Radar system design method and device for optimizing MDO based on multidisciplinary design

Abstract

The invention provides a radar system design method and device based on multidisciplinary design optimization MDO, and relates to the field of electronic reconnaissance, and the method comprises the steps: decomposing a radar system into a transmitting subsystem and a receiving subsystem based on a cost variable part in the radar system design; constructing a radar system design optimization model according to a multidisciplinary design optimization (MDO) method, and screening and sorting historical sample data based on a Latin hypersquare test design method to obtain a first target data set; and adopting a Kriging agent model method, and performing algorithm training and optimal point prediction on the radar system design optimization model by using the first target data set. According to the invention, a complex multidisciplinary highly-coupled radar system design problem is decomposed, and design parameters of a transmitting subsystem and a receiving subsystem are optimized, so that the total cost of the system is lowest; in addition, the scheme has little dependence on radar system designers, and is convenient to propagate and inherit in practical application.

Description

Technical Field

[0001] The present application relates to the field of electronic reconnaissance technology, and in particular to a radar system design method and device based on multidisciplinary design optimization (MDO). Background Art

[0002] Radar system design is a highly complex system engineering project, involving multiple disciplines, including electronics science, industrial design, mechanical engineering, signal processing, computer science, information and communications engineering, and machine learning algorithms. Given the unique characteristics of radar detection missions, effectively integrating the independent designs of each discipline and the interplay between them to ultimately meet the radar system's performance requirements has always been a key issue in radar design.

[0003] In the related art, when conducting actual radar system overall design, the main reference is previous project experience or similar cases, adjusting relevant parameter designs, and calculating according to theoretical formulas such as the radar equation to meet new design requirements. The above radar system design method has certain flaws. First, radar system design is completely dependent on the professional level of the specific designer, requiring a relatively rich accumulation of project experience. Second, the project experience of radar system overall design is not well inherited and disseminated, which is not conducive to the continuous optimization and iterative update of radar system overall design. Summary of the Invention

[0004] To address the shortcomings of the existing technology, the present application provides a radar system design method and device based on multidisciplinary design optimization (MDO), which solves the problems that current radar system design relies heavily on professionals, design experience is difficult to effectively inherit, and is not conducive to the continuous optimization of the overall system design.

[0005] To achieve the above objectives, this application is implemented through the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a radar system design method based on multidisciplinary design optimization (MDO), the radar system design method including: decomposing the radar system into a transmitting subsystem and a receiving subsystem based on the cost variable part in the radar system design; constructing a radar system design optimization model based on the transmitting subsystem and the receiving subsystem according to the multidisciplinary design optimization (MDO) method, wherein the radar system design optimization model is a physical model; obtaining historical sample data related to the radar system design, screening and organizing the historical sample data based on the Latin hypersquare experimental design method, and obtaining a first target data set; adopting the Kriging proxy model method, using the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model, and obtaining a target solution to determine the radar system structure to be designed.

[0007] According to the first aspect of the embodiment of the present application, the aforementioned Kriging proxy model method is used to perform algorithm training and optimal point prediction on the radar system design optimization model using the first target data set to obtain a target solution to determine the radar system structure to be designed. Specifically, the following steps may be included: establishing a mathematical function of the Kriging proxy model and selecting a related function of the Kriging proxy model; wherein the mathematical function is a linear weighted value of a known sample function response value; constructing a Kriging proxy model corresponding to the radar system design optimization model, and using the first target data set to train the parameters of the Kriging proxy model; based on the trained Kriging proxy model, calculating the predicted estimated value of the unknown point, and selecting the target point with the minimum total cost under the condition of satisfying a preset constraint function to determine the target solution of the radar system design optimization model.

[0008] According to the first aspect of the embodiment of the present application, the optimization goal of the radar system design optimization model is: based on typical radar application scenarios, while meeting the radar's maximum range technical performance indicators, to minimize the total cost of radar system design; the mathematical function of the Kriging proxy model is the linear weighting of the known sample function response value; the related functions of the Kriging proxy model include Gaussian function and cubic spline function.

