System and method for testing radio frequency performance of antenna

Abstract

The invention provides an antenna radio frequency performance test system and method, and relates to the technical field of antenna testing, the system adopts an intelligent signal source module, uses a quantum random number generator to generate a test signal of an ultra-wide frequency spectrum, and an adaptive matching network module can automatically adjust impedance according to impedance characteristics of an antenna to be tested. The space electromagnetic environment reconstruction module accurately simulates various electromagnetic environments through an electromagnetic radiation source and a wave-absorbing material, the multi-dimensional signal acquisition module simultaneously acquires electric field, magnetic field, phase and frequency spectrum information, and the intelligent analysis and diagnosis module analyzes signal data by using an artificial intelligence algorithm and performs fault diagnosis based on a machine learning model. In general, the system and the method improve the comprehensiveness, the accuracy and the intelligentization of the antenna test, and provide a new test solution for the field of wireless communication.

Description

Technical Field

[0001] The present invention relates to the technical field of antenna testing, and more specifically, to a system and method for testing antenna radio frequency performance. Background Art

[0002] In today's era of rapid development of wireless communications, antennas play a vital role. The quality of their RF performance directly determines key indicators such as communication quality and coverage. Traditional antenna RF performance test systems and methods have gradually failed to meet the needs. From the perspective of signal sources, in the early days, they could only generate signals with conventional frequency bands and simple modulation, which made it difficult to simulate the complex high-frequency, ultra-wideband and diverse modulation methods of real signal scenarios such as 5G and even future 6G communications. This limits the accurate testing of antenna performance in actual complex communication environments. In terms of test environment simulation, in the past, only basic electromagnetic environments could be constructed. For multipath effects, complex interference sources, and special application scenarios such as aerospace and deep-sea communications, the test results were not accurate. Insufficient simulation of the end environment leads to deviations between the test results and actual usage. In terms of signal acquisition, traditional methods often focus on a single dimension, such as measuring only the electric field strength or power, etc., and lack the synchronous acquisition of multi-dimensional information such as electric field, magnetic field, phase, and spectrum, resulting in the inability to fully grasp the antenna characteristics. The analysis methods also rely more on basic algorithms. It is difficult to deeply explore the performance details in the face of complex RF signals. With the advancement of science and technology, new technologies have brought about a turning point. For example, microelectromechanical systems (MEMS) technology can create highly sensitive sensors, quantum technology is expected to generate test signals with special performance, high-speed digital signal processing chips can quickly process large amounts of data, and artificial intelligence algorithms can intelligently analyze the results, bringing new ways to antenna testing technology.

[0003] The existing technology has existing technical problems: narrow spectrum, poor impedance matching, single environmental simulation, few signal acquisition dimensions, and unintelligent fault diagnosis. Summary of the invention

[0004] In order to overcome the problems of narrow spectrum, poor impedance matching, single environmental simulation, few signal acquisition dimensions, and unintelligent fault diagnosis in the prior art, the present invention designs a test system and method for antenna RF performance that can effectively solve the above technical problems.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A test system for antenna radio frequency performance, comprising:

[0007] Intelligent signal source module, used to generate test signals with ultra-wide spectrum and precisely controllable frequency based on quantum random number generator;

[0008] An adaptive matching network module, connected to the intelligent signal source module, automatically adjusting its own impedance according to the impedance characteristics of the antenna to be tested;

[0009] The space electromagnetic environment reconstruction module accommodates the antenna to be tested and accurately reconstructs different space electromagnetic environments through multiple sets of adjustable electromagnetic radiation sources and absorbing materials;

[0010] A multi-dimensional signal acquisition module is connected to the antenna to be tested, and simultaneously collects the electric field strength, magnetic field strength, phase and signal spectrum information radiated by the antenna to be tested under the test signal excitation and specific electromagnetic environment;

[0011] The intelligent analysis and diagnosis module is connected to the multi-dimensional signal acquisition module, and uses an artificial intelligence algorithm to analyze the collected multi-dimensional signals, determine the radio frequency performance parameters of the antenna to be tested, and perform fault diagnosis on the antenna to be tested based on a machine learning model.

[0012] Preferably, the intelligent signal source module comprises:

[0013] Quantum random number generation unit, which generates true random number sequences based on the principles of quantum physics;

[0014] A frequency synthesis and control unit receives the true random number sequence and generates a test signal of a specific frequency according to a preset frequency control algorithm;

[0015] The signal conditioning unit performs power amplification and filtering processing on the generated test signal.

[0016] Preferably, the adaptive matching network module comprises:

[0017] An impedance detection unit, for detecting the impedance value of the antenna to be tested in real time;

[0018] A control unit, which calculates adjustment parameters required for the matching network according to the detected impedance value and generates a control instruction;

[0019] The adjustable impedance network unit adjusts the impedance of the antenna to be tested according to the control instruction of the control unit.

[0020] Preferably, the space electromagnetic environment reconstruction module includes:

[0021] An electromagnetic radiation source array unit, consisting of a plurality of independently controllable electromagnetic radiation sources, for generating electromagnetic waves of different frequencies, intensities and polarizations;

[0022] The absorbing material array units are distributed in the electromagnetic environment reconstruction cabin and are used to absorb and adjust the reflection and scattering of the electromagnetic waves;

[0023] The environment control computer unit controls the working states of the electromagnetic radiation source array unit and the absorbing material array unit according to preset electromagnetic environment parameters, so as to realize accurate reconstruction of the electromagnetic environment.

