Multi-frequency mixed signal signal-to-noise ratio estimation method and device based on windowing and medium
By applying windowing and spectral correction to the time-domain signal, the energy leakage problem in signal-to-noise ratio estimation for multi-frequency component signals is solved, thus improving the accuracy of the signal-to-noise ratio.
Patent Information
- Application Number
- CN202511015530.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-23
- Publication Date
- 2025-10-17
AI Technical Summary
Existing technologies suffer from energy leakage when estimating the signal-to-noise ratio in multi-frequency component signals, leading to inaccurate noise power calculations.
The time-domain signal is processed using windowing technology. The peak position of the spectrum is determined by weighting with a cosine window function and fast Fourier transform. The amplitude is corrected, the signal spectrum value is removed, and the noise power is calculated.
This reduces signal energy leakage in the frequency domain, improves the accuracy of noise power calculation, and thus improves the accuracy of signal-to-noise ratio estimation.
Smart Images
Figure CN120811515A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of signal processing, and in particular to a window-based multi-frequency mixed signal SNR estimation method, device and medium. BACKGROUND
[0002] Signal to Noise Ratio (SNR) is a physical quantity for measuring the ratio of signal and noise intensity. In the field of signal processing, especially in the scene of radar, communication and other fields involving multi-frequency component signal analysis, accurate estimation of signal power and noise power is the core link to realize target detection, parameter measurement and performance evaluation.
[0003] The prior art directly estimates the power of the signal and the power of the noise in the frequency domain, and there is a serious energy leakage phenomenon in the frequency domain. When there are multiple frequency components in the signal, the energy leakage of each frequency component leads to inaccurate noise power calculation, and thus inaccurate SNR calculation. SUMMARY
[0004] Therefore, it is necessary to provide a window-based multi-frequency mixed signal SNR estimation method, device and medium to improve the accuracy of SNR estimation when there are multiple frequency components in the signal.
[0005] To achieve the above purpose, in a first aspect, the present application provides a window-based multi-frequency mixed signal SNR estimation method, comprising: windowing the sampled time domain signal to obtain a windowed signal, and converting the windowed signal into a frequency domain signal; the time domain signal contains a first signal, a second signal and a noise signal; the first frequency of the first signal and the second frequency of the second signal are different; determining the first peak position corresponding to the first frequency and the second peak position corresponding to the second frequency based on the frequency spectrum of the frequency domain signal; correcting the amplitudes corresponding to the first peak position and the second peak position respectively to determine the first power and the second power; removing the spectral values of the first signal and the second signal in the frequency spectrum to obtain a remaining spectrum, and determining the third power of the noise signal based on the remaining spectrum; determining the SNR of the time domain signal based on the first power, the second power and the third power.
[0006] In a possible implementation, the windowing the sampled time domain signal to obtain a windowed signal, and converting the windowed signal into a frequency domain signal, comprises: weighting the time domain signal using a cosine window function to obtain the windowed signal; performing a preset-point fast Fourier transform on the windowed signal to obtain the frequency domain signal.
[0007] In a possible implementation, the method further includes: determining a correction coefficient based on the number of sampling points and a shape parameter of the cosine window function; correcting the amplitude corresponding to the first peak position based on the correction coefficient to determine a first amplitude estimation value; the first amplitude estimation value is used to determine the first power; correcting the amplitude corresponding to the second peak position based on the correction coefficient to determine a second amplitude estimation value; the second amplitude estimation value is used to determine the second power.
[0008] In a possible implementation, the correction coefficient is determined according to the following expression:
[0009] wherein, the correction coefficient is denoted as, the number of sampling points is denoted as, the shape parameter of the cosine window function is denoted as.
[0010] In a possible implementation, the signal-to-noise ratio is determined according to the following expression:
[0011]
[0012] wherein, the signal-to-noise ratio of the first signal is denoted as, the first amplitude estimation value is denoted as, the third power is denoted as, the signal-to-noise ratio of the second signal is denoted as, the second amplitude estimation value is denoted as.
[0013] In a possible implementation, the method further includes: determining a target frequency band based on a preset removal number of points, the first peak position, and the second peak position; the target frequency band is used to determine the spectral values of the first signal and the second signal; removing, in a spectrum of the frequency domain signal, the spectral values in the target frequency band to obtain a residual spectrum.