[0009] According to the first aspect of the embodiment of the present application, the transmitting subsystem and the receiving subsystem correspond to the transmitting subsystem discipline and the receiving subsystem discipline in the multidisciplinary design optimization MDO; the transmitting subsystem includes a transmitting source and a transmitting antenna unit, and the receiving subsystem includes a receiving unit, a receiving analog channel, and a receiving digital channel.

[0010] According to the first aspect of the embodiment of the present application, the transmitting subsystem discipline constitutes a first subspace X1: X1 = {P t ,τ,f,G t 、F t 、L t 、T s}; Where, P t is the peak power, τ is the pulse width, f is the operating frequency, G t is the transmission gain, F t is the transmission noise coefficient, L t is the RF transmission loss, T s is the pulse repetition period; the receiving subsystem discipline constitutes the second subspace X2: X2={G r 、F r 、L r}; where G r is the receiving gain, F r is the receiving noise coefficient, L ris the receiving processing loss; the first subspace X1 and the second subspace X2 constitute the system level X, and the system level X satisfies the expression: X={P t ,τ,f,G t 、F t 、L t 、T s , G r 、F r 、L r}.

[0011] According to a first aspect of the embodiment of the present application, the optimization objective function of the radar system design optimization model satisfies the expression:

[0012] C total =C t ×N t +C r ×N r +const

[0013] Where C t is the unit price of the transmitting unit, N t is the number of transmitting units, C r is the unit price of receiving unit, N r is the number of receiving units; const represents a constant; C total represents the total cost;

[0014] The constraint function of the radar system design optimization model satisfies the expression:

[0015]

[0016] Where D max is the maximum power range, σ is the target scattering cross-sectional area, L Σ is the system loss, D0 is the detection factor, C B is the bandwidth correction factor.

[0017] According to the first aspect of the embodiment of the present application, the historical sample data includes the overall system performance index requirements, the design parameters of the transmitting subsystem and the receiving subsystem, the total system cost, and the cost of the transmitting subsystem and the receiving subsystem.

[0018] According to the first aspect of the embodiment of the present application, after constructing a Kriging proxy model based on the aforementioned radar system design optimization model and performing algorithm training and optimal point prediction on the Kriging proxy model using a first target data set to obtain a target solution, the radar system design method based on multidisciplinary design optimization (MDO) further includes: based on the application of the model in actual radar system design projects, continuously expanding sample data to the first target data set to obtain a second target data set to continuously iterate and optimize the radar system design optimization model.

[0019] In a second aspect, an embodiment of the present application provides a radar system design device based on multidisciplinary design optimization (MDO), which includes a decomposition module, a model construction module, a data screening module, and a training prediction module; specifically, the decomposition module is used to decompose the radar system into a transmitting subsystem and a receiving subsystem based on the cost variable part in the radar system design; the model construction module is used to construct a radar system design optimization model based on the transmitting subsystem and the receiving subsystem according to the multidisciplinary design optimization (MDO) method, and the radar system design optimization model is a physical model; the data screening module is used to obtain historical sample data related to the radar system design, and to screen and organize the historical sample data based on the Latin hypersquare experimental design method to obtain a first target data set; the training prediction module is used to adopt the Kriging proxy model method, and use the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model to obtain a target solution to determine the radar system structure to be designed.

[0020] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a program stored in the memory and executable on the processor. When the program is executed by the processor, the radar system design method based on multidisciplinary design optimization (MDO) in the first aspect is implemented.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a program or instruction. When the program or instruction is executed by a processor, the radar system design method based on multidisciplinary design optimization (MDO) in the first aspect is implemented.

[0022] This application provides a radar system design method and device based on multidisciplinary design optimization (MDO). Compared with the existing technology, it has the following advantages:

[0023] This application is based on the multidisciplinary design optimization (MDO) method, comprehensively considering the coupling relationship between the single-disciplinary design of each radar subsystem and the mutual influence between subsystems, decomposes the radar system into a transmitting subsystem and a receiving subsystem, and constructs a radar system design optimization model; in order to reduce the complexity of model analysis and processing, historical sample data are screened and sorted based on the Latin hypersquare experimental design method to obtain a first target data set; this application also introduces the Kriging proxy model method, combines the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model, and obtains the target solution to determine the radar system structure to be designed; this application decomposes the complex multidisciplinary and highly coupled radar system design problem, and optimizes the design parameters of the transmitting subsystem and the receiving subsystem under the constraint of meeting the radar system performance index requirements, so as to minimize the total system cost; and this solution has low dependence on radar system designers, and is easy to disseminate and inherit in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0025] Figure 1 1 is a flow chart of a radar system design method based on multidisciplinary design optimization (MDO) provided in an embodiment of the present application;

