WO2023050407A1 - 电磁场近场测试方法、***、可读存储介质及计算机设备 - Google Patents

电磁场近场测试方法、***、可读存储介质及计算机设备 Download PDF

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WO2023050407A1
WO2023050407A1 PCT/CN2021/122419 CN2021122419W WO2023050407A1 WO 2023050407 A1 WO2023050407 A1 WO 2023050407A1 CN 2021122419 W CN2021122419 W CN 2021122419W WO 2023050407 A1 WO2023050407 A1 WO 2023050407A1
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dut
electromagnetic field
probe
field
coefficient
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PCT/CN2021/122419
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English (en)
French (fr)
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苏栋才
东君伟
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中山香山微波科技有限公司
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Priority to PCT/CN2021/122419 priority Critical patent/WO2023050407A1/zh
Publication of WO2023050407A1 publication Critical patent/WO2023050407A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
    • G01R29/08—Measuring electromagnetic field characteristics

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  • the present application belongs to the field of testing, and in particular relates to an electromagnetic field near-field testing method, system, computer-readable storage medium and computer equipment.
  • Traditional electromagnetic field near-field test methods include: planar near-field test method, cylindrical near-field test method and spherical near-field test method. These near-field test methods are to discretize the Lorenz reciprocity theorem in the physical equation in the plane coordinate system, cylindrical coordinate system and spherical coordinate system respectively, so that the variables to be obtained (such as DUT (Device Under Test, the object under test, ) plane wave coefficient, cylindrical wave coefficient or spherical wave coefficient) and the measurement value collected by the probe have a Fourier transform relationship, which makes the measurement point of the probe fixed on the sampling plane, sampling cylinder or sampling spherical surface Grid points, the interval of the grid points satisfies the Nyquist sampling law, that is, the interval of the grid points is half a wavelength.
  • DUT Device Under Test, the object under test, ) plane wave coefficient, cylindrical wave coefficient or spherical wave coefficient
  • the measurement value collected by the probe have a Fourier transform relationship, which makes the measurement point of the
  • the traditional planar near-field test method needs at least (2/ ⁇ ) 2 measurement points in the square measurement area to solve the far-field pattern of the DUT, where ⁇ represents the wavelength, and the working Frequency is inversely proportional. Therefore, when the operating frequency of the DUT increases, the total number of measurement points required by the traditional electromagnetic field near-field test method will increase in direct proportion to the square of the operating frequency, and the test efficiency will also decrease in direct proportion to the square of the operating frequency. It greatly limits its test efficiency in high frequency scenarios (such as 5G, 6G DUT).
  • the purpose of this application is to provide an electromagnetic field near-field test method, system, computer-readable storage medium and computer equipment, aiming to solve the problem that when the operating frequency of the DUT increases, the total number of measurement points required by the traditional electromagnetic field near-field test method will be reduced. As the square of the operating frequency increases, the test efficiency decreases proportionally to the square of the operating frequency, which greatly limits the test efficiency in high-frequency scenarios.
  • the present application provides an electromagnetic field near-field test system, including computer equipment and a signal source, a signal receiver, a moving device and at least one probe connected to the computer equipment for generating test signals,
  • the signal source, signal receiver, probe and DUT form a closed link of the test signal
  • the moving device is used to accept the control of the computer equipment to make the DUT and the probe move randomly relative to each other to generate a plurality of random measurement points;
  • the signal source is connected to the DUT
  • the signal receiver is connected to the DUT
  • the probe is used to collect multiple
  • the measured value of the electromagnetic field signal at the random measurement point is directly transmitted to the signal receiver or transmitted to the DUT and then transmitted to the signal receiver by the DUT;
  • the signal receiver is used to analyze and process the electromagnetic field signal measurement value collected by the probe and provide it to the computer equipment;
  • the computer equipment is used to select any coordinate system, so that the electromagnetic field coefficient of the DUT to be obtained presents a sparse feature; under the selected coordinate system, the motion device is controlled to cause random relative motion between the DUT and the probe, and multiple random measurement points are generated , and determine one or more attitudes of the probe, and obtain the electromagnetic field coefficients corresponding to the attitude of the probe respectively; obtain the measured values of the electromagnetic field signals collected by all the probes after the signal receiver has been analyzed and processed, and obtain the set of measured values; according to the measured values According to the Lorenz reciprocity law in electromagnetism, the electromagnetic field coefficients corresponding to the attitude of the probe are collected and the electromagnetic field coefficients of the DUT are solved by a convex optimization algorithm, and the far field direction of the DUT is obtained according to the electromagnetic field coefficients of the DUT The electric and/or magnetic field at any point outside the graph or DUT.
