is The desired positions of particle.

S106: using population as parent population, according to the fitness value of particle, parent population is calculated using immunity Method, obtains the population of future generation of parent population；Immune algorithm includes clone, high frequency closedown and selection operation.

Immune algorithm is merged by the beam form-endowing method of the array antenna of the present embodiment with particle cluster algorithm, by particle Clone, high frequency closedown and the selection operation of immune algorithm is introduced in group's algorithm.Wherein, clone operations make the outstanding particle in population Preserved, high frequency closedown operation produces new individuality, effectively increased population diversity, selection operation is selected optimum individual, Algorithm is avoided to degenerate.

S108: the optimal value according to preset rules more new particle and the optimal solution of problem, wherein, the optimal value of particle and asking The optimal solution of topic determines, preset rules are according to the position of particle:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, i.e. i-th particle warp in population The desired positions gone through,For its corresponding adaptive value degree；For the optimal solution of problem, i.e. all particle warps in population The desired positions gone through,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is Iterationses.Wherein, the optimal solution of problem and the optimal value of particle obtain according to position calculation.

S110: judge whether to reach default maximum iteration time.If so, then execution step s112, if it is not, then execute step Rapid s113.

S112: determine phase place and the signal amplitude of each array element according to the optimal solution of problem, figuration obtains required array antenna Wave beam.

The beam form-endowing method of above-mentioned array antenna, by solving fitness letter using particle cluster algorithm and immune algorithm The optimal solution of the problem of number, based on particle cluster algorithm, incorporates immune algorithm wherein, multiple using the clone entering immune algorithm System, high frequency closedown, Immune Clone Selection etc. operate to improve diversity of particle swarm and convergence of algorithm speed, effectively increases feature choosing Select efficiency, so that antenna shaped-beam is met and require.

In another embodiment, step s106 comprises the following steps 1 to step 3:

Step 1: according to the fitness value of particle, particle is carried out with the filial generation particle that clone operations obtain particle；Particle quilt The number of clone is proportionate with the fitness value of particle.

Specifically, the number that particle is carried out with the filial generation particle that clone operations obtain particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness of particle Value.

Outstanding particle in parent population is made to be preserved by particle is carried out with clone operations.

Step 2: filial generation particle is carried out with high frequency closedown operation and obtains Variant progeny particle.

Wherein, mutation probability meets Gauss distribution n (0,1).New individuality is produced by mutation operation, effectively increases and plant Group's multiformity.

Step 3: calculate the fitness value of variation particle, and the collection from parent and Variant progeny composition according to fitness function The larger particle of n1 adaptive value is selected, with the n-n1 new particle composition population of future generation randomly generating in conjunction.

By selection operation, select optimum individual, it is to avoid algorithm is degenerated.

In another embodiment, if the judged result of step s110 is no, i.e. not up to default maximum iteration time, Then execution step:

S113: the speed of more new particle and position.And after the step of step s113, return to step s114, according to suitable The fitness value of each particle in response function and the speed of particle updating, position calculation next generation's population.

The formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is:

x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1, and 2 ..., n represent the d dimension of particle, and w is inertia weight, C1 and c2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.

The beam form-endowing method of above-mentioned array antenna, by solving fitness letter using particle cluster algorithm and immune algorithm The optimal solution of the problem of number, immune algorithm includes clone, high frequency closedown and selection operation, and clone operations make the outstanding grain in population Son is preserved, and high frequency closedown operation produces new individuality, effectively increases population diversity, and selection operation selects optimum Body, it is to avoid algorithm is degenerated.The optimal solution of the problem of fitness function is the amplitude and phase value needed for wave beam, calculates in conjunction with population When method and immune algorithm can overcome array antenna beam synthesis in prior art, degree of fitting is low, is difficult to find globally optimal solution Problem, can effectively improve search speed, efficiency high, so that antenna shaped-beam is met and require.

Below, in conjunction with specific case, the beam form-endowing method of the array antenna to the present invention illustrates.

In the present embodiment, the antenna schematic diagram of ten unit mobile communication base stations is as shown in Fig. 2 ten half-wave dipole groups Become an equidistant linear array structure, element spacing is 0.8 λ, away from reflector height 0.25 λ, wherein λ is the ripple of operating frequency to oscillator Long.By changing the amplitude of each oscillator feed current and phase place so that secondary lobe suppression is less than -20db on elevation radiation patytern, Lower first zero filling is more than -15db, to suppress adjacent area interference and to avoid black situation under tower.