[0024] Preferably, the multi-dimensional signal acquisition module includes:

[0025] a sensor unit, comprising an electric field sensor and a magnetic field sensor;

[0026] The phase measurement unit uses the phase-locked loop technology to accurately measure the radiation phase of the antenna to be measured;

[0027] The spectrum analysis unit uses a high-speed digital signal processing chip to perform spectrum analysis on the collected multi-dimensional signals.

[0028] Preferably, the intelligent analysis and diagnosis module includes:

[0029] A data preprocessing unit performs denoising and normalization processing on the collected multi-dimensional signal data;

[0030] A performance parameter calculation unit, which calculates the antenna's gain, directivity and standing wave ratio radio frequency performance parameters based on a pre-trained neural network model;

[0031] A fault diagnosis unit performs fault diagnosis on the antenna to be tested according to the radio frequency performance parameters using a neural network model optimized by a genetic algorithm.

[0032] A method for testing antenna radio frequency performance comprises the following steps:

[0033] Generate a test signal with an ultra-wide spectrum and precisely controllable frequency. When generating the test signal, a true random number sequence is generated by a quantum random number generator, and then a test signal of a specific frequency is generated based on the true random number sequence by frequency synthesis and control. The test signal is determined based on the quantum random number generator to ensure the randomness and low correlation of the signal.

[0034] Automatically adjust the impedance according to the impedance characteristics of the antenna to be tested, detect the impedance of the antenna to be tested in real time, calculate the adjustment parameters of the matching network according to the detection results and send control instructions to adjust the impedance to achieve the best match with the antenna to be tested;

[0035] Construct a specific spatial electromagnetic environment, control the electromagnetic radiation source to generate corresponding electromagnetic waves according to the preset electromagnetic environment parameters, and adjust the state of the absorbing material, including the intensity of the incident electromagnetic waves in different directions, polarization mode, and spatial interference signal distribution;

[0036] Collecting the electric field strength, magnetic field strength, phase and signal spectrum information of the antenna to be tested under the test signal excitation and specific electromagnetic environment;

[0037] The collected multi-dimensional signal data is processed to calculate the radio frequency performance parameters of the antenna to be tested, and to diagnose whether the antenna to be tested has a fault. If a fault exists, the fault type and location are determined.

[0038] An electronic device, comprising:

[0039] A memory storing executable program code;

[0040] a processor coupled to the memory;

[0041] The processor calls the executable program code stored in the memory to execute the above-mentioned method for testing the antenna radio frequency performance.

[0042] A computer storage medium stores computer instructions, which, when called, are used to execute the above-mentioned method for testing antenna radio frequency performance.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows: by adopting an intelligent signal source module, a test signal with an ultra-wide spectrum and precisely controllable frequency is generated based on a quantum random number generator, thereby solving the problem of narrow spectrum, so that the test signal can cover a wider frequency range and adapt to the antenna test requirements of different frequency bands; the adaptive matching network module can automatically adjust the impedance according to the impedance characteristics of the antenna to be tested, thereby achieving the best match with the antenna to be tested and effectively solving the problem of poor impedance matching; this module detects the impedance value of the antenna to be tested in real time, and calculates the adjustment parameters required for the matching network according to the detection results, thereby dynamically adjusting the impedance to ensure signal transmission efficiency and test accuracy; in terms of space electromagnetic environment simulation, the system uses a plurality of groups of adjustable electromagnetic radiation sources and absorbing materials through a space electromagnetic environment reconstruction module, Accurately reconstructing different spatial electromagnetic environments breaks the limitation of single environmental simulation and provides a more realistic and diverse test environment for antenna testing. The introduction of the multi-dimensional signal acquisition module enables the system to simultaneously collect the electric field strength, magnetic field strength, phase and signal spectrum information radiated by the antenna to be tested, which not only increases the dimension of signal acquisition, but also provides richer data support for the comprehensive evaluation of the performance of the antenna to be tested. Finally, the intelligent analysis and diagnosis module uses artificial intelligence algorithms to analyze the collected multi-dimensional signals, determine the RF performance parameters of the antenna to be tested, and perform fault diagnosis on the antenna to be tested based on the machine learning model, solving the problem of unintelligent fault diagnosis. This method not only improves the accuracy of fault diagnosis, but also shortens the diagnosis time, providing strong technical support for the maintenance and optimization of the antenna to be tested. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0045] Figure 1 The structure diagram of a test system for antenna radio frequency performance is shown;

[0046] Figure 2 A step diagram of a method for testing antenna radio frequency performance. DETAILED DESCRIPTION

[0047] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0048] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0049] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0050] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0051] Example 1

[0052] A test system for antenna radio frequency performance, such as Figure 1 As shown, including:

[0053] Intelligent signal source module, used to generate test signals with ultra-wide spectrum and precisely controllable frequency based on quantum random number generator;

[0054] The quantum random number generator is based on the quantum uncertainty principle. For example, it uses quantum phenomena such as quantum entanglement or random flipping of quantum bits to generate true random number sequences with extremely high randomness. These sequences lay the foundation for the subsequent generation of diversified and unpredictable test signals. After receiving the true random number sequence, the frequency synthesis and control unit combines complex digital signal processing algorithms with precise frequency synthesis technology to quickly and accurately generate test signals of specific frequencies within an extremely wide frequency range, such as from a few megahertz to the terahertz level. It can flexibly switch between different frequency bands according to the preset test plan to simulate the signal frequency characteristics in various actual communication scenarios. The signal conditioning unit amplifies the generated test signal and uses high-efficiency and high-linearity power amplifier components to meet the signal strength requirements of different types of antenna tests. At the same time, high-performance filters are used to remove spurious frequency components, noise and harmonics in the signal to ensure that the output test signal has pure spectrum characteristics and reduce interference with the test results.