  • the present application provides an electromagnetic field near-field testing method, the method comprising:
  • control the motion device to cause random relative motion between the DUT and the probe, generate multiple random measurement points, and determine one or more attitudes of the probe, and obtain the electromagnetic field coefficients corresponding to the attitude of the probe respectively;
  • the electromagnetic field coefficient of the DUT is solved by the convex optimization algorithm
  • the far field pattern of the DUT or the electric field and/or magnetic field at any point other than the DUT are obtained.
  • the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the electromagnetic field near-field testing method described above are realized.
  • the present application provides a computer device, including:
  • processors one or more processors
  • the processor and the memory are connected by a bus, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processors , characterized in that, when the processor executes the computer program, the steps of the electromagnetic field near-field testing method are realized.
  • the electromagnetic field coefficient of the DUT obtained by solving presents a sparse characteristic, and a plurality of random measurement points are selected under the coordinate system, Therefore, the set of measured values has a random linear relationship with the electromagnetic field coefficient of the DUT to be obtained, so the problem of solving the electromagnetic field coefficient of the DUT can be reduced to a convex optimization problem in which the objective function is a convex function, so that the DUT can be solved by a convex optimization algorithm electromagnetic field coefficient.
  • FIG. 1 is a first schematic diagram of an electromagnetic field near-field test system provided by an embodiment of the present application.
  • FIG. 2 is a second schematic diagram of an electromagnetic field near-field test system provided by an embodiment of the present application.
  • Fig. 3 is a flow chart of an electromagnetic near-field testing method provided by an embodiment of the present application.
  • Figure 4 is a magnitude plot of the true value of the DUT far-field pattern.
  • Figure 5 is a magnitude plot of the estimated value of the DUT far-field pattern.
  • Figure 6 is a plot of the magnitude of the difference between the estimated value of the DUT's far-field pattern and the true value of the far-field pattern.
  • Fig. 7 is a specific structural block diagram of a computer device provided by an embodiment of the present application.
  • the moving device 13 is used to accept the control of the computer equipment 14, so that the DUT 16 and the probe 15 are randomly moved relative to each other to generate a plurality of random measurement points;
  • the signal source 11 is connected to the DUT16, and when the probe 15 is connected to the signal source 11, the signal receiver 12 is connected to the DUT16, and the signal source 11 is connected to the DUT16.
  • the probe 15 is used to collect the electromagnetic field signal measurement values of a plurality of random measurement points, and directly transmits to the signal receiver or transmits to the DUT and then transmits to the signal receiver by the DUT;
  • the signal receiver 12 is used to analyze and process the electromagnetic field signal measurement value collected by the probe and provide it to the computer equipment; the analysis and processing may specifically include radio frequency signal denoising, sampling, solving amplitude, phase, etc.;
  • the computer equipment 14 is used to select any coordinate system, so that the electromagnetic field coefficient of the DUT 16 to be sought presents a sparse feature; under the selected coordinate system, the motion device 13 is controlled to cause the DUT 16 and the probe 15 to move randomly relative to each other, resulting in A plurality of random measurement points, and determine one or more postures of the probe 15, and obtain electromagnetic field coefficients corresponding to the postures of the probe 15 respectively; obtain the electromagnetic field signal measurements collected by all the probes 15 after analysis and processing by the signal receiver value to obtain a set of measured values; according to the set of measured values and the electromagnetic field coefficients corresponding to the attitude of the probe 15 respectively, according to the Lorenz reciprocity law in electromagnetism, and solve the electromagnetic field coefficient of the DUT through a convex optimization algorithm, and according to the The far-field pattern of the DUT or the electric field and/or magnetic field at any point outside the DUT can be obtained from the electromagnetic field coefficient of the DUT.
  • the computer equipment 14 is connected with the signal source 11, the signal receiver 12, the movement device 13 and at least one probe 15, and is mainly used for controlling the signal source 11, the signal receiver 12, the movement device 13 and at least one probe 15, and performing data transmission .
  • the measured value of the electromagnetic field signal may include one or any combination of frequency, amplitude, phase information, and the like.
  • Convex optimization algorithm refers to a special kind of optimization, which refers to the optimization problem in which the objective function is a convex function and the domain of definition obtained by constraints is a convex set.
  • the movement device may be connected to the DUT to control the movement of the DUT, or connected to the probe to control the movement of the probe, or connected to both the DUT and the probe to control the movement of the DUT and the probe.
