CN104636558A - Novel antenna evolution method - Google Patents

Abstract

The invention provides a novel antenna evolution method which includes the steps: setting an antenna working frequency range, an antenna working azimuth angle and an elevation angle range, constrained optimization conditions, the range of sizes in an antenna simulation physical model and the number of iterations, building an antenna simulation physical model, and acquiring a parent by the aid of an antenna evolution algorithm; judging whether a size variation in a current simulation physical model meets the constrained optimization conditions or reaches the maximum number of iterations or not, and finishing evolution if the size variation in the current simulation physical model meets the constrained optimization conditions or reaches the maximum number of iterations; substituting an assessed value and the constrained conditions into the antenna evolution algorithm for iterations if not to a size variation of a child until the size variation in the current simulation physical model meets the constrained optimization conditions or reaches the maximum number of iterations. The novel antenna evolution method is independent of electromagnetic theoretical knowledge and experience of antenna designers and can meet a plurality of antenna design requirements, and an antenna can be automatically and intelligently evolved by the aid of smart computing technology and existing electromagnetic simulation technology.

Description

A kind of novel evolution method of antenna

Technical field

The present invention relates to a kind of novel evolution method of antenna, belong to antenna technical field.

Background technology

The research of evolution antenna starts from 1990s, updating in recent years along with intelligent algorithm, and the operational speed of a computer increases, and the improvement of electromagnetic simulation software, the research and development of evolution antenna is very fast.The antenna of NASA evolution automated antenna design Software for Design obtains application of result because being better than traditional antenna on the ST5 satellite of transmitting in 2006.From then on after, evolution antenna has a wide range of applications in military aviation field, but does not still effectively apply at civil area.Along with the arrival of information age, need to exchange information fast, utilize existing method for designing to design, the antenna obtained usually cannot reach the object of miniaturization, and frequency range is often lower, cannot meet higher transmission of wireless signals demand.

WiFi technology is a kind of wireless network login technique, and nearly all nearly all smart mobile phone, panel computer and notebook computer are all supported to get online without being tethered to a cable.When mobile terminal loses nowhere in life, and for wireless network requirements more next high time, high-performance WiFi antenna important in inhibiting.

Traditional antenna design method depends on electromagnetic theory knowledge and the experience of antenna designer, when in the face of challenging demand, the such as antenna for mobile phone etc. of satellite antenna, missile antenna and miniaturization, be difficult to rapidly and efficiently find good solution, based on computer technology, Intelligent Computation Technology and electromagnetic simulation technique etc. automatic antenna method for designing for solution above-mentioned challenge have potential advantages.

Summary of the invention

In order to solve the deficiencies in the prior art, the invention provides a kind of novel evolution method of antenna, the method need not depend on electromagnetic theory knowledge and the experience of antenna designer, multiple Antenna Design demand can be tackled, Intelligent Computation Technology and existing electromagnetic simulation technique can be utilized to complete automatic intelligent antenna and develop.

The technical scheme that the present invention adopts for its technical matters of solution is: the novel evolution method providing a kind of antenna, comprise the following steps: the scope and the iterations that arrange size in operating frequency of antenna scope, the scope at the position angle of Antenna Operation and the elevation angle, constrained optimization condition, antenna emulated physics model, described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition; Arrange antenna pattern according to operating frequency of antenna scope, set up the emulated physics model of antenna, utilize antenna evolution algorithmic to obtain parent, described parent is the size variable in emulated physics model; Whether the size variable judging in current emulated physics model meets constrained optimization conditioned disjunction reaches maximum iteration time, if then develop end, the size variable in emulated physics model is evolution result; Otherwise utilize the size variable in current emulated physics model to calculate assessed value, and bring assessed value and constraint condition into antenna evolution algorithmic and carry out iteration, obtain the size variable of filial generation, until the size variable in current emulated physics model meets constrained optimization conditioned disjunction reach maximum iteration time.

