Metering equipment interference signal suppression method and system in electromagnetic compatibility test

Abstract

The invention discloses a metering equipment interference signal suppression method and system in an electromagnetic compatibility test, and the method comprises the steps: obtaining an input signal of metering equipment in the electromagnetic compatibility test, performing windowing processing on the input signal by adopting a self-adaptive fractional order window function, and then obtaining a frequency spectrum component of the input signal through self-adaptive fractional order Fourier transform; calculating the amplitude of the frequency spectrum component, comparing the amplitude with a power threshold value, and screening out the frequency spectrum component of the interference signal; establishing a spectrum model of the interference signal based on the interference signal spectrum component; and generating a frequency domain compensation signal considering interference signal phase correction, converting the frequency domain compensation signal into a time domain compensation signal, and superposing the time domain compensation signal and the input signal to obtain a signal after interference suppression. According to the method, the frequency spectrum characteristics of the signals in different frequency bands can be ensured to be clear, the interference signal components can be accurately identified, the energy distribution of the interference signals can be effectively simulated, and the high-efficiency interference suppression capability can still be kept in a variable signal environment.

Description

Technical Field

[0001] The invention belongs to the technical field of electromagnetic compatibility testing, and relates to a method and system for suppressing interference signals of metering equipment in electromagnetic compatibility testing. Background Art

[0002] In the context of the rapid development of modern electronic equipment, electromagnetic compatibility issues have become an important factor that cannot be ignored in equipment design, manufacturing and application. In electromagnetic compatibility testing, metrological equipment, as a precision measurement tool, is the core link to ensure product quality, equipment safety and industrial production efficiency. It is used to monitor, record and evaluate the performance of electronic equipment in a specific electromagnetic environment. It is sensitive to external electromagnetic interference and must be able to work accurately and reliably in a strong electromagnetic interference environment. However, since the metrological equipment itself may also be affected by interference signals, it may cause distortion of measurement data, reduced accuracy and even equipment damage. Therefore, it is of great significance to study and develop effective interference signal suppression methods.

[0003] The interference signal suppression technology of measuring equipment in electromagnetic compatibility testing can provide a strong guarantee for the stability and accuracy of measuring equipment to meet the increasingly stringent requirements of electromagnetic compatibility testing. However, the traditional interference signal suppression technology of measuring equipment in electromagnetic compatibility testing has at least the following technical problems: the traditional spectrum analysis method is limited by the limitations of the fixed window function, and it is impossible to dynamically adjust the analysis accuracy according to different signal characteristics, resulting in the inability to flexibly optimize the spectrum resolution, especially when the signal contains complex frequency components; the traditional method relies on a fixed power threshold or rough spectrum separation, resulting in the inability to accurately distinguish interference signals from valid signals; it is difficult to capture the nonlinear characteristics of the interference signal, resulting in poor compensation signal effect, especially in the case of broadband or complex frequency band interference signals, the interference cannot be effectively eliminated; when facing changing signals and interference environments, there is a problem of poor adaptability, the intensity and frequency components of the interference signal will change over time, resulting in the inability of the traditional method to effectively adapt to the changes, thus affecting the quality of the signal. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a method and system for suppressing interference signals of measuring equipment in an electromagnetic compatibility test.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of the present invention provides a method for suppressing interference signals of measuring equipment in an electromagnetic compatibility test, comprising:

[0007] The input signal of the measuring equipment in the electromagnetic compatibility test is obtained, and the input signal is windowed by using an adaptive fractional-order window function, and then the spectral component of the input signal is obtained by an adaptive fractional-order Fourier transform;

[0008] Calculate the amplitude of the spectral component and compare it with the power threshold dynamically adjusted according to the environmental noise, and select the spectral component with an amplitude greater than the power threshold as the spectral component of the interference signal;

[0009] Based on the spectral components of the interference signal, nonlinear adaptive frequency domain modeling is performed on the interference signal to obtain a spectral model of the interference signal;

[0010] A frequency domain compensation signal taking into account the phase correction of the interference signal is generated based on the spectrum model of the interference signal, and the frequency domain compensation signal is converted into a time domain compensation signal by using inverse Fourier transform. The time domain compensation signal is superimposed on the input signal to obtain the interference suppressed signal.

