Signal processing method, signal processing device and storage medium

Abstract

The present application discloses a signal processing method, a signal processing device and a storage medium, and relates to the field of wireless communication technology. The signal processing method is disclosed, including: obtaining the power spectrum of the frequency domain signal to be processed, and determining the target power spectrum corresponding to the power spectrum according to the spectrum power jitter information of the power spectrum; determining the suppression coefficient of the frequency domain signal to be processed according to the quotient value set or difference value set of each frequency point of the power spectrum and the target power spectrum; updating the power spectrum based on the suppression coefficient to suppress interference of the frequency domain signal to be processed. Based on this, after the signal is transformed in the frequency domain, the corresponding suppression coefficient is calculated to adjust its power spectrum, so as to dynamically adjust it according to the actual state of the current spectrum, without relying on a fixed threshold to determine when to suppress interference, so that the spectrum can be adjusted in real time to improve the anti-interference effect.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a signal processing method, a signal processing device and a storage medium. Background Art

[0002] In the 5G (5th Generation Mobile Communication Technology) signal processing method, the power spectrum of the signal describes in detail the power distribution of the signal in the frequency domain. Based on the mean and variance in this power distribution information, we can perform interference suppression on the signal. The mean of the signal is used to reflect the average power or DC component of the signal, while the variance describes the volatility or dynamic range of the signal.

[0003] Current anti-interference suppression algorithms usually use multiple iterations in the time domain to find the best suppression strategy, and use a preset fixed threshold to determine the interference strength. However, since the multiple iterations usually cannot be adjusted dynamically according to real-time conditions, and the fixed threshold setting may not accurately reflect the actual changes in interference, the signal anti-interference effect is poor.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present application is to provide a signal processing method, a signal processing device and a storage medium, aiming to solve the technical problem that the current signal anti-interference method has poor interference suppression effect.

[0006] To achieve the above object, the present application proposes a signal processing method, the method comprising:

[0007] Acquire a first power spectrum of a frequency domain signal to be processed, determine a window function and a window length according to spectral power jitter information of the first power spectrum, and perform windowing processing on the frequency domain signal to be processed based on the window function and the window length;

[0008] Determine a frequency band to be processed of a second power spectrum of the frequency domain signal to be processed after windowing, and perform weighted processing based on the second power spectrum of the frequency band to be processed;

[0009] performing smoothing processing on the second power spectrum after weighted processing to obtain a target power spectrum;

[0010] Determining a suppression coefficient of the frequency domain signal to be processed according to a quotient value set or a difference value set of each frequency point of the first power spectrum and the target power spectrum;

[0011] The first power spectrum is updated based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed.

[0012] In one embodiment, before the step of obtaining a first power spectrum of the frequency domain signal to be processed, determining a window function and a window length according to the spectrum power jitter information of the first power spectrum, and performing windowing processing on the frequency domain signal to be processed based on the window function and the window length, it also includes:

[0013] Determine a standard deviation or a variance of a signal of the first power spectrum, and determine the spectrum power jitter information based on a mapping relationship between the standard deviation or the variance; or

[0014] Determining a signal to be processed of the frequency domain signal to be processed;

[0015] Performing a short-time Fourier transform based on the signal to be processed, and determining the spectrum power jitter information based on power spectrum change information in a continuous window, wherein the signal to be processed is a time domain signal; or

[0016] Power spectrum difference information of adjacent time windows is determined, and the spectrum power jitter information is generated according to the power spectrum difference information.

[0017] In one embodiment, the step of determining the suppression coefficient of the frequency domain signal to be processed according to the quotient value set or the difference value set of each frequency point of the first power spectrum and the target power spectrum includes:

[0018] Determine a weighted average of the quotient value set at each frequency point, and set the weighted average as the suppression coefficient; or

[0019] determining a maximum subset corresponding to the quotient value set, and setting the quotient value of the maximum subset as the suppression coefficient; or

[0020] determining an average quotient value of a plurality of quotient values ​​located in the same frequency band, and setting the average quotient value as the suppression coefficient; or

[0021] Based on the quotient and a preset threshold, a frequency band to be suppressed is determined, and the suppression coefficient is set according to an average quotient of the frequency band to be suppressed.

[0022] In one embodiment, the step of determining the suppression coefficient of the frequency domain signal to be processed according to the quotient value set or the difference value set of each frequency point of the first power spectrum and the target power spectrum includes:

[0023] Obtaining a preset scaling factor, and setting the product of the preset scaling factor and the weighted difference average of the difference set, the difference of the largest subset, or the average difference of multiple differences on the same frequency band as the suppression coefficient; or

[0024] The difference interval corresponding to the difference set is determined based on a preset piecewise function, and the suppression coefficient associated with the difference interval is obtained.

[0025] In one embodiment, after the step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed, the method further includes:

[0026] Determine difference information between the updated first power spectrum and the target power spectrum, the difference information at least including a mean square error;

[0027] updating the suppression coefficient based on a target suppression coefficient corresponding to the mean square error, wherein the target suppression coefficient is outside a numerical range corresponding to the suppression coefficient;

[0028] The step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed is performed according to the updated suppression coefficient.

