CN115000685A - Vehicle-mounted PIFA antenna design method based on genetic algorithm and antenna thereof - Google Patents
Vehicle-mounted PIFA antenna design method based on genetic algorithm and antenna thereof Download PDFInfo
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01Q—ANTENNAS, i.e. RADIO AERIALS
- H01Q13/00—Waveguide horns or mouths; Slot antennas; Leaky-waveguide antennas; Equivalent structures causing radiation along the transmission path of a guided wave
- H01Q13/10—Resonant slot antennas
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- H—ELECTRICITY
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- H01Q—ANTENNAS, i.e. RADIO AERIALS
- H01Q5/00—Arrangements for simultaneous operation of antennas on two or more different wavebands, e.g. dual-band or multi-band arrangements
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Abstract
A design method of a vehicle PIFA antenna based on a genetic algorithm and an antenna thereof realize multiband by changing the structure of a radiation unit of the antenna and combining an improved genetic algorithm. Wherein the improvement of the genetic algorithm is embodied in the selection of a coding mode, a population initializing method and fitness; the structure of the radiation unit is easier to represent in a coding mode; the method for initializing the population considers the communication of the designed antenna and can greatly shorten the operation time; the fitness is also a suitable choice for the target result of the antenna. The radiation unit is provided with various grooves, the structure is optimized by combining a genetic algorithm, and multiple frequency bands are realized by a multi-gap method. The working frequency band covers 2.4-2.484GHz and 4.8-5 GHz. The bandwidth of the antenna in two frequency bands is 0.05GHz and 0.4GHz respectively, and the antenna has the advantages of miniaturization, horizontal omnidirectional radiation and convenience for integration with other microwave devices. And the genetic algorithm used by the antenna can be applied to the design of other antennas, and has the characteristics of expandability and optimizability.
Description
Technical Field
The invention belongs to the technical field of 5G and antennas, and particularly relates to a vehicle-mounted PIFA antenna which can be applied to the fields of radio communication, wireless energy transmission and the like.
Background
The high-speed development of new energy automobile for the car is not only simple vehicle, is the product that collects audio-visual, amusement, autopilot in an organic whole moreover, and these intelligent, amusement, the product of house have improved driver and passenger's trip greatly and have experienced, and improved trip safety to a certain extent. The experience of the video entertainment safety can be achieved through the integration of the antennas in different frequency bands, so as to meet the pursuit of people.
Radio services and mobile communications are the main components of the antenna module in automobiles. Automotive antenna modules are increasingly becoming smaller in size, but require constant or improved capabilities for processing and communicating information. Therefore, the requirements for antenna design are increasing day by day, and the miniaturization of the antenna is becoming the direction of antenna development. But the reduction in antenna size tends to result in losses in efficiency and bandwidth. Therefore, it is an urgent technical problem to design a miniaturized and efficient vehicle-mounted antenna applied to the 5G frequency band.
Disclosure of Invention
Aiming at the defects of the prior art, one of the purposes of the invention is to provide a design method of a vehicle-mounted PIFA antenna based on a genetic algorithm. Different from the direct design and optimization of the antenna, the method utilizes the genetic algorithm to design the slotting condition of the antenna radiation unit, utilizes HFSS software to scan and analyze parameters, explores the influence of the size parameters of the slot on the antenna performance, and optimizes the parameters.
The second purpose of the invention is that the vehicle PIFA antenna obtained by the design method has the advantages of miniaturization, low cost and the like, and the working frequency band covers the vehicle WLAN and the 5G communication frequency band covers 2.4-2.484GHz and 4.8-5 GHz. The size of the antenna is small, only 10mm by 15mm by 8 mm.
The technical scheme of the invention is as follows.