[0014] In a possible implementation, the third power is determined according to the following expression:
[0015] wherein, represents a third power, represents a preset point, represents a removed spectral value point, represents a remaining spectrum, represents a sampling point, represents a cosine window function.
[0016] In a second aspect, the present application further provides a window-based multi-frequency mixed signal SNR estimation device, comprising: a windowing module, configured to perform windowing processing on a sampled time-domain signal to obtain a windowed signal, and convert the windowed signal into a frequency-domain signal; the time-domain signal comprises a first signal, a second signal and a noise signal; the first frequency of the first signal and the second frequency of the second signal are different; a first determination module, configured to determine a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency based on a spectrum of the frequency-domain signal; a correction module, configured to correct amplitudes corresponding to the first peak position and the second peak position respectively, and determine a first power and a second power; a second determination module, configured to remove spectral values of the first signal and the second signal in the spectrum to obtain a remaining spectrum, and determine a third power of the noise signal based on the remaining spectrum; a third determination module, configured to determine an SNR of the time-domain signal based on the first power, the second power and the third power.
[0017] In a third aspect, the present application further provides an electronic device, comprising a memory and a processor, wherein, the memory is configured to store a program; the processor is coupled with the memory, and is configured to execute the program stored in the memory, so as to implement the window-based multi-frequency mixed signal SNR estimation method in any of the above implementation manners.
[0018] In a fourth aspect, the present application further provides a computer readable storage medium, configured to store a computer readable program or instruction, which is executed by a processor to implement the steps of the window-based multi-frequency mixed signal SNR estimation method in any of the above implementation manners.
[0019] The beneficial effects of the present application are: the window-based multi-frequency mixed signal SNR estimation method, device and medium provided by the present application, the windowed signal is obtained by windowing the sampled time domain signal, and the windowed signal is converted into a frequency domain signal, the first peak position corresponding to the first frequency and the second peak position corresponding to the second frequency are determined based on the spectrum of the frequency domain signal, the amplitudes corresponding to the first peak position and the second peak position are corrected respectively, the first power and the second power are determined, when multiple frequency components exist in the frequency domain at the same time, time domain windowing can reduce the mutual influence between different frequency components, improve the accuracy of signal amplitude estimation, remove the spectral values of the first signal and the second signal in the spectrum to obtain the remaining spectrum, and determine the third power of the noise signal based on the remaining spectrum, through time domain windowing, the leakage of signal energy in the frequency domain is reduced, thereby reducing the number of removed spectral points when calculating the noise power in the frequency domain, improving the accuracy of noise power calculation, and improving the estimation accuracy of the signal-to-noise ratio. BRIEF DESCRIPTION OF DRAWINGS
[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.
[0021] Figure 1 One of the embodiment flowcharts of the window-based multi-frequency mixed signal SNR estimation method provided by the present application; Figure 2 The spectrum change comparison diagram before and after windowing provided by the present application; Figure 3 One of the Monte Carlo simulation diagrams of the window-based multi-frequency mixed signal SNR estimation method provided by the present application; Figure 4 The second Monte Carlo simulation diagram of the window-based multi-frequency mixed signal SNR estimation method provided by the present application; Figure 5 The second embodiment flowchart of the window-based multi-frequency mixed signal SNR estimation method provided by the present application; Figure 6 The embodiment structure diagram of the window-based multi-frequency mixed signal SNR estimation device provided by the present application; Figure 7 The embodiment structure diagram of the electronic device provided by the present application. DETAILED DESCRIPTION
[0022] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.
[0023] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more. The association relationship of the associated objects is described by "and / or", which means that there can be three relationships, for example: A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone.
[0024] The "first", "second", and the like described in the embodiments of the present application are only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the technical features limited by "first" and "second" can explicitly or implicitly include at least one of the features.
[0025] In this document, the reference to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily all refer to the same embodiment, nor does it necessarily refer to a particular independent or alternative embodiment in isolation or in combination with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0026] The present application provides a window-based multi-frequency mixed signal SNR estimation method, device and medium, which are described below.