[0029] In one embodiment, the step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed includes:

[0030] determining a regulating factor associated with the inhibition coefficient;

[0031] Based on the processing frequency band corresponding to the suppression coefficient and the adjustment factor, the target frequency band corresponding to the processing frequency band in the first power spectrum is updated to perform interference suppression on the frequency domain signal to be processed.

[0032] In one embodiment, before the step of obtaining a first power spectrum of the frequency domain signal to be processed, determining a window function and a window length according to the spectrum power jitter information of the first power spectrum, and performing windowing processing on the frequency domain signal to be processed based on the window function and the window length, it also includes:

[0033] Acquire a signal to be processed, and perform windowing processing on the signal to be processed based on a preset windowing function;

[0034] Performing fast Fourier transform processing on the signal to be processed after the windowing processing to obtain the frequency domain signal to be processed;

[0035] After the step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed, the method further includes:

[0036] The updated first power spectrum is transformed based on inverse fast Fourier transform, and the transformed signal is inversely windowed to obtain a processed signal after interference suppression.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes a signal processing device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the signal processing method described above.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the signal processing method described above are implemented.

[0039] One or more technical solutions proposed in this application have at least the following technical effects:

[0040] By acquiring the power spectrum information of the frequency domain signal to be processed, the power spectrum is analyzed to understand the main frequency components of the signal and the energy distribution of each frequency component, so as to identify potential interference signals, and then the target power spectrum is calculated based on the spectrum power jitter information of the power spectrum, so as to more accurately locate the interference signal that needs to be suppressed. Then, by comparing the power spectrum of the frequency domain signal to be processed with the target power spectrum, it is identified which frequency components need to be suppressed, and finally the suppression coefficient of the frequency domain signal is calculated through the two power spectra. This suppression coefficient reflects the degree of suppression required on different frequency components, and the power spectrum is updated based on the suppression coefficient, thereby reducing the interference of the interference source of the frequency domain signal to be processed. The anti-interference method of the power spectrum relies on the calculation and comparison of the power spectrum. These operations are relatively simple and easy to implement, avoiding the need for multiple iterations of the power spectrum. At the same time, due to the reduced calculation complexity, the interference suppression effect is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1A schematic diagram of a flow chart of a first embodiment of a signal processing method of the present application;

[0044] Figure 2 A flowchart diagram of a second embodiment of a signal processing method of the present application;

[0045] Figure 3 A flowchart of a third embodiment of a signal processing method of the present application is provided;

[0046] Figure 4 A flowchart diagram of a fourth embodiment of a signal processing method of the present application;

[0047] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the signal processing method in the embodiment of the present application.

[0048] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] The main solution of the embodiment of the present application is: obtaining a power spectrum of the frequency domain signal to be processed, and determining a target power spectrum corresponding to the power spectrum according to the spectrum power jitter information of the power spectrum;

[0052] Determining a suppression coefficient of the frequency domain signal to be processed according to a quotient value set or a difference value set of each frequency point of the power spectrum and the target power spectrum;

[0053] The power spectrum is updated based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed.

[0054] In this embodiment, for the convenience of description, the following description is made by taking the signal processing device as the execution subject.

[0055] Current anti-interference suppression algorithms usually use multiple iterations in the time domain to find the best suppression strategy, and use a preset fixed threshold to determine the interference strength. However, since the multiple iterations usually cannot be adjusted dynamically according to real-time conditions, and the fixed threshold setting may not accurately reflect the actual changes in interference, the signal anti-interference effect is poor.

[0056] The present application provides a solution, which can quantify the deviation of different frequency components in the frequency domain signal to be processed in detail by calculating the quotient value set or difference value set of the power spectrum and the target power spectrum at each frequency point, thereby determining the suppression coefficient, and improving the accuracy and pertinence of signal processing. Then, the power spectrum is updated based on the determined suppression coefficient, effectively reducing the interference of the interference source in the frequency domain signal to be processed. In the scenario where the signal needs to be dynamically adjusted, the signal can be subjected to real-time dynamic interference suppression processing to improve the anti-interference effect of the signal.

[0057] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a signal processing device, etc. The following takes a signal processing device as an example to illustrate this embodiment and the following embodiments.

[0058] Based on this, the present application embodiment provides a signal processing method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the signal processing method of the present application.

[0059] In this embodiment, the signal processing method includes steps S10 to S30:

[0060] Step S10: acquiring a power spectrum of the frequency domain signal to be processed, and determining a target power spectrum corresponding to the power spectrum according to spectrum power jitter information of the power spectrum.

[0061] It should be noted that the power spectrum of the frequency domain signal to be processed is the first power spectrum. The frequency domain signal to be processed is a signal obtained by transforming the time domain signal by FFT (Fast Fourier Transform). Among them, the time domain signal is preferably a 5G frequency band signal. The power spectrum refers to the power distribution characteristics of the signal in the frequency domain, which can be obtained through spectrum analysis technology. The target power spectrum refers to the power distribution characteristics that the signal should have under ideal conditions, which is usually determined by the characteristics of the signal and the performance requirements of the communication system. Determining the target power spectrum is one of the key steps in anti-interference processing, because only by clarifying the target power spectrum can the signal be effectively adjusted to achieve the purpose of reducing interference and improving signal quality.

