Low-sidelobe directional diagram synthesis method and device, equipment and storage medium

Abstract

The invention discloses a low-sidelobe directional diagram synthesis method, device and equipment and a storage medium, and relates to the technical field of antennae, and the method comprises the following steps: simplifying an array factor response expression according to the structural symmetry of a to-be-optimized antenna array, and representing the simplified array factor response expression in a vector form; taking the maximum simplified array factor response on a discrete sampling point in a minimized side lobe area as an optimization target, taking keeping the main lobe gain of an antenna array to be optimized and the initial upper bound and the initial lower bound of an array element weight as constraints, and modeling a low side lobe directional diagram comprehensive problem as a linear programming problem; and solving the linear programming problem to obtain an optimized array element weight and a corresponding array factor directional diagram, if the EIRP or G / T value of the system does not meet the corresponding set value, adjusting the initial upper bound and lower bound of the array element weight, and solving the linear programming problem again. According to the method, the optimization variable dimension and the constraint number of the convex optimization problem are reduced, and the operation efficiency is greatly improved under the condition of global optimum.

Description

Technical Field

[0001] The present invention relates to the field of antenna technology, and in particular to a low sidelobe pattern synthesis method, device, equipment and storage medium. Background Art

[0002] Antenna arrays utilize the properties of coherent superposition of electromagnetic waves and can achieve higher gain, stronger directivity and narrower beams than single antennas. Therefore, they are widely used in wireless communications, radar detection, satellite navigation, radio astronomy and other fields, and play a key role in modern information systems.

[0003] Traditional arrays use uniform feeding. For a large-scale rectangular grid array, the sidelobe height is about -13.5dB. To ensure that the system can still work effectively in complex environments, it is necessary to study the low sidelobe pattern synthesis method to reduce the array peak sidelobe and improve the system signal-to-noise ratio, thereby enhancing the array's anti-interference ability and improving the overall efficiency of the system to meet the needs of the evolving information system. Among them, low sidelobe pattern synthesis refers to the optimization of the radiation pattern of the antenna array through specific technologies and methods in the field of array signal processing to reduce the radiation beam intensity outside the desired radiation direction. In actual engineering applications, the dynamic range of analog phased array attenuators / amplifiers is limited, and the link design of the array system needs to consider indicators such as EIRP (equivalent isotropic radiated power) and G / T value, where G is the antenna gain and T is the system noise. Therefore, the low sidelobe pattern synthesis algorithm needs to consider the dynamic range of the array element excitation at the same time. Under the requirements of the link budget, the array element weights can be adjusted to improve the system robustness and meet the system design indicators.

[0004] For antenna arrays with rectangular grid structures, the window function method of traditional digital filter design can be used to design array element weights, such as Taylor synthesis method and Chebyshev synthesis method, to reduce the array peak sidelobe. However, these window function methods cannot control the dynamic range of array element excitation, and for general arrays with other grid structures, it is often necessary to sample or interpolate the results of the window function method, which is not suitable for general grid arrays and cannot ensure that the synthesis results reach the global optimal. Intelligent optimization methods such as genetic algorithms and particle swarm algorithms can also be used for low sidelobe pattern synthesis problems. However, when the number of array elements is large, the dimension of the optimization variables is large and the degree of freedom is high, resulting in slow optimization speed and low computational efficiency. In addition, intelligent optimization methods cannot guarantee the global optimal solution. Numerical optimization methods based on convex optimization can guarantee the global optimal solution, but the difficulty lies in how to theoretically model the problem of low sidelobe pattern synthesis of arrays under the premise of considering the constraints of the dynamic range of the array elements. Different optimization models have different computational complexities and optimization objectives. The low sidelobe pattern synthesis method based on second-order cone programming aims to minimize the sidelobe level and can find the optimal solution that minimizes the sidelobe in the visible area. However, its calculation amount is large, and the problem modeling cannot take into account indicators such as aperture efficiency and EIRP, G / T value, etc.

[0005] In summary, the existing low sidelobe pattern synthesis algorithms have limited control over indicators such as array element dynamic range, array EIRP and G / T value in array system design, and cannot take into account both computational efficiency and solution accuracy. There is an urgent need for a low sidelobe pattern synthesis method with efficient solution, controllable indicators and optimal results. Summary of the invention

[0006] Based on the defects of the above-mentioned prior art, the present invention provides a low sidelobe pattern synthesis method, device, equipment and storage medium, which solves the problem that the existing low sidelobe pattern synthesis algorithm has limited control ability on indicators such as array element dynamic range, array EIRP and G / T value designed for array systems, and cannot take into account both computational efficiency and solution accuracy.