The novel evolution method of described a kind of antenna specifically comprises the following steps:

(1) scope and the maximum iteration time of size in operating frequency of antenna scope, the constrained optimization condition of antenna, the scope at the position angle of Antenna Operation and the elevation angle, antenna emulated physics model are set; Described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition;

(2) the emulated physics model of antenna is set up, in described emulated physics model, described antenna comprises flat rectangular body insulated substrate, the upper surface of insulated substrate posts the conductor patch identical with insulated substrate size, described conductor patch central authorities are provided with elliptical aperture, the longer axis parallel of elliptical aperture in the long limit of upper surface, the lower surface horizontally set strip feeder line of insulated substrate, the right-hand member of feeder line is provided with feedback point, and described feedback point is concordant with the right hand edge of insulated substrate lower surface; The height of insulated substrate be h, long for w, wide be l, the elliptical aperture major semi-axis in conductor patch is a, minor semi-axis b, and the thickness of conductor patch is c, and the width of feeder line is fw, length is fl, and feedback dot center is d to the distance of the minor axis of elliptical aperture; Utilize antenna evolution algorithmic to obtain parent, described parent is the individuality comprising h, w, l, a, b, c, fw, fl and d of more than 2 groups; H, w, l, a, b, c, fw, fl and d are size variable; Arrange variable N to indicate iterations, the initial value of N is 0;

(3) individual for the often group in parent, calculate assessed value according to following assessed value computing formula

Wherein, represent assessed value, the vector that is element with h, w, l, a, b, c, fw, fl and d, point in representation space spheric coordinate system, position angle and the elevation angle of space spheric coordinate system is respectively with θ, be Antenna Design working range with the scope of θ;

$\mathrm{VSWRVariance}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{({\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-\mathrm{MeanVSW}{R}_{\left(\mathrm{freq}\right)})}^2;$

$\mathrm{Mean}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}/3;$

the antenna of to be frequency of operation be freq exists the gain at place;

the antenna of to be frequency of operation be freq exists the axial ratio at place;

VSWR _(freq)the standing-wave ratio (SWR) of antenna when frequency of operation is freq;

Within the scope of the operating frequency of antenna that the span of freq is arranged in step (1);

and VSWR _(freq)be and utilize simulation algorithm to emulate the result obtained according to emulated physics model;

Iterations N cumulative 1;

(4) if there is one group of individuality to make the constrained optimization condition of antenna all satisfied in parent, then end of developing, this group individuality is evolution result; If iterations N is greater than the iterations that step (2) is arranged, then make in parent the minimum individuality of value is evolution result; Otherwise enter step (5);

(5) individual for each group in parent, carry out following steps: by what calculate substitute into antenna evolution algorithmic with constraint optimal conditions and carry out iteration, obtain the individuality that new size variable is filial generation; Each group of filial generation is combined as new parent, returns step (3) and carries out next round iteration.

The constrained optimization condition of the antenna described in step (1) comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition, wherein,

Gain constraint condition is

Axial ratio constraint condition is

Standing-wave ratio (SWR) constraint condition is $g{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}\left(\stackrel{\→}{x}\right)={\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-1.5\≤0.$

The present invention is based on the beneficial effect that its technical scheme has to be:

(1) the novel evolution method of antenna provided by the invention need not depend on electromagnetic theory knowledge and the experience of antenna designer, multiple Antenna Design demand can be tackled, Intelligent Computation Technology and existing electromagnetic simulation technique can be utilized to complete automatic intelligent antenna and develop.

(2) the present invention is especially applicable to developing to microband paste WiFi antenna, the emulated physics model of this microband paste WiFi antenna adopts rectangular parallelepiped insulated substrate and hollows out the structure of conductor patch of elliptical aperture, elliptical aperture border in such conductor patch is smooth, suddenly can distort by anti-stop signal, make the stable performance of antenna receiving and transmitting signal;

(3) the invention provides the assessed value computing formula in a kind of evolutionary process, utilize this assessed value computing formula can provide for antenna evolutionary process the foundation judging antenna structure quality, substitute into the parameter that evolution algorithmic can be met the emulated physics model of the antenna of requirement exactly;

(4) according to the microband paste WiFi antenna that method provided by the invention obtains, compare smaller and more exquisite with wire antenna, the bandwidth of this antenna is more than 1.1GHz, and between 1.75GHz to 2.85GHz, center operating frequency can reach 2.4GHz.

Accompanying drawing explanation

Fig. 1 is structural representation of the present invention.

In figure: 1-conductor patch, 2-presents point, 3-elliptical aperture, 4-insulated substrate, 5-feeder line.

Embodiment

Below in conjunction with drawings and Examples, the invention will be further described.