  • the signal source may be an independent external signal transmitting device, or may be a signal transmitting device built into a radio frequency device (such as a DUT or a probe).
  • the signal receiver can be an independent external signal receiving device, or a built-in signal receiving device in a radio frequency device (such as a DUT or a probe).
  • DUT can be any wireless communication device, such as antenna, radar, mobile phone, etc.
  • the signal source and the signal receiver may be integrated, or may be independent devices.
  • the closed link of the test signal formed by the signal source, the signal receiver, the probe and the DUT is specifically exemplified as follows:
  • the signal is emitted by the signal source, detected by the probe, then passed through the space, transmitted to the DUT, and then transmitted to the signal receiver by the DUT. or,
  • the signal is emitted by the signal source, then radiated by the DUT, then passes through the space, and finally detected by the probe, and then enters the signal receiver.
  • Computer equipment can monitor the parameters of the transmitted and received signals, and use these parameters to invert the characteristics of the DUT.
  • FIG. 3 is a flow chart of an electromagnetic near-field testing method provided by an embodiment of the present application. This embodiment is mainly illustrated by taking the electromagnetic near-field testing method applied to computer equipment as an example.
  • An electromagnetic field near-field testing method provided by an embodiment of the present application includes the following steps:
  • any orthogonal Cartesian coordinate system rotated in three-dimensional space can be used as a coordinate system that can sparsely express the electromagnetic field coefficient.
  • control the motion device to cause random relative motion between the DUT and the probe, generate multiple random measurement points, determine one or more attitudes of the probe, and obtain electromagnetic field coefficients corresponding to the attitudes of the probe.
  • S102 may specifically be:
  • K is a natural number greater than or equal to 1;
  • S103 may specifically be:
  • S104 may specifically be:
  • the sparse characteristic of the electromagnetic field coefficient of the DUT to be obtained is described by a convex function f(v), and the electromagnetic field coefficient v of the DUT constrained by the Lorenz reciprocity law and the set of measured values There is a random linear relationship between As a constraint or a penalty function in the field of optimization, the convex function f(v) and the random linear relationship Combined with a convex optimization algorithm, where A is a random matrix, and the elements of A are determined by the position of the random measurement point and the electromagnetic field coefficient corresponding to each attitude of the probe;
  • the basis function corresponding to the electromagnetic wave coefficient of DUT is determined. For example, when the electromagnetic wave coefficient of DUT is a plane wave coefficient, then its basis function is a plane wave vector function. For example, when the electromagnetic wave coefficient of DUT is spherical wave coefficient, then its basis function is the spherical wave vector function.
  • S105 may specifically be:
  • the electric field E(x) and magnetic field H(x) of any point x other than the DUT are expressed as in, is the basis function related to the electric field, is the basis function related to the magnetic field.
  • the measurement value of the probe to the DUT in a certain state can be expressed as the linearity of the electromagnetic field coefficient of the DUT (that is, the variable to be obtained) and the electromagnetic field coefficient of the probe in this state (the known variable) coupling.
  • the probe collects electromagnetic field signal measurement values at multiple random measurement points
  • this application requires much fewer measurement points than the traditional algorithm to solve the far-field pattern of the DUT and other information. This greatly improves the test efficiency.
  • Experiments have found that only 1/25 of the sampling points of the traditional plane near-field are needed to restore the far-field pattern of the DUT very well.
  • the DUT is a high-gain antenna
  • the amplitude diagram of the true value of the far-field pattern is shown in Figure 4.
  • Theta axis and the Phi axis represent the theta angle and the phi angle of the spherical coordinate system (in degrees), and the height represents the far field.
  • the magnitude of the field pattern vector is shown in Figure 4.
  • FIG. 5 A magnitude plot of the estimated value of the DUT far-field pattern is shown in Figure 5.
  • Figure 6 represents the magnitude diagram of the difference between the estimated value of the far-field pattern and the true value of the far-field pattern, and the relative error recovered by the algorithm is less than 3%.
  • An embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the electromagnetic field near-field testing method provided in an embodiment of the present application is implemented. A step of.
  • FIG. 7 shows a specific structural block diagram of a computer device provided by an embodiment of the present application.
  • a computer device 100 includes: one or more processors 101, memory 102, and one or more computer programs, wherein the processor 101 and the memory 102 are connected by a bus, the one or more computer programs are stored in the memory 102, and configured to be executed by the one or more processors 101, and the processor 101 executes the
  • the computer program is used to implement the steps of the electromagnetic field near-field testing method provided in an embodiment of the present application.