[0007] The present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a low sidelobe pattern synthesis method, comprising the following steps:

[0009] Setting the initial upper and lower bounds of the array element weights according to the RF link dynamic range of the antenna array to be optimized;

[0010] Obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression;

[0011] Taking minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region as the optimization goal and keeping the initial upper and lower bounds of the main lobe gain and element weights of the antenna array to be optimized as constraints, the low sidelobe pattern synthesis problem is modeled as a linear programming problem.

[0012] The linear programming problem is solved to obtain the optimized array element weights and the corresponding array factor pattern. The equivalent isotropic radiated power EIRP or G / T value of the antenna array system is obtained according to the optimized array element weights. If the EIRP or G / T value does not meet the corresponding set value, the initial upper and lower bounds of the array element weights are adjusted and the linear programming problem is solved again; if they meet the set value, the optimized array element weights and the corresponding array factor pattern are output.

[0013] Preferably, the step of obtaining the structural symmetry of the antenna array to be optimized, simplifying the array factor response expression according to the structural symmetry and expressing it in vector form to obtain a simplified array factor response expression specifically includes the following steps:

[0014] For an array with 2M+1 units and a centrally symmetrical layout, under amplitude weighted optimization, the angle The array factor pattern expression on is as follows:

[0015]

[0016] in,

[0017]

[0018] In the formula, is the array factor pattern expression of the centrosymmetric array, k x and k y are two wave number components, λ is the wavelength corresponding to the array operating frequency, (x m ,y m ) is the position of the mth array element, w 0 is the central element excitation coefficient, θ is the polar angle, is the azimuth, w m is the excitation coefficient of the mth array element;

[0019] In a centrosymmetric array, the sidelobe area to be optimized is θ sl is the starting polar angle of the sidelobe area to be optimized;

[0020] For an array with 4M+1 units and a mirror-symmetric layout, under amplitude-weighted optimization, the angle The array factor pattern expression on is as follows:

[0021]

[0022] In the mirror-symmetric array, the sidelobe area to be optimized is

[0023] The simplified array factor is expressed in vector form:

[0024]

[0025] In the formula, To simplify the array factor response expression, h n is the steering vector in the nth direction, and w is the simplified array element weight vector.

[0026] Preferably, the low sidelobe pattern synthesis problem is modeled as a linear programming problem, and the linear programming problem is specifically as follows:

[0027]

[0028] α 0 ≤w m ≤β 0 ,m=0,···,M,

[0029]

[0030] In the formula, is an M+1-dimensional vector composed of positive real numbers, g is the maximum simplified array factor response after the discretization of the sidelobe region to be optimized, N is the number of sampling points in the sidelobe region, is the main lobe response, α 0 is the initial upper bound of the array element weight, β 0 is the initial lower bound of the array element weight.

[0031] Preferably, the outputting of the optimized array element weights and the corresponding array factor pattern comprises the following steps:

[0032] Get the guidance vectors in different directions;

[0033] The steering vectors in different directions and the optimized array element weights are input into the simplified array factor response expression to obtain the array factor directivity patterns at different angles.

[0034] In a second aspect, the present invention provides a low sidelobe pattern synthesis device, comprising:

[0035] A setting module, used to set the initial upper and lower bounds of the array element weights according to the RF link dynamic range of the antenna array to be optimized;

[0036] A simplification module is used to obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression;

[0037] The construction module takes minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region as the optimization goal, and takes maintaining the initial upper and lower bounds of the main lobe gain of the antenna array to be optimized and the element weights as constraints, and models the low sidelobe pattern synthesis problem as a linear programming problem;

[0038] The solving module is used to solve the linear programming problem, obtain the optimized array element weights and the corresponding array factor pattern, and obtain the equivalent isotropic radiated power EIRP or G / T value of the antenna array system according to the optimized array element weights. If the EIRP or G / T value does not meet the corresponding set value, the initial upper and lower bounds of the array element weights are adjusted, and the linear programming problem is solved again; if it meets the set value, the optimized array element weights and the corresponding array factor pattern are output.

[0039] In a third aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned low sidelobe pattern synthesis method when executing the program.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the low sidelobe pattern synthesis method described above is implemented.