[0062] Spectral power jitter information, also known as spectral power jitter size, refers to the degree of fluctuation of the power spectrum of the signal in the frequency domain. The jitter size of the power spectrum can be evaluated by the standard deviation and variance, or by the change in the gain size. The fluctuation of the power spectrum may be caused by many factors, such as the instability of the signal source itself, external interference, noise, etc. In signal processing and analysis, spectral power jitter information can reflect the stability and quality of the signal. Spectral power jitter information can be quantified by calculating the local standard deviation, coefficient of variation or other statistics of the power spectrum. These statistics can describe the fluctuation of the power spectrum at different frequencies, so as to understand the spectral characteristics of the signal and determine its corresponding target power spectrum.

[0063] In this embodiment, after receiving the time domain signal to be processed, it is converted into a frequency domain signal, and the power spectrum of the converted frequency domain signal is extracted by spectrum analysis technology, so as to obtain the spectrum power jitter information of the power spectrum, and then calculate the target power spectrum by the jitter information. The method of calculating the power spectrum can be a conventional calculation method, which is not limited in this application.

[0064] In the process of determining the target power spectrum, a suitable window function such as a Hamming window, a Hanning window, etc., and a suitable window length can be selected based on the spectrum power jitter information so as to perform appropriate windowing processing on it, thereby reducing spectrum leakage. For example, if the spectrum power jitter is large, it is necessary to select a window function with better sidelobe suppression capability, such as a Hanning window or a Hamming window. These window functions reduce leakage by smoothing the edges. It is understandable that the size of the spectrum power jitter can be set based on the actual scenario and is not limited here. After determining the window function and the window length, the frequency domain signal to be processed can be windowed. This is usually achieved by multiplying the window function with the frequency domain signal. Windowing can significantly reduce spectrum leakage and sidelobe effects, thereby improving spectrum characteristics.

[0065] After the frequency domain signal to be processed is windowed, some frequency points of the power spectrum of the frequency domain signal to be processed after the windowing process are weighted to suppress noise or interference frequency bands, that is, the frequency band to be processed of the power spectrum of the frequency domain signal to be processed after the windowing process is determined, and weighted processing is performed based on the frequency band to be processed. For example, the power spectrum after the windowing process shows the power distribution at different frequencies. Wherein, the power spectrum of the frequency domain signal to be processed after the windowing process is the second power spectrum.

[0066] In some frequency bands, due to the influence of noise or interference, the power spectrum will have abnormal fluctuations or peaks. In order to improve the signal quality, these frequency bands need to be frequency-weighted. That is, the frequency bands to be processed are weighted. For example, if the power spectrum shows that there is obvious noise interference in the 5kHz to 10kHz frequency band, this frequency band can be weighted attenuated. The weighting method can be to suppress the noise in this frequency band through a weighted filter while keeping the signals in other frequency bands unchanged.

[0067] Finally, the power spectrum can be smoothed using moving average or other smoothing algorithms to reduce random fluctuations in the power spectrum, thereby extracting stable signal features, that is, obtaining a stable spectrum signal. Among them, smoothing can reduce random fluctuations in the power spectrum, thereby improving the signal's anti-interference ability.

[0068] Optionally, in the process of determining the target power spectrum, a jitter threshold can be set based on the spectrum power jitter information to distinguish normal fluctuations from abnormal fluctuations, and then the power is adjusted for the frequency intervals that exceed the jitter threshold. The adjustment strategy includes smoothing the abnormal fluctuation intervals, such as using a moving average method, an exponential smoothing method, etc., to make the power spectrum more stable in these intervals, or enhancing or suppressing the abnormal fluctuation intervals according to signal characteristics and application requirements, such as enhancing the power of important characteristic frequencies and suppressing the power of interference frequencies. Finally, the adjusted power spectrum and the unadjusted frequency intervals are combined to synthesize the target power spectrum.

[0069] Step S20: determining the suppression coefficient of the frequency domain signal to be processed according to the power spectrum and the quotient value set or the difference value set of each frequency point of the target power spectrum.

[0070] In this embodiment, when calculating the suppression coefficient, it is necessary to compare the difference information of each frequency point in the two power spectra, so as to determine the suppression parameter required for suppressing the signal based on the difference information of the two. The suppression coefficient can be obtained by calculating the ratio or difference of the power spectra.

[0071] Specifically, when determining the suppression coefficient based on the quotient value set, the weighted average of the quotient values ​​at all frequency points can be calculated, and this average can be used as the suppression coefficient of the entire signal. This processing method can accurately reflect the characteristics of important frequency points in the signal; in addition, peak suppression can be used. If the power of some frequency points is much higher than that of other frequency points, these high-frequency points can be regarded as interference that needs to be suppressed, and the suppression coefficient can be calculated for these high-frequency points. In addition, the signal can be divided into different frequency bands by frequency band division, and the average value in each frequency band can be calculated to obtain the suppression coefficient corresponding to the frequency band.