[0011] Preferably, the adaptive fractional-order window function is used to perform windowing processing on the input signal and then the spectral components of the input signal are obtained by adaptive fractional-order Fourier transform. The adaptive fractional-order Fourier transform formula is:

[0012]

[0013] Where S(k) represents the kth spectral component;

[0014] M represents the number of spectrum sampling points;

[0015] x(n) represents the input signal;

[0016] n represents the sampling point number of the input signal;

[0017] w(n) represents the adaptive fractional-order window function;

[0018] Represents the complex exponential term in Fourier transform;

[0019] e is the base of natural logarithms;

[0020] j is the imaginary unit;

[0021] α represents the fractional order parameter.

[0022] Preferably, the adaptive fractional-order window function is:

[0023]

[0024] Where n represents the sampling point number of the input signal;

[0025] N represents the number of sampling points of the input signal;

[0026] β represents the window function shape control parameter.

[0027] Preferably, the power threshold dynamically adjusted according to the environmental noise is specifically formulated as follows:

[0028]

[0029] Among them, P 0 (k) represents the power threshold;

[0030] γ represents the power gain coefficient;

[0031] x(n) represents the input signal;

[0032] n represents the sampling point number of the input signal;

[0033] N represents the number of sampling points of the input signal;

[0034] δ is the offset control constant of the power threshold.

[0035] Preferably, the interference signal is subjected to nonlinear adaptive frequency domain modeling based on the spectral component of the interference signal to obtain a spectral model of the interference signal, and the specific formula is:

[0036]

[0037] Wherein, H(k) represents the spectrum model of the interference signal;

[0038] S i (k) represents the kth spectral component of the i-th interference signal;

[0039] b represents the modeling parameters that control the spectral translation and scaling effects;

[0040] is the phase correction term for the interference signal;

[0041] e is the base of natural logarithms; j is the imaginary unit.

[0042] Preferably, the frequency domain compensation signal based on the spectrum model of the interference signal is generated considering the phase correction of the interference signal as follows:

[0043]

[0044] Wherein, C(k) represents the frequency domain compensation signal;

[0045] H(k) represents the spectrum model of the interference signal;

[0046] represents a complex exponential function used to correct the phase of the interference signal;

[0047] e is the base of natural logarithm; j is the imaginary unit;

[0048] μ represents the optimal adjustment parameter for compensating signal sensitivity or intensity;

[0049] γ represents the optimal adjustment parameter for controlling the adjustment accuracy of the compensation signal;

[0050] S i (k) represents the spectral component of the interference signal;

[0051] a represents the parameter controlling the compensation accuracy;

[0052] θ(k) represents the phase of the interference signal.

[0053] Preferably, the phase of the interference signal is as follows:

[0054]

[0055] Among them, tan -1 represents the inverse tangent function;

[0056] Im{S i (k)} represents the spectral component S of the interference signal i (k) the imaginary part;

[0057] Re{S i (k)} represents the spectral component S of the interference signal i The real part of (k).

[0058] Preferably, the frequency domain compensation signal is converted into a time domain compensation signal by using inverse Fourier transform, and the specific formula is as follows:

[0059]

[0060] Wherein, c(n) represents the time domain compensation signal;

[0061] M represents the number of spectrum sampling points;

[0062] C(k) represents the frequency domain compensation signal;

[0063] e is the base of natural logarithms;

[0064] j is the imaginary unit;

[0065] k represents the frequency domain sampling point;

[0066] n represents the sampling point number of the input signal.