[0026] Figure 2 This is a schematic diagram of the multidisciplinary decomposition of the radar system MDO provided in an embodiment of the present application;

[0027] Figure 3 1 is a schematic structural diagram of a radar system design device based on multidisciplinary design optimization (MDO) according to an embodiment of the present application;

[0028] Figure 4 1 is a schematic structural diagram of another radar system design device based on multidisciplinary design optimization (MDO) provided in an embodiment of the present application;

[0029] Figure 5 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0031] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0032] The embodiments of the present application provide a radar system design method and apparatus based on multidisciplinary design optimization (MDO), thereby addressing the current problems of radar system design, such as its strong reliance on professionals, difficulty in effectively inheriting design experience, and the resulting difficulties in continuous optimization of the overall system design.

[0033] The technical solution in the embodiments of the present application is to solve the above technical problems, and the overall idea is as follows:

[0034] Radar system design is a highly complex system engineering project, involving multiple disciplines, including electronics science, industrial design, mechanical engineering, signal processing, computer science, information and communications engineering, and machine learning algorithms. Given the unique characteristics of radar detection missions, effectively integrating the independent designs of each discipline and the interplay between them to ultimately meet the radar system's performance requirements has always been a key issue in radar design.

[0035] In the related art, when conducting actual radar system overall design, the main reference is previous project experience or similar cases, adjusting relevant parameter designs, and calculating according to theoretical formulas such as the radar equation to meet new design requirements. The above-mentioned radar system design method has certain shortcomings. First, radar system design is completely dependent on the professional level of the specific designer, requiring a relatively rich accumulation of project experience. Second, the project experience of radar system overall design is not well inherited and disseminated. Furthermore, the above-mentioned radar system design method is not conducive to the continuous optimization and iterative update of the radar system overall design.

[0036] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0037] The following first introduces a radar system design method based on multidisciplinary design optimization (MDO) provided in an embodiment of the present application.

[0038] The embodiment of the present application provides a flow chart of a radar system design method based on multidisciplinary design optimization MDO, as shown in FIG. Figure 1 As shown, the radar system design method based on multidisciplinary design optimization (MDO) may include the following steps S110 - S140 .

[0039] S110. Based on the cost-variable part in radar system design, decompose the radar system into a transmitting subsystem and a receiving subsystem.

[0040] S120. Based on the transmitting subsystem and the receiving subsystem, a radar system design optimization model is constructed according to the multidisciplinary design optimization (MDO) method. The radar system design optimization model is a physical model.

[0041] S130 , obtaining historical sample data related to radar system design, screening and sorting the historical sample data based on a Latin hypersquare experimental design method, and obtaining a first target data set.

[0042] S140. Using the Kriging surrogate model method, the radar system design optimization model is trained and the optimal point prediction is performed using the first target data set to obtain a target solution to determine the radar system structure to be designed.

[0043] The above is a specific implementation method of a radar system design method based on multidisciplinary design optimization (MDO) provided in an embodiment of the present application. It can be understood that the present application is based on the multidisciplinary design optimization (MDO) method, comprehensively considering the coupling relationship between the single-disciplinary design of each radar subsystem and the mutual influence between subsystems, decomposing the radar system into a transmitting subsystem and a receiving subsystem, and constructing a radar system design optimization model; in order to reduce the complexity of model analysis and processing, historical sample data is screened and organized based on the Latin hypersquare experimental design method to obtain a first target data set for model training.

[0044] Furthermore, this application introduces a Kriging surrogate model approach, combining a first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model, obtaining a target solution to determine the radar system structure to be designed. This application decomposes the complex, multidisciplinary, and highly coupled radar system design problem, optimizing the design parameters of the transmitting and receiving subsystems while meeting the radar system's performance requirements to minimize total system cost. Furthermore, this solution has minimal reliance on radar system designers, making it easy to disseminate and inherit in practical applications.