[0027] Figure 1 One of the embodiment flowcharts of the window-based multi-frequency mixed signal SNR estimation method provided by the present application is shown in Figure 1 The window-based multi-frequency mixed signal SNR estimation method includes: S101, performing windowing processing on a sampled time domain signal to obtain a windowed signal, and converting the windowed signal into a frequency domain signal; the time domain signal contains a first signal, a second signal and a noise signal; the first frequency of the first signal and the second frequency of the second signal are different; S102, determining a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency based on the spectrum of the frequency domain signal; S103, correcting the amplitudes corresponding to the first peak position and the second peak position respectively to determine a first power and a second power; S104, removing the spectral values of the first signal and the second signal in the spectrum to obtain a residual spectrum, and determining a third power of the noise signal based on the residual spectrum; S105, determining a signal-to-noise ratio of the time-domain signal based on the first power, the second power and the third power.
[0028] In S101, the sampled time-domain signal is a multi-frequency mixed signal, the time-domain signal contains a first signal and a second signal with different frequencies, and the time-domain signal also contains a noise signal.
[0029] The sampled time-domain signal is windowed, for example, a cosine window function can be used to weight the time-domain signal to obtain a windowed signal, then the windowed signal is transformed into a frequency domain to obtain a frequency domain signal, and power estimation of the signal and power estimation of the noise are performed in the frequency domain.
[0030] When multiple frequency components exist in the frequency domain at the same time, time-domain windowing can reduce the mutual influence between different frequency components and improve the accuracy of signal amplitude estimation. At the same time, time-domain windowing reduces the leakage of signal energy in the frequency domain.
[0031] In S102, the spectrum refers to a representation of a time-domain signal in the frequency domain, which is obtained by Fourier transform of the signal. The amplitude spectrum represents the situation that the amplitude changes with the frequency.
[0032] According to the spectrum of the frequency domain signal, a peak search is performed to obtain a first peak position corresponding to a first frequency and a second peak position corresponding to a second frequency.
[0033] In S103, in the spectrum, the amplitude value corresponding to the first peak position is the amplitude value of the first signal, and the first amplitude estimate is obtained by correcting the amplitude value. The first power of the first signal can be calculated according to the first amplitude estimate.
[0034] Similarly, the amplitude value corresponding to the second peak position is the amplitude value of the second signal, and the second amplitude estimate is obtained by correcting the amplitude value. The second power of the second signal can be calculated according to the second amplitude estimate.
[0035] In S104, the spectral values of all first signals and second signals in the spectrum are removed, and the number of points of each signal spectral value removed can be selected according to the spectral decay of the window function to obtain a residual spectrum. The third power of the noise signal is determined according to the residual spectrum.
[0036] Through time-domain windowing, the leakage of signal energy in the frequency domain is reduced, thereby reducing the number of spectral points removed when calculating the noise power in the frequency domain, and improving the accuracy of noise power calculation.
[0037] In S105, according to the first power, the second power and the third power, the signal-to-noise ratio of the first signal and the second signal can be respectively calculated by using a signal-to-noise ratio calculation formula.
[0038] In conclusion, the method for estimating the signal-to-noise ratio of the mixed signal of multiple frequencies based on windowing provided by the embodiment of the application can obtain a windowed signal by performing windowing processing on the sampled time-domain signal, convert the windowed signal into a frequency-domain signal, determine the first peak position corresponding to the first frequency and the second peak position corresponding to the second frequency based on the spectrum of the frequency-domain signal, correct the amplitudes corresponding to the first peak position and the second peak position respectively, determine the first power and the second power, when multiple frequency components exist in the frequency domain at the same time, the time-domain windowing can reduce the mutual influence between different frequency components and improve the accuracy of the signal amplitude estimation, remove the spectral values of the first signal and the second signal in the spectrum to obtain a residual spectrum, and determine the third power of the noise signal based on the residual spectrum, through the time-domain windowing, the leakage of the signal energy in the frequency domain is reduced, and then the number of removed spectral points when calculating the noise power in the frequency domain is reduced, the accuracy of the noise power calculation is improved, and thus the estimation accuracy of the signal-to-noise ratio is improved.
