Design method of concentric circular ring sparse array circular polarization phased array antenna of random rotation array

Abstract

The invention discloses a design method of a random rotation array concentric circular ring sparse array circular polarization phased array antenna. The design method comprises the following steps: establishing a sparse concentric circular ring array optimization model and parameterizing the sparse concentric circular ring array optimization model; optimizing parameterized parameters through a non-dominated sorting multi-target differential evolution algorithm by using an antenna array overall directional diagram of a sparse concentric circular ring array optimization model and taking requirements of indexes including antenna sidelobe suppression, beam width and antenna unit spacing as targets; randomly rotating the antenna units in the four rotationally symmetrical sub-arrays; and obtaining a segmentation line. According to the invention, a sparse concentric circular ring array arrangement mode, a non-dominated sorting multi-target differential evolution algorithm and random rotation array formation are adopted, and an integrated assembly array is adopted, so that only one type of model required to be manufactured by the whole array is ensured, the number of gaps between the sub-arrays is small, and due to the fact that the sub-arrays are tightly attached to each other and the gaps are very small, the manufacturing efficiency of the array is greatly improved. Therefore, parasitic radiation caused by discontinuity of the gap is weakened, and the performance of the antenna array is improved.

Description

Technical Field

[0001] The present invention relates to a phased array antenna design method, and particularly to a design method for a concentric circular ring sparse array circularly polarized phased array antenna with randomly rotated array formation. Background Art

[0002] Due to the characteristics of the on-orbit platform of the spaceborne communication phased array antenna, such as precious space and tight payload, etc., the array scale, weight, overall power consumption and manufacturing cost of the antenna design are all highly restricted. The mainstream trend of satellite antenna design is to pursue achieving the required index requirements with fewer antenna elements. Currently, the communication method between the spaceborne phased array antenna and ground equipment is mostly the frequency division full-duplex system, that is, the satellite platform has two phased array antennas for receiving and transmitting. Inevitably, the transmitting array antenna will interfere with the receiving array antenna.

[0003] The array formation method of the phased array antenna mostly adopts the regular array formation method, and this array formation method has the following deficiencies:

[0004] (1) In the regular array formation method, the array elements are arranged densely, and the mutual coupling between the array elements is higher, which has an adverse effect on the active standing wave of the array elements. Sometimes, a decoupling structure needs to be added, increasing the design difficulty and manufacturing cost;

[0005] (2) Under the same gain requirement, the regular array formation requires a larger number of array elements, resulting in higher cost and weight;

[0006] (3) For multi-beam phased array antennas, the AOB-like array architecture is adopted, that is, radio frequency chips such as power amplifiers, low-noise amplifiers and amplitude-phase multifunctional chips are all surface-mounted on the PCB board. If the regular arrangement design method is adopted, in order to avoid the appearance of grating lobes, it should be ensured that the transmitting array element spacing dt < (1 - 1 / M) / (1 + sinθ0) * λh = 7.35 mm, and the receiving array element spacing dr < (1 - 1 / N) / (1 + sinθ0) * λh = 5 mm. At this spacing, it is difficult to integrate the devices by surface mounting and it is difficult to layout the circuits;

[0007] (4) When arranging regularly, the heat source distribution is more concentrated and the space is more tense, which increases the difficulty of heat dissipation design and is not conducive to the heat dissipation of the phased array;

[0008] (5) The array surface of the regular array antenna is composed of a large number of small sub-arrays processed separately and spliced together, and there will be gaps at the joints between the sub-arrays. When this array surface structure is applied to a circularly polarized array antenna, gap parasitic radiation may occur at some frequency points within the working frequency band. Since the parasitic radiation is not controlled and diverts a part of the energy that should be normally radiated electromagnetically, the array gain is reduced, and the sidelobe level and axial ratio deteriorate;

[0009] To improve the circular polarization performance of circularly polarized array antennas in large-angle scanning and broadband satellite communication applications, the traditional array arrangement method adopts the sequential rotation technique. By arranging the array elements in a small sub-array according to a certain rule, the axial ratio of the beam can be reduced, and thus the circular polarization performance of the large array antenna composed of several sub-arrays can be effectively improved. However, when the beam is scanned, a high-level sidelobe will appear in the visible area, resulting in the deterioration of the sidelobe level and not meeting the index requirements.

[0010] Based on the above defects of the regular array arrangement, the sparse layout method will be a better choice. However, while solving the above deficiencies, the existing sparse array arrangement schemes will also cause new problems:

[0011] (1) There are more parameters for controlling the arrangement of array elements and more requirements for the sidelobe level. Therefore, the array arrangement design is a multi-variable + multi-objective optimization problem. Solving the multi-variable + multi-objective optimization problem itself is very challenging;

[0012] (2) The sidelobe level of the array deteriorates. Especially when scanned, higher-level sidelobes enter the visible area from the non-visible area, resulting in the sidelobe level not meeting the index requirements;

[0013] (3) The sequential rotation array combination method used in the conventional array cannot be used (and there are also the aforementioned high sidelobe problems). How to reduce the beam axial ratio will become a new problem;

[0014] (4) There are many types of antenna boards, resulting in increased design workload and processing costs. In addition, it also brings inconvenience to material management and product assembly. Summary of the Invention

[0015] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a design method for a circularly polarized phased array antenna with a sparse concentric ring array arranged by random rotation.