[0067] The second aspect of the present invention provides a system for suppressing interference signals of measuring equipment in electromagnetic compatibility testing, comprising:

[0068] The spectrum component calculation module is used to obtain the input signal of the measuring equipment in the electromagnetic compatibility test, and the spectrum component of the input signal is obtained by adaptive fractional-order Fourier transform after windowing the input signal using an adaptive fractional-order window function;

[0069] A spectrum component screening module is used to calculate the amplitude of the spectrum component and compare it with the power threshold dynamically adjusted according to the environmental noise, and screen out the spectrum component with an amplitude greater than the power threshold as the spectrum component of the interference signal;

[0070] A spectrum model building module is used to perform nonlinear adaptive frequency domain modeling on the interference signal based on the spectrum components of the interference signal to obtain a spectrum model of the interference signal;

[0071] The signal compensation module is used to generate a frequency domain compensation signal taking into account the phase correction of the interference signal based on the spectrum model of the interference signal, and convert the frequency domain compensation signal into a time domain compensation signal by using inverse Fourier transform, and superimpose the time domain compensation signal with the input signal to obtain the interference suppressed signal.

[0072] A third aspect of the present invention provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0073] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0074] Compared with the prior art, the beneficial effects of the present invention include at least:

[0075] 1. The present invention uses an adaptive fractional-order window function to perform windowing processing on an input signal and then obtains the spectral component of the input signal through an adaptive fractional-order Fourier transform. Through the adaptive fractional-order window function and the adaptive fractional-order Fourier transform, the shape of the window function can be dynamically adjusted according to the characteristics of the input signal, thereby providing detailed signal spectrum characteristics in the time-frequency domain. The fractional-order parameters allow an optimized balance point to be found between high resolution and low resolution, thereby effectively improving the accuracy of spectrum analysis, having flexibility, ensuring that the spectral characteristics of signals in different frequency bands are clear, and can make real-time adjustments according to the different characteristics of the signal, avoiding the rigid limitations of traditional methods.

[0076] 2. The present invention achieves accurate identification of interference signal components by calculating the amplitude of each spectral component and comparing it with the power threshold dynamically adjusted according to the environmental noise. It can automatically adjust the power threshold based on the environmental noise to adapt to different signals and interference intensities, so that the interference signal can be accurately separated from the valid signal, effectively improving the accuracy of signal separation and enhancing adaptability in complex interference environments.

[0077] 3. The present invention performs nonlinear adaptive frequency domain modeling on the interference signal based on the spectral components of the interference signal. Specifically, by combining the square term of the amplitude, the square root term of the amplitude and the frequency modulation of the phase, the nonlinear characteristics of the interference signal can be accurately captured, especially the broadband or complex frequency band interference signal. The interference signal can be accurately modeled in the spectral domain, and the energy distribution of the interference signal can be effectively simulated, which provides an accurate basis for subsequent compensation and suppression, which not only improves the modeling accuracy, but also ensures strong adaptability to complex interference environments.

[0078] 4. In the process of interference signal compensation, the present invention can accurately generate a compensation signal and realize superposition with a phase opposite to the interference signal, thereby effectively suppressing the interference signal. By optimizing the amplitude and phase of the compensation signal, it is ensured that the compensation signal can accurately offset the influence of the interference signal in the time and frequency domain, thereby minimizing the influence of interference on the effective signal. The introduction of the first adjustment parameter, the second adjustment parameter and the parameter for controlling the compensation accuracy further improves the sensitivity and accuracy of interference suppression, so that the efficient interference suppression capability can still be maintained in a changing signal environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 The present invention is a flow chart of a method for suppressing interference signals of measuring equipment in an electromagnetic compatibility test. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0081] Embodiment 1 of the present invention provides a method for suppressing interference signals of measuring equipment in an electromagnetic compatibility test, such as Figure 1 As shown, the method comprises the following steps:

[0082] S1: Obtain the input signal of the measuring equipment in the electromagnetic compatibility test, use an adaptive fractional-order window function to perform windowing on the input signal, and then use an adaptive fractional-order Fourier transform to obtain the spectral component of the input signal;

[0083] Further preferably, a metering device is used to obtain an input signal, and an adaptive spectrum analysis algorithm is used to process the input signal to obtain a spectrum analysis result, as follows:

