Ultra-wideband common-caliber heterogeneous arraying and beamforming optimization method

Abstract

The invention discloses an ultra-wideband common-caliber heterogeneous arraying and beamforming optimization method, which adopts an array caliber sharing technology, adopts a 1-16GHz full-band pull-through design on an array element frequency band, and is planned to be recommended to be divided into two groups of arrays on an arraying interval group, so that full-band fuzziness can be avoided, and the high-gain requirement of an X-band and a higher frequency band can be met; therefore, the number of channels is comprehensively reduced, and the layout requirements of multiple functions, integration, compactness, light weight, low side lobe and high efficiency are met. According to the common-caliber array layout optimization method based on the hummingbird algorithm, the number of sub-arrays, the scale of the sub-arrays, the position of the sub-arrays and the feed phase are used as optimization variables to meet the low-sidelobe constraint condition of a wide-band wide-angle scanning large-scale array, and an algorithm schematic diagram and an algorithm overall block diagram are given. And the S wave band is optimized by using the algorithm, and the indexes that the scanning angle is + / -45 degrees and the main-to-auxiliary ratio in the S wave band is greater than or equal to 30dB are completed.

Description

Technical Field

[0001] The present invention relates to the field of large-scale phased array radars, and particularly to an ultra-wideband co-aperture heterogeneous array arrangement and beamforming optimization method. Background Art

[0002] Ultra-wideband is an inevitable requirement for airborne multi-functional integrated electromagnetic spectrum warfare equipment to adapt to complex electromagnetic environments. Electronic warfare functions such as reconnaissance and interference necessarily require electronic information systems to have ultra-wideband characteristics. Airborne electromagnetic spectrum warfare mainly focuses on electronic warfare functions, and also takes into account functions such as detection and communication. To adapt to the characteristics of dynamic, variable, dense, and complex electromagnetic spectrum space in future air battlefields, airborne multi-functional integrated electromagnetic spectrum warfare equipment needs to meet ultra-wideband requirements.

[0003] The high-density integration of multi-functional wideband active RF arrays has important military significance.

[0004] The application of multi-functional highly integrated wideband active RF array technology, in terms of platform adaptability, can adapt to various types of airborne combat platforms through flexible reconfiguration, and in terms of combat use, the force allocation is simple, significantly enhancing the platform adaptability of airborne electromagnetic spectrum warfare equipment; in terms of maintainability, the multi-functional highly integrated wideband active RF array is convenient to maintain, can shorten the troubleshooting time, simplify logistics support, and the maintenance has convenience and durability. "Warfare is about logistics and support", and the generalization and standardization of spare parts are beneficial to war reserves, with important economic and military value; in terms of upgradability, the multi-functional highly integrated wideband active RF array is flexible to upgrade, the array structure has the ability to be spliced and expanded, and through the software definition and reconfiguration of the backend signal processing capabilities, the performance of airborne electromagnetic spectrum warfare equipment can be quickly upgraded to quickly and effectively respond to the rapid development and changes of new targets, new threats, and requirements, subverting the existing "threat-based" equipment generation mode and enhancing the rapid response ability of the equipment generation mode. Therefore, the multi-functional highly integrated wideband active RF array is the core technology that drives the leapfrog development of the comprehensive support capabilities of future airborne electromagnetic spectrum warfare equipment in our army, such as streamlining the spectrum, facilitating maintenance, and flexible upgrading. Summary of the Invention

[0005] The purpose of the present invention is to propose an ultra-wideband co-aperture heterogeneous array arrangement and beamforming optimization method.

[0006] The technical solution to achieve the purpose of the present invention is: an ultra-wideband co-aperture heterogeneous array arrangement and beamforming optimization method, including:

[0007] In the first step, estimate the array aperture according to requirements;

[0008] The second step is array layout design: the array element frequency band is divided into 1-16 GHz full-band pull-through design, and the array spacing is divided into two groups of arrays, namely array A and array B. Array A is a 3 GHz half-wavelength array, and array B is a 16 GHz half-wavelength array.

[0009] The third step is to introduce the spatial mapping optimization method. A coarse model is used for calculation during the optimization process. The coarse model adopts the common-aperture array layout optimization method based on the hummingbird algorithm. After the coarse model optimization meets the design goals, a fine model is used for verification.

[0010] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the processor executes the program.

[0011] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0012] A computer program product comprises a computer program, which implements the steps of the above method when executed by a processor.