[0072] Optionally, the suppression coefficient may also be determined from the quotient value set by an optimization algorithm, a machine learning method, or the like.

[0073] Optionally, the suppression coefficient may be determined based on specific standard data, for example, when the power change at a certain frequency point exceeds a preset threshold, the frequency component with the largest change amplitude is regarded as an interference frequency band to be suppressed.

[0074] Optionally, when determining the suppression coefficient based on the difference set of each frequency point, the suppression coefficient can be determined by the product relationship between the difference and a preset proportional factor, for example, a maximum value, an average value, etc. of the difference set is selected, and it is multiplied by the proportional factor, and the multiplied result is used as the suppression coefficient.

[0075] In the present embodiment, the quotient set or difference set of the power spectrum and the target power spectrum at each frequency point is calculated, and this step itself can be performed in real time. Therefore, as long as a new frequency domain signal to be processed is obtained, its power spectrum can be immediately calculated and compared with a preset or dynamically generated target power spectrum. This immediacy enables the system to respond quickly to changes in signals. At the same time, based on the comparison results of the power spectrum and the target power spectrum, a suppression coefficient reflecting the deviation of each frequency component in the current signal is calculated in real time. Therefore, when the signal changes, the suppression coefficient will also be updated accordingly. Based on this, when the power spectrum is updated by the suppression coefficient, as the suppression coefficient is dynamically updated, the power spectrum of the frequency domain signal to be processed is also dynamically updated in real time, thereby improving the interference suppression effect of the frequency domain signal to be processed.

[0076] It should be noted that, in this embodiment, when the suppression coefficient is determined, it is mainly processed by size comparison and addition and subtraction calculation, which can effectively reduce the calculation complexity.

[0077] Step S30: updating the power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed.

[0078] In this embodiment, after obtaining the suppression coefficients, the signal processing device can update the power spectrum in real time based on these coefficients. Among them, this update is dynamic and can be adjusted according to the real-time changes of the signal. By updating the power spectrum, the system can effectively reduce the interference of the interference source, thereby improving the anti-interference effect of the signal.

[0079] Specifically, in the process of updating the power spectrum, the suppression coefficient is applied to the original power spectrum, for example, the suppression coefficient is multiplied by the power value of all frequency points of the power spectrum. In addition, when the suppression coefficient is applied to the original power spectrum, an adjustment factor needs to be determined, and the application intensity of the suppression coefficient is controlled based on the adjustment factor, so that when the adjustment factor is small, the signal integrity and clarity are maintained while suppressing noise or other unnecessary components; or when the adjustment factor is large, the noise or other unnecessary components are effectively suppressed. Provide a more reliable and high-quality signal source for subsequent signal processing and applications.

[0080] Therefore, the process of updating the power spectrum includes determining the adjustment factor associated with the suppression coefficient, and then updating the target frequency band in the power spectrum corresponding to the processing frequency band based on the processing frequency band corresponding to the suppression coefficient and the adjustment factor to obtain the target power spectrum.

[0081] It can be understood that after updating the power spectrum of the frequency domain signal to be processed, the signal needs to be converted into a time domain signal. Therefore, after the power spectrum changes, the frequency domain signal to be processed changes accordingly, and the corresponding converted time domain signal is also different from the original time domain signal. At the same time, compared with the original time domain signal, the processed time domain signal is a signal after interference suppression of the original time domain signal.

[0082] Exemplarily, after performing FFT processing on the original time domain signal, a power spectrum X(f) is obtained, and then a target power spectrum X'(f) is determined based on the power spectrum, in which the peak at 50Hz remains unchanged, while the power at other frequencies is significantly reduced. Based on this, the suppression coefficient calculated by the two power spectra is C(f), for example, using the quotient method: C(f) = X'(f) / X(f) (for frequencies other than 50Hz). Finally, the power spectrum is updated using a smooth transition method, that is, the calculation formula of the updated power spectrum X''(f) is as follows:

[0083] X''(f) = X(f) × (1 - α × (1 - C(f))), where α is a regulation factor used to control the strength of suppression, and its value is between 0 and 1. For example, α=0.5 means that X''(f) is a compromise between X(f) and X'(f). When α=0, X''(f) = X(f), that is, no suppression is performed; when α=1, X''(f) = X(f) × C(f) (when C(f) is not 0), that is, suppression is performed completely according to the suppression coefficient.

[0084] Therefore, based on the dynamics of calculating the target power spectrum, the real-time determination of the suppression coefficient and the dynamic update of the power spectrum, the signal processing device can perform anti-interference suppression processing in real time and dynamically, thereby improving the anti-interference effect of the signal.

