A method, device and storage medium for reliability evaluation of a large-scale array antenna

Abstract

The embodiment of the specification provides a large-scale array antenna reliability evaluation method, device and storage medium. The method comprises the following steps: determining a subarray of an array to be evaluated and a preset number of failed array elements in the subarray; determining a minimum number of failed array elements of the subarray based on a preset set of numbers of failed array elements; determining a target subarray according to the minimum number of failed array elements and the number of failed array elements; determining a fault state of the target subarray; and determining a fault probability of the array to be evaluated according to the fault state of the target subarray. The technical scheme provided in the application does not consider the position of the failed array element.

Description

Technical Field

[0001] This document relates to the field of array antennas, and in particular to a method, apparatus and storage medium for reliability assessment of large-scale array antennas. Background Technology

[0002] In an array antenna, the failure of a single element only affects the signal radiation of the elements it is connected to; the performance of other elements and the channels formed by them remains unchanged. Furthermore, the failure of a small number of elements has a relatively small impact on the overall performance of the array antenna. Therefore, an active array antenna is a typical voting system where i out of n elements are selected; that is, if i out of the n elements of the array antenna are functioning normally, the array antenna can perform its intended function. Let the reliability function of an element be r(t), then the reliability function of the array antenna is...

[0003]

[0004] The system's mean lifetime θ, also known as the mean time to failure (MTTF), is...

[0005]

[0006] In practical applications, when the number of failed array elements is less than 10% of the total number of array elements in the system, the performance of the array antenna remains essentially unchanged, i.e., k = 90% × n, and the maximum number of failed array elements is f. max =10% × n.

[0007] This reliability model only considers the number of failed elements, not their locations. The impact of failed elements on the array antenna performance, especially on sidelobe performance, varies depending on their location. Therefore, even if the number of failed elements f < ff, the reliability model may still be affected by the location of the failed elements. max If faulty elements are concentrated in a certain area, the performance of the array antenna will deteriorate, and it will fail to meet the usage requirements and become unusable. Therefore, using this reliability model to evaluate the reliability of array antennas results in an overestimation problem. Summary of the Invention

[0008] Based on the above analysis, this application aims to propose a method, apparatus, and storage medium for evaluating the reliability of large-scale array antennas, which determines the maximum number of failed array elements and the average lifetime of the array antenna based on the location of failed array elements, thereby improving the reliability of evaluating the performance of the array antenna.

[0009] Firstly, one or more embodiments of this specification provide a method for evaluating the reliability of large-scale array antennas, including:

[0010] Determine the subarray of the array to be evaluated and the preset number of failed array elements in the subarray;

[0011] Based on a preset set of failure element numbers, the minimum number of failure elements in the subarray is determined.

[0012] The target subarray is determined based on the minimum number of failed array elements and the number of failed array elements.

[0013] Determine the fault state of the target subarray;

[0014] The failure probability of the array to be evaluated is determined based on the failure state of the target subarray.

[0015] Further, determining the subarray of the array to be evaluated includes:

[0016] A circular subarray is obtained on the array to be evaluated with the center as the center and a preset length as the radius;

[0017] The preset length is the number of array elements arranged consecutively.

[0018] Furthermore, there are multiple subarrays;

[0019] The step of determining the target subarray based on the minimum number of failed array elements and the number of failed array elements includes:

[0020] The failure probability of the array to be evaluated includes:

[0021] The current subarray is determined according to the order in which the radius increases;

[0022] Determine whether the minimum number of failed array elements in the current subarray is greater than the total number of failed array elements;

[0023] If so, end the current process; otherwise, determine the current subarray as the target subarray.

[0024] Further, determining the fault state of the target subarray includes:

[0025] Based on the number of failed array elements, each state subarray of the target subarray is determined, and the arrangement of failed array elements in each state subarray is different.

[0026] A subarray is identified as unavailable, which represents a fault state of the target subarray.

[0027] Furthermore, the set of failed array elements includes: multiple sets of failed array elements, the number of failed array elements being 0-m, where m is the number of array elements in the subarray; each set of failed array elements corresponds to at least one state subarray, wherein the arrangement of failed array elements in each state subarray is different;

[0028] The determination of the minimum number of failed array elements for the subarray based on a preset set of failed array element numbers includes:

[0029] Determine the number of currently failed array elements in ascending order;

[0030] In the state subarrays corresponding to the current number of failed array elements, a preset number of target state subarrays are determined;

[0031] Determine the preset performance parameters for each of the target state subarrays;

[0032] Determine the average value of each of the aforementioned performance parameters;

[0033] When the subarray corresponding to the current number of failed array elements is determined to be unavailable based on the average value, the current number of failed array elements is determined to be the minimum number of failed array elements.