  • Computer equipment includes servers and terminals, etc.
  • the computer device may be a desktop computer, a mobile terminal, or a vehicle-mounted device, and the mobile terminal includes at least one of a mobile phone, a tablet computer, a personal digital assistant, or a wearable device.
  • steps in the embodiments of the present application are not necessarily executed sequentially in the order indicated by the step numbers. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution of these sub-steps or stages The order is not necessarily performed sequentially, but may be performed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.
  • Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
  • SRAM Static RAM
  • DRAM Dynamic RAM
  • SDRAM Synchronous DRAM
  • DDRSDRAM Double Data Rate SDRAM
  • ESDRAM Enhanced SDRAM
  • SLDRAM Synchronous Chain Synchlink DRAM
  • Rambus direct RAM
  • DRAM direct memory bus dynamic RAM
  • RDRAM memory bus dynamic RAM

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Abstract

本申请适用于测试领域，提供了一种电磁场近场测试方法、***、计算机可读存储介质及计算机设备。所述方法包括：在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数；获取所有探头采集到的电磁场信号测量值，得到测量值集合；根据测量值集合和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，并通过凸优化算法求解出DUT的电磁场系数；根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。本申请需要的测量点比传统算法少得多，极大提高了测试效率，且对DUT电磁场的计算范围要比传统方法的要广。

Description

电磁场近场测试方法、***、可读存储介质及计算机设备 技术领域
本申请属于测试领域，尤其涉及一种电磁场近场测试方法、***、计算机可读存储介质及计算机设备。
背景技术
传统的电磁场近场测试方法包括：平面近场测试方法、柱面近场测试方法以及球面近场测试方法。这些近场测试方法分别是在平面坐标系、柱面坐标系以及球面坐标系下对物理方程中的洛伦茨互易定理进行离散，使得待求变量(例如DUT(Device Under Test，待测物)的平面波系数、柱面波系数或球面波系数)与探头采集到的测量值呈傅里叶变换关系，这种关系使得探头的测量点是在采样平面、采样柱面或采样球面上固定的网格点，网格点的间隔满足Nyquist采样定律，即网格点的间隔为半波长。当DUT的工作频率增加时，所需要的测量点总数会急剧增多。例如在给定一个正方形测量区域内，传统的平面近场测试方法需要至少(2/λ) 2个在正方形测量区域内的测量点才能求解出DUT的远场方向图，λ表示波长，与工作频率成反比。因此当DUT的工作频率增加时，传统的电磁场近场测试方法所需的测量点总数就随着工作频率的平方成正比的增长，测试效率也就随工作频率的平方成正比的下降，从而极大限制了其在高频率场景(如5G，6G的DUT)的测试效率。
技术问题
本申请的目的在于提供一种电磁场近场测试方法、***、计算机可读存储介质及计算机设备，旨在解决当DUT的工作频率增加时，传统的电磁场近场测试方法所需的测量点总数就随着工作频率的平方成正比的增长，测试效率也就随工作频率的平方成正比的下降，从而极大限制了其在高频率场景的测试效率的问题。
技术解决方案
第一方面，本申请提供了一种电磁场近场测试***，包括计算机设备和分别与计算机设备连接的用于产生测试信号的信号源、信号接收机、运动装置和至少一探头，
其中信号源、信号接收机、探头和待测物DUT形成测试信号的闭合链路；
所述运动装置用于接受所述计算机设备的控制，使DUT和探头发生随机相对运动，产生多个随机测量点；
当所述探头与所述信号接收机连接时，所述信号源与DUT连接，当所述探头与所述信号源连接时，所述信号接收机与DUT连接，所述探头用于采集多个随机测量点的电磁场信号测量值，并直接传输给所述信号接收机或者传输给DUT后再由DUT传输给所述信号接收机；
所述信号接收机用于对所述探头采集的电磁场信号测量值进行分析处理后提供给计算机设备；