[0084] The input signal of the measuring equipment in the electromagnetic compatibility test is obtained. In order to identify the different frequency components in the input signal and extract the time-frequency characteristics of the different frequency components, the adaptive spectrum analysis algorithm is used to obtain the spectrum analysis result;

[0085] The adaptive spectrum analysis algorithm adopts an adaptive fractional-order window function to perform windowing processing on the signal. Compared with the traditional window function, the adaptive fractional-order window function uses a fractional-order parameter to dynamically adjust the spectrum concentration of the window function according to the signal characteristics when controlling the spectrum resolution. Specifically, the shape of the window function can change with the change of the fractional-order parameter, which helps to find a balance between high resolution and low resolution, so that the spectrum characteristics of the signal are clear within a specific frequency band;

[0086] The adaptive spectrum analysis algorithm uses adaptive fractional Fourier transform to analyze the spectrum characteristics of the signal, and can flexibly convert between the time domain and the frequency domain by adjusting the fractional order parameters, so that the representation in the time and frequency domain can maintain the time locality of the signal and take into account the accuracy of the frequency domain;

[0087] The calculation formula of spectral components is:

[0088]

[0089] In the above adaptive fractional Fourier transform formula, S(k) represents the kth spectral component, that is, the result of spectrum analysis, which provides the strength of the signal at different frequency points and reveals the spectral characteristics of the signal;

[0090] k represents the frequency domain sampling point, that is, the discrete point position sampled in the frequency domain;

[0091] x(n) represents the input signal;

[0092] M represents the number of spectrum sampling points, which determines the resolution of the signal in the frequency domain;

[0093] It means to sum the input signal from point n=0 to point n=M-1. Through the summation operation, the signal conversion from time domain to frequency domain can be realized;

[0094] It represents the complex exponential term in Fourier transform, reflecting the conversion of the signal from time domain to frequency domain. The real and imaginary parts of the complex exponential correspond to the conversion of the signal in sine and cosine frequency components respectively. e is the base of natural logarithm, and j is the imaginary unit.

[0095] 2π represents a full circle angle;

[0096] α represents the fractional order parameter, which determines the balance of time-frequency conversion and adjusts the level of detail of spectrum analysis. It can be set according to the specific implementation scenario and is not limited here.

[0097] w(n) represents an adaptive fractional-order window function, which is used to weight the input signal. It will be dynamically adjusted according to the characteristics of the input signal to optimize the accuracy of spectrum analysis. The calculation formula is:

[0098]

[0099] Where n represents each sampling point of the input signal;

[0100] N represents the number of sampling points of the input signal, which determines the length of the window function;

[0101] γ represents the window function morphology control parameter, which affects the width of the window function and controls the conversion balance between the time domain and the frequency domain of the signal. The larger the window width, the lower the spectrum resolution, and vice versa. By adjusting the window function morphology control parameter, the separation of different signal frequency components can be optimized. It can be set according to the specific implementation scenario and is not limited here.

[0102] The adaptive spectrum analysis algorithm can dynamically adjust the analysis parameters according to the characteristics of the signal by introducing adaptive fractional-order window function and adaptive fractional-order Fourier transform, thereby providing higher resolution and flexibility in different frequency ranges, thereby improving the effect of signal separation and interference suppression;

[0103] S2: Calculate the amplitude of the spectral component and compare it with the power threshold dynamically adjusted according to the environmental noise, and select the spectral component with an amplitude greater than the power threshold as the spectral component of the interference signal;

[0104] Further preferably, after the spectrum analysis, the spectrum components of the interference signal are extracted using an interference signal spectrum component extraction algorithm, as follows:

[0105] After completing the spectrum analysis, the interference signal spectrum component extraction algorithm is used to analyze the spectrum of the signal, calculate the amplitude of each spectrum component, and judge and filter the spectrum components in combination with the set power threshold, so as to extract the spectrum components of the interference signal;

[0106] For each spectral component, the amplitude of the spectral component needs to be calculated. The spectral component consists of a real part and an imaginary part. The calculation formula for the amplitude of the spectral component is as follows:

[0107]