[0034] Furthermore, the performance parameter is the main lobe-to-side lobe ratio;

[0035] or,

[0036] The performance parameters include multiple of the following: maximum sidelobe level, average sidelobe level, half-power beamwidth, first zero-point beamwidth, and directional coefficient.

[0037] Furthermore, the performance parameters include: the maximum sidelobe level, the average sidelobe level, the half-power beamwidth, the first zero-point beamwidth, and the directional coefficient;

[0038] The step of determining that the subarray corresponding to the current number of failed array elements is unavailable based on the average value includes:

[0039] If any one of the average value of the maximum sidelobe level, the average value of the average sidelobe level, the average value of the half-power beamwidth, the average value of the first zero-point beamwidth, and the average value of the directional coefficient does not reach a threshold, the subarray corresponding to the current number of failed array elements is determined to be unusable.

[0040] Furthermore, the average lifetime of the array under evaluation is determined based on the failure probability of the array under evaluation.

[0041] Secondly, one or more embodiments of this specification provide a large-scale array antenna reliability evaluation device, including: a first determination module, a second determination module, and a data processing module;

[0042] The first determining module is used to determine the subarray of the array to be evaluated and the number of preset failed array elements in the subarray;

[0043] The second determining module is used to determine the minimum number of failed array elements of the subarray based on a preset set of failed array element numbers;

[0044] The data processing module is used to determine the target subarray based on the minimum number of failed array elements and the number of failed array elements; determine the fault state of the target subarray; and determine the fault probability of the array to be evaluated based on the fault state of the target subarray.

[0045] Thirdly, one or more embodiments of this specification provide a storage medium, including:

[0046] Used to store computer-executable instructions, which, when executed, implement the method described in the first aspect.

[0047] Compared with the prior art, this application can achieve at least the following technical effects:

[0048] The more array elements there are, the greater the minimum number of failed array elements. Based on this principle, a certain number of failed array elements are set in the subarray of the array to be evaluated. As can be seen from the above principle, when the minimum number of failed array elements is greater than the number of failed array elements, the corresponding subarray does not have an unusable state. Therefore, the subarray with an unusable state is taken as the target subarray, and its failure probability is calculated. Then, based on the failure probability of the target subarray, the failure probability of the array to be evaluated is calculated to reduce the computational load. Furthermore, determining the minimum number of failed array elements and the failure state of the target subarray requires consideration of the arrangement of failed array elements; therefore, this application achieves the consideration of the arrangement of failed array elements in the process of determining the failure of the array to be evaluated through the above method. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a method for evaluating the reliability of a large-scale array antenna, provided for one or more embodiments of this specification. Detailed Implementation

[0051] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0052] To address the issue that existing technologies cannot consider the position of array elements, it is necessary to accurately calculate the performance of the array antenna under each state, determine whether a state is usable based on performance thresholds, and then determine the number of usable or unusable states in order to calculate the reliability of the array antenna.

[0053] Specifically, the number of failed array elements is specified for different application scenarios. Based on the specified number of failed array elements, each operating state of the array antenna is evaluated, and the usability of the state is determined according to the performance of the array antenna in that state. The number of usable states in the array is accurately determined, and the array antenna reliability function and average lifetime are calculated accordingly. This calculation process can accurately calculate the reliability of the array antenna and takes into account the impact of fault location on performance.

[0054] Furthermore, for an array antenna of size N, when performing average lifetime and reliability tests, if the specified number of failed elements is N, it is necessary to determine the performance of the array antenna when the number of failed elements ranges from 0 to N. The above method requires analyzing and calculating 2^N array antenna states. N It can be seen that the computational load in the above process increases exponentially with the size of the array antenna. Therefore, for small-scale array antennas, this method can accurately obtain their reliability and average lifetime. For large-scale array antennas, the number of states increases dramatically, the computational load increases significantly, and the computational time cost becomes unbearable.