[0055] An adaptive matching network module, connected to the intelligent signal source module, automatically adjusting its own impedance according to the impedance characteristics of the antenna to be tested;

[0056] The impedance detection unit adopts high-precision impedance measurement technology to monitor the impedance value changes of the antenna to be tested in real time and continuously. It can use advanced technical means such as high-frequency signal injection method or reflection coefficient measurement method to quickly and accurately obtain the impedance information of the antenna. The control unit runs a specially designed intelligent algorithm based on the detected impedance data to calculate the adjustment parameters required for the matching network. The algorithm comprehensively considers the changes in the real and imaginary parts of the antenna impedance and the optimal matching conditions for signal transmission to achieve minimum signal reflection and maximum power transmission efficiency. The adjustable impedance network unit quickly changes its own impedance according to the control instructions generated by the control unit by adjusting internal variable capacitors, inductors and other passive components or using active impedance matching technology to dynamically match the impedance of the antenna to be tested. This adaptive adjustment capability is particularly important when the antenna operating frequency changes or the antenna's own characteristics change due to environmental factors. It can always keep the signal transmission link in the best matching state to ensure the accuracy and reliability of the test.

[0057] The space electromagnetic environment reconstruction module accommodates the antenna to be tested and accurately reconstructs different space electromagnetic environments through multiple sets of adjustable electromagnetic radiation sources and absorbing materials;

[0058] The electromagnetic radiation source array unit is composed of multiple independently controllable electromagnetic radiation sources. These radiation sources use advanced radio frequency transmission technology and can generate electromagnetic waves of different frequencies, intensities and polarization modes. For example, the emission frequency of the radiation source can be accurately set through digital frequency synthesis technology, the intensity of the electromagnetic wave can be controlled by a power amplifier, and the switching of different polarization modes such as linear polarization, circular polarization or elliptical polarization can be achieved with the help of a polarization adjustment device. The absorbing material array units are distributed in specific positions in the electromagnetic environment reconstruction cabin and use high-performance absorbing materials, such as ferrite absorbing materials, carbon fiber absorbing materials, etc., which can effectively absorb and adjust the reflection and scattering of electromagnetic waves. The environment control computer unit serves as the control core of the entire module. It accurately controls the working status of the electromagnetic radiation source array unit and the absorbing material array unit according to the preset electromagnetic environment parameters. It can construct various complex space electromagnetic environments through complex electromagnetic simulation algorithms and real-time feedback adjustment mechanisms, such as simulating the multipath propagation environment in the city, strong electromagnetic interference environment, such as radar frequency band interference, industrial electromagnetic noise interference, and electromagnetic environment in special application scenarios, such as the cosmic ray background electromagnetic environment in satellite communications, and the high-salinity seawater electromagnetic environment in deep-sea communications, etc., to provide conditions for comprehensively testing the RF performance of the antenna in different actual environments.

[0059] A multi-dimensional signal acquisition module is connected to the antenna to be tested, and simultaneously collects the electric field strength, magnetic field strength, phase and signal spectrum information radiated by the antenna to be tested under the test signal excitation and specific electromagnetic environment;

[0060] The electric field sensor in the sensor unit is based on micro-electromechanical system (MEMS) technology, and has the characteristics of miniaturization, high sensitivity and fast response. Its sensitive structure adopts a special capacitive or piezoelectric design, which can convert weak electric field changes into measurable electrical signals. The minimum detectable electric field strength can reach the nanovolt per meter level. The magnetic field sensor uses the Hall effect principle or magnetic sensor technology based on magnetic resonance phenomenon to accurately measure the magnetic field strength and can accurately capture the slight changes in the magnetic field around the antenna. The measurement accuracy can reach the micro-Tesla level. The phase measurement unit adopts high-precision phase-locked loop technology. By comparing the phase of the input signal with the local reference signal, it can accurately measure the phase information of the signal. The phase measurement accuracy can reach the millidegree level. The spectrum analysis unit uses a high-speed digital signal processing chip and adopts the fast Fourier transform (FFT) algorithm or other advanced spectrum analysis algorithms to perform spectrum analysis on the collected signals. It can process a large amount of signal data in a very short time and realize high-resolution spectrum analysis. The spectrum resolution can reach the Hertz level, thereby clearly showing the energy distribution and frequency components of the signal at different frequencies, providing rich spectrum information for comprehensive evaluation of the antenna's RF performance.

[0061] The intelligent analysis and diagnosis module is connected to the multi-dimensional signal acquisition module, and uses an artificial intelligence algorithm to analyze the collected multi-dimensional signals, determine the radio frequency performance parameters of the antenna to be tested, and perform fault diagnosis on the antenna to be tested based on a machine learning model.

[0062] The data preprocessing unit first performs denoising on the collected multi-dimensional signal data, and uses advanced signal processing technologies such as wavelet transform and adaptive filtering to effectively remove the impact of environmental noise, measurement equipment noise and other interference signals on the original data. Then, the data is converted to a unified numerical range through normalization processing to facilitate subsequent analysis and processing. The performance parameter calculation unit is based on a pre-trained neural network model. The model has been trained with a large amount of antenna sample data and can accurately calculate the key RF performance parameters of the antenna such as gain, directivity, standing wave ratio, etc. based on the collected electric field strength, magnetic field strength, phase and spectrum information. For example, when calculating the gain, the model comprehensively considers the electric field and magnetic field strength in different directions. The distribution relationship and phase information of the antenna are used to calculate the radiation gain of the antenna in all directions through a complex mathematical model. The fault diagnosis unit uses the neural network model optimized by the genetic algorithm to diagnose the antenna fault according to the calculated RF performance parameters. The genetic algorithm improves the diagnostic accuracy and generalization ability of the model by optimizing the weights and structure of the neural network. When abnormal antenna performance is detected, the model can accurately determine the fault type based on the abnormal performance parameter characteristics, such as antenna element damage, feeder failure, matching network imbalance, etc., and accurately locate the fault location by analyzing the abnormal performance of the signal in different dimensions, providing strong support for antenna maintenance and repair, and improving the reliability and stability of the antenna system.