[0039] In some embodiments of the application, the windowing processing on the sampled time-domain signal to obtain a windowed signal and the conversion of the windowed signal into a frequency-domain signal comprise: performing weighting processing on the time-domain signal by using a cosine window function to obtain the windowed signal; performing fast Fourier transform on the windowed signal by a preset number of points to obtain the frequency-domain signal.
[0040] Exemplarily, taking a mixed signal of two frequencies as an example, assuming that the received signal has a mathematical expression as follows:
[0041] wherein, is the first signal, is the second signal, is the noise signal, and there are N sampling points.
[0042]
[0043]
[0044] wherein, and are signal amplitudes, and are frequencies of the signals, and are phases of the signals, is a sampling rate, White noise in the environment, subject to normal distribution.
[0045] The signal is windowed In the invention, a cosine window function is used The expression is as follows:
[0046] The shape parameter of the cosine window function.
[0047] The windowed signal can be represented as:
[0048] The windowed signal is subjected to a preset number (M points) of fast Fourier transform (FFT), which can be represented as:
[0049] Wherein,
[0050]
[0051]
[0052] Wherein, The number of points of the zero-padding method FFT is represented by M, Generally set as a multiple of the number of sampling points The larger the number of FFT points, the denser the spectral line, the more accurate the peak point obtained, and the more accurate the calculated signal-to-noise ratio, but the corresponding calculation complexity is larger.
[0053] Figure 2 The frequency spectrum change comparison diagram before and after windowing processing provided by the present application, from Figure 2 It can be seen that after windowing, the sidelobe is obviously reduced, and the energy leakage is smaller. However, the amplitude of the signal and the noise also changes obviously, which needs to be corrected.
[0054] The signal-to-noise ratio estimation method for multiple frequency mixed signals based on windowing provided by the embodiment of the present application can effectively suppress signal energy leakage by using windowing technology, so as to limit the power of the signal within a certain frequency range, and accurately calculate the noise power in other frequency bands.
[0055] In some embodiments of the present application, the respective amplitudes corresponding to the first peak position and the second peak position are corrected to determine the first power and the second power, including: Based on the number of sampling points and the shape parameter of the cosine window function, a correction coefficient is determined; Correcting the amplitude corresponding to the first peak position based on the correction coefficient to determine a first amplitude estimation value; the first amplitude estimation value is used to determine the first power; The amplitude corresponding to the second peak position is corrected based on the correction coefficient to determine a second amplitude estimation value; the second amplitude estimation value is used to determine the second power.
[0056] In some embodiments of the present invention, the correction coefficient is expressed as follows:
[0057] in, represents the correction factor, Indicates the number of sampling points, Represents the shape parameter of the cosine window function.
[0058] Right | |Perform a peak search to get the frequency The corresponding first peak position is:
[0059] frequency The corresponding second peak position is:
[0060] Among them, the brackets [] indicate rounding to the nearest integer, that is, and The value of is an integer.
[0061] So, assuming the frequency and No overlap, you can get the frequency First amplitude estimate and frequency of the signal The second amplitude estimates of the signal are:
[0062]
[0063] in, is the correction factor.
[0064] The embodiment of the present invention provides a multi-frequency mixed signal signal-to-noise ratio estimation method based on windowing. The method first performs window function weighting on the time domain signal, then transforms the signal into the frequency domain, and performs signal power estimation and noise power estimation in the frequency domain. Due to the use of window function weighting, coefficient correction is required when performing power estimation in the frequency domain. The present invention provides corresponding correction coefficients and adopts windowing technology to effectively suppress signal energy leakage, thereby limiting the signal power within a certain frequency band, thereby accurately calculating the noise power in other frequency bands.
[0065] In some embodiments of the present application, the removing the spectral values of the first signal and the second signal in the spectrum to obtain a residual spectrum comprises: determining a target frequency band based on a preset removal point number, the first peak position and the second peak position; the target frequency band is used to determine the spectral values of the first signal and the second signal; removing the spectral values in the target frequency band in the spectrum of the frequency domain signal to obtain the residual spectrum.
[0066] In some embodiments of the present application, the expression of the third power is as follows:
[0067] wherein, the third power is represented by P, the preset point number is represented by N, the removed spectral value point number is represented by M, the residual spectrum is represented by S, the sampling point number is represented by N, and the cosine window function is represented by W.