[0016] The purpose of the present invention is achieved by the following technical solutions:

[0017] In the first aspect of the present invention, a design method for a circularly polarized phased array antenna with a sparse concentric ring array arranged by random rotation is provided, including the following steps:

[0018] Establish a sparse concentric ring array optimization model and parameterize it; the sparse concentric ring array optimization model includes four rotationally symmetric sub-arrays, each sub-array includes multiple antenna elements, and the parameters for parameterization include the radii of 1 to N circles, the number of antenna elements in 1 to N circles, and the starting angles of 1 to N circles;

[0019] Optimize the overall radiation pattern of the antenna array using the sparse concentric circular array optimization model. Targeting the requirements of indicators including antenna sidelobe suppression, beam width, and antenna element spacing, optimize the parameters of the parameterized model through the non-dominated sorting multi-objective differential evolution algorithm;

[0020] Randomly rotate the antenna elements in four rotationally symmetric sub-arrays, and simulate to confirm that the radiation pattern of the antenna array meets the expectations;

[0021] Obtain the boundary between two of the sub-arrays. Starting from the center of the array surface, divide the array with a polyline so that the polyline passes through the center between the closest sides of adjacent elements on both sides of the boundary and extends to the outer edge of the array surface to obtain the dividing line; Rotate the dividing line 90° around the center and copy it three times.

[0022] Furthermore, establishing the sparse concentric circular array optimization model and parameterizing it includes:

[0023] According to the gain requirement, calculate the required aperture size and the number of antenna elements;

[0024] Use an integer multiple of 4 as the number of antenna elements, and these antenna elements respectively form four rotationally symmetric sub-arrays;

[0025] Select a 90° sector for element position allocation. Determine the number of circles according to the number of antenna elements, and allocate the number of elements in each circle according to the arc length of each circle;

[0026] The elements in each circle are evenly arranged on a 90° arc, and calculate the angular difference between the elements relative to the center of the array surface;

[0027] Assign a starting angle to the starting element of each circle of elements, and the starting angle is greater than 0 and not greater than the angular difference between the elements;

[0028] Rotate the obtained quarter sub-array symmetrically 90° four times around the center of the array surface to obtain the complete antenna array surface, and at this time the position of each element on the array surface is uniquely determined;

[0029] The antenna array is divided into N r circles, then a total of 3N parameters are required to constrain the position of each element in this antenna array surface, which are: the radii of the 1st to Nth circles, namely R1, R2, …, R N , the number of antenna elements in the 1st to Nth circles, namely N1, N2, …, N N , the starting angles of the 1st to Nth circles, namely Complete the parameterization of the element positions in the concentric circular array.

[0030] Furthermore, the overall radiation pattern of the antenna array of the sparse concentric circular array optimization model includes:

[0031] Determine the fluctuation range of the parameters;

[0032] The element pattern is obtained through the simulation of the antenna element;

[0033] Based on the coordinates of the antenna elements in the array and the element pattern, the overall pattern of the synthesized antenna array is calculated:

[0034]

[0035] where EF is the element pattern; N r is the number of turns of the concentric circular array; N m is the number of elements on the n-th turn, and it is an integer multiple of 4 so as to divide the array into 4 rotationally symmetric regions; w n is the vector weighting value of the elements on the n-th turn; k is the wave number, and k = 2π / λ; r n is the radius of the n-th turn circular ring; is the sampling angle in the S1 space, and is the beam pointing angle;

[0036] beta(n,m) is the rotation angle of the m-th element on the n-th turn relative to the x-axis, and the angular difference between each element is equal, and there is where c is a constant, is a variable, c and determine the additional angular rotation amount of the elements on each turn;

[0037] For the array layout design, amplitude and phase weighting are not performed to avoid losses in transmitted EIRP or received G / T. Therefore, for all w n = 1, so there is

[0038]

[0039] Furthermore, aiming at the requirements of indicators including antenna sidelobe suppression, beam width, and antenna element spacing, it includes:

[0040] First, the number of elements on each turn is given, and then, under the conditions of meeting the beam width and being greater than the minimum spacing, the radius r n and are optimized; since different sidelobe level requirements are required when the beam scans to different angles in the indicators, this problem is a multi-objective optimization problem, and it is expressed as follows:

[0041]

[0042]

[0043] St.HPBW s ≥3.5°

[0044] Δd≥Δd s = 9.5 mm

[0045] wherein, is the maximum sidelobe level required at the beam pointing angle, and the is different for the interference avoidance mode and the non-interference avoidance mode; ; is the peak sidelobe level obtained from the pattern of the individual; HPBW s is the required minimum beam width; Δd is the spacing between adjacent array elements; Δd s is the required minimum spacing between adjacent array elements.