[0108] Among them, |S(k)| represents the amplitude of the kth spectral component, which helps to determine the strength of the signal at different frequency components; S(k) represents the kth spectral component; Re{S(k)} represents the real part of the spectral component; Im{S(k)} represents the imaginary part of the spectral component;

[0109] The power threshold of the signal is used to distinguish whether the spectrum component belongs to the interference signal. The power threshold of the signal is dynamically adjusted according to the environmental noise to adapt to different interference strengths and signal characteristics. The calculation formula is as follows:

[0110]

[0111] Among them, P 0 (k) represents the power threshold of the signal; γ represents the power gain coefficient, which adjusts the sensitivity of the power threshold and can be set according to the specific implementation scenario and is not limited here; It represents the average power of the input signal, reflecting the overall strength of the input signal. The input signal power is directly related to the environmental noise. The higher the input signal power, the smaller the impact of the noise may be. Conversely, the impact of the noise is greater. δ represents a constant, which is used to control the offset of the power threshold. It can be set according to the specific implementation scenario and is not limited here.

[0112] The amplitude of each spectral component is compared with the corresponding power threshold. If the amplitude of the spectral component is greater than the power threshold of the signal, the spectral component is considered to be the main component of the interference signal. The formula is as follows:

[0113] S i (k)={S(k)||S(k)|>P 0 (k)}

[0114] Among them, S i (k) represents the kth spectral component of the i-th interference signal;

[0115] The extracted interference signal spectrum components are accurate identification and extraction of interference components in the input signal, which helps to optimize the effect of signal processing and reduce the impact of external interference;

[0116] S3: performing nonlinear adaptive frequency domain modeling on the interference signal based on the spectral components of the interference signal to obtain a spectral model of the interference signal;

[0117] Further preferably, a nonlinear adaptive frequency domain modeling algorithm is used to accurately model the interference signal based on the spectral components of the interference signal, and a spectral model of the interference signal is generated, as follows:

[0118] Using a nonlinear adaptive frequency domain modeling algorithm to accurately model the interference signal based on the spectral components of the interference signal, and generating a spectral model of the interference signal;

[0119] The nonlinear adaptive frequency domain modeling algorithm determines the energy distribution of the interference signal in the spectrum domain by performing accurate amplitude calculation on the extracted interference signal spectrum components; in order to accurately simulate the interference signal, a nonlinear modeling method is introduced, which combines the amplitude square term and the amplitude square root term of the signal through joint analysis of amplitude and phase information, and introduces frequency modulation of the phase, so as to accurately capture the nonlinear characteristics of the interference signal, especially when modeling broadband or complex frequency band interference signals, and shows extremely strong adaptability;

[0120] The calculation formula of the spectrum model of the interference signal is:

[0121]

[0122] Where H(k) represents the spectrum model of the interference signal; |S i (k)| represents the amplitude of the spectral component of the interference signal, reflecting the strength of the interference signal; b represents a modeling parameter, which is used to adjust the spectrum of the interference signal and control the translation and scaling effects of the spectrum. It can be set according to the specific implementation scenario and is not limited here; Indicates the phase correction of the interference signal; sin(|S i (k)| represents the sinusoidal operation of the interference signal amplitude. By transforming the interference signal amplitude sinusoidally, the phase correction is made smooth and accurate, thereby improving the quality of spectrum correction;

[0123] S4: Generate a frequency domain compensation signal taking into account the phase correction of the interference signal based on the spectrum model of the interference signal, and use inverse Fourier transform to convert the frequency domain compensation signal into a time domain compensation signal, and superimpose the time domain compensation signal with the input signal to obtain an interference suppressed signal.

[0124] Further preferably, an interference signal compensation and phase correction algorithm is used to calculate a compensation signal based on the spectrum model of the interference signal, and an inverse Fourier transform is used to convert the generated compensation signal from the frequency domain back to the time domain signal, and the time domain compensation signal is synthesized with the input signal to finally obtain an interference suppressed signal, as follows:

[0125] In order to effectively suppress interference signals and improve communication quality, an interference signal compensation and phase correction algorithm is used to generate a compensation signal based on the spectrum model of the interference signal, thereby offsetting the impact of the interference signal on the effective signal.