[0085] This embodiment provides a signal processing method, which obtains the power spectrum of the frequency domain signal to be processed, and accurately determines the target power spectrum based on the spectrum power jitter information in the power spectrum, providing an accurate reference for the subsequent calculation of the suppression coefficient, and then determines the suppression parameters that can reflect the suppression requirements of the signal at different frequencies by calculating the quotient value set or difference value set between the power spectrum and the target power spectrum at each frequency point, and updates the power spectrum based on the suppression parameter, thereby effectively suppressing unnecessary components in the signal. Therefore, by converting the time domain signal into a frequency domain signal for processing, and calculating the suppression coefficient in real time based on the power spectrum information and performing suppression processing on the power spectrum, in scenarios with high real-time requirements, the algorithm does not need to iterate multiple times to complete real-time interference suppression processing, thereby improving the interference suppression effect.

[0086] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can refer to the above introduction, and will not be repeated in the following. Figure 2 , before step S10, the signal processing method further includes step S01:

[0087] Step S01: determine the standard deviation or variance of the power spectrum signal, and determine spectrum power jitter information based on a mapping relationship between the standard deviation or the variance.

[0088] In this embodiment, as an optional implementation for determining spectrum power jitter information, the power jitter degree is evaluated by calculating the standard deviation or variance of the power spectrum signal. The greater the jitter, the greater the standard deviation, reflecting the instability of spectrum power changes.

[0089] Exemplarily, the power spectrum signal is x(n). During the calculation process, the power spectrum density function Pxx(k) of the signal x(n) is first calculated. Then the power spectrum density function Pxx(k) is converted into the autocorrelation function Rxx(n) of the signal. After obtaining the autocorrelation function Rxx(n), it is integrated to obtain the variance Var[X] of the signal x(n). It can be understood that the variance measures the discreteness of the signal power, that is, the degree of jitter. At this time, the jitter information can be determined by the mapping relationship between the variance and the spectrum power jitter information.

[0090] Optionally, the standard deviation is calculated as follows:

[0091] Standard deviation = √(Σ((xi - μ)^2) / N), where xi represents the value of the power spectrum signal at each frequency point, μ represents the average of these values, and N represents the number of frequency points. In actual calculations, the formula may need to be adjusted appropriately to suit specific data and calculation requirements. For example, if the data is continuous, integration needs to be used instead of summation; if the data contains noise or outliers, preprocessing or filtering may be required to eliminate their effects.

[0092] Based on this, the frequency domain power jitter information of the power spectrum is evaluated through standard deviation and variance, so as to improve the effectiveness and accuracy of subsequent calculations through the frequency domain power jitter information.

[0093] Optionally, before step S10, a short-time Fourier transform (STFT) can also be performed in the time domain signal to observe the change of the power spectrum in each window, so as to monitor the power spectrum jitter in real time, that is, by extracting the time domain change information, the power spectrum jitter information is detected. Specifically, it is necessary to first determine the signal to be processed of the frequency domain signal to be processed, which is the original time domain signal, and then perform a short-time Fourier transform based on the signal to be processed, and determine the spectrum power jitter information based on the power spectrum change information in the continuous window.

[0094] Exemplarily, during processing, the original time domain signal is first divided into multiple time periods, i.e., windows, and then the signal in each time period is subjected to short-time Fourier transform to obtain the spectrum information of the time period. Then, the time-frequency distribution matrix of the entire signal is obtained by sliding the window, and the power spectrum jitter information in the continuous window is calculated.

[0095] For example, there is a non-stationary signal with multiple frequency components, with a sampling rate of 1000Hz and a duration of 1 second. When the spectral power jitter information of the signal is analyzed by STFT, the original signal x(t) is: x = [10*cos(2*pi*10*t), 20*cos(2*pi*20*t), ..., 40*cos(2*pi*40*t)], where t is the time vector, from 0 to 1 second, with a step size of 1 / 1000 second. Then select a window function, such as the Hanning window, with a window length of 256 points (about 0.256 seconds), set the step size (hop size) of the sliding window to 128 points (about 0.128 seconds) to ensure that there is overlap between windows, and then perform STFT on the original signal to obtain the time-frequency distribution matrix STFT(t, ω), where t is time and ω is frequency. For each time window t, its power spectrum P(t, ω) = |STFT(t, ω)|^2 is calculated, and then the power spectra of consecutive time windows are compared to evaluate the jitter of the power spectrum.

[0096] Optionally, the power spectrum difference between adjacent time windows may be calculated, so as to further analyze the jitter characteristics through the frequencies with significant changes.

[0097] Optionally, the presence of interference signals can be detected by monitoring the change in relative gain of each frequency point in the power spectrum as a measure of the power jitter size, that is, by determining the gain change information of each frequency point in the power spectrum, and determining the spectrum power jitter information based on the gain change information.

[0098] This embodiment provides a signal processing method, which obtains spectrum power jitter parameters by means of the standard deviation or variance of the power spectrum signal, or determines spectrum power jitter information based on the power spectrum transformation information of the continuous serial port by performing a short-time Fourier transform on the original time domain signal. The spectrum power jitter information is determined by multiple calculation methods, thereby improving the accuracy of the calculation of the spectrum power jitter information, and further improving the accuracy of determining the target power spectrum based on the spectrum power jitter information.

[0099] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the first embodiment can refer to the above introduction, and will not be repeated later. Figure 3 , step S20 further includes step S21:

[0100] Step S21: determine a weighted average of the quotient value sets of the power spectrum and the target power spectrum at each frequency point, and set the weighted average as the suppression coefficient.