所述计算机设备用于选择任意一个坐标系，使得待求的DUT的电磁场系数呈现出稀疏特征；在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数；获取经信号接收机分析处理后的所有探头采集到的电磁场信号测量值，得到测量值集合；根据测量值集合和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，并通过凸优化算法求解出DUT的电磁场系数，并根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
第二方面，本申请提供了一种电磁场近场测试方法，所述方法包括：
选择任意一个坐标系，使得待求的DUT的电磁场系数呈现出稀疏特征；
在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数；
获取所有探头采集到的电磁场信号测量值，得到测量值集合；
根据测量值集合、随机测量点的位置和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，通过凸优化算法求解出DUT的电磁场系数；
根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
第三方面，本申请提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如所述的电磁场近场测试方法的步骤。
第四方面，本申请提供了一种计算机设备，包括：
一个或多个处理器；
存储器；以及
一个或多个计算机程序，所述处理器和所述存储器通过总线连接，其中所述一个或多个计算机程序被存储在所述存储器中，并且被配置成由所述一个或多个处理器执行，其特征在于，所述处理器执行所述计算机程序时实现如所述的电磁场近场测试方法的步骤。
有益效果
在本申请中，由于选择的是使得待求的DUT的电磁场系数呈现出稀疏特征的坐标系，所以求解出的DUT的电磁场系数呈现出稀疏特征，在该坐标系下选择多个随机测量点，因此测量值集合与待求的DUT的电磁场系数呈随机线性关系，因此求解DUT的电磁场系数问题就可以归约为一个目标函数为凸函数的凸优化问题，从而可以通过凸优化算法来求解出DUT的电磁场系数。又由于探头是在多个随机测量点采集电磁场信号测量值，因此当DUT为中高增益DUT时，本申请需要的测量点比传统算法少得多即可求解出DUT的远场方向图等信息，这样就极大提高了测试效率。实验发现仅需要1/25于传统平面近场的采样点即可对DUT的远场方向图进行很好的恢复。
附图说明
图1是本申请一实施例提供的电磁场近场测试***的示意图一。
图2是本申请一实施例提供的电磁场近场测试***的示意图二。
图3是本申请一实施例提供的电磁场近场测试方法的流程图。
图4是DUT远场方向图真值的幅值图。
图5是DUT远场方向图估算值的幅值图。
图6是DUT远场方向图估算值与远场方向图真值之差的幅值图。
图7是本申请一实施例提供的计算机设备的具体结构框图。
本发明的实施方式
为了使本申请的目的、技术方案及有益效果更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
为了说明本申请所述的技术方案，下面通过具体实施例来进行说明。
请参阅图1和图2，本申请一实施例提供的电磁场近场测试***包括计算机设备14和分别与计算机设备14连接的用于产生测试信号的信号源11、信号接收机12、运动装置13和至少一探头15，其中信号源11、信号接收机12、探头15和DUT 16形成测试信号的闭合链路；
所述运动装置13用于接受所述计算机设备14的控制，使DUT 16和探头15发生随机相对运动，产生多个随机测量点；
当所述探头15与所述信号接收机12连接时，所述信号源11与DUT16连接，当所述探头15与所述信号源11连接时，所述信号接收机12与DUT16连接，所述探头15用于采集多个随机测量点的电磁场信号测量值，并直接传输给所述信号接收机或者传输给DUT后再由DUT传输给所述信号接收机；
信号接收机12用于对所述探头采集的电磁场信号测量值进行分析处理后提供给计算机设备；进行分析处理具体可以包括射频信号去噪声、采样、求解幅度、相位等；
所述计算机设备14用于选择任意一个坐标系，使得待求的DUT 16的电磁场系数呈现出稀疏特征；在选择的坐标系下，控制运动装置13使DUT 16和探头15发生随机相对运动，产生多个随机测量点，并确定探头15的一个或多个姿态，得出分别与探头15的姿态对应的电磁场系数；获取经所述信号接收机分析处理后的所有探头15采集到的电磁场信号测量值，得到测量值集合；根据测量值集合和分别与探头15的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，并通过凸优化算法求解出DUT的电磁场系数，并根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
计算机设备14与信号源11、信号接收机12、运动装置13和至少一探头15连接，主要是用于控制信号源11、信号接收机12、运动装置13和至少一探头15，并进行数据传输。
在本申请一实施例中，所述电磁场信号测量值可以包括频率、幅值、相位信息等中的一种或任意组合。
凸优化算法是指一种比较特殊的优化，是指目标函数为凸函数且由约束条件得到的定义域为凸集的优化问题。
在本申请一实施例中，运动装置可以是与DUT连接，以控制DUT运动，也可以是与探头连接，以控制探头运动，也可以是同时与DUT和探头连接，以控制DUT和探头运动。