[0046] Furthermore, optimizing the parameters of the parameterization by the non-dominated sorting multi-objective differential evolution algorithm includes:

[0047] a. Parameter setting: population size, maximum number of execution generations, crossover constant, number of variables;

[0048] b. Randomly generate an initial population according to the following expression:

[0049]

[0050] c. Randomly select different individuals within the population and repeatedly execute the DE / rand / 1 mutation operation

[0051]

[0052] and obtain the population pop m ; the scaling factor F i,j is not a constant, and for each gene locus mutation, it is a random number between [0,1];

[0053] d. Perform a two-point crossover operation on the population pop m and obtain the population pop c ;

[0054] e. Evaluate the fitness values of the experimental individuals c in the population pop and the target individual x i ;

[0055] f. Combine the populations pop m and pop c and perform non-dominated sorting;

[0056] g. Calculate the crowding degree and sort it in descending order;

[0057] h. Select the first PS individuals as the next generation population and re-perform non-dominated sorting, crowding degree calculation, and sorting in descending order;

[0058] Repeat the above steps c to h until the required number of generations is evolved, and then save the results.

[0059] Further, the calculation of the fitness value includes:

[0060] Calculate the array point corresponding to the parameter and the minimum element spacing D0;

[0061] Calculate the array pattern and the half-power beam width W0 of the main lobe;

[0062] Normalize the pattern, remove the main lobe part, and screen out all unqualified sidelobe point excess values Pi and their total number Np according to the sidelobe requirements;

[0063] The fitness calculation formula is as follows:

[0064]

[0065] D lim and W lim are the minimum element spacing and half-power beam width requirements, a1 and a2 are coefficients greater than 1, and b1 is a coefficient less than 1 and greater than 0, which are selected according to the situation.

[0066] Further, the non-dominated sorting includes:

[0067] Calculate the number of dominated individuals Ni and the number of individuals being dominated Si for each individual in the population; domination means that all indicators of an individual A are not weaker than those of an individual B and there exists an indicator that is better than those of individual B, that is, A dominates B; the indicators include beam width, minimum element spacing, and sidelobe;

[0068] Find all individuals in the population with Ni = 0, store them in the set F1, and assign a unified non-dominated ordinal number Ti to all individuals;

[0069] Subtract 1 from the individuals S1 in the remaining individuals that are dominated by the set F1;

[0070] Repeat the above steps until all individuals are stratified into F1 to FN respectively.

[0071] Further, the crowding degree calculation includes:

[0072] Place each individual in the N-dimensional space according to the N parameters it has;

[0073] Calculate the crowding degree operator Ri, and Ri is the distance between an individual and its nearest individual.

[0074] Further, the descending order arrangement includes:

[0075] All individuals are assigned a non-dominated ordinal number and a crowding degree operator. When two individuals have different non-dominated rankings, the individual with the smaller ranking number is selected. If the non-dominated rankings are the same, the less crowded individual, i.e., the one with a larger Ri, is selected, and they are sorted in this order.

[0076] Further, randomly rotating the antenna elements in the four rotationally symmetric sub-arrays, and simulating to confirm that the antenna array pattern meets the expectations, including:

[0077] Obtain the coordinate positions of the elements in the optimized 1 / 4 sub-array;

[0078] Use electromagnetic simulation software to paste and place the antenna element models at each point in turn and number them;

[0079] Generate a random number array with a length equal to the number of elements in the sub-array, and the range is 0° to 360°;

[0080] Rotate the antenna elements along the unit central axis in turn according to the random angles corresponding to the numbers in the array;

[0081] Then rotate and copy the 1 / 4 sub-array 90° around the array central axis three times to obtain the models of all elements;

[0082] Fill in the gaps between the element models, improve the conditions of materials, boundary conditions, and feed amplitude and phase, simulate the array, and confirm whether the antenna array pattern after rotation at random angles meets the expectations.

[0083] The beneficial effects of the present invention are:

[0084] In an exemplary embodiment of the present invention, a sparse concentric circular array layout is adopted. The spacing between the elements is larger than that of the regular layout. Therefore, the mutual coupling between the elements is reduced, the port active standing wave is lower, and no additional decoupling structure is required;

[0085] The non-dominated sorting multi-objective differential evolution algorithm adopted can optimize multiple optimization target parameters simultaneously, with higher efficiency, and can meet the characteristics of complex index requirements in the field of array calculation;

[0086] Adopting the method of randomly rotating and forming an array breaks the periodicity of the structure, and evenly distributes the energy of the high-level side lobes introduced by the periodicity to other side lobes, avoiding the deterioration of the side lobes caused by energy concentration;

[0087] Adopting an integrated assembly array not only ensures that there is only one type of plate to be manufactured for the entire array, but also makes the number of gaps between the sub-arrays small. Moreover, because the sub-arrays are closely attached to each other and the gaps are also very small, the parasitic radiation caused by the discontinuity at the gaps is weakened, and the performance of the antenna array is improved. Description of the Drawings