[0063] The intelligent signal source module comprises:

[0064] Quantum random number generation unit, which generates true random number sequences based on the principles of quantum physics;

[0065] A frequency synthesis and control unit receives the true random number sequence and generates a test signal of a specific frequency according to a preset frequency control algorithm;

[0066] The signal conditioning unit performs power amplification and filtering processing on the generated test signal.

[0067] After the antenna RF performance test system is started, the quantum random number generation unit starts working first. It uses a photon pair generation device based on quantum entanglement. After the photon pair is generated, the polarization state of one of the photons is randomly measured. Due to the characteristics of quantum entanglement, the polarization state of the other photon will be instantly determined and present a completely random state. This random polarization state information is converted into a binary digital sequence to obtain a true random number sequence. This sequence is generated at an extremely high rate, such as billions of bits per second, to ensure the randomness and diversity of subsequent signal generation.

[0068] After receiving the true random number sequence, the frequency synthesis and control unit processes it according to the preset frequency control algorithm. Assuming that the current test requirement is to simulate the signal test of the 5G communication frequency band and some potential future communication frequency bands, the algorithm will first parse the true random number sequence and extract the key information used to determine the frequency range and step value. For example, the initial frequency is determined based on the random number, and a starting point is randomly selected between 3GHz-3.5GHz. Then, the frequency is scanned within the frequency band with a random step value of 1MHz. The frequency synthesizer uses direct digital frequency synthesis (DDS) technology, combined with a high-performance clock source and digital signal processing chip, to quickly convert these randomly determined frequency parameters into corresponding analog signal frequencies. In a very short time, such as a few microseconds, a test signal with a specific frequency can be generated, and the frequency stability is extremely high, with the error controlled within ±1Hz.

[0069] After the signal conditioning unit receives the test signal generated by the frequency synthesis and control unit, the power amplifier circuit starts to work. If the current test is an antenna for an outdoor long-distance communication base station, according to the pre-set test parameters and antenna specifications, the power amplifier increases the signal power from the initial milliwatt level to the appropriate level of 10 watts. The power amplifier adopts a high-efficiency ClassAB amplification architecture with good linearity. While amplifying the signal power, it can minimize signal distortion. At the same time, the filter circuit starts to process the amplified signal. It uses a 7th-order bandpass filter with a center frequency set at the center of the current test frequency band. The bandwidth is set to 100MHz according to the spectral characteristics of the signal and the test requirements. This filter can effectively remove spurious frequency components in the signal, such as suppressing all frequency components below 2.9GHz and above 3.6GHz, as well as possible harmonic signals. After filtering, the spectral purity of the test signal is greatly improved, and the spurious suppression ratio reaches more than 50dB, thereby obtaining a test signal with appropriate power and pure spectrum, which is ready to be transmitted to the subsequent adaptive matching network module for antenna testing.

[0070] The adaptive matching network module comprises:

[0071] An impedance detection unit, for detecting the impedance value of the antenna to be tested in real time;

[0072] A control unit, which calculates adjustment parameters required for the matching network according to the detected impedance value and generates a control instruction;

[0073] The adjustable impedance network unit adjusts the impedance of the antenna to be tested according to the control instruction of the control unit.

[0074] In the antenna RF performance test system, when the test process is started, the impedance detection unit starts working. It uses a high-frequency signal injection method to inject a weak high-frequency signal with a specific frequency value, such as 100MHz, into the antenna to be tested, and then obtains the signal reflected by the antenna through a high-precision signal acquisition device. The reflection coefficient calculation formula is used to compare and analyze the amplitude and phase information of the reflected signal and the incident signal. After a series of complex mathematical operations, the current impedance value of the antenna to be tested is calculated. This impedance value includes real and imaginary parts, which can accurately reflect the antenna's obstruction characteristics to signal transmission in the current state. After the control unit receives the antenna impedance value from the impedance detection unit, it immediately calls the internally stored intelligent matching algorithm program. The algorithm is constructed based on a large number of antenna theoretical models and actual test data, and can quickly calculate the ideal adjustment parameters of the matching network according to different antenna impedance conditions. For example, if it is detected that the real part of the antenna impedance is large and the imaginary part is small, it indicates that the antenna is The control unit will calculate the need to add a certain amount of inductance value to the adjustable impedance network unit based on the algorithm, and appropriately reduce the capacitance value at the same time to offset the resistive influence of the antenna and adjust the reactance part to match the output impedance of the signal source. After the calculation is completed, the control unit generates detailed control instructions, which include specific adjustment actions and target parameter values ​​for each variable element in the adjustable impedance network unit. After receiving the control instruction from the control unit, the adjustable impedance network unit quickly performs the impedance adjustment operation. Assuming that the adjustable impedance network unit is composed of multiple variable capacitors and variable inductors, when the instruction requires adjusting the inductance of a certain variable inductor, the motor is driven by the electrical signal sent by the control unit, and the motor drives the movement of the inductor core to change the position of the core in the coil, thereby accurately changing the inductance. For the variable capacitor, by changing the voltage applied to the capacitor plates, the effective capacitance value between the capacitor plates is changed by using the polarization characteristics of the dielectric. During the adjustment process, each variable element cooperates with each other and gradually adjusts its own parameters according to the control instructions until the impedance of the entire adjustable impedance network unit reaches the best matching state with the impedance of the antenna to be tested. For example, after adjustment, when the test signal output from the intelligent signal source module is transmitted to the antenna, the reflection coefficient is reduced to a minimum value, such as below 0.05, and the signal can be received and radiated by the antenna to the maximum extent, which effectively improves the accuracy and reliability of the test and lays a good foundation for the subsequent RF performance testing of the antenna under different frequencies, different signal strengths and different electromagnetic environments.