在本申请一实施例中，信号源可以是独立的外部信号发射装置，也可以是射频器件(例如DUT或探头)中自带的信号发射装置。信号接收机可以是独立的外部信号接收装置，也可以是射频器件(例如DUT或探头)中自带的信号接收装置。DUT可以是任意的无线通信装置，例如天线、雷达、手机等。
在本申请一实施例中，信号源和信号接收机可以是一体的，也可以是分别独立的装置。
在本申请一实施例中，信号源、信号接收机、探头和DUT形成测试信号 的闭合链路具体举例如下：
如图1所示，信号通过信号源发射出来，由探头探测到，然后经过空间，传输给DUT，再由DUT传输给信号接收机。或者，
如图2所示，信号通过信号源发射出来，然后经过DUT辐射出来，然后经过空间，最后由探头探测到，进而再进入信号接收机。
计算机设备可以监控到发射和接收的信号参数，通过这些参数来反演DUT的特性。
请参阅图3，是本申请一实施例提供的电磁场近场测试方法的流程图，本实施例主要以该电磁场近场测试方法应用于计算机设备为例来举例说明。本申请一实施例提供的电磁场近场测试方法包括以下步骤：
S101、选择任意一个坐标系，使得待求的DUT的电磁场系数呈现出稀疏特征。
例如如果电磁场系数是平面波系数，那么在三维空间内旋转任意一个正交的直角坐标系都可以作为能稀疏表达电磁场系数的坐标系。
S102、在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数。
在本申请一实施例中，S102具体可以为：
在选择的坐标系下，定义随机分布的测量点，在DUT以外的空间区域Ω c随机生成N个测量点p i，1≤i≤N，N是大于1的自然数；
以探头中心点为原点，确定探头在选择的坐标系下对应的K个姿态，K是大于或等于1的自然数；
根据探头的规格以及探头的K个姿态，得出分别与探头的K个姿态对应的K个电磁场系数。
S103、获取所有探头采集到的电磁场信号测量值，得到测量值集合。
在本申请一实施例中，S103具体可以为：
获取所有探头采集到的电磁场信号测量值，得到测量值集合
Figure PCTCN2021122419-appb-000001
Figure PCTCN2021122419-appb-000002
其中
Figure PCTCN2021122419-appb-000003
表示探头位于j姿态，位于测量点p i时，对DUT的测量值。
S104、根据测量值集合、随机测量点的位置和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，通过凸优化算法求解出DUT的电磁场系数。
在本申请一实施例中，S104具体可以为：
将待求的DUT的电磁场系数的稀疏特性用一个凸函数f(v)来描述，由洛伦茨互易定律所约束的DUT的电磁场系数v和测量值集合
Figure PCTCN2021122419-appb-000004
之间存在的随机线性关系
Figure PCTCN2021122419-appb-000005
作为约束条件或者优化领域里的惩罚函数，凸函数f(v)和随机线性关系
Figure PCTCN2021122419-appb-000006
结合成凸优化算法，其中A为随机矩阵，A的元素由随机测量点的位置以及探头在各个姿态对应的电磁场系数来决定；
当
Figure PCTCN2021122419-appb-000007
作为约束条件时，凸优化算法写为
Figure PCTCN2021122419-appb-000008
Figure PCTCN2021122419-appb-000009
当
Figure PCTCN2021122419-appb-000010
作为惩罚函数时，凸优化算法写为
Figure PCTCN2021122419-appb-000011
Figure PCTCN2021122419-appb-000012
其中P(.)为凸函数，随着向量
Figure PCTCN2021122419-appb-000013
的模增加而增加，因此式(1)和式(2)均为经典的凸规划问题，可用经典的凸优化算法进行求解，解得的变量v即为DUT的电磁场系数。
S105、根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
由于当DUT的电磁波系数的类型确定后，DUT的电磁波系数所对应的基函数就确定了，如当DUT的电磁波系数为平面波系数，那么其基函数就是平面波向量函数，如当DUT的电磁波系数为球面波系数，那么其基函数就是球面波向量函数。
因此在本申请一实施例中，S105具体可以为：
根据DUT的电磁场系数对应的基函数
Figure PCTCN2021122419-appb-000014
当S104解出DUT的电磁场系数v以后，对于DUT以外的任意一点x的电场E(x)和磁场H(x)分别表达为
Figure PCTCN2021122419-appb-000015
其中，
Figure PCTCN2021122419-appb-000016
是与电场相关的基函数，
Figure PCTCN2021122419-appb-000017
是与磁场相关的基函数。
根据电磁学中的洛伦茨互易定律，探头在某一个状态对DUT的测量值可表示为DUT的电磁场系数(即待求变量)与探头在该状态的电磁场系数(已知变量)的线性耦合。