[0068] The spectral values of all target signals (target signals are signals with frequencies and frequencies ) in the spectrum are removed, and the point number of each target signal spectral value removed can be selected according to the spectral decay of the window function.
[0069] The more the point number of the spectral values of the target signals removed in the spectrum, the closer the residual spectrum is to the white noise spectrum, but in the case of multiple targets, it can cause the point number removed to be too much, so that the point number remaining in the spectrum is too small, and the white noise power cannot be calculated correctly.
[0070] The point number of the spectral values of the target signals removed in the FFT spectrum can be selected according to the spectral decay of the window function.
[0071] Suppose the removed spectral value point number is 2 K (i.e. the preset removal point number), then the removed frequency band is and .
[0072] The target frequency band includes , and the spectral values in the target frequency band in the spectrum of the frequency domain signal are removed, i.e. the residual spectrum is obtained, and the expression of the residual spectrum is as follows:
[0073] Considering that the noise also passes through the windowing process, the third power of the original noise is:
[0074] The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing provided by the embodiment of the application reduces the leakage of signal energy in the frequency domain through time domain windowing, can reduce the number of removed spectral points when calculating the noise power in the frequency domain, and improves the accuracy of noise power calculation. Meanwhile, when multiple frequency components exist simultaneously in the frequency domain, time domain windowing can reduce the mutual influence between different frequency components and improve the accuracy of signal amplitude estimation.
[0075] In some embodiments of the application, the expression of the signal-to-noise ratio is as follows:
[0076]
[0077] wherein, the signal-to-noise ratio of the first signal, the first amplitude estimation value, the third power, the signal-to-noise ratio of the second signal, the second amplitude estimation value.
[0078] The frequency The first signal-to-noise ratio of the signal and the frequency The second signal-to-noise ratio of the signal are respectively:
[0079]
[0080] Monte Carlo simulation is performed on the signal-to-noise ratio estimation method proposed in the application under different signal-to-noise ratios, Figure 3 and Figure 4 The Monte Carlo simulation schematic diagram of the method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing provided by the application is shown in Figure 3 and Figure 4 The simulation results are shown in the figures. It can be seen that the signal-to-noise ratio estimation method proposed in the application can accurately estimate the signal-to-noise ratio of a mixed frequency signal.
[0081] The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing provided by the embodiment of the application reduces the leakage of signal energy in the frequency domain through time domain windowing, can reduce the number of removed spectral points when calculating the noise power in the frequency domain, and improves the accuracy of noise power calculation. Meanwhile, when multiple frequency components exist simultaneously in the frequency domain, time domain windowing can reduce the mutual influence between different frequency components and improve the accuracy of signal amplitude estimation.
[0082] Figure 5Figure 2 is a flowchart of another embodiment of the window-based multi-frequency mixed signal SNR estimation method provided by the present application, as shown in Figure 5 The present application first performs window function weighting on the time domain signal, then transforms the signal to the frequency domain, and performs power estimation of the signal and power estimation of the noise in the frequency domain. Since the window function weighting is used, the power estimation in the frequency domain also needs to be corrected by using the corresponding correction coefficient. The prior art does not use the time domain windowing technology, and directly performs power estimation of the signal and power estimation of the noise in the frequency domain.
[0083] The prior art does not use the time domain windowing technology, and there is a serious energy leakage phenomenon in the frequency domain. When there are multiple frequency components in the signal, the energy leakage of each frequency component leads to inaccurate noise power calculation. The present application uses the windowing technology to effectively suppress the signal energy leakage, thereby limiting the power of the signal within a certain frequency range, and accurately calculating the noise power in other frequency ranges.
[0084] In order to better implement the window-based multi-frequency mixed signal SNR estimation method in the embodiment of the present application, based on the window-based multi-frequency mixed signal SNR estimation method, as shown in Figure 6 The present application also provides a window-based multi-frequency mixed signal SNR estimation device, as shown in The windowing module 610 is configured to perform windowing processing on the sampled time domain signal to obtain a windowed signal, and convert the windowed signal into a frequency domain signal. The time domain signal includes a first signal, a second signal, and a noise signal. The first frequency of the first signal and the second frequency of the second signal are different. The first determination module 620 is configured to determine a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency based on the frequency spectrum of the frequency domain signal. The correction module 630 is configured to correct the amplitudes corresponding to the first peak position and the second peak position respectively, and determine a first power and a second power. The second determination module 640 is configured to remove the frequency spectrum values of the first signal and the second signal from the frequency spectrum to obtain a remaining frequency spectrum, and determine a third power of the noise signal based on the remaining frequency spectrum. The third determination module 650 is configured to determine the SNR of the time domain signal based on the first power, the second power, and the third power.