[0075] The space electromagnetic environment reconstruction module includes:

[0076] An electromagnetic radiation source array unit, consisting of a plurality of independently controllable electromagnetic radiation sources, for generating electromagnetic waves of different frequencies, intensities and polarizations;

[0077] The absorbing material array units are distributed in the electromagnetic environment reconstruction cabin and are used to absorb and adjust the reflection and scattering of the electromagnetic waves;

[0078] The environment control computer unit controls the working states of the electromagnetic radiation source array unit and the absorbing material array unit according to preset electromagnetic environment parameters, so as to realize accurate reconstruction of the electromagnetic environment.

[0079] First, set detailed electromagnetic environment parameters in the environmental control computer unit according to the test requirements. For example, to simulate a specific scenario in a complex urban electromagnetic environment, set multiple interference signals of different intensities and polarizations in the 900MHz-1.8GHz frequency band, and at the same time have a stronger main interference source in the 2.4GHz frequency band, and simulate a multipath reflection environment.

[0080] The environment control computer unit sends instructions to the electromagnetic radiation source array unit according to these preset parameters, and each electromagnetic radiation source in the electromagnetic radiation source array unit starts to work. Some of the radiation sources are set to generate electromagnetic waves of different intensities ranging from -50dBm to -10dBm at a specific frequency interval, such as 10MHz, within the 900MHz-1.8GHz frequency band, and the polarization modes include vertical polarization, horizontal polarization, and 45-degree tilted polarization to simulate the stray interference signals within the frequency band. For the main interference source of 2.4GHz, a specific electromagnetic radiation source is adjusted to this frequency, and the output intensity is set to a stronger signal of -5dBm, using circular polarization to simulate strong interference sources such as Wi-Fi hotspots.

[0081] At the same time, the absorbing material array unit functions under the control of the environmental control computer unit. In some areas where electromagnetic wave reflection needs to be reduced, such as the rear and side parts close to the antenna to be tested, the environmental control computer unit instructs to increase the density and thickness of the absorbing material. These absorbing materials use new composite absorbing materials, which have a good absorption effect on electromagnetic waves in the 900MHz-2.4GHz frequency band and can reduce the intensity of reflected waves by more than 80%. In some areas where specific reflection paths need to be simulated, the scattering direction and intensity of the electromagnetic waves are controlled by adjusting the angle and distribution density of the absorbing material. For example, a partial absorbing and partial reflecting structure is set on one side 3 meters away from the antenna to be tested, so that the electromagnetic waves are reflected back at a preset angle to simulate the reflection effect of buildings in an urban environment.

[0082] Through the coordinated work of the electromagnetic radiation source array unit and the absorbing material array unit, a spatial electromagnetic environment that is highly similar to the preset scene is accurately constructed in the electromagnetic environment reconstruction cabin. In this environment, the antenna to be tested is subjected to electromagnetic waves similar to the complex electromagnetic environment of the actual city, including multi-frequency interference, signals of different polarization modes, and multipath reflection, etc., so that the RF performance of the antenna in this complex electromagnetic environment can be more realistically tested, such as anti-interference ability, stability of signal reception, and signal quality under multipath effects, etc., providing a reliable testing basis for the optimization design and performance evaluation of the antenna.

[0083] The multi-dimensional signal acquisition module comprises:

[0084] a sensor unit, comprising an electric field sensor and a magnetic field sensor;

[0085] The phase measurement unit uses the phase-locked loop technology to accurately measure the radiation phase of the antenna to be measured;

[0086] The spectrum analysis unit uses a high-speed digital signal processing chip to perform spectrum analysis on the collected multi-dimensional signals.

[0087] When the antenna to be tested is in a specific electromagnetic environment constructed by the space electromagnetic environment reconstruction module and receives the test signal transmitted from the intelligent signal source module via the adaptive matching network module, the multi-dimensional signal acquisition module starts to operate.

[0088] The electric field sensor in the sensor unit adopts a capacitive electric field sensor structure based on a micro-electromechanical system (MEMS). Its tiny capacitor plates can sensitively sense changes in the electric field strength around the antenna. When the electric field acts on the plates, it causes changes in the capacitance value between the plates. The change in capacitance value is converted into a voltage signal output through a high-precision capacitance measurement circuit. The electric field sensor has a high sensitivity of nanovolts per meter and can accurately capture the weak electric field signals radiated by the antenna. The magnetic field sensor uses the principle of magnetoresistance effect and uses special magnetic materials to make sensitive elements. When the magnetic field passes through the element, its resistance value changes. The change in resistance is converted into a voltage signal through a Wheatstone bridge circuit, thereby realizing accurate measurement of the magnetic field strength. Its measurement accuracy can reach the micro-Tesla level.