A design method of a vehicle-mounted PIFA antenna based on a genetic algorithm comprises the following steps:
And 2, optimizing the antenna structure by using a genetic algorithm, and improving the coding mode, initializing population and calculating fitness:
firstly, the coding mode adopts binary coding, and the gene sequence is represented by a binary character string or a binary number group; different slots are formed on the PIFA antenna for the radiating elements to generate a plurality of working frequency bands, and the structure of the surface of the PIFA serves as a gene on a chromosome in a genetic algorithm. Dividing a surface radiation unit of the PIFA antenna into a plurality of small squares, wherein the value of each small square is '1' or '0'; when the value of the small square is 1, the position is metal, and conversely 0 represents that the position needs to be opened; a two-dimensional array is used for representing the structure of the PIFA antenna radiating unit, namely corresponding to different PIFA antennas;
secondly, two cross-shaped gap structures are adopted in the initialized population, and the specific operation is as follows: first, a set of decimal array (X) with eight digits arranged from small to large is randomly generated 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ) Then two sets of four decimal digit decimal arrays (Y) arranged from small to large are randomly generated 11 ,Y 12 ,Y 13 ,Y 14 ) And (Y) 21 ,Y 22 ,Y 23 ,Y 24 ) That is, the straight line X ═ X 1 X is a straight line 4 Y being a straight line 11 And a straight line Y ═ Y 14 Form a rectangle by enclosing, and then use the straight line X ═ X 2 X is a straight line 3 Line Y ═Y 12 And a straight line Y ═ Y 13 Cutting the rectangle into a cross-shaped structure, wherein the value of a square grid in the internal area of the cross-shaped structure is 0, and the square grid is a gap; for the same reason, the straight line X ═ X 5 X is a straight line 6 X is a straight line 7 Wherein X is X 8 Y being a straight line 21 Y being a straight line 24 Y being a straight line 21 And a straight line Y ═ Y 24 Also enclose into a "ten" font structure, the value of the square in the internal area of "ten" font is "0";
finally, for calculating fitness of each child: because the antenna designed by the invention is dual-frequency, only the reflection coefficient of the antenna, namely S, needs to be considered 11 A value of a parameter; selecting 2.4-2.484GHz and 4.8-5GHz as working frequency bands of the designed vehicle-mounted communication antenna, wherein the adaptability is two frequency bands S 11 Sum of absolute values of the parameters.
A vehicle PIFA antenna based on genetic algorithm comprises a radiation unit, a metal short-circuit sheet, a coaxial feeder line and a ground plane, wherein multiband is realized by adopting a multi-slot method and genetic algorithm optimization, the working frequency band of the antenna covers 2.4-2.484GHz and 4.8-5GHz, and the bandwidths of the two frequency bands are 0.05GHz and 0.4GHz respectively;
the radiation unit, the metal short-circuit sheet and the ground plane are made of the same material and are made of metal copper plates with the thickness of 1 mm;
the size of the PIFA antenna is 10mm multiplied by 15mm multiplied by 8 mm;
the radiation unit is a special-shaped metal plate obtained by genetic algorithm optimization verification, and the size of the outer frame is 10mm multiplied by 15 mm; the size parameters of the slotted gap are as follows: w1 is 5mm, W2 is 1.5mm, W3 is 4.5 mm; l1 is 9.5mm, L2 is 4mm, L3 is 1 mm;
the size of the ground plane is 10mm multiplied by 15 mm;
the size of the metal short circuit board is 2.5mm multiplied by 8 mm;
the position of the coaxial feeder line is as follows: the distance from the long side of the ground plane is 1.9mm, and the distance from the short side of the ground plane is 5 mm;
the SMA connected with the feeder line is D361D25F02-430 model of Nanjing Aoyao literary company.
Compared with the prior art, the invention has the following beneficial effects:
the present invention realizes multiple frequency bands by changing the structure of the radiating element of the antenna in combination with an improved genetic algorithm. Wherein the improvement of the genetic algorithm is embodied in the selection of a coding mode, a population initializing method and fitness; the structure of the radiation unit is more easily represented in a coding mode; the method for initializing the population considers the communication of the designed antenna and can greatly shorten the operation time; the fitness is also suitably selected for the target result of the antenna.
The working frequency band of the vehicle-mounted PIFA antenna based on the genetic algorithm provided by the invention covers 2.4-2.484GHz and 4.8-5 GHz. The bandwidth of the antenna in two frequency bands is 0.05GHz and 0.4GHz respectively, and the antenna has the advantages of miniaturization, horizontal omnidirectional radiation and convenience for integration with other microwave devices. And the genetic algorithm used by the antenna can be applied to the design of other antennas, and has the characteristics of expandability and optimizability.