[0101] In this embodiment, when calculating the suppression coefficient based on the weighted average value, the weighted average of the quotients at all frequency points can be calculated, and this average value is used as the suppression coefficient of the entire signal. This calculation method is simple and intuitive, but may not accurately reflect the characteristics of some important frequency points in the signal.

[0102] Therefore, in another optional implementation, peak suppression processing can be performed, that is, determining the maximum subset corresponding to the quotient value set, and setting the quotient value of the maximum subset as the suppression coefficient. In this process, the power of some frequency points in the quotient value set is much higher than that of other frequency points. At this time, these high-frequency points are regarded as interference that needs to be suppressed, and the suppression coefficient can be calculated only for these high-frequency points. Specifically, the peaks in the power spectrum (or frequency points exceeding a certain threshold) can be found, and the suppression coefficients can be calculated for these peak points. Among them, this calculation method can more effectively reduce obvious signal interference.

[0103] Optionally, the frequency range of the signal may be divided into a plurality of frequency bands, and an average quotient value may be calculated in each frequency band, and then a suppression coefficient may be determined for each frequency band based on the average quotient value, so that an average quotient value of a plurality of quotient values ​​in the same frequency band may be determined, and the average quotient value may be set as the suppression coefficient. In this process, when calculating the suppression coefficient, the characteristics of the signal in different frequency bands can be retained, and independent suppression processing can be performed on each frequency band.

[0104] Optionally, the frequency band that needs to be suppressed in the signal can also be determined, and the average quotient value of the frequency band can be set as the suppression coefficient, that is, based on the quotient value and a preset threshold, the frequency band to be suppressed is determined, and the suppression coefficient is set according to the average quotient value of the frequency band to be suppressed.

[0105] In addition, in the process of determining the suppression coefficient of the frequency domain signal to be processed based on the difference set of each frequency point, the average of the weighted differences can also be selected from the difference set, or the difference corresponding to the largest subset can be selected, or the average difference of multiple differences on the same frequency band can be selected, and then the suppression coefficient can be determined based on the proportional relationship. Specifically, a preset proportional factor can be obtained, and the product of the preset proportional factor and the weighted difference average of the difference set, the difference of the largest subset, or the average difference of multiple differences on the same frequency band can be set as the suppression coefficient. For example, if the set proportional factor is k, the calculated average difference, the difference corresponding to the largest subset, or the average of the weighted difference is ΔP, then the product kΔP of the two is calculated, and the product is used as the suppression coefficient.

[0106] Optionally, the suppression coefficient can also be determined by means of a piecewise function, the difference interval corresponding to the difference set is determined based on a preset piecewise function, and the suppression coefficient associated with the difference interval is obtained. Specifically, all differences are first divided into different intervals according to their sizes, and a specific suppression coefficient is defined for each interval. In this way, when ΔP falls within a certain interval, the suppression coefficient corresponding to the interval can be directly used. Based on this, it is possible to flexibly handle differences ΔP of different sizes, and different suppression coefficients can be defined for each interval according to actual needs.

[0107] Optionally, the suppression coefficient can be determined by machine learning, and a machine learning algorithm can be used to automatically learn the relationship between the suppression coefficient and the difference ΔP. In this process, a large amount of training data (including the difference ΔP and the corresponding suppression coefficient) needs to be collected first, and then a machine learning model is trained using this data. After the training is completed, the model can be used to predict the suppression coefficient corresponding to the new difference ΔP. Based on this, complex relationships in signal data can be automatically learned, and adaptive adjustments can be made based on new data.

[0108] This embodiment provides a signal processing method. When determining the suppression coefficient according to the quotient value set or the difference value set at each frequency point, the calculation and processing are performed through the weighted average of the quotient value set or the difference value set, the quotient value or the difference value of the largest subset, or the average of multiple quotient values ​​or the difference value on the same frequency band. Therefore, in the process of determining the suppression coefficient, the importance of each frequency point is fully considered, the largest subset of the suppression effect or the effect of processing on a specific frequency band is highlighted, and the corresponding processing method is selected based on actual needs. In practical applications, it meets various usage requirements, thereby improving the flexibility and adaptability of signal processing and the accuracy of the suppression coefficient, and further improving the effect of interference suppression on spectrum signals.

[0109] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the first embodiment can refer to the above introduction, and will not be repeated later. Figure 4 , after step S30, further comprising steps S40 to S60:

[0110] Step S40: determining difference information between the updated power spectrum and the target power spectrum.

[0111] In this embodiment, after the power spectrum is updated based on the suppression coefficient, if the current suppression effect cannot meet the actual interference suppression requirements, it is necessary to dynamically adjust the suppression parameters to perform real-time update and optimization processing on the power spectrum to further improve the interference suppression effect.

[0112] Specifically, in the process of determining the difference information, the mean square error between the power spectrum and the target power spectrum can be calculated, wherein the mean square error (MSE) is a common method for measuring the difference between two signals. When measuring the difference between two power spectra, the mean square error can also be used for analysis.