[0089] The phase measurement unit works using phase-locked loop technology. It first inputs the signal radiated by the antenna to be measured and an internal high-precision reference signal into the phase detector at the same time. The phase detector compares the phase difference between the two signals and outputs an error voltage signal proportional to the phase difference. This error voltage signal is filtered out by a low-pass filter to remove high-frequency noise, and then input into the voltage-controlled oscillator (VCO) to control the frequency and phase of the VCO so that the phase of the VCO output signal gradually approaches the phase of the signal to be measured. Through a continuous feedback adjustment process, the VCO output signal and the signal to be measured are finally made highly consistent in phase. At this time, the phase information of the signal to be measured can be accurately obtained from the control voltage of the VCO, and its phase measurement accuracy can reach the millidegree level.

[0090] The spectrum analysis unit uses a high-speed digital signal processing chip, such as an advanced field programmable gate array (FPGA) chip combined with a digital signal processing algorithm. It first performs high-speed sampling of the multi-dimensional signal containing electric field and magnetic field information collected by the sensor unit and the phase information obtained by the phase measurement unit, with a sampling rate of up to several gigahertz. Then, the fast Fourier transform (FFT) algorithm is used to perform spectrum conversion on the sampled time domain signal, converting the signal from the time domain to the frequency domain. During the spectrum conversion process, by reasonably setting the number of FFT points and the sampling frequency, extremely high spectrum resolution can be achieved, for example, a resolution of 1 Hz or even smaller can be achieved. In this way, the energy distribution of the antenna radiation signal at different frequencies can be clearly obtained, and the spectrum composition of the signal, including the fundamental frequency, each harmonic frequency, and possible spurious frequency components, can be accurately analyzed, providing a rich and accurate spectrum data basis for a comprehensive evaluation of the antenna's RF performance, and helping to gain an in-depth understanding of the antenna's radiation characteristics at different frequencies, bandwidth performance, and key indicators such as signal purity.

[0091] The intelligent analysis and diagnosis module includes:

[0092] A data preprocessing unit performs denoising and normalization processing on the collected multi-dimensional signal data;

[0093] A performance parameter calculation unit, which calculates the antenna's gain, directivity and standing wave ratio radio frequency performance parameters based on a pre-trained neural network model;

[0094] A fault diagnosis unit performs fault diagnosis on the antenna to be tested according to the radio frequency performance parameters using a neural network model optimized by a genetic algorithm.

[0095] When the multi-dimensional signal acquisition module completes the signal acquisition of the antenna to be tested, the data is transmitted to the intelligent analysis and diagnosis module. The data preprocessing unit first processes the collected multi-dimensional signal data and uses the wavelet transform algorithm for denoising. It decomposes the signal into sub-bands of different frequencies. By setting appropriate thresholds, it removes those sub-band components with low energy and mainly caused by noise, thereby effectively reducing the impact of environmental noise, measurement equipment noise and other interference signals on the original data. For example, high-frequency noise spikes in the electric field strength signal and weak fluctuation noise in the magnetic field signal can be accurately removed. After that, normalization processing is performed to map the denoised electric field strength, magnetic field strength, phase and spectrum data to a unified numerical range according to specific rules, such as normalizing all data to between 0 and 1. The performance parameter calculation unit works based on a pre-trained neural network model, which is trained with a large number of test data of different types of antennas in various standard and non-standard electromagnetic environments. When calculating the antenna gain, the neural network model comprehensively considers the distribution data of the electric field strength and magnetic field strength in different directions and the phase information. For example, by analyzing the electric field and magnetic field strength data of multiple sampling points in the horizontal and vertical directions of the antenna, combined with the phase change of the signal, and using the complex neuron connections and weight calculations within the neural network, the radiation gain value of the antenna in all directions can be accurately obtained. The calculation error is significantly reduced compared with the traditional calculation method and can be controlled within ±0.Within 1dB, for the calculation of directivity, the model judges the characteristics such as the concentration direction and beam width of the antenna radiation energy according to the difference in signal strength in different directions and the change law of phase. When calculating the standing wave ratio, the standing wave ratio value is obtained through the reasoning calculation of the neural network based on the collected signal reflection data and transmission characteristics, which can accurately reflect the matching degree between the antenna and the transmission line. The fault diagnosis unit uses the neural network model optimized by the genetic algorithm to make fault judgments. The genetic algorithm first optimizes and adjusts the initial weights and structure of the neural network model, and finds the optimal combination of neural network model parameters by simulating the inheritance, crossover and mutation operations in the biological evolution process, so as to improve the generalization ability and diagnostic accuracy of the model. When the performance parameter calculation unit obtains the RF performance parameters of the antenna, the fault The diagnostic unit inputs these parameters into the optimized neural network model. For example, if the calculated antenna gain is far below the normal range in a certain direction, and the directivity diverges abnormally, and the standing wave ratio is too large, the model will combine these abnormal parameter characteristics to comprehensively judge the fault type. It may be that the antenna array is damaged, resulting in reduced radiation efficiency and poor directivity; or there is a short circuit or open circuit problem in the feeder, causing the standing wave ratio to increase abnormally. In addition, the model can further accurately locate the fault location based on the abnormal performance of the signal in different dimensions, such as determining whether it is a specific array in the antenna array, or a problem with a connection point near the antenna end of the feeder, etc., providing valuable guidance information for the subsequent maintenance and optimization of the antenna, effectively improving the reliability and maintenance efficiency of the antenna system. .

[0096] Example 2

[0097] A method for testing the radio frequency performance of an antenna, such as Figure 2 As shown, the following steps are included:

[0098] Generate a test signal with an ultra-wide spectrum and precisely controllable frequency. When generating the test signal, a true random number sequence is generated by a quantum random number generator, and then a test signal of a specific frequency is generated based on the true random number sequence by frequency synthesis and control. The test signal is determined based on the quantum random number generator to ensure the randomness and low correlation of the signal.