Drawings
Fig. 1 is a perspective view of a basic PIFA antenna structure;
FIG. 2 is a flow chart of a genetic algorithm;
FIG. 3 is a schematic diagram of the encoding mode of the genetic algorithm of the present invention;
fig. 4 is a schematic diagram of the overall structure of the antenna of the vehicle-mounted PIFA antenna design based on the genetic algorithm of embodiment 1;
fig. 5 shows the antenna radiating element and ground plane structure of the vehicle PIFA antenna design based on genetic algorithm of example 1;
FIG. 6 is a flow chart of the joint simulation of HFSS and Matlab in example 1;
fig. 7 is a simulation result of S parameters before PIFA antenna optimization in embodiment 1;
FIG. 8 is a fitness change map of the genetic algorithm in example 1;
FIG. 9 is the output optimum result (array form) of the genetic algorithm in example 1;
fig. 10 is a simulation result of the optimized S parameter of the PIFA antenna in embodiment 1;
fig. 11 is the radiation characteristic of the PIFA antenna optimized in embodiment 1;
fig. 12 is the current distribution of the PIFA antenna optimized in example 1 at 2.4 GHz;
fig. 13 shows the current distribution of the PIFA antenna optimized in embodiment 1 at 24 GHz;
FIG. 14 shows the parameter L in example 1 1 When the antenna changes from 7.5mm to 11.5mm, the simulation result of the S parameter of the antenna is obtained;
FIG. 15 shows the parameter L in example 1 2 When the distance is changed from 2mm to 4mm, the simulation result of the S parameter of the antenna is obtained;
FIG. 16 shows the parameter L in example 1 3 Taking simulation results of S parameters of the antenna when the S parameters are 0.5mm, 1mm and 1.5 mm;
FIG. 17 shows the parameter W in example 1 1 When the distance is changed from 2.5mm to 7.5mm, the simulation result of the S parameter of the antenna is obtained;
fig. 18 is the measurement result of the S parameter of the practical PIFA antenna in embodiment 2;
reference numerals:
1 radiating element, 2 metal shorting strips, 3 coaxial feed lines and 4 ground planes.
Detailed Description
The technical scheme of the invention is described in detail below with reference to the accompanying drawings.
A design method of a vehicle-mounted PIFA antenna based on a genetic algorithm comprises the following steps:
And 2, improving the genetic algorithm in terms of coding mode, population initialization and fitness calculation.
Genetic algorithms can solve the non-linearity problem and are used to optimize the antenna.
The selection, crossing and variation are used in genetic algorithm to correspond to the selection, crossing and mutation of organisms, and the three genetic operators act on the population P (t) in sequence to obtain a new population P (t + 1). The specific steps for these three genetic operators are as follows;
selecting an operator: according to the set method, according to the calculated fitness of each generation of individuals, selecting a part of individuals with higher fitness from the t generation population P (t), and then transmitting the individuals to the next generation population P (t + 1);
and (3) a crossover operator: firstly, randomly collocating individuals in a population P (t), then exchanging partial chromosomes of the individuals per se for each pair of individuals according to the probability set in advance, wherein the probability set by the individuals is called as cross probability or cross rate;
mutation operator: for each individual in the population P (t), the gene values at certain positions are replaced by alleles with a certain probability, which is called the mutation rate.
As shown in fig. 2, the operation logic of the genetic algorithm is: firstly, carrying out initialization operation to model actual problems; then setting an evolutionary termination condition, and taking M randomly generated individuals as an initial population P (0); then, evaluating the individuals of each generation, wherein the main method is to calculate the fitness value of each individual in the current population P (1); and finally, judging whether the current population P (t) reaches a termination condition or not according to the fitness value of each generation: if the termination condition is reached, stopping circulation, and outputting the individual with the maximum fitness in the contemporary population as an optimal solution; if the termination condition is not met, the genetic operation is carried out on the individuals in the current population P (t), then the next generation population P (t +1) can be obtained, and then the second step and the third step are carried out on the P (t +1) repeatedly until the termination condition is met.