[0088] Figure 1Flowchart of the design method for a concentric circular ring sparse array circularly polarized phased array antenna with random rotation array in an exemplary embodiment of the present invention;

[0089] Figure 2 Schematic diagram of the layout of the concentric circular ring array in an exemplary embodiment of the present invention;

[0090] Figure 3 Flowchart of the non - dominated sorting multi - objective differential evolution algorithm in an exemplary embodiment of the present invention;

[0091] Figure 4 Schematic diagram of the array surface segmentation method in an exemplary embodiment of the present invention;

[0092] Figure 5 Schematic diagram of the sequential rotation array in the prior art;

[0093] Figure 6 Schematic diagram of the random rotation array in an exemplary embodiment of the present invention;

[0094] Figure 7 Sequential rotation array scanning pattern in the prior art;

[0095] Figure 8 Random rotation array scanning pattern in an exemplary embodiment of the present invention. Detailed implementation manners

[0096] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0097] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. In addition, terms such as "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0098] In the description of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0099] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0100] See Figure 1 , Figure 1 which shows a flowchart of a design method for a concentric circular ring sparse array circularly polarized phased array antenna with a randomly rotating array in an exemplary embodiment of the present invention, including the following steps:

[0101] Establish an optimization model for the sparse concentric circular ring array and parameterize it; the optimization model for the sparse concentric circular ring array includes four rotationally symmetric sub-arrays, each sub-array includes a plurality of antenna elements, and the parameters for parameterization include the radii of 1 to N circles, the number of antenna elements in 1 to N circles, and the starting angles of 1 to N circles;

[0102] Utilize the overall radiation pattern of the antenna array of the sparse concentric circular ring array optimization model, and optimize the parameterized parameters through a non-dominated sorting multi-objective differential evolution algorithm with the requirements of indicators including antenna sidelobe suppression, beam width, and antenna element spacing as the objectives;

[0103] Randomly rotate the antenna elements in the four rotationally symmetric sub-arrays, and simulate to confirm that the radiation pattern of the antenna array meets the expectations;

[0104] Obtain the boundary between two of the sub-arrays, divide the array with a broken line starting from the center of the array plane, so that the broken line passes through the center of the closest sides between adjacent units on both sides of the boundary and extends to the end of the array plane extension to obtain a dividing line; the dividing line is rotated 90° around the center of the circle and copied three times.

[0105] Specifically, in this exemplary embodiment, compared with the prior art, it has the following differences and advantages:

[0106] (1) The present invention adopts a sparse array method. The principle of the sparse array is to change the radius and rotation angle of each circle of the concentric circles, so that the distribution law of the array elements changes, obtaining better results, with the number of array elements remaining unchanged and the positions changing.

[0107] (1-1) The present invention adopts a sparse concentric circular array arrangement method. The spacing between array elements is larger than that of the regular arrangement method. Therefore, the mutual coupling between elements is reduced, the active standing wave at the ports is lower, and no additional decoupling structure is required.

[0108] (1-2) Under the condition of the same array gain, the number of array elements in the sparse array is less than that in the regular array. It can reduce the processing cost, design difficulty and weight while having good performance.

[0109] (1-3) The sparse arrangement has a larger space reserved for other devices such as intelligent inspection systems and methods for a strong network security protection requirement system under the AOB architecture, such as chips like PA, LNA, and amplitude-phase multifunction, etc. The layout design difficulty and processing technology difficulty are both reduced.

[0110] (1-4) Due to the increase in spacing, both the number and concentration degree of heat sources are reduced, and there is more design space for heat dissipation.

[0111] (2) The non-dominated sorting multi-objective differential evolution algorithm adopted by the present invention:

[0112] (2-1) This optimization algorithm can optimize multiple optimization target parameters simultaneously, with higher efficiency, and can meet the characteristics of complex index requirements in the field of array calculation;

[0113] (2-2) Without prior knowledge, this algorithm will not fall into a local optimal solution, the solution is more accurate, and the problem of layout rigidity is avoided.

[0114] (3) The advantages of the random rotation array arrangement adopted by the present invention are as follows:

[0115] (3-1) Improve the axial ratio and gain degradation during beam scanning;

[0116] (3-2) Compared with the sequential rotation array arrangement, the random rotation array arrangement scheme breaks the periodicity of the structure, and evenly distributes the energy of the high-level side lobes introduced by the periodicity to other side lobes, avoiding the side lobe deterioration caused by energy concentration.

[0117] The fixed-angle rotation array arrangement has a certain pattern, and this pattern will cause the energy in the side lobes to concentrate regularly, making individual side lobes "stand out". The random rotation array arrangement is completely irregular, the energy distribution in the side lobes is uniform, there are no prominent side lobes, which is more conducive to the suppression of side lobes

[0118] (3-3) Compared with the sequential rotation array arrangement, the random rotation array arrangement has a wider application range and can also be used in irregular arrangements such as the concentric circular sparse array in the present invention

[0119] (4) The advantages of the integrated assembly array adopted by the present invention are as follows:

[0120] (4-1) The integrated assembly means that according to the layout characteristics, the array surface is divided into 4 identical rotationally symmetric sub-arrays. Each sub-array is a complete multi-layer PCB antenna array, so the length and number of the slots are greatly reduced, and the influence on the receiving or radiation performance of the antenna is minimized.