[0041] Compared with the prior art, at least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects:

[0042] The present invention utilizes the structural symmetry of the antenna array layout to be optimized, simplifies the representation of the array factor response, and constructs a linear programming problem with the optimization goal of minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region, thereby reducing the dimension of the optimization goal and the number of constraints, and greatly improving the computational efficiency while ensuring the accuracy of the solution. The dynamic range constraints of the array elements are also considered in the linear programming problem, and the corresponding hardware indicators are obtained based on the solution results. The present invention allows the optimization results to be adjusted according to the system link budget and hardware indicators, thereby improving the system robustness and reducing the error sensitivity. It can be used for amplitude weighting of large-scale arrays, and provides a powerful tool for the optimization design of applications such as satellite-borne phased arrays. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A flowchart of a low sidelobe pattern synthesis method of the present invention;

[0045] Figure 2 The array element excitation and array factor patterns are obtained by the low sidelobe pattern synthesis method based on second-order cone programming;

[0046] in, Figure 2 (a): Array element excitation pattern, Figure 2 (b): Array factor pattern;

[0047] Figure 3 The array element excitation and array factor directional diagram obtained by the present invention without dynamic range constraints;

[0048] in, Figure 3 (a): Array element excitation pattern, Figure 3 (b): Array factor pattern;

[0049] Figure 4 The array element excitation and array factor directivity diagram obtained by the present invention under the constraint of 12dB dynamic range;

[0050] in, Figure 4 (a): Array element excitation pattern, Figure 4 (b): Array factor pattern; DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] 1. Explanatory Examples In order to enable those skilled in the art to fully understand how to implement the present invention, this section provides an illustrative example that expands and describes the technical solution of the claims.

[0053] The present invention aims to address the problems of complex optimization models and low computational efficiency of existing low sidelobe pattern synthesis methods based on convex optimization, as well as the constraints of system hardware indicators and link budget on the dynamic range of array elements in engineering applications, and proposes a low sidelobe pattern synthesis method with adjustable dynamic range based on linear programming. This method utilizes the structural symmetry of the array layout and simplifies the representation of array factors, thereby greatly reducing the variable dimension and number of constraints of the optimization problem, and on this basis introduces upper and lower bound constraints on array element weights, thereby achieving adjustable dynamic range of array element weights and improving the aperture efficiency of the antenna array. The following is combined with Figure 1 A low sidelobe pattern synthesis method provided by an embodiment of the present invention is described in detail, which specifically includes the following steps:

[0054] S1: Determine the symmetry of the array structure to be optimized, and pre-set the starting polar angle θ of the sidelobe area to be optimized according to the array aperture. sl , set the initial upper bound α of the array element weight according to the dynamic range of the RF link 0 and the initial lower bound β 0 Array element weight is also known as array element excitation, which refers to the excitation coefficient of the antenna port.

[0055] S2: Obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression.

[0056] According to the symmetry of the array structure, the array factor response expression is simplified to reduce the sidelobe optimization range. The array factor refers to the relative radiation intensity of the array in a given direction. It depends on the excitation coefficient of each array element. The array factor can be obtained by taking the inner product of the vector composed of the array element weights and the steering vector in a given direction. For an array with 2M+1 elements and a centrally symmetrical layout, under amplitude weighted optimization, the angle The array factor response expression on is as follows:

[0057]

[0058] in,

[0059]

[0060] In the formula, is the array factor pattern expression of the centrosymmetric array, k x and k y are two wave number components, λ is the wavelength corresponding to the array operating frequency, (x m ,y m ) is the position of the mth array element, w 0 is the central element excitation coefficient, θ is the polar angle, is the azimuth, w mis the excitation coefficient of the mth array element;

[0061] In a centrosymmetric array, the sidelobe area to be optimized is θ sl is the starting polar angle of the sidelobe area to be optimized;

[0062] For an array with 4M+1 units and a mirror-symmetric layout, under amplitude-weighted optimization, the angle The array factor response expression on is as follows:

[0063]

[0064] In the mirror-symmetric array, the sidelobe area to be optimized is

[0065] The simplified array factor is expressed in vector form:

[0066]

[0067] In the formula, h n is the steering vector in the nth direction, and w is the simplified array element weight vector.