[0126] The interference signal compensation and phase correction algorithm calculates the phase of each frequency point through the real and imaginary parts of the signal. By decomposing the interference signal spectrum, the phase information of each frequency point can be obtained. The phase calculation adopts the inverse tangent function, and the return value is the phase angle. The amplitude and phase of the compensation signal are inversely proportional to the amplitude and phase of the interference signal, so that the two can cancel each other out after addition. The formula for generating the compensation signal combines the first adjustment parameter, the second adjustment parameter and the parameter for controlling the compensation accuracy, which can help adjust the accuracy and strength of the compensation signal to ensure that the interference signal is eliminated most effectively.

[0127] The frequency domain representation of the compensation signal is calculated as:

[0128]

[0129] Wherein, C(k) represents the frequency domain representation of the compensation signal, which is used to offset the interference part in the input signal; H(k) represents the spectrum model of the interference signal, which describes the characteristics of the interference signal in the frequency domain; represents a complex exponential function, which is used to correct the phase of the interference signal to ensure that the compensation signal can accurately offset the phase of the interference signal; μ represents the first adjustment parameter, which is used to optimize the compensation signal and adjust the sensitivity or strength of the compensation signal. It can be set according to the specific implementation scenario and is not limited here; γ represents the second adjustment parameter, which is used to optimize the compensation signal, further control the adjustment accuracy of the compensation signal, and affect the ability of the compensation signal to suppress interference. It can be set according to the specific implementation scenario and is not limited here; |S i (k)| a represents the a-th power of the amplitude of the frequency component of the interference signal, weights the signal amplitude, and controls the behavior of the compensation signal under different signal strengths; a represents the parameter for controlling the compensation accuracy, adjusts the weighting of the interference signal amplitude, affects the accuracy of the compensation signal, and can be set according to the specific implementation scenario, which is not limited here; θ(k) represents the phase of the interference signal, describes the phase information of the interference signal in the frequency domain, and is a key parameter in the compensation signal generation process, which is used to ensure that the phase of the compensation signal is opposite to that of the interference signal, thereby achieving interference cancellation. The specific calculation formula is:

[0130]

[0131] Among them, tan -1 represents the inverse tangent function, which is used to calculate the phase of the interference signal; Im{S i (k)} represents the imaginary part of the interference signal; Re{S i (k)} represents the real part of the interference signal;

[0132] The inverse Fourier transform is used to convert the generated compensation signal from the frequency domain back to the time domain signal. The specific formula is as follows:

[0133]

[0134] Wherein, c(n) represents a time domain compensation signal, which is obtained by inverse Fourier transform. The inverse Fourier transform method is a technical means well known to those skilled in the art and will not be described in detail here;

[0135] The time domain compensation signal is synthesized with the input signal to finally obtain the interference suppressed signal. The formula is as follows:

[0136] y(n)=x(n)+c(n)

[0137] Where y(n) represents the signal after interference suppression;

[0138] Through the synthesis operation, the input signal and the time domain compensation signal are superimposed in the time domain, so that the interference part in the input signal is effectively suppressed, thereby restoring the true characteristics of the signal, and completing a kind of interference signal suppression of the measurement equipment in the electromagnetic compatibility test.

[0139] Embodiment 2 of the present invention provides a system for suppressing interference signals of measuring equipment in an electromagnetic compatibility test, comprising:

[0140] The spectrum component calculation module is used to obtain the input signal of the measuring equipment in the electromagnetic compatibility test, and the spectrum component of the input signal is obtained by adaptive fractional-order Fourier transform after windowing the input signal using an adaptive fractional-order window function;

[0141] A spectrum component screening module is used to calculate the amplitude of the spectrum component and compare it with the power threshold dynamically adjusted according to the environmental noise, and screen out the spectrum component with an amplitude greater than the power threshold as the spectrum component of the interference signal;

[0142] A spectrum model building module is used to perform nonlinear adaptive frequency domain modeling on the interference signal based on the spectrum components of the interference signal to obtain a spectrum model of the interference signal;

[0143] The signal compensation module is used to generate a frequency domain compensation signal taking into account the phase correction of the interference signal based on the spectrum model of the interference signal, and convert the frequency domain compensation signal into a time domain compensation signal by using inverse Fourier transform, and superimpose the time domain compensation signal with the input signal to obtain the interference suppressed signal.