[0121] (4-2) It reduces the types of PCB boards required for manufacturing the antenna array, and reduces the costs, time and material management difficulties of design and processing;

[0122] (4-3) The number of sub-arrays of the array surface is smaller, reducing the assembly difficulty and time.

[0123] (4-4) The cutting method of this application not only ensures that there is only one type of board to be manufactured for the entire array, but also makes the number of slots between the sub-arrays small; and because the sub-arrays are closely attached to each other and the slots are also very small, the parasitic radiation caused by the discontinuity at the slots is weakened, improving the performance of the antenna array.

[0124] The following content will elaborate on the specific implementation manners of each step in detail:

[0125] Preferably, in an exemplary embodiment, the establishment of the sparse concentric ring array optimization model and parameterization includes:

[0126] According to the gain requirement, calculate the required aperture size and the number of antenna elements;

[0127] Adopt a number of antenna elements that is a multiple of 4, and these antenna elements respectively form four rotationally symmetric sub-arrays;

[0128] Select a 90° sector for element position allocation. Determine the number of circles according to the number of antenna elements, and allocate the number of elements in each circle according to the arc length of each circle; when allocating, pay attention that the radius difference between adjacent circles is not too small and the number of elements in each circle is not too large, so as to ensure that the elements will not conflict with each other in physical space;

[0129] The elements in each circle are evenly arranged on the 90° arc, and calculate the angular difference between the elements relative to the center of the array surface;

[0130] Allocate a starting angle for the starting element of each circle of elements, and the starting angle is greater than 0 and not greater than the angular difference between the elements;

[0131] Rotate the obtained quarter sub-array around the center of the array surface symmetrically by 90° four times to obtain the complete antenna array surface, and at this time the position of each element on the array surface is uniquely determined;

[0132] The antenna array is divided into N r circles, then a total of 3N parameters are required to constrain the position of each element in the antenna array surface, which are respectively: the radii of the 1st to Nth circles, i.e., R 1, R2, …R N The number of antenna elements in 1 to N circles, i.e., N 1, N 2, …N N , the starting angle of 1 to N circles is The parameterization of the element positions in the concentric circular array is completed.

[0133] More preferably, in an exemplary embodiment, the overall antenna pattern of the sparse concentric circular array optimization model includes:

[0134] Determine the fluctuation range of the parameters;

[0135] Obtain the element pattern through simulation of the antenna elements;

[0136] Calculate the synthesized overall antenna pattern through the antenna element coordinates and element patterns in the array, as Figure 2 shown:

[0137]

[0138] where EF is the element pattern; N r The number of circles of the concentric circular array; N m is the number of elements on the nth circle and is an integer multiple of 4 to divide the array into 4 rotationally symmetric regions; w n is the vector weighting value of the elements on the nth circle; k is the wave number and k = 2π / λ; r n is the radius of the nth circle; is the sampling angle in the S1 space, and is the beam pointing angle;

[0139] beta(n,m) is the rotation angle of the mth element on the nth circle relative to the x-axis, and the angle difference between each element is equal, and there is where c is a constant, is a variable, c and determine the additional angular rotation amount of the elements on each circle;

[0140] For the array layout design, no amplitude and phase weighting are performed to avoid losses in transmitted EIRP or received G / T. Therefore, for all w n = 1, so there is

[0141]

[0142] More preferably, in an exemplary embodiment, the target is the requirements of indicators including antenna sidelobe suppression, beam width, and antenna element spacing, including:

[0143] According to the theoretical analysis results and design experience of the circular array, first determine the number of array elements in each circle, and then optimize the radius r under the conditions of meeting the beam width and being greater than the minimum spacing. n and are optimized; since the requirements for the sidelobe level are different when the beam scans to different angles in the specifications, this problem is a multi-objective optimization problem, and is described as follows:

[0144]

[0145] St.HPBW s ≥3.5°

[0146] Δd≥Δd s =9.5mm

[0147] wherein, is the maximum sidelobe level required when the beam pointing angle is , and the is different for the interference avoidance mode and the non-interference avoidance mode; is the peak sidelobe level calculated from the radiation pattern of the individual; HPBW s is the required minimum beam width; Δd is the spacing between adjacent array elements; Δd s is the required minimum spacing between adjacent array elements.