[0085] The window-based multi-frequency mixed signal SNR estimation device 600 provided by the above embodiment can implement the technical solutions described in the above window-based multi-frequency mixed signal SNR estimation method embodiment, and the principles of the implementation of the above modules or units can be referred to the corresponding content in the above window-based multi-frequency mixed signal SNR estimation method embodiment, which will not be described here.
[0086] As shown in Figure 7 The present application also correspondingly provides an electronic device 700. The electronic device 700 includes a processor 701, a memory 702 and a display 703. Figure 7 Only part of the components of the electronic device 700 are shown, but it should be understood that all the shown components are not required to be implemented, and more or less components can be alternatively implemented.
[0087] The processor 701 can be a central processing unit (CPU), a microprocessor or other data processing chip in some embodiments, used to run the program code or process data stored in the memory 702, such as the window-based multi-frequency mixed signal SNR estimation method in the present application.
[0088] In some embodiments, the processor 701 can be a single server or a server group. The server group can be centralized or distributed. In some embodiments, the processor 701 can be local or remote. In some embodiments, the processor 701 can be implemented in a cloud platform. In some embodiments, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multiple cloud, etc., or any combination thereof.
[0089] The memory 702 can be an internal storage unit of the electronic device 700 in some embodiments, such as a hard disk or a memory of the electronic device 700. The memory 702 can also be an external storage device of the electronic device 700 in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 700.
[0090] Further, the memory 702 can include both the internal storage unit and the external storage device of the electronic device 700. The memory 702 is used to store the application software and various data installed on the electronic device 700.
[0091] The display 703 can be, in some embodiments, an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an Organic Light-Emitting Diode (OLED) touch, or the like. The display 703 is used to display information at the electronic device 700 and to display visualized user interfaces. The components 701-703 of the electronic device 700 communicate with each other through a system bus.
[0092] In an embodiment, when the processor 701 executes the windowing-based multi-frequency mixed signal signal-to-noise ratio estimation program in the memory 702, the following steps can be implemented: windowing a sampled time-domain signal to obtain a windowed signal, and converting the windowed signal into a frequency-domain signal; the time-domain signal comprises a first signal, a second signal, and a noise signal; the first signal has a first frequency and the second signal has a second frequency, and the first frequency is different from the second frequency; determining a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency based on a spectrum of the frequency-domain signal; respectively correcting amplitudes corresponding to the first peak position and the second peak position to determine a first power and a second power; removing spectral values of the first signal and the second signal in the spectrum to obtain a residual spectrum, and determining a third power of the noise signal based on the residual spectrum; determining a signal-to-noise ratio of the time-domain signal based on the first power, the second power, and the third power.
[0093] It should be understood that, when the processor 701 executes the windowing-based multi-frequency mixed signal signal-to-noise ratio estimation program in the memory 702, the processor 701 can implement other functions in addition to the above functions, which can be referred to the description of the corresponding method embodiments.
[0094] Further, the type of the electronic device 700 referred to in the embodiments of the present application is not specifically limited, and the electronic device 700 can be a portable electronic device such as a mobile phone, a tablet computer, a Personal Digital Assistant (PDA), a wearable device, a laptop, or the like. Exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device running an IOS, an android, a microsoft, or another operating system. The portable electronic device described above can also be another portable electronic device, such as a laptop having a touch-sensitive surface (e.g., a touch panel). It should also be understood that, in some other embodiments of the present application, the electronic device 700 can not be a portable electronic device, but a desktop computer having a touch-sensitive surface (e.g., a touch panel).
[0095] Correspondingly, the embodiment of the present application further provides a computer readable storage medium for storing computer readable programs or instructions, which can realize the steps or functions in the method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing when the programs or instructions are executed by a processor.