[0099] Automatically adjust the impedance according to the impedance characteristics of the antenna to be tested, detect the impedance of the antenna to be tested in real time, calculate the adjustment parameters of the matching network according to the detection results and send control instructions to adjust the impedance to achieve the best match with the antenna to be tested;

[0100] Construct a specific spatial electromagnetic environment, control the electromagnetic radiation source to generate corresponding electromagnetic waves according to the preset electromagnetic environment parameters, and adjust the state of the absorbing material, including the intensity of the incident electromagnetic waves in different directions, polarization mode, and spatial interference signal distribution;

[0101] Collecting the electric field strength, magnetic field strength, phase and signal spectrum information of the antenna to be tested under the test signal excitation and specific electromagnetic environment;

[0102] The collected multi-dimensional signal data is processed to calculate the radio frequency performance parameters of the antenna to be tested, and to diagnose whether the antenna to be tested has a fault. If a fault exists, the fault type and location are determined.

[0103] An electronic device, comprising:

[0104] A memory storing executable program code;

[0105] a processor coupled to the memory;

[0106] The processor calls the executable program code stored in the memory to execute the above-mentioned method for testing the antenna radio frequency performance.

[0107] A computer storage medium stores computer instructions, which, when called, are used to execute the above-mentioned method for testing antenna radio frequency performance.

[0108] Generate a test signal and turn on the quantum random number generator, which uses the uncertainty principle of quantum states. For example, in quantum optical systems, a true random number sequence is generated by measuring the random polarization state changes of single photons. This sequence is transmitted to the frequency synthesis and control unit.

[0109] The frequency synthesis and control unit generates the test signal frequency based on the received true random number sequence and the preset frequency generation rules. For example, it is set in a wide frequency band, such as 1GHz-6GHz, and generates the test signal frequency according to random frequency steps, such as 100kHz-1MHz random changes, and then converts it into an actual test signal using digital frequency synthesis technology to ensure that the signal spectrum covers a wide range and the frequency is accurate.

[0110] Impedance matching adjustment: the impedance detection unit transmits a low-power, specific frequency, such as 300MHz, detection signal to the antenna to be tested, and calculates the impedance value of the antenna by analyzing the characteristics of the reflected signal.

[0111] The control unit uses a built-in matching algorithm to calculate the adjustment parameters of the variable capacitor and inductor in the adjustable impedance network unit based on the detected impedance value and generates a control instruction.

[0112] The adjustable impedance network unit adjusts the variable element according to the instruction to achieve good impedance matching between the antenna and the signal source, for example, reducing the reflection coefficient to below 0.1.

[0113] Constructing the electromagnetic environment, the environment control computer unit controls the electromagnetic radiation source array unit according to the preset electromagnetic environment requirements. For example, some radiation sources are set to generate electromagnetic wave simulation interference signals of different intensities (-40dBm--20dBm) and polarizations (vertical or horizontal) at 800MHz-1.2GHz, and at the same time there is a specific polarization interference source of -10dBm at 2.4GHz.

[0114] The absorbing material array unit adjusts the layout and angle of the absorbing material in specific areas according to the instructions. For example, it increases the density of absorbing materials behind the antenna to reduce reflection, and adjusts the angle in certain areas to simulate special reflection paths, thereby constructing an electromagnetic environment similar to the actual usage scenario.

[0115] Signal acquisition: The electric field sensor (based on MEMS technology) and the magnetic field sensor (using the Hall effect) respectively collect the electric field strength and magnetic field strength signals radiated by the antenna, convert them into electrical signals and transmit them.

[0116] The phase measurement unit uses phase-locked loop technology to accurately measure the signal phase by comparing the phase difference between the antenna signal and the reference signal, with an accuracy of up to ±0.5 degrees.

[0117] The spectrum analysis unit uses a high-speed digital signal processing chip to sample and analyze the collected signals, with a sampling rate of 5GHz and a spectrum resolution of 10Hz to obtain signal spectrum information.

[0118] Data processing and analysis,The data preprocessing unit uses a simple filtering algorithm to remove,the obvious noise in the signal, and then normalizes the electric,magnetic field, phase and spectrum data to make their,values ​​range between 0-1.

[0119] The performance parameter calculation unit inputs the processed data into a pre-trained neural network model to calculate parameters such as the antenna gain, directivity and standing wave ratio. For example, the gain is calculated through the distribution of electric and magnetic field strengths, the directivity is determined based on the change in signal strength in different directions, and the standing wave ratio is obtained based on the reflected signal.

[0120] The fault diagnosis unit uses a neural network model optimized based on a genetic algorithm to determine whether the antenna is faulty based on the calculated performance parameters. If there is a fault, such as abnormally low gain and high standing wave ratio, the model is combined to determine that the antenna element may be damaged or the feeder is faulty, and the approximate fault location is determined.

[0121] The electronic device uses an ordinary desktop computer as its hardware basis, and the storage is the hard disk and memory of the computer. The hard disk stores the software program of the antenna test system, including the execution code of the above-mentioned test method, neural network model data, and test data records, etc. The memory is used to temporarily store data and variables when the program is running during the test process, etc. The processor is the CPU of the computer. When running the test program, the CPU reads the program code from the hard disk to the memory and executes it. It calls the code of related functional modules in sequence according to the steps of the test method, such as driving the quantum random number generator hardware interface to generate random numbers, controlling the frequency synthesizer to generate test signals, communicating with the impedance detection hardware to obtain impedance values ​​and calculate matching parameters, controlling the working status of the electromagnetic radiation source and the absorbing material array, processing the collected signal data, etc., and improving the processing efficiency through multi-threading technology to complete the antenna RF performance test process.