[0148] As mentioned above, the sparse array design of this concentric circular array is a multi-objective optimization problem. It is proposed to use the non-dominated sorting multi-objective differential evolution algorithm to optimize the above problem. More preferably, in an exemplary embodiment, the parameters of the parameterization are optimized by the non-dominated sorting multi-objective differential evolution algorithm, including, as Figure 3 shown:

[0149] a. Parameter setting: population size, maximum number of execution generations, crossover constant, number of variables. The parameters affecting the array radiation pattern are the number of circles N r , the number of elements in each circle N m , the radius of each circle, the starting rotation angle of each circle and the excitation amplitude and phase values;

[0150] b. Randomly generate the initial population according to the following expression:

[0151]

[0152] c. Randomly select different individuals within the population and repeatedly execute the DE / rand / 1 mutation operation

[0153]

[0154] and obtain the population pop m; Scaling factor F i,j is not a constant and is a random number between [0, 1] for each genetic locus variation;

[0155] d. Perform two-point crossover operation on the population pop m and obtain the population pop c ;

[0156] e. Evaluate the fitness values of the experimental individuals c in the population pop and the target individual x i ;

[0157] f. Merge the population pop m and pop c and perform non-dominated sorting;

[0158] g. Calculate the crowding degree and sort in descending order;

[0159] h. Select the first PS individuals as the next generation population and re-perform non-dominated sorting, crowding degree calculation, and sorting in descending order;

[0160] Repeat the above steps c to h until the required number of generations is evolved, and then save the results.

[0161] Specifically, in this exemplary embodiment, the goal of optimizing the array is some or all of its parameters. An array composed of a set of target parameters is an individual, and a collection of many individuals is a population. The formation of an individual in the initial population is random. Each target parameter will be set with an optimization range, and parameter values are randomly generated within this range to form an initial individual. And repeat this step to form the entire population.

[0162] More preferably, in an exemplary embodiment, the calculation of the fitness value includes:

[0163] Calculate the array point corresponding to the parameter and the minimum unit spacing D0;

[0164] Calculate the array pattern and the main lobe half-power beam width W0;

[0165] Normalize the pattern, remove the main lobe part, and screen out all unqualified sidelobe point excess values Pi and their total number Np according to the sidelobe requirements;

[0166] The fitness calculation formula is as follows:

[0167]

[0168] D lim and W limFor the requirements of the minimum unit spacing and the half-power beamwidth, a1 and a2 are coefficients greater than 1, and b1 is a coefficient less than 1 and greater than 0, which are selected according to the situation.

[0169] Specifically, in this exemplary embodiment, in order to reduce the solution time of the 3D pattern of the planar array involved in the fitness calculation, the pattern of the concentric circular array is quickly solved and calculated based on the developed chirp-z transform algorithm, and the time used for algorithm optimization is lower.

[0170] More preferably, in an exemplary embodiment, the non-dominated sorting includes:

[0171] Calculate the number of dominated individuals Ni and the number of individuals being dominated Si for each individual in the population; the domination means that all indicators of an individual A are not weaker than those of an individual B and there is a certain indicator that is better than those of individual B, that is, A dominates B; the indicators include beamwidth, minimum unit spacing, and sidelobe.

[0172] Find all individuals in the population with Ni = 0, store them in the set F1, and assign a unified non-dominated ordinal number Ti to all individuals.

[0173] Subtract 1 from the individuals S1 in the remaining individuals that are dominated by the set F1.

[0174] Repeat the above steps until all individuals are respectively stratified into F1 to FN.

[0175] More preferably, in an exemplary embodiment, the crowding degree calculation includes:

[0176] Place each individual in the N-dimensional space according to the N parameters it has.

[0177] Calculate the crowding degree operator Ri, where Ri is the distance between an individual and its nearest individual.

[0178] More preferably, in an exemplary embodiment, the descending order arrangement includes:

[0179] All individuals obtain the non-dominated ordinal number and the crowding degree operator. When the non-dominated sorting of two individuals is different, select the individual with a smaller sorting number. If the non-dominated sorting is the same, select the less crowded individual, that is, the individual with a larger Ri, and sort them in this order.

[0180] More preferably, in an exemplary embodiment, the random rotation of the antenna elements in the four rotationally symmetric sub-arrays and the simulation to confirm that the antenna array pattern meets the expectations include:

[0181] Obtain the coordinate positions of the array elements in the optimized 1 / 4 sub-array.

[0182] Use electromagnetic simulation software to paste and place the antenna element models at each point in turn and number them.

[0183] Generate a random number array with a length equal to the number of elements in the sub-array, ranging from 0° to 360°;

[0184] Rotate the antenna elements along the unit central axis in sequence according to the random angles corresponding to their numbers in the array;

[0185] Then rotate and copy the 1 / 4 sub-array 90° around the central axis of the array three times to obtain the models of all elements;

[0186] Fill in the gaps between the unit models, improve the conditions of materials, boundary conditions, and the amplitude and phase of the feed source, and simulate the array to confirm whether the radiation pattern of the antenna array rotated at random angles meets the expectations.

[0187] Specifically, in this exemplary embodiment, to avoid the parasitic radiation problem caused by the discontinuity of the array surface, according to the layout characteristics, the array surface is divided into Figure 4 4 identical rotationally symmetric sub-arrays. Each sub-array is a complete multi-layer PCB antenna array, so the length and number of the gaps are significantly reduced, and the influence on the receiving or radiation performance of the antenna is minimized.