[0096] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware (such as a processor, a controller, etc.) to complete, and the computer program can be stored in a computer readable storage medium. The computer readable storage medium is a disk, an optical disk, a read-only memory or a random access memory, etc.
[0097] The above describes the method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing, the device and the medium provided by the present application in detail. The principle and implementation mode of the present application are described by applying specific examples in this paper. The above embodiment is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and the application range will be changed. In conclusion, the content of the specification should not be understood as a limitation of the present application.
Claims
1. A method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing, characterized in that: include: Performing windowing processing on the sampled time domain signal to obtain a windowed signal, and converting the windowed signal into a frequency domain signal; The time domain signal comprises a first signal, a second signal and a noise signal; a first frequency of the first signal and a second frequency of the second signal are different; determining, based on the frequency spectrum of the frequency domain signal, a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency; Correcting the amplitudes corresponding to the first peak position and the second peak position respectively to determine a first power and a second power; removing spectrum values of the first signal and the second signal from the spectrum to obtain a residual spectrum, and determining a third power of the noise signal based on the residual spectrum; A signal-to-noise ratio of the time domain signal is determined based on the first power, the second power, and the third power.
2. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 1, wherein: The step of performing windowing processing on the sampled time domain signal to obtain a windowed signal, and converting the windowed signal into a frequency domain signal comprises: Performing weighted processing on the time domain signal using a cosine window function to obtain the windowed signal; Performing a fast Fourier transform of a preset number of points on the windowed signal to obtain the frequency domain signal.
3. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 2, wherein: The step of respectively correcting the amplitudes corresponding to the first peak position and the second peak position to determine the first power and the second power includes: Determining a correction coefficient based on the number of sampling points and a shape parameter of the cosine window function; Correcting the amplitude corresponding to the first peak position based on the correction coefficient to determine a first amplitude estimation value; the first amplitude estimation value is used to determine the first power; The amplitude corresponding to the second peak position is corrected based on the correction coefficient to determine a second amplitude estimation value; the second amplitude estimation value is used to determine the second power.
4. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 3, wherein: The expression of the correction coefficient is as follows: in, represents the correction factor, Indicates the number of sampling points, Represents the shape parameter of the cosine window function.
5. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 3, wherein: The expression of the signal-to-noise ratio is as follows: in, represents the signal-to-noise ratio of the first signal, represents the first amplitude estimate, represents the third power, represents the signal-to-noise ratio of the second signal, Represents the second amplitude estimate.
6. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 2, wherein: The removing the spectrum values of the first signal and the second signal from the spectrum to obtain a remaining spectrum includes: Determining a target frequency band based on a preset number of removal points, the first peak position, and the second peak position; the target frequency band is used to determine frequency spectrum values of the first signal and the second signal; The spectrum values within the target frequency band are removed from the spectrum of the frequency domain signal to obtain the remaining spectrum.
7. The method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing according to claim 6, wherein: The expression of the third power is as follows: in, represents the third power, Indicates the preset points, Indicates the number of spectrum value points removed, represents the remaining spectrum, Indicates the number of sampling points, Represents the cosine window function.
8. A device for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing, characterized in that: include: A windowing module is used to perform windowing processing on the sampled time domain signal to obtain a windowed signal, and convert the windowed signal into a frequency domain signal; The time domain signal comprises a first signal, a second signal and a noise signal; a first frequency of the first signal and a second frequency of the second signal are different; a first determining module, configured to determine a first peak position corresponding to the first frequency and a second peak position corresponding to the second frequency based on a frequency spectrum of the frequency domain signal; a correction module, configured to correct the amplitudes corresponding to the first peak position and the second peak position respectively to determine a first power and a second power; a second determining module, configured to remove the spectrum values of the first signal and the second signal from the spectrum to obtain a residual spectrum, and determine a third power of the noise signal based on the residual spectrum; A third determining module is configured to determine a signal-to-noise ratio of the time domain signal based on the first power, the second power, and the third power.
9. An electronic device, characterized in that: comprising a memory and a processor, wherein, The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to implement the steps in the method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the method for estimating the signal-to-noise ratio of a multi-frequency mixed signal based on windowing as described in any one of claims 1 to 7.