[0122] The computer storage medium uses an ordinary USB flash drive, and the written antenna RF performance test software program, including the code of the above-mentioned test method and related configuration files, neural network model parameter files, etc. are stored in the USB flash drive. When the antenna test is needed, the USB flash drive is inserted into the USB port of the desktop computer. After the computer operating system recognizes it, the test program can be directly run. The data generated during the test, such as the collected signal data, calculated performance parameters and fault diagnosis results, can also be stored back in the USB flash drive, which is convenient for data transfer and preservation, so as to facilitate further analysis and evaluation of the antenna performance.

[0123] The same or similar reference numerals correspond to the same or similar components;

[0124] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0125] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A test system for antenna radio frequency performance, characterized in that: include: Intelligent signal source module, used to generate test signals with ultra-wide spectrum and precisely controllable frequency based on quantum random number generator; An adaptive matching network module, connected to the intelligent signal source module, automatically adjusting its own impedance according to the impedance characteristics of the antenna to be tested; The space electromagnetic environment reconstruction module accommodates the antenna to be tested and accurately reconstructs different space electromagnetic environments through multiple sets of adjustable electromagnetic radiation sources and absorbing materials; A multi-dimensional signal acquisition module is connected to the antenna to be tested, and simultaneously collects the electric field strength, magnetic field strength, phase and signal spectrum information radiated by the antenna to be tested under the test signal excitation and specific electromagnetic environment; The intelligent analysis and diagnosis module is connected to the multi-dimensional signal acquisition module, and uses an artificial intelligence algorithm to analyze the collected multi-dimensional signals, determine the radio frequency performance parameters of the antenna to be tested, and perform fault diagnosis on the antenna to be tested based on a machine learning model.

2. The antenna radio frequency performance testing system according to claim 1, characterized in that: The intelligent signal source module comprises: Quantum random number generation unit, which generates true random number sequences based on the principles of quantum physics; A frequency synthesis and control unit receives the true random number sequence and generates a test signal of a specific frequency according to a preset frequency control algorithm; The signal conditioning unit performs power amplification and filtering processing on the generated test signal.

3. The antenna radio frequency performance testing system according to claim 1, characterized in that: The adaptive matching network module comprises: An impedance detection unit, for detecting the impedance value of the antenna to be tested in real time; A control unit, which calculates adjustment parameters required for the matching network according to the detected impedance value and generates a control instruction; The adjustable impedance network unit adjusts the impedance of the antenna to be tested according to the control instruction of the control unit.

4. The antenna radio frequency performance testing system according to claim 1, characterized in that: The space electromagnetic environment reconstruction module includes: An electromagnetic radiation source array unit, consisting of a plurality of independently controllable electromagnetic radiation sources, for generating electromagnetic waves of different frequencies, intensities and polarizations; The absorbing material array units are distributed in the electromagnetic environment reconstruction cabin and are used to absorb and adjust the reflection and scattering of the electromagnetic waves; The environment control computer unit controls the working states of the electromagnetic radiation source array unit and the absorbing material array unit according to preset electromagnetic environment parameters, so as to realize accurate reconstruction of the electromagnetic environment.

5. The antenna radio frequency performance testing system according to claim 1, characterized in that: The multi-dimensional signal acquisition module comprises: a sensor unit, comprising an electric field sensor and a magnetic field sensor; The phase measurement unit uses the phase-locked loop technology to accurately measure the radiation phase of the antenna to be measured; The spectrum analysis unit uses a high-speed digital signal processing chip to perform spectrum analysis on the collected multi-dimensional signals.

6. The antenna radio frequency performance testing system according to claim 1, characterized in that: The intelligent analysis and diagnosis module includes: A data preprocessing unit performs denoising and normalization processing on the collected multi-dimensional signal data; A performance parameter calculation unit, which calculates the antenna's gain, directivity and standing wave ratio radio frequency performance parameters based on a pre-trained neural network model; A fault diagnosis unit performs fault diagnosis on the antenna to be tested according to the radio frequency performance parameters using a neural network model optimized by a genetic algorithm.

7. A method for testing antenna radio frequency performance, used to implement a system for testing antenna radio frequency performance as claimed in any one of claims 1 to 6, characterized in that: The following steps are involved: Generate a test signal with an ultra-wide spectrum and precisely controllable frequency. When generating the test signal, a true random number sequence is generated by a quantum random number generator, and then a test signal of a specific frequency is generated based on the true random number sequence by frequency synthesis and control. The test signal is determined based on the quantum random number generator to ensure the randomness and low correlation of the signal. Automatically adjust the impedance according to the impedance characteristics of the antenna to be tested, detect the impedance of the antenna to be tested in real time, calculate the adjustment parameters of the matching network according to the detection results and send control instructions to adjust the impedance to achieve the best match with the antenna to be tested; Construct a specific spatial electromagnetic environment, control the electromagnetic radiation source to generate corresponding electromagnetic waves according to the preset electromagnetic environment parameters, and adjust the state of the absorbing material, including the intensity of the incident electromagnetic waves in different directions, polarization mode, and spatial interference signal distribution; Collecting the electric field strength, magnetic field strength, phase and signal spectrum information of the antenna to be tested under the test signal excitation and specific electromagnetic environment; The collected multi-dimensional signal data is processed to calculate the radio frequency performance parameters of the antenna to be tested, and to diagnose whether the antenna to be tested has a fault. If a fault exists, the fault type and location are determined.

8. An electronic device, characterized in that: The electronic device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the antenna radio frequency performance testing method as described in claim 7.

9. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the antenna radio frequency performance testing method as claimed in claim 7.

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