The improvement of the invention in coding mode, initializing population and calculating fitness is as follows:
first, in the encoding method, binary encoding is used, and the gene sequence is represented by a binary string or a binary array. Different slots are formed on the PIFA antenna for the radiating elements to generate a plurality of working frequency bands, and the structure of the surface of the PIFA is used as a gene on a chromosome in a genetic algorithm. The surface radiation element of the PIFA antenna is divided into a plurality of small squares, as shown in fig. 3, each small square having a value of "1" or "0"; when the value of the small square is 1, the position is metal, and conversely 0 represents that the position needs to be opened; a two-dimensional array is used for representing the structure of the radiation unit of the PIFA antenna, namely corresponding to different PIFA antennas.
Second, the initialization population is refined. According to design experience, U-shaped and T-shaped gap structures are usually adopted when the radiation units are grooved, in order to avoid the condition of a suspended structure, a cross-shaped gap structure is adopted when a seed group is initialized, and the U-shaped or T-shaped gap structure can be generated after genetic operation of the cross-shaped gap structure. On the other hand, it can be known from the multi-frequency technology that two slots are generally used to generate a dual-frequency result, so that two cross-shaped slot structures are adopted in the initialization population. Specific operations As shown in FIG. 3, a set of decimal arrays (X) of eight digits arranged from small to large is first randomly generated 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ) Then randomly generating two sets of four-digit decimal arrays (Y) arranged from small to large 11 ,Y 12 ,Y 13 ,Y 14 ) And (Y) 21 ,Y 22 ,Y 23 ,Y 24 ). That is, the straight line X ═ X 1 X is a straight line 4 Y being a straight line 11 And a straight line Y ═ Y 14 Can be enclosed into a rectangle, and then a straight line X is equal to X 2 Wherein X is X 3 Y being a straight line 12 And a straight line Y ═ Y 13 This rectangle is cut into a cross-shaped structure. The value of the square grid in the cross-shaped internal area is 0, namely the gap is formed. By the same token, line X ═ X 5 X is a straight line 6 X is a straight line 7 X is a straight line 8 Y being a straight line 21 Y being a straight line 24 Y being a straight line 21 And a straight line Y ═ Y 24 Or a cross-shaped structure can be enclosed, and the value of the square in the internal area of the cross-shaped structure is also 0. Due to (X) 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ) The double-cross-shaped structure generated by the method can not be crossed, namely, suspended patches can not be generated. The initialized population generated by the method can ensure that the structure of each filial generation is correct, and the iteration times are greatly reduced, thereby reducing the calculation amount and further shortening the calculation time of a computer.
Finally, the optimization method for calculating the fitness of each child is as follows: because the antenna designed by the invention is dual-frequency, only the reflection coefficient of the antenna, namely S, needs to be considered 11 The value of the parameter. The working frequency of the WLAN applied in the invention is mainly as follows: 2.4-2.484GHz, 5.12-5.35GHz and 5.725-5.825GHz, the working frequency of 5G is mainly as follows: 3.3-3.4GHz, 3.400-3.6GHz and 4.8-5 GHz. 2.4-2.484GHz and 4.8-5GHz are selected as working frequency bands of the designed vehicle-mounted communication antenna as an embodiment, so that the adaptability is two frequency bands S 11 Sum of absolute values of the parameters.
A vehicle PIFA antenna based on genetic algorithm comprises a radiation unit, a metal short-circuit sheet, a coaxial feeder line and a ground plane, wherein the slot condition of the antenna radiation unit is designed by utilizing the genetic algorithm, the working frequency band of the antenna covers 2.4-2.484GHz and 4.8-5GHz, and the bandwidths of the two frequency bands are 0.05GHz and 0.4GHz respectively; as shown in fig. 4 and 5, the antenna characteristic parameters are as follows:
the radiation unit, the metal short-circuit sheet and the ground plane are made of the same material and are made of metal copper plates with the thickness of 1 mm;
the size of the PIFA antenna is 10mm multiplied by 15mm multiplied by 8 mm;
the radiation unit is a special-shaped metal plate obtained by genetic algorithm optimization verification, and the size of an outer frame of the radiation unit is 10mm multiplied by 15 mm; the size parameters of the slot on the upper part are as follows: w1 is 5mm, W2 is 1.5mm, W3 is 4.5 mm; l1 is 9.5mm, L2 is 4mm, L3 is 1 mm;
the size of the ground plane is 10mm multiplied by 15 mm;
the size of the metal short circuit board is 2.5mm multiplied by 8 mm;
the position of the coaxial feeder line is as follows: the distance from the long side of the ground plane is 1.9mm, and the distance from the short side of the ground plane is 5 mm;
the SMA connected with the feeder line is D361D25F02-430 model of Nanjing Aoyao literary company.