[0068] S3: The low sidelobe pattern synthesis problem is modeled as a linear programming problem, and its optimization model is:

[0069]

[0070] α 0 ≤w m ≤β 0 ,θm=0,···,M;

[0071]

[0072] In the formula, is an M+1-dimensional vector composed of positive real numbers, g is the maximum simplified array factor response after the discretization of the sidelobe region to be optimized, N is the number of sampling points in the sidelobe region, is the main lobe response, α 0 is the initial upper bound of the array element weight, β 0 is the initial lower bound of the array element weight.

[0073] Since this problem is a linear optimization problem, and the dimension of the optimization variables and the number of constraints in the sidelobe region are greatly reduced compared to direct modeling, the problem has high computational efficiency, and convex problem modeling ensures the optimality of the solution.

[0074] S4: Determine whether the array element excitation meets the system EIRP or G / T value indicators based on the solution of the linear programming problem. If not, adjust the upper and lower bounds α and β of the array element weights and solve again until the system indicators are met.

[0075] S5: Output the optimized array element weights and the corresponding directional diagram. At a given angle, the array elements have different path differences due to different arrangement positions, and then the steering vector is calculated. The inner product of the steering vector and the array element weight vector is the array factor response in that direction. Responses in different directions constitute the directional diagram.

[0076] 2. Evidence of the effects of the embodiments. The embodiments of the present invention have achieved some positive effects during the development or use process, and indeed have great advantages over the prior art. The following contents Figure 2-Figure 4 Give a description.

[0077] The effect of the present invention is achieved through Figure 2-Figure 4 Explanation: The array in the simulation experiment is a 32×32 square grid array with a mirror-symmetrical layout and half-wavelength spacing, and the starting polar angle of the sidelobe area is preset to θ sl =5°, Figure 2 (a) is the optimization result of array element weights obtained by the low sidelobe pattern synthesis method based on second-order cone programming. It can be seen that the weights of array elements at different positions vary greatly. Figure 2 (b) is the array factor radiation pattern, in which the peak sidelobe in the visible area is about -31.11dB, and the maximum peak sidelobe during scanning is -23.48dB. During scanning, there will be obvious sidelobe rise, which reduces the system performance.

[0078] Figure 3 This is the optimization result obtained by the present invention without dynamic range constraints on the array element weights. Figure 3 The weight distribution diagram of the array element in (a) and Figure 2 From the comparison of (a), we can see that the full-power output units of the array are significantly more than the optimization result of the low sidelobe pattern synthesis method based on second-order cone programming, and the array aperture efficiency is higher. Figure 3 (b) is its array factor radiation pattern, and its peak sidelobe in the visible area is -27.79dB, and the maximum sidelobe during scanning is -27.43dB, with no obvious increase.

[0079] Figure 4This is the optimization result obtained by the present invention under the constraint of 12dB dynamic range of the element weight. The maximum element weight result is 0dB, the minimum is -12dB, the peak sidelobe in the visible area is -25.69dB, and the maximum sidelobe during scanning is -25.24dB, achieving a compromise between the hardware dynamic range constraint and the array scanning performance. By comparing the present invention with the low sidelobe pattern synthesis method based on second-order cone programming, it can be found that the present invention can obtain easy-to-use excitation coefficients and relatively ideal patterns, which can greatly improve the performance of the array during scanning, and while taking into account the low sidelobe requirements, consider the constraints of the system hardware indicators and link budget on the element dynamic range, improve the aperture efficiency of the antenna array, and enhance the system robustness.

[0080] Based on the same concept, the present invention also provides a low sidelobe pattern synthesis device, including a setting module, a simplification module, a construction module and a solution module.

[0081] The setting module is used to set the initial upper and lower bounds of the array element weights according to the dynamic range of the radio frequency link of the antenna array to be optimized.

[0082] The simplification module is used to obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression.

[0083] The building module is used to model the low sidelobe pattern synthesis problem as a linear programming problem, with the optimization objective of minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region and maintaining the initial upper and lower bounds of the mainlobe gain of the antenna array to be optimized and the array element weights as constraints.

[0084] The solving module is used to solve the linear programming problem, obtain the optimized array element weights and the corresponding array factor pattern, and obtain the equivalent isotropic radiated power EIRP or G / T value of the antenna array system according to the optimized array element weights. If the EIRP or G / T value does not meet the corresponding set value, the initial upper and lower bounds of the array element weights are adjusted, and the linear programming problem is solved again; if it meets the set value, the optimized array element weights and the corresponding array factor pattern are output.