[0113] Exemplarily, for each frequency point fi on the two power spectra, the square of the error between the two power spectra at the frequency point is calculated, that is, (P1(fi)−P2(fi)) 2 . Among them, P1 refers to the power spectrum, and P2 refers to the target power spectrum. Then add the squares of the errors at all frequency points and divide them by the total number of frequency points N to get the mean square error (MSE). The smaller the MSE value, the smaller the difference between the two power spectra, that is, the more similar their shapes and energy distributions are. The larger the MSE value, the greater the difference between the two power spectra, that is, the more obvious the difference in their shapes and energy distributions is. Based on this, the suppression coefficient that meets the actual needs can be determined through the mean square error of the two, so as to update the original suppression coefficient.

[0114] Step S50: updating the suppression coefficient based on the target suppression coefficient corresponding to the mean square error.

[0115] Step S60, performing the step of updating the power spectrum based on the suppression coefficient according to the updated suppression coefficient to perform interference suppression on the frequency domain signal to be processed.

[0116] In this embodiment, after obtaining the mean square error, the target suppression coefficient associated with the mean square error can be determined. For example, in a pre-stored mapping table, the range interval in which the mean square error is located is associated with a target suppression coefficient. At this time, the suppression coefficient can be updated based on the target suppression coefficient, that is, the target suppression coefficient is used as the new suppression coefficient, and then step S30 is executed to update the power processing action through the suppression coefficient.

[0117] It is understandable that if the target suppression coefficient is the same as the filling value of the current suppression coefficient, there is no need to perform the action of updating the suppression coefficient in step 50. That is, when the numerical values ​​of the suppression coefficients differ greatly, the target suppression coefficient is outside the numerical range corresponding to the suppression coefficient, such as the suppression coefficient is 0.5, and its corresponding numerical range is 0.45-0.55. If the target suppression coefficient is outside this range, the step of updating the suppression coefficient is performed. The above parameters are only used for explanation and are not intended to limit the present application.

[0118] This embodiment provides a signal processing method, which enables a signal processing device to update a power spectrum in real time by performing real-time updating on a suppression coefficient, thereby improving a processing effect when performing interference suppression on a signal.

[0119] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. On this basis, before step S10, it is necessary to obtain a signal to be processed, and perform windowing processing on the signal to be processed based on a preset windowing function, and then perform fast Fourier transform processing on the signal to be processed after the windowing processing to obtain the frequency domain signal to be processed.

[0120] It is understandable that the signal for interference suppression is usually a time domain signal, and in order to ensure that the signal can be adjusted in real time, it needs to be converted into a frequency domain signal first, so as to process the power spectrum of the frequency domain signal.

[0121] Exemplarily, in this process, after the signal processing device receives the 5G signal that needs to be interfered with, it is necessary to truncate it, that is, add a window, because it is currently impossible to directly process an infinitely long signal. At this time, you can select a suitable window function (such as a preset rectangular window, Hanning window, etc.) and a window length, and then truncate the 5G signal. Then, the windowed 5G signal is input into the FFT algorithm or FFT model for frequency domain transformation. It can be understood that the FFT algorithm or FFT model will convert the signal from the time domain to the frequency domain to obtain a spectrum representation of the signal. This spectrum represents the components and amplitudes of the signal at different frequencies.

[0122] Furthermore, the time domain signal that needs to be interfered with is converted into a frequency domain signal, the suppression coefficient is calculated according to the power spectrum of the frequency domain signal, and after the power spectrum is optimized based on the suppression coefficient, the signal needs to be converted back to a time domain signal to complete the interference suppression processing of the signal. In this process, the updated power spectrum is transformed based on the inverse fast Fourier transform, and the transformed signal is subjected to inverse windowing to obtain a processed signal after interference suppression.

[0123] Based on this, after interference suppression, the signal is converted back to the time domain through IFFT, which can significantly reduce the noise and distortion in the time domain signal, thereby improving the quality of the signal.

[0124] The present application provides a signal processing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the signal processing method in the first embodiment described above.

[0125] Reference below Figure 5 , which shows a schematic diagram of the structure of a signal processing device suitable for implementing the embodiment of the present application. The signal processing device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The signal processing device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0126] like Figure 5As shown, the signal processing device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the signal processing device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the signal processing device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a signal processing device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0127] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0128] The signal processing device provided by the present application adopts the signal processing method in the above embodiment, which can solve the technical problem that the current signal anti-interference method has poor interference suppression effect. Compared with the prior art, the beneficial effects of the signal processing device provided by the present application are the same as the beneficial effects of the signal processing method provided by the above embodiment, and other technical features in the signal processing device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0129] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0130] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0131] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the signal processing method in the above-mentioned embodiment.

[0132] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0133] The computer-readable storage medium may be included in the signal processing device; or may exist independently without being installed in the signal processing device.

[0134] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by a signal processing device, the signal processing device:

[0135] Acquire a power spectrum of the frequency domain signal to be processed, and determine a target power spectrum corresponding to the power spectrum according to spectral power jitter information of the power spectrum;

[0136] Determining a suppression coefficient of the frequency domain signal to be processed according to a quotient value set or a difference value set of each frequency point of the power spectrum and the target power spectrum;

[0137] The power spectrum is updated based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed.