Using the beam form-endowing method of array antenna, synthesis is carried out to the directional diagram of 2.2ghz center frequency point, calculating is entered the arena Array antenna figuration becomes amplitude and phase value needed for object beam.

In this example, setting population size is 40, iterationses 30, and inertia weight w is 0.5, aceleration pulse c1 and c2 It is taken as 2.Fitness function is defined as:

Fitness=α usl-g1sl+β dnf-gnf+γ dsl-g2sl

Wherein: usl is upper secondary lobe maximum level, dnf is lower first null depth, and dsl is lower secondary lobe maximum level, g1sl And g2sl is expectation minor level, gnf is expectation null depth, and α, β, γ are weight factor.

The directional diagram of the wave beam of the array antenna that figuration obtains is as shown in figure 3, from the figure, it can be seen that forming main lobe Simultaneously it is suppressed that the upper minor level of antenna array, to below -20db, defines the zero point an of -15db in overlay area simultaneously Filling region, the directional diagram after synthesis is consistent with the directional diagram of object beam, width phase excited data such as table 1 institute of the wave beam of figuration Show.

The width phase excited data of the wave beam of table 1 figuration

Unit	1	2	3	4	5	6	7	8	9	10
											Amplitude (w)	1	1.1	1.4	1.4	1.8	2.7	3	3	1.5	1.6
Phase place (°)	25	4.6	5.3	14.8	24	25	23.8	18.6	0	0

The excitation of width phase is updated in high-frequency structure simulation software three-D high frequency electromagnetic-field simulation instrument and is confirmed, obtain The antenna pattern of antenna array is as shown in Figure 4.It is identical that relatively Fig. 3 and Fig. 4 can be seen that the result that simulation result obtains with algorithm Degree is very high, thus demonstrating the effectiveness of the beam form-endowing method of the array antenna of the present invention.

A kind of beam size enlargement apparatus of array antenna, as shown in Figure 5, comprising: initialization module 501, fitness calculate mould Block 502, Immune computation module 503, update module 504, judge module 505 and figuration module 506.

Initialization module 501, pre-sets population scale for basis and produces population, and initialize each ginseng of population Number；Parameter includes: the original position of particle and initial velocity.

Fitness computing module 502, for according to the fitness function calculating pre-setting according to the determination of required wave beam The fitness value of each particle in population；The optimal solution of the problem of fitness function is the amplitude and phase needed for synthesis object beam Place value；

Immune computation module 503, for using population as parent population, according to the fitness value of particle, to parent Population adopts immune algorithm, obtains the population of future generation of parent population；Immune algorithm includes clone, high frequency closedown and choosing Select operation.

Update module 504, for the optimal value of the optimal value according to preset rules more new particle and population, wherein, presets Rule is:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, i.e. i-th particle experience in population Desired positions,For its corresponding adaptive value degree；For the optimal solution of problem, i.e. all particle experience in population The desired positions crossed,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is repeatedly Generation number.

Judge module 505, is used for judging whether to reach default maximum iteration time.

Figuration module 506, for when the judged result of judge module is for being, determining each array element according to the optimal solution of problem Phase place and signal amplitude, figuration obtains the wave beam of required array antenna.

Immune algorithm is merged by the beam size enlargement apparatus of the array antenna of the present embodiment with particle cluster algorithm, by particle Clone, high frequency closedown and the selection operation of immune algorithm is introduced in group's algorithm.Wherein, clone operations make the outstanding particle in population Preserved, high frequency closedown operation produces new individuality, effectively increased population diversity, selection operation is selected optimum individual, Algorithm is avoided to degenerate.

In another embodiment, Immune computation module 503 includes: clone operations module, mutation operation module and selection Operation module；

Clone operations module, for the fitness value according to particle, carries out, to particle, the filial generation that clone operations obtain particle Particle；The number that particle is cloned is proportionate with the fitness value of particle.

Specifically, the number that particle is carried out with the filial generation particle that clone operations obtain particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness of particle Value.