[0013] Compared with the prior art, the present invention has the following significant advantages: (1) a 16-fold ultra-wideband common-aperture heterogeneous array antenna with an operating frequency band of 1 GHz to 16 GHz is designed and optimized; (2) for this array antenna, full-band wide-angle scanning, grating lobe suppression and low sidelobe optimization are achieved by using an optimization algorithm; (3) the number of units is greatly reduced, cost is saved, weight is reduced, and the complexity of the problem during optimization is reduced.

[0014] The present invention is further described in detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is the overall layout of the antenna array in the present invention.

[0016] Figure 2 It is a schematic diagram of the ultra-wideband array layout, grating lobe suppression and side lobe optimization process in the present invention.

[0017] Figure 3 It is a schematic diagram of extracting active directional patterns of array elements at different positions in the present invention.

[0018] Figure 4 It is the framework diagram of the hummingbird algorithm in the present invention.

[0019] Figure 5 It is a schematic diagram of the algorithm in the present invention.

[0020] Figure 6It is a comparison chart of the 2GHz sidelobe optimization results in the present invention, where (a), (b), (c), and (d) respectively represent the comparison charts of the low sidelobe results of the full array pattern at the elevation pointing angles of 0°, 15°, 30°, and 45°.

[0021] Figure 7 It is the 2GHz array low sidelobe optimization result and the array gain in the present invention.

[0022] Figure 8 It is a comparison chart of the 3GHz sidelobe optimization results in the present invention, where (a), (b), (c), and (d) respectively represent the comparison charts of the low sidelobe results of the full array pattern at the elevation pointing angles of 0°, 15°, 30°, and 45°.

[0023] Figure 9 It is the 3GHz array low sidelobe optimization result in the present invention.

[0024] Figure 10 It is a comparison chart of the 4GHz sidelobe optimization results in the present invention, where (a), (b), (c), and (d) respectively represent the comparison charts of the low sidelobe results of the full array pattern at the elevation pointing angles of 0°, 15°, 30°, and 45°.

[0025] Figure 11 It is the 4GHz array low sidelobe optimization result in the present invention.

[0026] Figure 12 It is the 6GHz array pattern scanning result in the present invention.

[0027] Figure 13 It is the 8GHz array pattern scanning result in the present invention.

[0028] Figure 14 It is the 12GHz array pattern scanning result in the present invention.

[0029] Figure 15 It is the 16GHz array pattern scanning result in the present invention. Detailed implementation manners

[0030] The present invention proposes an ultra-wideband co-aperture heterogeneous array arrangement and beamforming optimization method, which adopts the array aperture sharing technology (heterogeneous multiplexing nested array). In the element frequency band, a full-band design from 1 to 16 GHz is planned to be adopted. In the arrangement spacing grouping, it is recommended to divide into 2 groups of arrays, which can avoid full-band ambiguity and meet the high-gain requirements in the X-band and higher frequency bands, thus comprehensively reducing the number of channels and being more in line with the layout requirements of multi-function, integration, compactness, light weight, low sidelobe, and high efficiency; a co-aperture array layout optimization method based on the hummingbird algorithm, with the number of sub-arrays, sub-array scale, sub-array position, and feeding phase as optimization variables, to meet the low-sidelobe constraint conditions of a wide-bandwidth wide-angle scanning large-scale array, and gives the algorithm schematic diagram and the overall algorithm block diagram. And this algorithm is used to optimize the S-band, and the scanning angle of ±45° and the main-to-side ratio greater than or equal to 30 dB in the S-band are completed. This method can optimize the sidelobe of a 16-fold frequency ultra-wideband array while significantly reducing the number of array elements, saving costs, reducing weight, and reducing the complexity of element amplitude and phase optimization, which is of great significance for large-scale array design.

[0031] An ultra-wideband co-aperture heterogeneous array arrangement and beamforming optimization method, the steps are as follows:

[0032] The first step: Estimate the array aperture according to actual requirements. For an ultra-wideband wide-angle scanning array, first of all, it should be noted that there are no grating lobes in the beam during high-frequency scanning, and this problem can be solved by constraining the element spacing d:

[0033]

[0034] Among them, λ n is the wavelength corresponding to the high frequency, and θ0 is the maximum scanning angle. When the element spacing d is determined within the working frequency band, the array aperture area is estimated by the array gain G constraint, so as to determine the specific layout and the number of array elements of the array. If the array meets the gain condition when working at low frequency, it also meets the condition at high frequency. Therefore, the aperture area S of the array can be estimated at low frequency:

[0035]

[0036] Among them, λ L is the wavelength corresponding to the low frequency, and η is the aperture efficiency. It is required that the array gain G is greater than 20 dB, and the aperture area S can be calculated to obtain the element layout.