[0045] In some embodiments, the transmitting subsystem and the receiving subsystem correspond to the transmitting subsystem discipline and the receiving subsystem discipline in the multidisciplinary design optimization MDO; the transmitting subsystem includes a transmitting source and a transmitting antenna unit, and the receiving subsystem includes a receiving unit, a receiving analog channel, and a receiving digital channel.

[0046] In one example, the historical sample data includes overall system performance requirements, design parameters for the transmit and receive subsystems, total system cost, and the costs of the transmit and receive subsystems. It is understood that when designing a radar system, the present application needs to adjust various quantifiable design parameters for the transmit and receive subsystems, and comprehensively consider the total system cost, the transmit subsystem cost, and the receive subsystem cost.

[0047] In some embodiments, the aforementioned Kriging surrogate model method is used to perform algorithm training and optimal point prediction on the radar system design optimization model using the first target data set to obtain a target solution to determine the radar system structure to be designed. That is, the aforementioned S140 may specifically include:

[0048] S210 , establishing a mathematical function of the Kriging surrogate model and selecting a related function of the Kriging surrogate model; wherein the mathematical function is a linear weighting of a known sample function response value.

[0049] S220: Construct a Kriging proxy model corresponding to the radar system design optimization model, and use the first target data set to train parameters of the Kriging proxy model.

[0050] S230. Calculate the predicted estimated value of the unknown point based on the trained Kriging proxy model, and select the target point with the minimum total cost to determine the target solution of the radar system design optimization model under the condition that a preset constraint function is satisfied.

[0051] In the embodiments of the present application, it can be understood that the core idea of establishing the Kriging proxy model in the present application is to construct an approximate model through a limited number of sample points to replace the radar system design optimization model with high computational cost and cumbersome processing process, so as to efficiently perform algorithm training and optimal point prediction.

[0052] In some embodiments, the optimization goal of the radar system design optimization model is: based on typical radar application scenarios, while meeting the radar's maximum range technical performance indicators, to minimize the total cost of radar system design; the mathematical function of the Kriging proxy model is the linear weighting of the known sample function response value; the related functions of the Kriging proxy model include Gaussian function and cubic spline function.

[0053] In one example, the mathematical function of the Kriging surrogate model satisfies the expression:

[0054]

[0055] Where, ω (i) Represents the weight and is the coefficient to be optimized, y (i) Indicates output.

[0056] The correlation function of the Kriging surrogate model satisfies the expression:

[0057]

[0058] Where n and m are both positive integers, θ k is the parameter to be optimized, x k represents the input, x′ k Represents sample data, x represents multiple x k A set of x′ represents multiple x′ k A set of; R(x, x′) represents the correlation coefficient between x and x′.

[0059] The Gaussian function satisfies the expression:

[0060]

[0061] 1≤p k ≤2; k=1, 2, ..., m

[0062] Where R k (θ k , x k -x′ k ) represents θ k and x k -x′ k The correlation coefficient between .

[0063] In another example, the cubic spline function satisfies the expression:

[0064]

[0065] Among them, ε k =θ k -|x k -x′ k |.

[0066] In some embodiments, please refer to Figure 2 , the emission subsystem discipline constitutes the first subspace X1: X1 = {P t ,τ,f,G t 、F t 、L t 、T s}; Where, P t is the peak power, τ is the pulse width, f is the operating frequency, G t is the transmission gain, F t is the transmission noise coefficient, L t is the RF transmission loss, T s is the pulse repetition period.

[0067] The receiving subsystem disciplines constitute the second subspace X2: X2 = {G r 、F r 、L r}; where G r is the receiving gain, F r is the receiving noise coefficient, L r This is the receiving processing loss.

[0068] The first subspace X1 and the second subspace X2 constitute the system level X, which satisfies the expression: X={P t ,τ,f,G t 、F t 、L t 、T s , G r 、F r 、L r}.