The invention is described in further detail below with reference to specific embodiments, simulations and drawings.
Example 1
The present embodiment utilizes a method of HFSS and Matlab joint simulation to design a PIFA antenna, which is applied to vehicle-mounted communications, mainly in WLAN and 5G communication modes, and the operating frequency band covers two frequency bands of 2.4-2.484GHz and 4.8-5 GHz. As shown in fig. 6, the HFSS-Matlab-Api script library is called in Matlab to perform modeling and performance simulation of the antenna, and then the shape of the antenna radiating element is optimized by using a modified genetic algorithm. The method comprises the following specific steps:
step S1: the basic PIFA antenna configuration is obtained by modeling. The basic PIFA antenna structure is shown in fig. 1, the materials are all copper, and the medium between the radiating element and the ground plate is air. The size of the radiating element and the ground plane is 10mm multiplied by 15mm, the size of the metal short circuit board is 2.5mm multiplied by 8mm, the distance between the position of the coaxial feeder line and the long side of the ground plane is 1.9mm, and the distance between the position of the coaxial feeder line and the short side of the ground plane is 5 mm. The simulation result of the S parameter before optimization is shown in FIG. 7, which has only one frequency band at 3.62GHz, the bandwidth of 3.5-3.7GHz, and the value of S11 is only-13 dB.
Step S2: and optimizing the basic PIFA antenna structure by combining a genetic algorithm, and realizing multi-frequency by using a multi-slot method.
The joint simulation process of HFSS and Matlab is as follows:
s2.1, coding and establishing an initialization population;
s2.2, evaluating the individual fitness in the group;
s2.3, judging whether the termination condition is met: if the termination condition is met, ending the algorithm and outputting an optimal result; if the termination condition is not met, performing genetic operation according to the fitness to generate new filial generations.
An improved genetic algorithm is operated in Matlab, and offspring is generated through encoding, population initialization, fitness calculation and genetic operation.
In step S2.1, the encoding is in a binary encoding manner. The radiation units of the present embodiment are divided into 0.5mm × 0.5mm small squares for a total of 600. Each filial generation is a binary two-dimensional array of 20 × 30, each digit corresponds to a small grid on the radiation unit, and if the value is "1", the position is metal, otherwise "0" indicates that the position needs to be opened.
In order to avoid errors caused by the fact that the cross-shaped gap and the radiating unit are surrounded by metal to form a suspended patch when a seed group is initialized, the cross-shaped gap is adopted. Randomly generating a set of decimal arrays (X) of eight digits arranged from small to large in the range of 2-29 1 ，X 2 ，X 3 ，X 4 ，X 5 ，X 6 ，X 7 ，X 8 ) Two sets of small to large arranged four digit decimal arrays (Y) are randomly generated in the range of 2-19 11 ，Y 12 ，Y 13 ，Y 14 ) And (Y) 21 ，Y 22 ，Y 23 ，Y 24 ) (ii) a Then the value of the grid in the formed double-cross-shaped internal area is 0; then, the number of the population is set to be 50, and the number of iterations is set to be 20.
In the step 2.2, the fitness is calculated, because the antenna designed by the invention is dual-frequency, only the reflection coefficient of the antenna, namely S, needs to be considered 11 The value of the parameter. The working frequency of the WLAN applied in the invention is mainly as follows: 2.4-2.484GHz, 5.12-5.35GHz and 5.725-5.825GHz, the working frequency of 5G is mainly as follows: 3.3-3.4GHz, 3.400-3.6GHz and 4.8-5 GHz. As shown in the embodiment of the invention, 2.4-2.484GHz and 4.8-5GHz are selected as the working frequency bands of the designed vehicle-mounted communication antenna, so that the adaptability is two frequency bands S 11 Sum of absolute values of the parameters. The specific frequency may be different according to the start frequency, the end frequency and the number of frequency bands set by the simulation.