[0085] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned low sidelobe pattern synthesis method when executing the program.

[0086] The present invention also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the low sidelobe pattern synthesis method described above is implemented.

[0087] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0088] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A low sidelobe pattern synthesis method, characterized in that: The following steps are involved: Setting the initial upper and lower bounds of the array element weights according to the RF link dynamic range of the antenna array to be optimized; Obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression; Taking minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region as the optimization goal and keeping the initial upper and lower bounds of the main lobe gain and element weights of the antenna array to be optimized as constraints, the low sidelobe pattern synthesis problem is modeled as a linear programming problem. The linear programming problem is solved to obtain the optimized array element weights and the corresponding array factor pattern. The equivalent isotropic radiated power EIRP or G / T value of the antenna array system is obtained according to the optimized array element weights. If the EIRP or G / T value does not meet the corresponding set value, the initial upper and lower bounds of the array element weights are adjusted and the linear programming problem is solved again; if they meet the set value, the optimized array element weights and the corresponding array factor pattern are output.

2. A low sidelobe pattern synthesis method as claimed in claim 1, characterized in that: The step of obtaining the structural symmetry of the antenna array to be optimized, simplifying the array factor response expression according to the structural symmetry and expressing it in vector form to obtain a simplified array factor response expression specifically includes the following steps: For an array with 2M+1 units and a centrally symmetrical layout, under amplitude weighted optimization, the angle The array factor pattern expression on is as follows: in, In the formula, is the array factor pattern expression of the centrosymmetric array, k x and k y are two wave number components, λ is the wavelength corresponding to the array operating frequency, (x m ,y m ) is the position of the mth array element, w0 is the central array element excitation coefficient, θ is the polar angle, is the azimuth, w m is the excitation coefficient of the mth array element; In a centrosymmetric array, the sidelobe area to be optimized is θ sl is the starting polar angle of the sidelobe area to be optimized; For an array with 4M+1 units and a mirror-symmetric layout, under amplitude-weighted optimization, the angle The array factor pattern expression on is as follows: In the mirror-symmetric array, the sidelobe area to be optimized is The simplified array factor is expressed in vector form: In the formula, To simplify the array factor response expression, h n is the steering vector in the nth direction, and w is the simplified array element weight vector.

3. A low sidelobe pattern synthesis method as claimed in claim 2, characterized in that: The low sidelobe pattern synthesis problem is modeled as a linear programming problem, which is specifically as follows: In the formula, is an M+1-dimensional vector composed of positive real numbers, g is the maximum simplified array factor response after the discretization of the sidelobe region to be optimized, N is the number of sampling points in the sidelobe region, is the main lobe response, α0 is the initial upper bound of the array element weight, and β0 is the initial lower bound of the array element weight.

4. A low sidelobe pattern synthesis method as claimed in claim 1, characterized in that: The step of outputting the optimized array element weights and the corresponding array factor directional diagram comprises the following steps: Get the guidance vectors in different directions; The steering vectors in different directions and the optimized array element weights are input into the simplified array factor response expression to obtain the array factor directivity patterns at different angles.

5. A low sidelobe pattern synthesis device, characterized in that: include: A setting module, used to set the initial upper and lower bounds of the array element weights according to the RF link dynamic range of the antenna array to be optimized; A simplification module is used to obtain the structural symmetry of the antenna array to be optimized, simplify the array factor response expression according to the structural symmetry and express it in vector form to obtain a simplified array factor response expression; The construction module takes minimizing the maximum simplified array factor response at discrete sampling points in the sidelobe region as the optimization goal, and takes maintaining the initial upper and lower bounds of the main lobe gain of the antenna array to be optimized and the element weights as constraints, and models the low sidelobe pattern synthesis problem as a linear programming problem; The solving module is used to solve the linear programming problem, obtain the optimized array element weights and the corresponding array factor pattern, and obtain the equivalent isotropic radiated power EIRP or G / T value of the antenna array system according to the optimized array element weights. If the EIRP or G / T value does not meet the corresponding set value, the initial upper and lower bounds of the array element weights are adjusted, and the linear programming problem is solved again; if it meets the set value, the optimized array element weights and the corresponding array factor pattern are output.

6. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the low sidelobe pattern synthesis method as described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the low sidelobe pattern synthesis method described in any one of claims 1 to 4 is implemented.

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