由于本申请中，选择的是使得待求的DUT的电磁场系数呈现出稀疏特征的坐标系，所以求解出的DUT的电磁场系数呈现出稀疏特征，在该坐标系下选择多个随机测量点，因此测量值集合与待求的DUT的电磁场系数呈随机线性关系，因此求解DUT的电磁场系数问题就可以归约为一个目标函数为凸函数的凸优化问题，从而可以通过凸优化算法来求解出DUT的电磁场系数。又由于探头是在多个随机测量点采集电磁场信号测量值，因此当DUT为中高增益DUT时，本申请需要的测量点比传统算法少得多即可求解出DUT的远场方向图等信息，这样就极大提高了测试效率。实验发现仅需要1/25于传统平面近场的采样点即可对DUT的远场方向图进行很好的恢复。假如DUT是一个高增益天线，其远场方向图真值的幅值图如图4所示，Theta轴、Phi轴分别代表球面坐标系的theta角、phi角(单位是度)，高度代表远场方向图向量的幅值。DUT远场方向图估算值的幅值图如图5所示。图6代表远场方向图估算值与远场方向图真值之差的幅值图，算法恢复的相对误差低于3％。
本申请一实施例提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如本申请一实施例提供的电磁场近场测试方法的步骤。
图7示出了本申请一实施例提供的计算机设备的具体结构框图，一种计算机设备100包括：一个或多个处理器101、存储器102、以及一个或多个计算机程序，其中所述处理器101和所述存储器102通过总线连接，所述一个或多个计算机程序被存储在所述存储器102中，并且被配置成由所述一个或多个处理器101执行，所述处理器101执行所述计算机程序时实现如本申请一实施例提供的电磁场近场测试方法的步骤。计算机设备包括服务器和终端等。该计算机设备可以是台式计算机、移动终端或车载设备，移动终端包括手机、平板电脑、个人数字助理或可穿戴设备等中的至少一种。
应该理解的是，本申请各实施例中的各个步骤并不是必然按照步骤标号指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，各实施例中至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的程序可存储于一非易失性计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM (ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。

Claims (10)

  1. 一种电磁场近场测试***，其特征在于，包括计算机设备和分别与计算机设备连接的用于产生测试信号的信号源、信号接收机、运动装置和至少一探头，其中信号源、信号接收机、探头和待测物DUT形成测试信号的闭合链路；
    所述运动装置用于接受所述计算机设备的控制，使DUT和探头发生随机相对运动，产生多个随机测量点；
    当所述探头与所述信号接收机连接时，所述信号源与DUT连接，当所述探头与所述信号源连接时，所述信号接收机与DUT连接，所述探头用于采集多个随机测量点的电磁场信号测量值，并直接传输给所述信号接收机或者传输给DUT后再由DUT传输给所述信号接收机；
    所述信号接收机用于对所述探头采集的电磁场信号测量值进行分析处理后提供给计算机设备；
    所述计算机设备用于选择任意一个坐标系，使得待求的DUT的电磁场系数呈现出稀疏特征；在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数；获取经所述信号接收机分析处理后所有探头采集到的电磁场信号测量值，得到测量值集合；根据测量值集合和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，并通过凸优化算法求解出DUT的电磁场系数，并根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
  2. 如权利要求1所述的***，其特征在于，所述运动装置与DUT连接，以控制DUT运动；或者，所述运动装置与探头连接，以控制探头运动；或者，所述运动装置同时与DUT和探头连接，以控制DUT和探头运动。
  3. 如权利要求1所述的***，其特征在于，所述信号源是独立的外部信号发射装置或者是射频器件中自带的信号发射装置；所述信号接收机是独立的外部信号接收装置或者是射频器件中自带的信号接收装置；
    或者，所述信号源和信号接收机是一体的。
  4. 一种电磁场近场测试方法，其特征在于，所述方法包括：
    S101、选择任意一个坐标系，使得待求的DUT的电磁场系数呈现出稀疏特征；
    S102、在选择的坐标系下，控制运动装置使DUT和探头发生随机相对运动，产生多个随机测量点，并确定探头的一个或多个姿态，得出分别与探头的姿态对应的电磁场系数；
    S103、获取所有探头采集到的电磁场信号测量值，得到测量值集合；
    S104、根据测量值集合、随机测量点的位置和分别与探头的姿态对应的电磁场系数，根据电磁学中的洛伦茨互易定律，通过凸优化算法求解出DUT的电磁场系数；
    S105、根据所述DUT的电磁场系数得到DUT的远场方向图或者DUT以外任意一点的电场和/或磁场。
  5. 如权利要求4所述的方法，其特征在于，所述S102具体为：
    在选择的坐标系下，定义随机分布的测量点，在DUT以外的空间区域Ω c随机生成N个测量点p i，1≤i≤N，N是大于1的自然数；
    以探头中心点为原点，确定探头在选择的坐标系下对应的K个姿态，K是大于或等于1的自然数；
    根据探头的规格以及探头的K个姿态，得出分别与探头的K个姿态对应的K个电磁场系数。
  6. 如权利要求5所述的方法，其特征在于，所述S103具体为：
    获取所有探头采集到的电磁场信号测量值，得到测量值集合
    Figure PCTCN2021122419-appb-100001