[0055] Based on the above problems and scenarios, embodiments of this application provide a method for evaluating the reliability of large-scale array antennas, such as... Figure 1 As shown, it includes:

[0056] Step 1: Determine the subarray of the array to be evaluated and the number of preset failed array elements in the subarray.

[0057] In this embodiment, a circular subarray is obtained on the array to be evaluated, with the center of the array as the center and a preset length as the radius. The preset length is the number of consecutively arranged array elements.

[0058] In the subarray, the number of failed array elements is set to f∈[1,f max The maximum number of failed array elements, fmax Typically, the number of failed elements does not exceed 10% of the total number of array elements to be evaluated. Among them, the number of failed elements in each subarray is the same.

[0059] Step 2: Based on the preset set of failure element numbers, determine the minimum number of failure elements for the subarray.

[0060] In the embodiments of this application, the minimum number of failed array elements of a subarray refers to the maximum number of array elements that a subarray can operate normally with. For example, if the minimum number of failed array elements of subarray A is 3, then subarray A can still operate normally when 1 or 2 array elements fail. However, when subarray A has 3 or more failed array elements, subarray A cannot operate normally.

[0061] The set of failed array element counts includes multiple failed array element counts, ranging from 0 to m, where m is the number of elements in the subarray. Each failed array element count corresponds to at least one state subarray, where the arrangement of failed array elements differs across state subarrays. For example, if a subarray has 10 elements, the elements in the set of failed array element counts are: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. The number of state subarrays corresponding to failed array element count 1 is... Similarly, each number of failed array elements corresponds to at least one state subarray.

[0062] The process for determining the minimum number of failure matrix elements is as follows:

[0063] S1. Determine the number of currently failed array elements in ascending order. This sorting method can reduce the amount of computation.

[0064] S2. In the state subarray corresponding to the current number of failed array elements, determine a preset number of target state subarrays.

[0065] For example, when the number of state subarrays is no greater than 4, the number of target state subarrays is the number of state subarrays;

[0066] When the number of state subarrays is greater than 4, the number of target state subarrays is 4. A preset number of target state subarrays is determined here to facilitate subsequent mean calculation, thereby reducing the computational burden of determining the minimum number of failure elements. It should be noted that the preset number can be set according to actual circumstances.

[0067] S3. Determine the preset performance parameters of each target state subarray.

[0068] In this application embodiment, the preset performance parameters include two cases:

[0069] In the first case, the performance parameter is the ratio of main lobe to sidelobe.

[0070] The main lobe-to-side lobe ratio best reflects the overall performance of an antenna. When the accuracy requirement for the minimum number of failed array elements is not high, only the main lobe-to-side lobe ratio can be calculated, and this ratio can be used as a criterion to determine the minimum number of failed array elements.

[0071] In the second case, the performance parameters include multiple parameters such as maximum sidelobe level, average sidelobe level, half-power beamwidth, first zero-point beamwidth, and directional coefficient.

[0072] When high precision is required for the minimum number of failed array elements, multiple parameters need to be considered. Then, using these multiple parameters as criteria, the minimum number of failed array elements for the subarray is determined.

[0073] S4. Determine the average value of each performance parameter.

[0074] In the embodiments of this application, for the first case, the average value of the performance parameters is the average value of the main-sidelobe ratio of each target state subarray. For the second case, the average value of the performance parameters includes multiple of the following: the average value of the maximum sidelobe level, the average value of the average sidelobe level, the average value of the half-power beamwidth, the average value of the first zero-point beamwidth, and the average value of the directional coefficient for each target state subarray.

[0075] S5. Based on the average value, when the subarray corresponding to the current number of failed array elements is unavailable, determine the current number of failed array elements as the minimum number of failed array elements.

[0076] In the embodiments of this application, for the first case, when the main lobe-to-side lobe ratio is less than half of the initial main lobe-to-side lobe ratio, the array is determined to be unusable.

[0077] In the second case, if any one of the average value of the maximum sidelobe level, the average value of the average sidelobe level, the average value of the half-power beamwidth, the average value of the first zero-point beamwidth, and the average value of the directional coefficient does not reach the threshold, the subarray corresponding to the number of currently failed array elements is determined to be unusable.