[0069] The optimization objective function of the radar system design optimization model satisfies the expression:

[0070] C total =C t ×N t +C r ×N r +const

[0071] Where C t is the unit price of the transmitting unit, N t is the number of transmitting units, Cr is the unit price of receiving unit, N r is the number of receiving units; const represents a constant; C total represents the total cost;

[0072] The constraint function of the radar system design optimization model satisfies the expression:

[0073]

[0074] Where R max is the maximum power range, σ is the target scattering cross-sectional area, L ∑ is the system loss, D0 is the detection factor, C B is the bandwidth correction factor.

[0075] In some embodiments, after constructing a Kriging proxy model based on the radar system design optimization model and performing algorithm training and optimal point prediction on the Kriging proxy model using the first target data set to obtain a target solution, that is, after S140, the radar system design method based on multidisciplinary design optimization (MDO) further includes:

[0076] S310. Based on the application of the model in the actual radar system design project, sample data is continuously added to the first target data set to obtain a second target data set to continuously iterate and optimize the radar system design optimization model.

[0077] In the embodiments of the present application, it can be understood that this solution decomposes the complex, multidisciplinary, and highly coupled radar system design problem through a multidisciplinary design optimization (MDO) approach, and optimizes the design parameters of each radar subsystem under the constraints of meeting the radar system performance index requirements, thereby minimizing the total system cost. This application has low dependence on radar system designers and is easy to disseminate and inherit in practical applications. By continuously expanding sample data to obtain a second target data set, the Kriging proxy model method can be used to retrain the radar system design optimization model using the second target data set and predict the optimal point, thereby achieving continuous iteration and optimization of the model, obtaining a new target solution, and optimizing the design of the radar system.

[0078] In some embodiments, the present application provides a radar system design device 400 based on multidisciplinary design optimization MDO, such as Figure 3 As shown, the radar system design device 400 based on multidisciplinary design optimization (MDO) may include the following modules:

[0079] a decomposition module 410 for decomposing the radar system into a transmitting subsystem and a receiving subsystem based on a cost-variable part in the radar system design;

[0080] A model building module 420 is used to build a radar system design optimization model based on the transmitting subsystem and the receiving subsystem according to the multidisciplinary design optimization (MDO) method, where the radar system design optimization model is a physical model;

[0081] A data screening module 430 is configured to obtain historical sample data related to radar system design, and to screen and organize the historical sample data based on a Latin hypersquare experimental design method to obtain a first target data set;

[0082] The training prediction module 440 is used to adopt the Kriging surrogate model method and use the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model to obtain the target solution to determine the radar system structure to be designed.

[0083] According to an embodiment of the present application, any multiple modules among the decomposition module 410, the model construction module 420, the data screening module 430, and the training prediction module 440 can be combined into a single module, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in a single module.

[0084] In some embodiments, the training prediction module 440 may be specifically used to:

[0085] Establishing a mathematical function of the Kriging surrogate model and selecting a related function of the Kriging surrogate model; wherein the mathematical function is a linear weighting of the response values of the known sample function;

[0086] Constructing a Kriging surrogate model corresponding to the radar system design optimization model, and training the parameters of the Kriging surrogate model using the first target data set;

[0087] According to the trained Kriging surrogate model, the predicted estimated value of the unknown point is calculated. Under the condition of satisfying the preset constraint function, the target point with the minimum total cost is selected to determine the target solution of the radar system design optimization model.

[0088] In some embodiments, as Figure 4As shown, the radar system design device 400 may further include a model optimization module 450, which may be specifically used to: construct a Kriging proxy model based on the radar system design optimization model; use a first target data set to perform algorithm training and optimal point prediction on the Kriging proxy model, and after obtaining the target solution, based on the application of the model in an actual radar system design project, continuously expand sample data into the first target data set to obtain a second target data set to continuously iterate and optimize the radar system design optimization model.

[0089] Figure 4 Each module in the illustrated apparatus has the function of implementing each step in the aforementioned radar system design method based on multidisciplinary design optimization (MDO) and can achieve its corresponding technical effects. For the sake of brevity, these steps will not be described in detail here.

[0090] In some embodiments, the present application provides an electronic device, the structural diagram of the electronic device is as follows Figure 5 shown.