[0138] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through 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., via the Internet using an Internet service provider).

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0140] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0141] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned signal processing method, and can solve the technical problem that the current signal anti-interference method has poor interference suppression effect. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the signal processing method provided by the above-mentioned embodiment, and will not be repeated here.

[0142] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A signal processing method, characterized in that: The method comprises: Determining a signal to be processed of a frequency domain signal to be processed, including dividing the signal to be processed into a plurality of windows; Performing short-time Fourier transform on the signal to be processed based on multiple windows to obtain spectrum information, determining a time-frequency distribution matrix of the signal to be processed according to a sliding window, and determining spectrum power jitter information based on the time-frequency distribution matrix in a continuous window, wherein the signal to be processed is a time domain signal; Acquire a first power spectrum of the frequency domain signal to be processed, determine a window function and a window length according to the spectrum power jitter information of the first power spectrum, and perform windowing processing on the frequency domain signal to be processed based on the window function and the window length; Determine a frequency band to be processed of a second power spectrum of the frequency domain signal to be processed after windowing, and perform weighted processing based on the second power spectrum of the frequency band to be processed; performing smoothing processing on the second power spectrum after weighted processing to obtain a target power spectrum; Determining a suppression coefficient of the frequency domain signal to be processed according to a quotient value set or a difference value set of each frequency point of the first power spectrum and the target power spectrum; Updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed; Determine difference information between the updated first power spectrum and the target power spectrum, the difference information at least including a mean square error; updating the suppression coefficient based on the target suppression coefficient corresponding to the mean square error, wherein the target suppression coefficient is outside the numerical interval corresponding to the suppression coefficient, and the range interval in which the mean square error is located is associated with the target suppression coefficient; The step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed is performed according to the updated suppression coefficient.

2. The signal processing method according to claim 1, characterized in that: Before the step of obtaining a first power spectrum of the frequency domain signal to be processed, determining a window function and a window length according to the spectral power jitter information of the first power spectrum, and performing windowing processing on the frequency domain signal to be processed based on the window function and the window length, it also includes: Determine a standard deviation or a variance of a signal of the first power spectrum, and determine the spectrum power jitter information based on a mapping relationship between the standard deviation or the variance; or Power spectrum difference information of adjacent time windows is determined, and the spectrum power jitter information is generated according to the power spectrum difference information.

3. The signal processing method according to claim 1, characterized in that: The step of determining the suppression coefficient of the frequency domain signal to be processed according to the quotient value set or the difference value set of each frequency point of the first power spectrum and the target power spectrum comprises: Determine a weighted average of the quotient value set at each frequency point, and set the weighted average as the suppression coefficient; or determining a maximum subset corresponding to the quotient value set, and setting the quotient value of the maximum subset as the suppression coefficient; or determining an average quotient value of a plurality of quotient values ​​located in the same frequency band, and setting the average quotient value as the suppression coefficient; or Based on the quotient and a preset threshold, a frequency band to be suppressed is determined, and the suppression coefficient is set according to an average quotient of the frequency band to be suppressed.

4. The signal processing method according to claim 1, characterized in that: The step of determining the suppression coefficient of the frequency domain signal to be processed according to the quotient value set or the difference value set of each frequency point of the first power spectrum and the target power spectrum comprises: Obtaining a preset scaling factor, and setting the product of the preset scaling factor and the weighted difference average of the difference set, the difference of the largest subset, or the average difference of multiple differences on the same frequency band as the suppression coefficient; or The difference interval corresponding to the difference set is determined based on a preset piecewise function, and the suppression coefficient associated with the difference interval is obtained.

5. The signal processing method according to claim 1, characterized in that: The step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed includes: determining a regulating factor associated with the inhibition coefficient; Based on the processing frequency band corresponding to the suppression coefficient and the adjustment factor, the target frequency band corresponding to the processing frequency band in the first power spectrum is updated to perform interference suppression on the frequency domain signal to be processed.

6. The signal processing method according to any one of claims 1 to 5, characterized in that: Before the step of obtaining a first power spectrum of the frequency domain signal to be processed, determining a window function and a window length according to the spectrum power jitter information of the first power spectrum, and performing windowing processing on the frequency domain signal to be processed based on the window function and the window length, it also includes: Acquire a signal to be processed, and perform windowing processing on the signal to be processed based on a preset windowing function; Performing fast Fourier transform processing on the signal to be processed after the windowing processing to obtain the frequency domain signal to be processed; After the step of updating the first power spectrum based on the suppression coefficient to perform interference suppression on the frequency domain signal to be processed, the method further includes: The updated first power spectrum is transformed based on inverse fast Fourier transform, and the transformed signal is inversely windowed to obtain a processed signal after interference suppression.

7. A signal processing device, characterized in that: The signal processing device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the signal processing method according to any one of claims 1 to 6.

8. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the signal processing method according to any one of claims 1 to 6 are implemented.

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