In the step 2.2, the step of the method,in the process of calculating the fitness, an HFSS-Matlab-Api script library is called in Matlab to automatically open the HFSS, and modeling simulation is carried out in HSS, so as to obtain the accurate S of each frequency band 11 Parameter, finally returning S of each frequency band 11 And the HFSS is automatically turned off as a result, the adaptability of each antenna structure is ensured to be obtained through simulation, and the accuracy of the result is improved. After 60 iterations, the optimized result is obtained.
The process of the above simulation, in which the fitness output by the process is changed, is shown in fig. 8, and it can be seen in the figure that the final output result is convergent, and the final fitness can reach 63.
The optimal result of the simulation output is shown in fig. 9, which is a 20 × 30 binary two-dimensional array reflecting the structure of the antenna radiating element.
The antenna structure for this optimal array of outputs is shown as: fig. 4 is a perspective view of the antenna, and fig. 5 is a structure of the antenna radiation unit and the ground plane. It can be seen that the slot of the last antenna is a rectangular slot connected to a "T" slot.
The simulation result of the optimized S parameter is shown in fig. 10, which shows that the antenna has two frequency bands, and the working frequency points of 2.4GHz and 4.9GHz completely meet the design requirements of the embodiment. The bandwidths of the two frequency bands are 0.05GHz and 0.4GHz respectively. The values of S11 at both frequency points are also lower than-10 dB, reaching-16.5 dB and-18 dB respectively.
And the optimized S parameter meets the design requirement, and then the radiation characteristic of the antenna is analyzed. The E and H plane directional patterns of the antenna at 2.4GHz are shown in FIG. 11 (a); the pattern of the E, H plane at 4.9GHz is shown in FIG. 11 (b); the 3D radiation patterns of the two frequency bands are shown in fig. 11(c) and 11 (D). The gain range of the antenna is shown in fig. 11 as-5 dB to 1.9dB at 2.4GHz and-9.5 dB to 3dB at 4.9GHz, the antenna having a horizontal omnidirectional radiation characteristic.
And then analyzing the parameters of the antenna, and checking the influence of the antenna parameters on the performance of the antenna to verify the accuracy of the genetic algorithm optimization. First, the antenna is dimensioned as shown in fig. 5, and if the influence of the antenna parameters on the antenna size is observed, the antenna must be observedSurface current profile of the wire, L, is seen from the current of the antenna of FIG. 12 operating at 2.4GHz 1 、L 2 And W 1 The current in the vicinity is large, and the three parameters influence the performance of the antenna when the antenna operates at 2.4 GHz. Similarly, L can be seen in FIG. 13 1 、L 2 、L 3 And W 1 These four parameters affect the performance of the antenna when operating at 4.9 GHz. Therefore, mainly explore L 1 、L 2 、L 3 And W 1 The effect of these three parameters on the antenna.
First, explore L 1 Impact on antenna performance. FIG. 14 reflects the parameter L 1 And when the S parameter of the antenna changes, the S parameter of the antenna changes. When L is 1 When the size is larger than or equal to 10.5mm, the rectangular slot exceeds the edge of the antenna, and the antenna only has one frequency band at 4.6 GHz. When L is 1 L is less than or equal to 10.5mm 1 The change of (b) has a greater influence on the radiation frequency of low frequencies, with L 1 The low frequency band may be shifted left. And L is 1 The reflection coefficient is mainly influenced for the high frequency band and is relatively less sensitive than the low frequency band. Comprehensively considering that the performance of the antenna is more in accordance with the requirement L when the value is equal to 9.5mm 1 And the result is matched with the optimization result of the genetic algorithm.
Next, explore L 2 Impact on antenna performance. FIG. 15 reflects the parameter L 2 And when the S parameter of the antenna changes, the S parameter of the antenna changes. When L is 2 When changed, the changes of both frequency bands are not obvious, so L 2 The antenna performance is less affected. After genetic algorithm optimization L 2 Results equal to 4mm are consistent with the sweep.