[0037] Step 2: Array layout design. In order to meet the requirements of ultra-wideband, lightweight, low sidelobe and high efficiency, it is necessary to achieve wide-angle scanning within the ultra-wide frequency band (1~16GHz) without ambiguity, and the array scale should not be too large. Therefore, it is necessary to design several groups of arrays working in different frequency bands / spacings. Too many or too few groups will lead to an increase in the number of array channels. The number of groups should be moderate. Considering the requirements of integrated and compact layout, array aperture sharing technology (heterogeneous multiplexing nested array) can be used. In terms of array element frequency band, it is planned to adopt a 1~16GHz full-band pull-through design. In terms of array spacing grouping, it is recommended to divide the array into two groups, namely array A (3GHz half-wavelength array) and array B (16GHz half-wavelength array). The array layout is as follows Figure 1 shown.

[0038] Step 3: Introduce the spatial mapping optimization method, consider the impact of mutual coupling between multi-frequency co-aperture array elements on array performance, and realize the layout design, grating lobe suppression and low sidelobe optimization of wide ultra-wideband high-density integrated co-aperture array. The method of this study includes two models of low ("coarse") precision and high ("fine") precision. The coarse model is used for calculation in the optimization process. The coarse model directly adopts the above-mentioned co-aperture array layout optimization method and technical ideas based on the hummingbird algorithm. After the coarse model optimization meets the design goals, the fine model is used for verification. The algorithm flow is as follows: Figure 2 shown.

[0039] Specifically include:

[0040] (1) Coarse model: An active pattern extraction mechanism is established for co-aperture elements at different positions, which are divided into edge units, adjacent units, and middle units. A certain number of elements around adjacent units are selected to extract the active pattern of elements at different positions, such as Figure 3 As shown in the figure, the array element selection mechanism is based on the active pattern change error within an acceptable range. Compared with directly extracting array factors from the entire array, it effectively improves the calculation accuracy of the coarse model and strengthens the mapping relationship between the coarse and fine models. The coarse model is optimized in combination with the Hummingbird algorithm.

[0041] (2) With the constraint of meeting the expected requirements of active standing wave ratio and radiation pattern at different scanning angles, the hummingbird algorithm is used to optimize the active standing wave ratio of the wide-angle scanning array, so as to achieve the optimal excitation amplitude of the array antenna for real-time dynamic reconstruction of the active standing wave ratio and radiation pattern of antennas with different directional directions. The coarse model adopts the common-aperture array layout optimization method based on the hummingbird algorithm. After the coarse model optimization meets the design goals, the fine model is used for verification. An efficient and accurate full-wave analysis method is designed to realize the rapid extraction of electromagnetic characteristic parameters of array antennas, effectively saving platform space, reducing the overall cost of the system, and avoiding electromagnetic compatibility problems between multiple antennas. is the expression of active S parameter, where a kThe complex number represented by the amplitude and phase of the k-th source, α p The complex number represented by the amplitude and phase of the p-th source, S pk is the passive S-parameter. From this equation, the passive S-parameter calculated by the full-wave simulation software can be used to calculate the active S-parameter through calculation, and then through calculating the active voltage standing wave ratio, where mag(ActiveS 11 ) represents the modulus (amplitude) of the active reflection coefficient ActiveS 11 .

[0042] Combined with the hummingbird algorithm, set the target value, and introduce the following piecewise-defined constraint function:

[0043]

[0044] Among them, represents the pattern model of the common aperture array at different scan angles, and u(·) is the unit step function, which is used to control the calculation area of the constraint function, used to limit the sidelobe region and beam pointing of the reconstructed pattern; is used to constrain the minimum value of the pattern in the main lobe region, that is, to limit the main lobe width of the pattern, represents the side error in the direction , represents the side error in the main direction. For the sidelobe constraint function (3), that is, the above formula (3), when the sidelobe level of the reconstructed pattern is greater than the -30dB constraint level, the error is recorded in the form of the difference between the two; otherwise, the default error is 0. Then, the difference between the active voltage standing wave ratio greater than the set target and the target value at each frequency point is taken as the absolute value, and multiplied by the corresponding weight; the sum of these weighted differences is used to obtain the fitness function, and then through population fitness detection and evaluation, self-search, guided search, and new population fitness detection and evaluation, the optimal solution is output and the process is terminated when the set target is met.