[0188] The dividing line is made of a continuous broken line. On both sides of the broken line are the elements of two 1 / 4 sub-arrays that are rotationally symmetric. The line segment starts from the center of the array surface and connects the centers between the closest sides of adjacent elements on both sides of the boundary in sequence, and extends to the end of the array surface extension. Since the array surface dividing line has the same central symmetry characteristic as the 1 / 4 sub-array, the method of first drawing the 1 / 4 dividing line and then rotating it symmetrically is also used to reduce the operation amount.

[0189] In addition, it should be noted that, in order to improve the circular polarization performance of the circular polarization array antenna in wide-angle scanning and broadband satellite communication applications, the traditional method uses Figure 5 the sequential rotation technique shown (the left is the overall view and the right is the partial view). By arranging the elements in the small sub-array in a certain regular order to reduce the axial ratio of the beam, the circular polarization performance of the large array antenna composed of several sub-arrays can be effectively improved. However, this method will cause the sidelobe level of the array to deteriorate. Especially when scanning, there are sidelobes with higher levels entering the visible area from the non-visible area, resulting in the sidelobe level not meeting the index requirements.

[0190] Based on the problems existing in the regular rotation array formation and the non-regular array formation in this scheme, a method based on random rotation array formation is proposed, Figure 6 as shown.

[0191] Applying the random rotation array formation method improves the axial ratio and gain drop during beam scanning and avoids the prominent sidelobes caused by energy concentration. Figure 7 and Figure 8The gain pattern during normal and large-angle scanning of the sequential rotation array and the random rotation array, respectively. As Figure 7 and Figure 8 As can be seen from the comparison, there is no abnormally prominent sidelobe in the random rotation array pattern ( Figure 8 ) caused by the excessive concentration of energy at the position marked by the circle in Figure 7 . The reason why the random rotation array scheme does not have the above problem is that it breaks the periodicity introduced by the sequential rotation array and distributes the energy of the high-level sidelobes introduced by the periodicity to other sidelobes, thereby suppressing the appearance of high levels. For other sidelobes, the increase in level is very small.

[0192] Obviously, the above embodiments are only examples given for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation manners here. And the obvious changes or modifications derived therefrom are still within the protection scope of the present invention.

Claims

1. A design method for a randomly rotated concentric ring sparsely distributed circularly polarized phased array antenna, characterized in that: The following steps are involved: Establish a sparse concentric ring array optimization model and perform parameterization; The sparse concentric circular array optimization model includes four rotationally symmetric subarrays, each subarray includes multiple antenna units, and the parameterized parameters include the radius of 1 to N circles, the number of antenna units in 1 to N circles, and the starting angle of 1 to N circles; Using the overall antenna array pattern of the sparse concentric ring array optimization model, taking the requirements of indicators including antenna sidelobe suppression, beam width, and antenna unit spacing as the target, the parameterized parameters are optimized through a non-dominated sorting multi-objective differential evolution algorithm; The antenna elements in the four rotationally symmetric subarrays were randomly rotated, and the simulation confirmed that the antenna array pattern was as expected; The boundary between two sub-arrays is obtained, and the array is divided with a broken line as the starting point at the center of the array circle, so that the broken line passes through the center of the closest edges of adjacent units on both sides of the boundary and extends to the end of the array extension to obtain a dividing line; the dividing line is rotated 90° around the center of the circle and replicated three times.

2. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 1 is characterized in that: The method of establishing a sparse concentric ring array optimization model and parameterizing it includes: Calculate the required aperture size and number of antenna units based on gain requirements; The number of antenna units is an integer multiple of 4, and these antenna units respectively form four rotationally symmetric sub-arrays; Select the 90° sector to allocate array element positions, determine the number of circles according to the number of antenna elements, and allocate the number of elements per circle according to the arc length of each circle; The array elements in each circle are evenly arranged on a 90° arc, and the angle difference between the array elements relative to the center of the array surface is calculated; Assigning a starting angle to the starting array element of each circle of array elements, wherein the starting angle is greater than 0 and not greater than the angle difference between the array elements; After rotating the obtained quarter sub-array 90° around the center of the array and the surface four times, the complete antenna array is obtained. At this time, the position of each array element on the array surface is uniquely determined; The antenna array is divided into N r circles, a total of 3N parameters are required to constrain the position of each element in the antenna array, which are: the radius of 1 to N circles, i.e. R 1, R 2, …R N , the number of antenna units in 1 to N circles is N 1, N 2, …N N , the starting angle of 1 to N circles is Complete the parameterization of the array element positions in the concentric ring array.

3. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 2 is characterized by: The overall antenna array pattern of the sparse concentric ring array optimization model includes: Determine the fluctuation range of the parameters; The unit radiation pattern is obtained by simulating the antenna unit; The overall radiation pattern of the synthesized antenna array is calculated by using the coordinates and radiation patterns of the antenna units in the array: Where EF is the array element pattern; N r The number of concentric ring arrays; N m is the number of array elements on the nth circle and is an integer multiple of 4 so as to divide the array into four rotationally symmetric regions; w n is the vector weight value of the nth circle array element; k is the wave number, and k = 2π / λ; r n is the radius of the nth circle; is the sampling angle in S1 space, and is the beam pointing angle; beta(n,m) is the rotation angle of the mth unit on the nth circle relative to the x-axis. The angle difference between each unit is equal, and there is Where c is a constant, For variables, c and Determines the additional angular rotation of the unit on each circle; For the array layout design, no amplitude and phase weighting is applied to avoid loss of transmit EIRP or receive G / T. Therefore, for all w n =1, so we have 4. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 3 is characterized by: The above targets include antenna sidelobe suppression, beam width, antenna unit spacing and other indicators, including: First, the number of array elements on each circle is given, and then the radius r is set while satisfying the beam width and being greater than the minimum spacing. n and Optimize; Since the index requires different requirements for the sidelobe level when the beam is scanned to different angles, this problem is a multi-objective optimization problem and is expressed as follows: in, is the beam pointing angle The maximum sidelobe level required when the interference avoidance mode and non-interference avoidance mode There is a difference; Peak sidelobe level calculated for an individual pattern; HPBW s is the required minimum beam width; Δd is the spacing between adjacent array elements; Δd s is the minimum required spacing between adjacent elements.

5. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 4 is characterized by: The multi-objective differential evolution algorithm for non-dominated sorting optimizes the parameterized parameters, including: a. Parameter settings: population size, maximum execution number of generations, crossover constant, number of variables; b. Randomly generate the initial population according to the following expression: c. Randomly select different individuals in the population and repeat the DE / rand / 1 mutation operation And get the population pop m ; Scaling factor F i,j It is not a constant. For each gene point variation, it is a random number between [0,1]. d. Population m Perform a two-point crossover operation and obtain the population pop c ; e. Evaluate population pop c The experimental individuals and the target individual x i The fitness value of f. Pop the population m and pop c Merge and perform non-dominated sorting; g. Calculate the congestion and sort in descending order; h. Select the first PS individuals as the next generation population, and re-perform non-dominated sorting, crowding calculation and descending order; Repeat steps c to h above until the required number of generations is reached, and then save the results.

6. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 5 is characterized by: The calculation of the fitness value includes: Calculate the array point corresponding to the parameter and the minimum distance D0 between the units; Calculate the array pattern and main lobe half-power beam width W0; Normalize the directional pattern, remove the main lobe part, and screen out all unqualified side lobe points with exceeding standard values ​​Pi and their total number Np according to the side lobe requirements; The fitness calculation formula is as follows: D lim With W lim It is the minimum unit spacing and half-power bandwidth requirement. a1 and a2 are coefficients greater than 1, and b1 is a coefficient less than 1 and greater than 0. It is selected according to the situation.

7. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 5 is characterized by: The non-dominated sorting includes: For each individual in the population, calculate the number of dominated individuals Ni and the number of dominated individuals Si; the domination means that all indicators of an individual A are not weaker than those of an individual B and there is an indicator that is better than that of individual B, that is, A dominates B; the indicators include bandwidth, minimum unit spacing and side lobes; Find all individuals in the population whose Ni is 0, store them in set F1, and assign a uniform non-dominated ordinal number Ti to all individuals; Subtract 1 from the remaining individuals S1 that are dominated by the set F1; Repeat the above steps until all individuals are stratified into values ​​F1 to FN.

8. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 7 is characterized in that: The congestion calculation includes: According to the N parameters of each individual, place it in N-dimensional space; Calculate the crowding operator Ri, where Ri is the distance between an individual and its nearest individual.

9. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 8, characterized in that: The descending order includes: All individuals are given a non-dominated ordinal number and a crowding operator. When two individuals have different non-dominated rankings, the one with the smaller ranking number is taken. If the non-dominated rankings are the same, the less crowded individual, i.e. the one with a larger Ri, is taken, and the order is ranked in this order.

10. The design method of the randomly rotated concentric ring sparse array circularly polarized phased array antenna according to claim 1, characterized in that: The antenna elements in the four rotationally symmetric sub-arrays are randomly rotated, and the simulation confirms that the antenna array pattern meets expectations, including: Obtain the coordinate position of the array element in the optimized 1 / 4 sub-array; Use electromagnetic simulation software to paste the antenna unit model on each point in turn and number them; Generate a random number array with a length equal to the number of units in the subarray, ranging from 0° to 360°; Rotate the antenna units along the unit center axis in sequence according to the random angles corresponding to the numbers in the array; Then the 1 / 4 subarray is rotated 90° around the array center axis and replicated three times to obtain the model of all units; Complete the gaps between unit models, improve the conditions of materials, boundary conditions, and feed amplitude and phase, simulate the array, and confirm whether the antenna array radiation pattern after rotating at a random angle meets expectations.

Images