[0144] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0145] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0146] Compared with the prior art, the beneficial effects of the present invention include at least:

[0147] 1. The present invention uses an adaptive fractional-order window function to perform windowing processing on an input signal and then obtains the spectral component of the input signal through an adaptive fractional-order Fourier transform. Through the adaptive fractional-order window function and the adaptive fractional-order Fourier transform, the shape of the window function can be dynamically adjusted according to the characteristics of the input signal, thereby providing detailed signal spectrum characteristics in the time-frequency domain. The fractional-order parameters allow an optimized balance point to be found between high resolution and low resolution, thereby effectively improving the accuracy of spectrum analysis, having flexibility, ensuring that the spectral characteristics of signals in different frequency bands are clear, and can make real-time adjustments according to the different characteristics of the signal, avoiding the rigid limitations of traditional methods.

[0148] 2. The present invention achieves accurate identification of interference signal components by calculating the amplitude of each spectral component and comparing it with the power threshold dynamically adjusted according to the environmental noise. It can automatically adjust the power threshold based on the environmental noise to adapt to different signals and interference intensities, so that the interference signal can be accurately separated from the valid signal, effectively improving the accuracy of signal separation and enhancing adaptability in complex interference environments.

[0149] 3. The present invention performs nonlinear adaptive frequency domain modeling on the interference signal based on the spectral components of the interference signal. Specifically, by combining the square term of the amplitude, the square root term of the amplitude and the frequency modulation of the phase, the nonlinear characteristics of the interference signal can be accurately captured, especially the broadband or complex frequency band interference signal. The interference signal can be accurately modeled in the spectral domain, and the energy distribution of the interference signal can be effectively simulated, which provides an accurate basis for subsequent compensation and suppression, which not only improves the modeling accuracy, but also ensures strong adaptability to complex interference environments.

[0150] 4. In the process of interference signal compensation, the present invention can accurately generate a compensation signal and realize superposition with a phase opposite to the interference signal, thereby effectively suppressing the interference signal. By optimizing the amplitude and phase of the compensation signal, it is ensured that the compensation signal can accurately offset the influence of the interference signal in the time and frequency domain, thereby minimizing the influence of interference on the effective signal. The introduction of the first adjustment parameter, the second adjustment parameter and the parameter for controlling the compensation accuracy further improves the sensitivity and accuracy of interference suppression, so that the efficient interference suppression capability can still be maintained in a changing signal environment.

[0151] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0152] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0153] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0154] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing, characterized in that: include: The input signal of the measuring equipment in the electromagnetic compatibility test is obtained, and the input signal is windowed by using an adaptive fractional-order window function, and then the spectral component of the input signal is obtained by an adaptive fractional-order Fourier transform; Calculate the amplitude of the spectral component and compare it with the power threshold dynamically adjusted according to the environmental noise, and select the spectral component with an amplitude greater than the power threshold as the spectral component of the interference signal; Based on the spectral components of the interference signal, nonlinear adaptive frequency domain modeling is performed on the interference signal to obtain a spectral model of the interference signal; A frequency domain compensation signal taking into account the phase correction of the interference signal is generated based on the spectrum model of the interference signal, and the frequency domain compensation signal is converted into a time domain compensation signal by using inverse Fourier transform. The time domain compensation signal is superimposed on the input signal to obtain the interference suppressed signal.

2. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing according to claim 1 is characterized in that: The adaptive fractional-order window function is used to perform windowing processing on the input signal, and then the frequency spectrum component of the input signal is obtained by adaptive fractional-order Fourier transform. The adaptive fractional-order Fourier transform formula is: Where S(k) represents the kth spectral component; M represents the number of spectrum sampling points; x(n) represents the input signal; n represents the sampling point number of the input signal; w(n) represents the adaptive fractional-order window function; Represents the complex exponential term in Fourier transform; e is the base of natural logarithms; j is the imaginary unit; α represents the fractional order parameter.

3. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility test according to claim 2 is characterized in that: The adaptive fractional-order window function is: Where n represents the sampling point number of the input signal; N represents the number of sampling points of the input signal; β represents the window function shape control parameter.

4. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing according to claim 1 is characterized in that: The power threshold dynamically adjusted according to the environmental noise is specifically formulated as follows: Wherein, P0(k) represents the power threshold; γ represents the power gain coefficient; x(n) represents the input signal; n represents the sampling point number of the input signal; N represents the number of sampling points of the input signal; δ is the offset control constant of the power threshold.

5. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility test according to claim 1 is characterized in that: The interference signal is subjected to nonlinear adaptive frequency domain modeling based on the spectral component of the interference signal to obtain a spectral model of the interference signal. The specific formula is: Wherein, H(k) represents the spectrum model of the interference signal; S i (k) represents the kth spectral component of the i-th interference signal; b represents the modeling parameters that control the spectral translation and scaling effects; is the phase correction term for the interference signal; e is the base of natural logarithms; j is the imaginary unit.

6. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing according to claim 1 is characterized in that: The generation of the frequency domain compensation signal taking into account the phase correction of the interference signal based on the spectrum model of the interference signal is specifically as follows: Wherein, C(k) represents the frequency domain compensation signal; H(k) represents the spectrum model of the interference signal; represents a complex exponential function used to correct the phase of the interference signal; e is the base of natural logarithm; j is the imaginary unit; μ represents the optimal adjustment parameter for compensating signal sensitivity or intensity; γ represents the optimal adjustment parameter for controlling the adjustment accuracy of the compensation signal; S i (k) represents the spectral component of the interference signal; a represents the parameter controlling the compensation accuracy; θ(k) represents the phase of the interference signal.

7. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing according to claim 6 is characterized in that: The phase of the interference signal is specifically as follows: Among them, tan -1 represents the inverse tangent function; Im{S i (k)} represents the spectral component S of the interference signal i (k) the imaginary part; Re{S i (k)} represents the spectral component S of the interference signal i The real part of (k).

8. The method for suppressing interference signals of measuring equipment in electromagnetic compatibility testing according to claim 1 is characterized in that: The frequency domain compensation signal is converted into a time domain compensation signal by using inverse Fourier transform. The specific formula is as follows: Wherein, c(n) represents the time domain compensation signal; M represents the number of spectrum sampling points; C(k) represents the frequency domain compensation signal; e is the base of natural logarithms; j is the imaginary unit; k represents the frequency domain sampling point; n represents the sampling point number of the input signal.

9. A system for suppressing interference signals of measuring equipment in electromagnetic compatibility testing, using the method according to any one of claims 1 to 8, characterized in that: The system comprises: The spectrum component calculation module is used to obtain the input signal of the measuring equipment in the electromagnetic compatibility test, and the spectrum component of the input signal is obtained by adaptive fractional-order Fourier transform after windowing the input signal using an adaptive fractional-order window function; A spectrum component screening module is used to calculate the amplitude of the spectrum component and compare it with the power threshold dynamically adjusted according to the environmental noise, and screen out the spectrum component with an amplitude greater than the power threshold as the spectrum component of the interference signal; A spectrum model building module is used to perform nonlinear adaptive frequency domain modeling on the interference signal based on the spectrum components of the interference signal to obtain a spectrum model of the interference signal; The signal compensation module is used to generate a frequency domain compensation signal taking into account the phase correction of the interference signal based on the spectrum model of the interference signal, and convert the frequency domain compensation signal into a time domain compensation signal by using inverse Fourier transform, and superimpose the time domain compensation signal with the input signal to obtain the interference suppressed signal.

10. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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