    Figure PCTCN2021122419-appb-100002
    其中
    Figure PCTCN2021122419-appb-100003
    表示探头位于j姿态，位于测量点p i时，对DUT的测量值。
  7. 如权利要求6所述的方法，其特征在于，所述S104具体为：
    将待求的DUT的电磁场系数的稀疏特性用一个凸函数f(v)来描述，由洛伦 茨互易定律所约束的DUT的电磁场系数v和测量值集合
    Figure PCTCN2021122419-appb-100004
    之间存在的随机线性关系
    Figure PCTCN2021122419-appb-100005
    作为约束条件或者优化领域里的惩罚函数，凸函数f(v)和随机线性关系
    Figure PCTCN2021122419-appb-100006
    结合成凸优化算法，其中A为随机矩阵，A的元素由随机测量点的位置以及探头在各个姿态对应的电磁场系数来决定；
    当
    Figure PCTCN2021122419-appb-100007
    作为约束条件时，凸优化算法写为
    Figure PCTCN2021122419-appb-100008
    当
    Figure PCTCN2021122419-appb-100009
    作为惩罚函数时，凸优化算法写为
    Figure PCTCN2021122419-appb-100010
    其中P(.)为凸函数，随着向量
    Figure PCTCN2021122419-appb-100011
    的模增加而增加，式(1)和式(2)用凸优化算法进行求解，解得的变量v即为DUT的电磁场系数。
  8. 如权利要求7所述的方法，其特征在于，所述S105具体为：
    根据DUT的电磁场系数对应的基函数
    Figure PCTCN2021122419-appb-100012
    对于DUT以外的任意一点x的电场E(x)和磁场H(x)分别表达为
    Figure PCTCN2021122419-appb-100013
    和
    Figure PCTCN2021122419-appb-100014
    其中，
    Figure PCTCN2021122419-appb-100015
    是与电场相关的基函数，
    Figure PCTCN2021122419-appb-100016
    是与磁场相关的基函数。
  9. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求4至8任一项所述的电磁场近场测试方法的步骤。
  10. 一种计算机设备，包括：
    一个或多个处理器；
    存储器；以及
    一个或多个计算机程序，所述处理器和所述存储器通过总线连接，其中所述一个或多个计算机程序被存储在所述存储器中，并且被配置成由所述一个或多个处理器执行，其特征在于，所述处理器执行所述计算机程序时实现如权利要求4至8任一项所述的电磁场近场测试方法的步骤。
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US20100308824A1 (en) * 2009-05-27 2010-12-09 Siemens Corporation Method for reconstructing images of an imaged subject from a parallel mri acquisition
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CN105866772A (zh) * 2016-04-18 2016-08-17 浙江大学 一种基于微波相干成像的新型人体内金属物体定位方法
CN111239730A (zh) * 2020-01-19 2020-06-05 浙江大学 一种基于时间反转和压缩感知的电磁非视线成像方法
CN113139157A (zh) * 2021-04-22 2021-07-20 中山香山微波科技有限公司 一种dut主能量方向的计算方法和计算机设备

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US20100308824A1 (en) * 2009-05-27 2010-12-09 Siemens Corporation Method for reconstructing images of an imaged subject from a parallel mri acquisition
US20120081114A1 (en) * 2009-05-27 2012-04-05 Daniel Weller System for Accelerated MR Image Reconstruction
CN105866772A (zh) * 2016-04-18 2016-08-17 浙江大学 一种基于微波相干成像的新型人体内金属物体定位方法
CN111239730A (zh) * 2020-01-19 2020-06-05 浙江大学 一种基于时间反转和压缩感知的电磁非视线成像方法
CN113139157A (zh) * 2021-04-22 2021-07-20 中山香山微波科技有限公司 一种dut主能量方向的计算方法和计算机设备

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