Then, explore L 3 Impact on antenna performance. FIG. 16 reflects the parameter L 3 And when the S parameter of the antenna changes, the S parameter of the antenna changes. When L is 3 When the frequency band is changed, the change of the low frequency band is insensitive, and the change of the high frequency band is more obvious. But with L 3 The two frequency bands are shifted to the right by increasing the reflection coefficient, and the reflection coefficient is reduced accordingly. Taking into account design requirements, L 3 The performance of the antenna is in accordance with the requirement when the antenna is equal to 1mm or 1.5mm, and the optimization result L of the genetic algorithm is included 3 ＝1.5mm。
Finally, explore W 1 Impact on antenna performance. FIG. 17 reflects the parameter W 1 And when the S parameter of the antenna changes, the S parameter of the antenna changes. When W is 1 Both frequency bands are sensitive to changes when changed. When W 1 When the size is larger than or equal to 7mm, the rectangular groove also exceeds the edge of the antenna, and the antenna only has one frequency band at 4.4 GHz. When W 1 Less than 7mm and follows W 1 The two frequency bands are shifted to the left, and the change of the reflection coefficient is not obvious. Two frequency bands, W, taking into account design requirements 1 The performance of the antenna is most consistent when the antenna is equal to 5mm, and is just the optimization result of the genetic algorithm.
Example 2
The final PIFA antenna obtained by the method of embodiment 1 includes a radiating element, a metal shorting strip, a coaxial feeder and a ground plane, the dimensions of the PIFA antenna are 10mm × 15mm × 8mm, the PIFA antenna is made of copper, and the thickness of the PIFA antenna is 1 mm.
Because the PIFA antenna is a three-dimensional structure, each side needs to be fabricated and then welded together. Drawing the designed PIFA antenna into an Autocad graph, and then entrusting a factory to cut a copper plate, and respectively cutting a radiating element, a grounding plate and a short-circuit piece. The adopted SMA is D361D25F02-430 of Nanjing Aoyao venturi technology company, and the SMA can provide a coaxial probe with the length of 10.92mm and the diameter of 0.64mm, so that the feeding requirement of the designed PIFA is met. Finally, welding the parts together to manufacture the PIFA antenna.
After the antenna is manufactured, the antenna index is measured. The equipment used was a vector network analyzer model KEYSIGHT N5227A, measured in a microwave dark room. Firstly, before measurement, a vector network analyzer needs to be initially calibrated; after calibration, the PIFA antenna is connected to a vector network analyzer, so that the S parameter of the antenna can be directly measured; finally, the measurement results are derived, and after the dead pixel is removed, a graph 18 can be drawn.
Because the antenna is manufactured by adopting a welding process, the radiation unit and the ground plane cannot be ensured to be completely parallel. And the antenna size is too small, and the welding spot can also have great influence on the antenna. The actually measured result and the simulation result of the PIFA antenna come in and go out. The reflection coefficient of the real object is significantly reduced and the frequency bands are also shifted slightly to the left.
Claims (10)
1. A design method of a vehicle-mounted PIFA antenna based on a genetic algorithm comprises the following steps:
step 1, obtaining a basic PIFA antenna structure through modeling; the antenna is of a three-dimensional structure and comprises a radiation unit, a metal short-circuit sheet, a coaxial feeder line and a ground plane; the edge of the radiating element is parallel to the ground plane, the metal short-circuit sheet is connected with the edge of the radiating element and the ground plane, and the coaxial feeder penetrates through the ground plane to feed;
step 2, realizing multi-frequency by changing the structure of the radiation unit of the antenna in the step 1: various grooves are formed in the radiating unit, structure optimization is performed by combining a genetic algorithm, and multiband is realized by a multi-gap method.