The invention provides a kind of novel evolution method of antenna, comprise the following steps: the scope and the iterations that arrange size in operating frequency of antenna scope, the scope at the position angle of Antenna Operation and the elevation angle, constrained optimization condition, antenna emulated physics model, described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition; Arrange antenna pattern according to operating frequency of antenna scope, set up the emulated physics model of antenna, utilize antenna evolution algorithmic to obtain parent, described parent is the size variable in emulated physics model; Whether the size variable judging in current emulated physics model meets constrained optimization conditioned disjunction reaches maximum iteration time, if then develop end, the size variable in emulated physics model is evolution result; Otherwise utilize the size variable in current emulated physics model to calculate assessed value, and bring assessed value and constraint condition into antenna evolution algorithmic and carry out iteration, obtain the size variable of filial generation, until the size variable in current emulated physics model meets constrained optimization conditioned disjunction reach maximum iteration time.

The novel evolution method of described antenna specifically comprises the following steps:

(1) scope and the maximum iteration time of size in operating frequency of antenna scope, the constrained optimization condition of antenna, the scope at the position angle of Antenna Operation and the elevation angle, antenna emulated physics model are set; Described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition;

(2) the emulated physics model of antenna is set up, with reference to Fig. 1, in described emulated physics model, described antenna comprises flat rectangular body insulated substrate 4, and the upper surface of insulated substrate posts the conductor patch 1 identical with insulated substrate size, and described conductor patch central authorities are provided with elliptical aperture 3, the longer axis parallel of elliptical aperture is in the long limit of upper surface, the lower surface horizontally set strip feeder line 5 of insulated substrate, the right-hand member of feeder line is provided with feedback point 2, and described feedback point is concordant with the right hand edge of insulated substrate lower surface; The height of insulated substrate be h, long for w, wide be l, the elliptical aperture major semi-axis in conductor patch is a, minor semi-axis b, and the thickness of conductor patch is c, and the width of feeder line is fw, length is fl, and feedback dot center is d to the distance of the minor axis of elliptical aperture; Utilize antenna evolution algorithmic to obtain parent, described parent is the individuality comprising h, w, l, a, b, c, fw, fl and d of more than 2 groups; H, w, l, a, b, c, fw, fl and d are size variable; Arrange variable N to indicate iterations, the initial value of N is 0;

(3) individual for the often group in parent, calculate assessed value according to following assessed value computing formula

Wherein, represent assessed value, the vector that is element with h, w, l, a, b, c, fw, fl and d, point in representation space spheric coordinate system, antenna azimuth and Downtilt is respectively with θ, with the scope of θ for making exhaust points all on microband paste WiFi antenna in emulated physics model;

$\mathrm{VSWRVariance}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{({\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-\mathrm{MeanVSW}{R}_{\left(\mathrm{freq}\right)})}^2;$

$\mathrm{Mean}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}/3;$

the antenna of to be frequency of operation be freq exists the gain at place;

the antenna of to be frequency of operation be freq exists the axial ratio at place;

VSWR _(freq)the standing-wave ratio (SWR) of antenna when frequency of operation is freq;

Within the scope of the operating frequency of antenna that the span of freq is arranged in step (1);

with be and utilize simulation algorithm to emulate the result obtained according to emulated physics model;

Iterations N cumulative 1;

(4) if there is one group of individuality to make the constrained optimization condition of antenna all satisfied in parent, then end of developing, this group individuality is evolution result; If iterations N is greater than the iterations that step (2) is arranged, then make in parent the minimum individuality of value is evolution result; Otherwise enter step (5);

(5) individual for each group in parent, carry out following steps: by what calculate substitute into antenna evolution algorithmic with constraint optimal conditions and carry out iteration, obtain the individuality that new size variable is filial generation; Each group of filial generation is combined as new parent, returns step (3) and carries out next round iteration.

The constrained optimization condition of the antenna described in step (1) comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition, wherein,

Gain constraint condition is

Axial ratio constraint condition is

Standing-wave ratio (SWR) constraint condition is $g{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}\left(\stackrel{\→}{x}\right)={\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-1.5\≤0.$

Process in accordance with the present invention obtains one group h=1.6mm, w=50mm, l=50mm, a=23.08mm, b=15.12mm, c=0.95mm, fw=2.53mm, fl=32.58mm, d=1.59mm, this size is utilized to make microband paste WiFi antenna, insulated substrate adopts epoxy resin board, conductor patch adopts tinfoil, the bandwidth of this antenna is more than 1.1GHz (1.75GHz to 2.85GHz), 2 are less than in this band width actual measurement standing-wave ratio (SWR), at center operating frequency 2.4GHz, obtain gain by electromagnetic simulation software Feko and be greater than 1dB, axial ratio is greater than 15dB, obtain gain by HFSS electromagnetic simulation software and be greater than-0.5dB, and most of angle gain is all greater than 0dB, axial ratio is greater than 15dB.