[0045] (3) For the accelerated calculation of the fine model: Combine the equivalent principle domain decomposition efficient analysis method to achieve the efficient and accurate extraction of the electromagnetic characteristics of the common aperture array, and then combine the multi-level fast multipole method MLFMA to accelerate the calculation and filling of the mutual coupling matrix of large-scale arrays and metasurface arrays, and obtain the electromagnetic performance of the entire array surface.

[0046] Figure 4 The schematic block diagram of the algorithm at Figure 5 The outer constraint function 1 in The inner constraint function 2 in The specific steps of the common aperture array layout optimization and low sidelobe reconstruction algorithm can be briefly summarized as:

[0047] 1) Determine the main lobe region and sidelobe region of the co-aperture array pattern.

[0048] 2) Construct two constraint functions (Formulas (3) and (4)). When constructing the first constraint function, set the main lobe region of the normalized planar array pattern to 0 and the sidelobe region to the constraint level value. When constructing the second constraint function, set all regions in the normalized planar array pattern that are less than -3 dB to a minimum value, and set the remaining regions below the desired sidelobe.

[0049] 3) Optimize the amplitude and phase excitation of the coarse model array elements through the hummingbird algorithm. While taking gain into account, calculate the error between the reconstructed pattern and the constraint function using the main and sidelobe constraint functions. The cumulative error value is the fitness value of the algorithm. Loop the above optimization process until the reconstructed pattern meets the desired radiation performance, and then replace the coarse model with the fine model to obtain the final result.

[0050] The low sidelobe simulation results of the full array at 2 GHz after optimization are as follows. Figure 6 Comparison diagrams of the low sidelobe results of the full array pattern at elevation pointing angles of 0°, 15°, 30°, and 45° are given respectively. Figure 7 The corresponding 3D pattern results are given. After normalization, it can be intuitively obtained that the sidelobe levels at different pointings meet the index of ≤ -30 dB.

[0051] Secondly, the low sidelobe optimization simulation results of the full array at 3 GHz are given. Figure 8 Comparison diagrams of the low sidelobe results of the full array pattern at elevation pointing angles of 0°, 15°, 30°, and 45° are given respectively. Figure 9 The 3D pattern results are given. After normalization, it can be intuitively obtained that the sidelobe levels at different pointings meet the index of ≤ -30 dB.

[0052] Finally, the low sidelobe optimization simulation results of the full array at 4 GHz are given. Figure 10 Comparison diagrams of the low sidelobe results of the full array pattern at elevation pointing angles of 0°, 15°, 30°, and 45° are given respectively. Figure 11 The 3D pattern results are given. After normalization, it can be intuitively obtained that the sidelobe levels at different pointings meet the index of ≤ -30 dB.

[0053] From Figures 6 - 11 it can be seen that through the optimization algorithm, it is possible to reduce the sidelobe of the array scanning pattern below -30 dB by optimizing the element amplitudes within the scanning range of ±45°. And when scanning at 45°, no grating lobes appear in the pattern, and the scanning angle of ±45° and the main-to-sidelobe ratio greater than or equal to 30 dB in the S-band are well achieved.

[0054] Figures 12 - 15The simulation results of the full-array pattern scanning at typical frequency points except the S-band are given. The simulation diagrams of the full-array pattern results at pitch pointing angles of 0°, 15°, 30°, and 45° are given respectively, and the corresponding 3D pattern results are given. After normalization, it can be intuitively obtained that except Figure 15 as shown, grating lobes will appear at 16 GHz during the 45° scan, and no grating lobes will appear at the remaining frequency points during the scan. Although there are grating lobes during the 45° scan at the 16 GHz frequency point, no grating lobes appear within the angular range of ±45°.