Mutation operation module, obtains Variant progeny particle for filial generation particle is carried out with high frequency closedown operation；

Selection operation module, for calculating the fitness value of variation particle, and from parent and variation according to fitness function The larger particle of n1 adaptive value is selected, with the n-n1 new particle composition grain of future generation randomly generating in the set of filial generation composition Subgroup.

The beam size enlargement apparatus of above-mentioned array antenna, by solving fitness letter using particle cluster algorithm and immune algorithm The optimal solution of the problem of number, based on particle cluster algorithm, incorporates immune algorithm wherein, multiple using the clone entering immune algorithm System, high frequency closedown, Immune Clone Selection etc. operate to improve diversity of particle swarm and convergence of algorithm speed, effectively increases feature choosing Select efficiency, so that antenna shaped-beam is met and require.

In yet another embodiment, the beam size enlargement apparatus of array antenna, also include parameter update module, and parameter updates mould Block, for when the judged result of judge module is no, the speed of more new particle and position, fitness computing module is according to adaptation The fitness value of each particle in degree function and the speed of particle updating, position calculation next generation's population.

The formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is:

x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1, and 2 ..., n represent the d dimension of particle, and w is inertia weight, C1 and c2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.On The beam size enlargement apparatus of the array antenna stated, by the problem using particle cluster algorithm and immune algorithm solution fitness function Optimal solution, immune algorithm includes clone, high frequency closedown and selection operation, and clone operations make the outstanding particle in population be protected Deposit, high frequency closedown operation produces new individuality, effectively increase population diversity, selection operation selects optimum individual, it is to avoid calculate Method is degenerated.The optimal solution of the problem of fitness function is the amplitude and phase value needed for wave beam, in conjunction with particle cluster algorithm and immunity When algorithm can overcome array antenna beam synthesis in prior art, degree of fitting is low, is difficult to find the problem of globally optimal solution, energy Enough effectively improve search speed, efficiency high, so that antenna shaped-beam is met and require.

Each technical characteristic of embodiment described above can arbitrarily be combined, for making description succinct, not to above-mentioned reality The all possible combination of each technical characteristic applied in example is all described, as long as however, the combination of these technical characteristics is not deposited In contradiction, all it is considered to be the scope of this specification record.

Embodiment described above only have expressed the several embodiments of the present invention, and its description is more concrete and detailed, but simultaneously Can not therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art Say, without departing from the inventive concept of the premise, some deformation can also be made and improve, these broadly fall into the protection of the present invention Scope.Therefore, the protection domain of patent of the present invention should be defined by claims.

Claims (10)

1. a kind of beam form-endowing method of array antenna is it is characterised in that include:

Produce population according to pre-setting population scale, and initialize each parameter of population；Described parameter includes: particle Original position and initial velocity；

According to the fitness pre-setting according to each particle in the fitness function described population of calculating of required wave beam determination Value；The optimal solution of the problem of described fitness function is the amplitude and phase value needed for synthesis object beam；

Using described population as parent population, according to the fitness value of described particle, to described parent population using exempting from Epidemic disease algorithm, obtains the population of future generation of described parent population；Described immune algorithm includes clone, high frequency closedown and selects behaviour Make；

Optimal value according to preset rules more new particle and the optimal solution of problem, wherein, the optimal value of particle and the optimum of problem Solution determines, described preset rules are according to the position of particle:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, that is, in population, i-th particle experiences Good position,For its corresponding adaptive value degree；For the optimal solution of problem, that is, in population, all particles live through Desired positions,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is iteration time Number；

Judge whether to reach default maximum iteration time；

If so, phase place and the signal amplitude of each array element are then determined according to the optimal solution of problem, figuration obtains required array antenna Wave beam.

2. method according to claim 1 it is characterised in that described using described population as parent population, according to The fitness value of described particle, adopts immune algorithm to described parent population, obtains the grain of future generation of described parent population The step of subgroup includes:

According to the fitness value of described particle, particle is carried out with the filial generation particle that clone operations obtain described particle；Described particle The number being cloned is proportionate with the fitness value of described particle；

Described filial generation particle is carried out with high frequency closedown operation and obtains Variant progeny particle；

Calculate the fitness value of described variation particle according to described fitness function, and the set from parent and Variant progeny composition The middle particle selecting n1 adaptive value larger, with the n-n1 new particle composition population of future generation randomly generating.