2. The design method of the vehicle-mounted PIFA antenna based on the genetic algorithm as claimed in claim 1, wherein the design method comprises the steps of (1); and 2, optimizing the antenna structure by using a genetic algorithm, and improving the coding mode, initializing population and calculating fitness:
firstly, the coding mode adopts binary coding, and the gene sequence is represented by a binary character string or a binary number group; different slots are formed on the PIFA antenna for the radiating unit to generate a plurality of working frequency bands, and the structure of the surface of the PIFA is used as a gene on a chromosome in a genetic algorithm; dividing a surface radiation unit of the PIFA antenna into a plurality of small squares, wherein the value of each small square is '1' or '0'; when the value of the small square is 1, the position is metal, and conversely, 0 represents that the position needs to be opened; a two-dimensional array is used for representing the structure of a PIFA antenna radiating unit, namely corresponding to different PIFA antennas;
secondly, two cross-shaped gap structures are adopted in the initialization population, and the specific operation is as follows: first, a set of decimal array (X) with eight digits arranged from small to large is randomly generated 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ) Then two sets of four decimal digit decimal arrays (Y) arranged from small to large are randomly generated 11 ,Y 12 ,Y 13 ,Y 14 ) And (Y) 21 ,Y 22 ,Y 23 ,Y 24 ) That is, the straight line X ═ X 1 X is a straight line 4 Y being a straight line 11 And a straight line Y ═ Y 14 Form a rectangle by enclosing, and then use the straight line X ═ X 2 X is a straight line 3 Y being a straight line 12 And a straight line Y ═ Y 13 Cutting the rectangle into a cross-shaped structure, wherein the value of a square grid in the internal area of the cross-shaped structure is 0, and the square grid is a gap; for the same reason, the straight line X ═ X 5 X is a straight line 6 X is a straight line 7 X is a straight line 8 Y being a straight line 21 Y being a straight line 24 Y being a straight line 21 And a straight line Y ═ Y 24 Also enclosing a cross-shaped structure, wherein the value of the square in the internal area of the cross-shaped structure is also 0;
finally, for calculating fitness of each child: because the antenna designed by the invention is dual-frequency, only the reflection coefficient of the antenna, namely S, needs to be considered 11 A value of a parameter; selecting 2.4-2.484GHz and 4.8-5GHz as working frequency bands of the designed vehicle-mounted communication antenna, wherein the adaptability is two frequency bands S 11 Sum of absolute values of the parameters.
3. The design method of the vehicle-mounted PIFA antenna based on the genetic algorithm as claimed in claim 1, wherein the design method comprises the steps of (1); the antenna comprises a radiation unit, a metal short-circuit sheet, a coaxial feeder line and a ground plane, and is optimized to realize multiple frequency bands by adopting a multi-slot method and a genetic algorithm, wherein the working frequency band of the antenna covers 2.4-2.484GHz and 4.8-5GHz, and the bandwidths of the two frequency bands are 0.05GHz and 0.4GHz respectively.
4. The design method of the vehicle PIFA antenna based on the genetic algorithm is characterized in that; the radiation unit, the metal short-circuit sheet and the ground plane are made of the same material and are all made of metal copper plates with the thickness of 1 mm.
5. The design method of the vehicle PIFA antenna based on the genetic algorithm is characterized in that; the dimensions of the PIFA antenna are 10mm multiplied by 15mm multiplied by 8 mm.
6. The design method of the vehicle-mounted PIFA antenna based on the genetic algorithm as claimed in claim 1, wherein the design method comprises the steps of (1); the radiation unit is a special-shaped metal plate obtained by genetic algorithm optimization verification, and the size of the outer frame is 10mm multiplied by 15 mm; the size parameters of the slotted gap are as follows: w1 is 5mm, W2 is 1.5mm, W3 is 4.5 mm; l1 was 9.5mm, L2 was 4mm, and L3 was 1 mm.
7. The design method of the vehicle-mounted PIFA antenna based on the genetic algorithm as claimed in claim 1, wherein the design method comprises the steps of (1); the dimensions of the ground plane are 10mm x 15 mm.
8. The design method of the vehicle PIFA antenna based on the genetic algorithm is characterized in that; the size of the metal short circuit board is 2.5mm multiplied by 8 mm.
9. The design method of the vehicle PIFA antenna based on the genetic algorithm is characterized in that; the position of the coaxial feeder line is as follows: the distance from the long side of the ground plane is 1.9mm and the distance from the short side of the ground plane is 5 mm.
10. The design method of the vehicle PIFA antenna based on the genetic algorithm is characterized in that; the SMA connected with the feeder line is D361D25F02-430 model of Nanjing Aoyao literary company.
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| US6714162B1 (en) * | 2002-10-10 | 2004-03-30 | Centurion Wireless Technologies, Inc. | Narrow width dual/tri ISM band PIFA for wireless applications |
| WO2006042562A1 (en) * | 2004-10-23 | 2006-04-27 | Electronics Research Institute | Compact single feed quad band antenna for wireless communication systems |
| CN205811043U (en) * | 2016-07-06 | 2016-12-14 | 吉林医药学院 | A kind of M shape three band Planer printed monopole antenna |
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Application publication date: 20220902 |