Claims

1. A method for ultra-wideband co-aperture heterogeneous array deployment and beamforming optimization, characterized in that include: The first step is to estimate the array aperture according to the requirements; The second step is array layout design: the array element frequency band is divided into 1-16 GHz full-band pull-through design, and the array spacing is divided into two groups of arrays, namely array A and array B. Array A is a 3 GHz half-wavelength array, and array B is a 16 GHz half-wavelength array. The third step is to introduce the spatial mapping optimization method. A coarse model is used for calculation during the optimization process. The coarse model adopts the common-aperture array layout optimization method based on the hummingbird algorithm. After the coarse model optimization meets the design goals, a fine model is used for verification.

2. The ultra-wideband co-aperture heterogeneous arraying and beamforming optimization method according to claim 1, wherein The first step is to estimate the array aperture according to the requirements, specifically: For an ultra-wide bandwidth scanning array, it is required that the beam does not have grating lobes when scanning at high frequency. This problem is solved by constraining the array element spacing d: where λ n is the wavelength corresponding to the high frequency, and θ0 is the maximum scanning angle; after the element spacing d is determined within the operating frequency band, the array aperture area is estimated through the array gain G constraint, so as to determine the specific layout and the number of array elements; if the array meets the gain condition at low frequency, it also meets the condition at high frequency; therefore, the aperture area S of the array is estimated at low frequency: where λ L is the wavelength corresponding to the low frequency, and η is the aperture efficiency; it is required that the array gain G is greater than 20 dB, and the aperture area S is calculated to obtain the array element layout.

3. The ultra-wideband co-aperture heterogeneous arraying and beamforming optimization method according to claim 1, wherein The third step is to introduce the spatial mapping optimization method. In the optimization process, a coarse model is used for calculation. The coarse model uses the common-aperture array layout optimization method based on the Hummingbird algorithm. After the coarse model optimization meets the design goal, a fine model is used for verification. Specifically: (1) Establish an active pattern extraction mechanism for co-aperture array elements at different positions, which are divided into edge units, adjacent units, and middle units. Select a certain number of array elements around adjacent units to extract active patterns of array elements at different positions. The array element selection mechanism is based on the active pattern change error being within an acceptable range. Combined with the intelligent optimization algorithm, the coarse model is optimized. (2) With the constraint of meeting the expected requirements of the active standing wave ratio and radiation pattern at different scanning angles, the hummingbird algorithm is used to optimize the active standing wave ratio of the wide-angle scanning array, and the optimal excitation amplitude of the active standing wave ratio and radiation pattern of the array antenna for reconstructing different pointing antennas under real-time dynamics is realized; an efficient and accurate full-wave analysis method is designed to quickly extract the electromagnetic characteristic parameters of the array antenna, effectively saving platform space, reducing the overall cost of the system, and avoiding electromagnetic compatibility problems existing between multiple antennas; is the expression of the active S parameter, where a k is the complex number represented by the amplitude and phase of the k-th source, and α p is the complex number represented by the amplitude and phase of the p-th source, and S pk is the passive S parameter; through calculate the active standing wave ratio, where mag(ActiveS 11 ) represents the modulus of the active reflection coefficient ActiveS 11 ; Combined with the Hummingbird algorithm, the target value is set and the following segmented constraint function is introduced: Among them, represents the pattern model of the common aperture array at different scan angles. u(·) is the unit step function, which is used to control the calculation region of the constraint function, and is used to limit the sidelobe region and beam pointing of the reconstructed pattern; is used to constrain the minimum value of the pattern within the main lobe region, that is, to limit the main lobe width of the pattern, represents the side error in the direction ; represents the side error in the main direction. For the sidelobe constraint function (3), when the sidelobe level of the reconstructed pattern is greater than the -30 dB constraint level, the error is recorded in the form of the difference between the two; otherwise, the default error is 0. Then, the absolute value of the difference between the active VSWR greater than the set target at each frequency point and the target value is taken, and each is multiplied by the corresponding weight. The sum of these weighted differences is used to obtain the fitness function, and then through population fitness detection and evaluation, self-search, guided search, and new population fitness detection and evaluation, the optimal solution is output and the process is terminated when the set target is met; (3) Accelerated calculation of detailed models: Combined with the efficient analysis method of equivalent principle regional decomposition, the electromagnetic characteristics of the common aperture array can be extracted. Then, combined with multi-layer fast multipole MLFMA, the calculation and filling of the mutual coupling matrix of large-scale arrays and metasurfaces can be accelerated to obtain the electromagnetic performance of the entire array.

4. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the method according to any one of claims 1 to 3 are implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, the steps of any method described in claims 1-3 are implemented.

6. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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