[0078] For example, when the average values ​​of performance parameters include the average maximum sidelobe level, average average sidelobe level, average half-power beamwidth, average first zero-point beamwidth, and average direction factor of each target state subarray, the average maximum sidelobe level is greater than the preset value A1, the average half-power beamwidth is greater than the preset value A2, the average half-power beamwidth is less than the preset value A3, the average first zero-point beamwidth is less than the preset value A4, and the average direction factor is greater than the preset value A5.

[0079] Step 3: Determine the target subarray based on the minimum number of failed array elements and the number of failed array elements.

[0080] In this embodiment of the application, the minimum number of failed array elements and the total number of failed array elements for any subarray have the following relationship:

[0081] When the minimum number of failed array elements is not greater than the number of failed array elements, the subarray is in an unusable state.

[0082] When the minimum number of failed array elements is greater than the number of failed array elements, the subarray does not have an unusable state.

[0083] Furthermore, as the radius increases, the number of minimum failure elements in the subarray increases.

[0084] Based on the above patterns, the target subarray is determined to include:

[0085] T1. Determine the current subarray according to the order of increasing radius.

[0086] In this embodiment, to improve the accuracy of calculating the failure probability of the array to be evaluated, multiple subarrays need to be set, and correspondingly, multiple radii need to be set. The radii of each subarray can be set regularly, for example, the radii of each subarray can be an arithmetic sequence. Alternatively, the radii of each subarray can be set irregularly, for example, the radii of each subarray can be 2, 3, 6, and 7. It should be noted that the more subarrays there are, the more state subarrays are generated, and the more unusable states there are, thus increasing the accuracy of calculating the failure probability of the array to be evaluated.

[0087] T2. Determine whether the minimum number of failed array elements in the current subarray is greater than the total number of failed array elements. If yes, execute T3; otherwise, execute T4.

[0088] T3. End the current process.

[0089] T4. Determine that the current subarray is the target subarray, and execute T1.

[0090] In this embodiment, the purpose of step T2 is to find all subarrays that are unusable. If the minimum number of failed elements in the current subarray is greater than the total number of failed elements, then following the order of increasing radius, the current subarray and subsequent subarrays will definitely not have any unusable states; that is, all subarrays with unusable states have been found. Therefore, the process in step T2 can end at this point, and proceed to step T5.

[0091] If the minimum number of failed array elements in the current subarray is not greater than the number of failed array elements, it indicates that there may be other subarrays that are unavailable, so T1 continues to be executed.

[0092] Step 4: Determine the fault status of the target subarray.

[0093] In this embodiment, the infeasibility state of the subarray is related to the arrangement of the failed array elements. Therefore, based on the number of failed array elements, each state subarray is determined, and the arrangement of failed array elements differs for each state subarray. By traversing all state subarrays of the subarray, the state subarray that is determined to be unusable is identified as the fault state of the target subarray.

[0094] Step 5: Determine the failure probability of the array to be evaluated based on the failure status of the target subarray.

[0095] In the embodiments of this application, for ease of explanation, the state subarray that is unavailable is referred to as the "unavailable state subarray".

[0096] Calculate the probability of each unusable state subarray occurring:

[0097]

[0098] Where p i (t) represents the probability of an unusable state subarray i occurring within time t, where λ is the failure rate, and N n The number of normal transmit / receive channels in the subarray whose state is unavailable, N f The number of faulty transmit / receive channels in the state subarray that is in an unavailable state.

[0099] Therefore, the failure probability of the array to be evaluated is the sum of the failure probabilities of each unusable state subarray:

[0100] S(t)=∑p i (t)

[0101] In this embodiment, the average lifetime of the array to be evaluated is determined based on the failure probability of the array. The average lifetime of the array to be evaluated is:

[0102]

[0103] Where R(t) is the probability that the array to be evaluated is operating normally, and S(t)+R(t)=1.

[0104] This application provides a large-scale array antenna reliability evaluation device, including: a first determination module, a second determination module, and a data processing module;

[0105] The first determining module is used to determine the subarray of the array to be evaluated and the number of preset failed array elements in the subarray;

[0106] The second determining module is used to determine the minimum number of failed array elements of the subarray based on a preset set of failed array element numbers;

[0107] The data processing module is used to determine the target subarray based on the minimum number of failed array elements and the number of failed array elements; determine the fault state of the target subarray; and determine the fault probability of the array to be evaluated based on the fault state of the target subarray.

[0108] This application provides a storage medium, including:

[0109] Used to store computer-executable instructions, which, when executed, implement the methods described in the above embodiments.