If 3. method according to claim 2 is it is characterised in that judge not reaching default maximum iteration time, more The speed of new particle and position；And in the speed according to fitness function and the particle updating, position calculation next generation's population The fitness value of each particle.

4. method according to claim 2 is it is characterised in that carry out, to described particle, the filial generation that clone operations obtain particle The number of particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness value of particle.

5. method according to claim 3 is it is characterised in that the formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is: x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1,2 ..., n represent particle d dimension, w be inertia weight, c1 and C2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.

6. a kind of beam size enlargement apparatus of array antenna are it is characterised in that include: initialization module, fitness computing module, exempt from Epidemic disease computing module, update module, judge module and figuration module；

Described initialization module, pre-sets population scale for basis and produces population, and initialize each parameter of population； Described parameter includes: the original position of particle and initial velocity；

Described fitness computing module, for according to pre-setting according to the fitness function that required wave beam determines calculates The fitness value of each particle in population；The optimal solution of the problem of described fitness function is the amplitude needed for synthesis object beam And phase value；

Described Immune computation module, for using described population as parent population, according to the fitness value of described particle, right Described parent population adopts immune algorithm, obtains the population of future generation of described parent population；Described immune algorithm includes Clone, high frequency closedown and selection operation；

Described update module, for the optimal value of the optimal value according to preset rules more new particle and population, wherein, preset rules For:

IfThen make

IfThen

Wherein, f_iT () is the fitness value of particle；For the optimal value of particle, that is, in population, i-th particle experiences Good position,For its corresponding adaptive value degree；For the optimal solution of problem, that is, in population, all particles live through Desired positions,For its corresponding fitness value；x_iT () is i-th particle position in the t time iteration, t is iteration time Number；

Described judge module, is used for judging whether to reach default maximum iteration time；

Described figuration module, for when the judged result of described judge module is for being, determining each battle array according to the optimal solution of problem The phase place of unit and signal amplitude, figuration obtains the wave beam of required array antenna.

7. device according to claim 6 is it is characterised in that described Immune computation module includes: clone operations module, change ETTHER-OR operation module and selection operation module；

Described clone operations module, for the fitness value according to described particle, carries out clone operations to particle and obtains described grain The filial generation particle of son；The number that described particle is cloned is proportionate with the fitness value of described particle；

Described mutation operation module, obtains Variant progeny particle for described filial generation particle is carried out with high frequency closedown operation；

Described selection operation module, for calculating the fitness value of described variation particle, and from father according to described fitness function The larger particle of n1 adaptive value is selected, with the n-n1 new particle composition randomly generating in the set of generation and Variant progeny composition Population of future generation.

8. device according to claim 7 is it is characterised in that also include parameter update module, described parameter update module, For when the judged result of described judge module is no, the speed of more new particle and position, described fitness computing module root Fitness value according to each particle in the speed of fitness function and the particle updating, position calculation next generation's population.

9. device according to claim 7 is it is characterised in that carry out, to described particle, the filial generation that clone operations obtain particle The number of particle is:

$m_i=\[\frac{f_i\left(t\right)}{{\mathrm{\σ}}_{i=1}^n{f}_i\left(t\right)}*n\]$

Wherein, m_iThe number being cloned for i-th particle；N is total number of particles in population；f_iT () is the fitness value of particle.

10. device according to claim 8 is it is characterised in that the formula of the speed of more new particle is:

$\begin{array}{c}{v}_{id}(t+1)={\mathrm{wv}}_{id}\left(t\right)+c_1{r}_1\left(p_{best,d}^i\right(t)-x_{id}(t\left)\right)+c_2{r}_2\left(p_{best,d}^g\right(t)-\\ x_{id}\left(t\right));\end{array}$

The formula of the position of more new particle is:

x_id(t+1)=x_id(t)+v_id(t+1)；

Wherein, i=1,2 ..., m represent i-th particle, d=1,2 ..., n represent particle d dimension, w be inertia weight, c1 and C2 is aceleration pulse, and r1, r2 are generally evenly distributed in the random function in (0,1) interval, and t is the step-length of iterationses.