[0091] The electronic device may include a processor 510 and a memory 520 storing computer program instructions.

[0092] Specifically, the processor 510 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0093] The memory 520 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 520 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 520 may include removable or non-removable (or fixed) media. Where appropriate, the memory 520 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 520 is a non-volatile solid-state memory.

[0094] The memory 520 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Therefore, generally, the memory 520 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it may perform the operations described in any one of the radar system design methods based on multidisciplinary design optimization (MDO) in the above-mentioned embodiments.

[0095] The processor 510 reads and executes computer program instructions stored in the memory 520 to implement any one of the radar system design methods based on multidisciplinary design optimization (MDO) in the above embodiments.

[0096] In one example, the electronic device may further include a communication interface 530 and a bus 500. Figure 5 As shown, the processor 510 , the memory 520 , and the communication interface 530 are connected via a bus 500 and communicate with each other.

[0097] The communication interface 530 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0098] Bus 500 includes hardware, software or both, and the parts of online data flow metering equipment are coupled to each other. For example, but not limitation, bus can include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 500 can include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0099] In addition, in conjunction with the radar system design method based on multidisciplinary design optimization (MDO) in the above-mentioned embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when executed by a processor, the computer program instructions implement any of the radar system design methods based on multidisciplinary design optimization (MDO) in the above-mentioned embodiments.

[0100] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0101] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. Programs or code segments can be stored in machine-readable media, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable media" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0102] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0103] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0104] In summary, compared with the prior art, this application has the following beneficial effects:

[0105] 1. This application is based on the multidisciplinary design optimization (MDO) method, comprehensively considering the coupling relationship between the single-disciplinary design of each radar subsystem and the mutual influence between subsystems, decomposing the radar system into a transmitting subsystem and a receiving subsystem, and constructing a radar system design optimization model; in order to reduce the complexity of model analysis and processing, historical sample data are screened and sorted based on the Latin hypersquare experimental design method to obtain a first target data set; this application also introduces the Kriging proxy model method, combined with the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model, and obtain the target solution to determine the radar system structure to be designed.

[0106] 2. This application decomposes the complex, multidisciplinary, and highly coupled radar system design problem through the multidisciplinary design optimization (MDO) method. Under the constraint of meeting the radar system performance requirements, the design parameters of each radar subsystem are optimized. The coupling relationship between the single-disciplinary design of each radar subsystem and the mutual influence between subsystems is comprehensively considered. An optimization model is established through decomposition and coordination methods to minimize the total system cost while meeting the overall system performance requirements.

[0107] 3. This application has low dependence on radar system designers and is easy to disseminate and inherit in practical applications. By continuously expanding the sample data, a second target data set is obtained, and then the Kriging proxy model method can be adopted to use the second target data set to retrain the algorithm and predict the optimal point of the radar system design optimization model, thereby achieving continuous iteration and optimization of the model, obtaining a new target solution, and optimizing the design of the radar system.

[0108] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A radar system design method based on multidisciplinary design optimization (MDO), characterized by: include: Based on the cost variable part in radar system design, the radar system is decomposed into transmitting subsystem and receiving subsystem; Based on the transmitting subsystem and the receiving subsystem, a radar system design optimization model is constructed according to a multidisciplinary design optimization (MDO) method, wherein the radar system design optimization model is a physical model; Acquire historical sample data related to radar system design, and screen and organize the historical sample data based on a Latin hypersquare experimental design method to obtain a first target data set; The Kriging surrogate model method is adopted and the first target data set is used to perform algorithm training and optimal point prediction on the radar system design optimization model, and a target solution is obtained to determine the radar system structure to be designed.

2. The radar system design method based on multidisciplinary design optimization (MDO) according to claim 1, characterized in that: The method of using the Kriging surrogate model to perform algorithm training and optimal point prediction on the radar system design optimization model using the first target data set to obtain a target solution to determine the radar system structure to be designed includes: Establishing a mathematical function of a Kriging surrogate model and selecting a related function of the Kriging surrogate model; wherein the mathematical function is a linear weighted value of a known sample function response value; Constructing a Kriging proxy model corresponding to the radar system design optimization model, and training parameters of the Kriging proxy model using the first target data set; According to the trained Kriging proxy model, the predicted estimated value of the unknown point is calculated, and under the condition of satisfying the preset constraint function, the target point with the minimum total cost is selected to determine the target solution of the radar system design optimization model.