Claims (3)

1. the novel evolution method of an antenna, it is characterized in that comprising the following steps: the scope and the iterations that arrange size in operating frequency of antenna scope, the scope at the position angle of Antenna Operation and the elevation angle, constrained optimization condition, antenna emulated physics model, described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition; Arrange antenna pattern according to operating frequency of antenna scope, set up the emulated physics model of antenna, utilize antenna evolution algorithmic to obtain parent, described parent is the size variable in emulated physics model; Whether the size variable judging in current emulated physics model meets constrained optimization conditioned disjunction reaches maximum iteration time, if then develop end, the size variable in emulated physics model is evolution result; Otherwise utilize the size variable in current emulated physics model to calculate assessed value, and bring assessed value and constraint condition into antenna evolution algorithmic and carry out iteration, obtain the size variable of filial generation, until the size variable in current emulated physics model meets constrained optimization conditioned disjunction reach maximum iteration time.

2. the novel evolution method of antenna according to claim 1, is characterized in that specifically comprising the following steps:

(1) scope and the maximum iteration time of size in operating frequency of antenna scope, the constrained optimization condition of antenna, the scope at the position angle of Antenna Operation and the elevation angle, antenna emulated physics model are set; Described constrained optimization condition comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition;

(2) the emulated physics model of antenna is set up, in described emulated physics model, described antenna comprises flat rectangular body insulated substrate, the upper surface of insulated substrate posts the conductor patch identical with insulated substrate size, described conductor patch central authorities are provided with elliptical aperture, the longer axis parallel of elliptical aperture in the long limit of upper surface, the lower surface horizontally set strip feeder line of insulated substrate, the right-hand member of feeder line is provided with feedback point, and described feedback point is concordant with the right hand edge of insulated substrate lower surface; The height of insulated substrate be h, long for w, wide be l, the elliptical aperture major semi-axis in conductor patch is a, minor semi-axis b, and the thickness of conductor patch is c, and the width of feeder line is fw, length is fl, and feedback dot center is d to the distance of the minor axis of elliptical aperture; Utilize antenna evolution algorithmic to obtain parent, described parent is the individuality comprising h, w, l, a, b, c, fw, fl and d of more than 2 groups; H, w, l, a, b, c, fw, fl and d are size variable; Arrange variable N to indicate iterations, the initial value of N is 0;

(3) individual for the often group in parent, calculate assessed value according to following assessed value computing formula

Wherein, represent assessed value, the vector that is element with h, w, l, a, b, c, fw, fl and d, point in representation space spheric coordinate system, position angle and the elevation angle of space spheric coordinate system is respectively with θ, with the span of θ respectively in the position angle of Antenna Operation that step (1) is arranged and the scope at the elevation angle;

$\mathrm{VSWRVariance}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{({\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-\mathrm{Mean}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)})}^2;$

${\mathrm{MeanVSWR}}_{\left(\mathrm{freq}\right)}=\underset{\mathrm{freq}}{\mathrm{\Σ}}{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}/3;$

the antenna of to be frequency of operation be freq exists the gain at place;

the antenna of to be frequency of operation be freq exists the axial ratio at place;

VSWR _(freq)the standing-wave ratio (SWR) of antenna when frequency of operation is freq;

Within the scope of the operating frequency of antenna that the span of freq is arranged in step (1);

and VSWR _(freq)be and utilize simulation algorithm to emulate the result obtained according to emulated physics model;

Iterations N cumulative 1;

(4) if there is one group of individuality to make the constrained optimization condition of antenna all satisfied in parent, then end of developing, this group individuality is evolution result; If iterations N is greater than the iterations that step (2) is arranged, then make in parent the minimum individuality of value is evolution result; Otherwise enter step (5);

(5) individual for each group in parent, carry out following steps: by what calculate substitute into antenna evolution algorithmic with constraint optimal conditions and carry out iteration, obtain the individuality that new size variable is filial generation; Each group of filial generation is combined as new parent, returns step (3) and carries out next round iteration.

3. the novel evolution method of antenna according to claim 2, is characterized in that: the constrained optimization condition of the antenna described in step (1) comprises gain constraint condition, axial ratio constraint condition and standing-wave ratio (SWR) constraint condition, wherein,

Gain constraint condition is

Axial ratio constraint condition is

Standing-wave ratio (SWR) constraint condition is $g{\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}\left(\stackrel{\→}{x}\right)={\mathrm{VSWR}}_{\left(\mathrm{freq}\right)}-1.5\≤0.$