[0110] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0111] In the 1930s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement to the methodology cannot be implemented using a hardware physical module. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0112] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0113] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0114] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0115] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0117] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0118] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0119] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0120] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0121] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0122] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0123] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0124] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0125] The above description is merely an embodiment of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A method for reliability assessment of large-scale array antennas, characterized in that, include: Determine the subarray of the array to be evaluated and the preset number of failed array elements in the subarray; Based on a preset set of failure element numbers, the minimum number of failure elements in the subarray is determined. The target subarray is determined based on the minimum number of failed array elements and the number of failed array elements. Determine the fault state of the target subarray; Based on the fault state of the target subarray, determine the fault probability of the array to be evaluated; The number of failed array elements is a preset number of failed array elements in the subarray, and this number is less than or equal to 10% of the total number of array elements to be evaluated.

2. The method according to claim 1, characterized in that, The process of determining the subarray of the array to be evaluated includes: A circular subarray is obtained on the array to be evaluated with the center as the center and a preset length as the radius; The preset length is the number of array elements arranged consecutively.

3. The method according to claim 2, characterized in that, There are multiple subarrays; The step of determining the target subarray based on the minimum number of failed array elements and the number of failed array elements includes: The failure probability of the array to be evaluated includes: The current subarray is determined according to the order in which the radius increases; Determine whether the minimum number of failed array elements in the current subarray is greater than the total number of failed array elements; If so, end the current process; otherwise, determine the current subarray as the target subarray.

4. The method according to claim 3, characterized in that, Determining the fault state of the target subarray includes: Based on the number of failed array elements, each state subarray of the target subarray is determined, and the arrangement of failed array elements in each state subarray is different. A subarray is identified as unavailable, which represents a fault state of the target subarray.

5. The method according to claim 1, characterized in that, The set of failed array elements includes: multiple sets of failed array elements, the number of failed array elements being 0-m, where m is the number of array elements in the subarray; each set of failed array elements corresponds to at least one state subarray, wherein the arrangement of failed array elements in each state subarray is different; Determining the minimum number of failed array elements for the subarray based on a preset set of failed array element numbers includes: Determine the number of currently failed array elements in ascending order; In the state subarrays corresponding to the current number of failed array elements, a preset number of target state subarrays are determined; Determine the preset performance parameters for each of the target state subarrays; Determine the average value of each of the aforementioned performance parameters; When the subarray corresponding to the current number of failed array elements is determined to be unavailable based on the average value, the current number of failed array elements is determined to be the minimum number of failed array elements.

6. The method according to claim 5, characterized in that, The performance parameter is the ratio of main lobe to side lobe. or, The performance parameters include multiple of the following: maximum sidelobe level, average sidelobe level, half-power beamwidth, first zero-point beamwidth, and directional coefficient.

7. The method according to claim 6, characterized in that, The performance parameters include: the maximum sidelobe level, the average sidelobe level, the half-power beamwidth, the first zero-point beamwidth, and the directional coefficient; The step of determining that the subarray corresponding to the current number of failed array elements is unavailable based on the average value includes: If any one of the average value of the maximum sidelobe level, the average value of the average sidelobe level, the average value of the half-power beamwidth, the average value of the first zero-point beamwidth, and the average value of the directional coefficient does not reach a threshold, the subarray corresponding to the current number of failed array elements is determined to be unusable.

8. The method according to claim 1, characterized in that, The method further includes: The average lifetime of the array to be evaluated is determined based on the failure probability of the array to be evaluated.

9. A reliability evaluation device for large-scale array antennas, characterized in that, include: The module comprises a first determination module, a second determination module, and a data processing module; The first determining module is used to determine the subarray of the array to be evaluated and the number of preset failed array elements in the subarray; The second determining module is used to determine the minimum number of failed array elements of the subarray based on a preset set of failed array element numbers; The data processing module is used to determine the target subarray based on the minimum number of failed array elements and the number of failed array elements; determine the fault state of the target subarray; and determine the fault probability of the array to be evaluated based on the fault state of the target subarray. The number of failed array elements is a preset number of failed array elements in the subarray, and this number is less than or equal to 10% of the total number of array elements to be evaluated.

10. A storage medium, characterized in that, include: Used to store computer-executable instructions, which, when executed, implement the method according to any one of claims 1-8.

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