3. The radar system design method based on multidisciplinary design optimization (MDO) according to claim 2, characterized in that: The optimization goal of the radar system design optimization model is to minimize the total cost of the radar system design based on typical radar application scenarios while meeting the radar's maximum range technical performance indicators. The mathematical function of the Kriging proxy model is the linear weighting of the known sample function response values. The related functions of the Kriging proxy model include Gaussian functions and cubic spline functions.

4. The radar system design method based on multidisciplinary design optimization (MDO) according to any one of claims 1 to 3, characterized in that: The transmitting subsystem and the receiving subsystem correspond to the transmitting subsystem discipline and the receiving subsystem discipline in the multidisciplinary design optimization MDO; The transmitting subsystem includes a transmitting source and a transmitting antenna unit, and the receiving subsystem includes a receiving unit, a receiving analog channel and a receiving digital channel.

5. The radar system design method based on multidisciplinary design optimization (MDO) according to claim 4, characterized in that: The emission subsystem disciplines constitute the first subspace X1: X1 = {P t ,τ,f,G t 、F t 、L t 、T s }; Where, P t is the peak power, τ is the pulse width, f is the operating frequency, G t is the transmission gain, F t is the transmission noise coefficient, L t is the RF transmission loss, T s is the pulse repetition period; The receiving subsystem disciplines constitute the second subspace X2: X2 = {G r 、F r 、L r }; where G r is the receiving gain, F r is the receiving noise coefficient, L r For receiving and processing losses; The first subspace X1 and the second subspace X2 constitute a system level X, and the system level X satisfies the expression: X={P t ,τ,f,G t 、F t 、L t 、T s , G r 、F r 、L r }.

6. The radar system design method based on multidisciplinary design optimization (MDO) according to claim 5, characterized in that: The optimization objective function of the radar system design optimization model satisfies the expression: C total =C t ×N t +C r ×N r +const Where C t is the unit price of the transmitting unit, N t is the number of transmitting units, C r is the unit price of receiving unit, N r is the number of receiving units; const represents a constant; C total represents the total cost; The constraint function of the radar system design optimization model satisfies the expression: Where R max is the maximum power range, σ is the target scattering cross-sectional area, L ∑ is the system loss, D0 is the detection factor, C B is the bandwidth correction factor.

7. The radar system design method based on multidisciplinary design optimization (MDO) according to any one of claims 1 to 3, characterized in that: The historical sample data includes system overall performance index requirements, design parameters of the transmitting subsystem and the receiving subsystem, total system cost, and costs of the transmitting subsystem and the receiving subsystem; After constructing a Kriging proxy model based on the radar system design optimization model; performing algorithm training and optimal point prediction on the Kriging proxy model using the first target data set to obtain a target solution, the radar system design method based on multidisciplinary design optimization (MDO) further includes: Based on the application of the model in actual radar system design projects, sample data is continuously added to the first target data set to obtain a second target data set to continuously iterate and optimize the radar system design optimization model.

8. A radar system design device based on multidisciplinary design optimization (MDO), characterized in that: include: A decomposition module for decomposing the radar system into a transmitting subsystem and a receiving subsystem based on the cost-variable parts in the radar system design; A model building module is used to build a radar system design optimization model based on the transmitting subsystem and the receiving subsystem according to the multidisciplinary design optimization (MDO) method, wherein the radar system design optimization model is a physical model; a data screening module, configured to obtain historical sample data related to radar system design, and screen and organize the historical sample data based on a Latin hypersquare experimental design method to obtain a first target data set; The training prediction module is used to adopt the Kriging proxy model method to use the first target data set to perform algorithm training and optimal point prediction on the radar system design optimization model, and obtain the target solution to determine the radar system structure to be designed.

9. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the radar system design method based on multidisciplinary design optimization (MDO) according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the radar system design method based on multidisciplinary design optimization (MDO) according to any one of claims 1 to 7 is implemented.

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