CN110442827B - Frequency estimation method, device and system and computer readable storage medium - Google Patents
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Abstract
The application discloses a frequency estimation method, which comprises the steps of sampling echo signals of a surface acoustic wave sensor to obtain an information matrix; reconstructing the information matrix to obtain a reconstructed matrix; performing noise reduction on the reconstruction matrix to obtain a noise reduction matrix; and carrying out Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result. In the method, the information matrix obtained by sampling the echo signals is reconstructed, the noise reduction processing is carried out on the reconstructed matrix to obtain the noise reduction matrix, then the frequency of the echo signals is estimated by utilizing the FFT algorithm, the redundant parts of the information are filtered through noise reduction, the operation amount is reduced, the operation speed of the FFT algorithm is improved, meanwhile, the interference of invalid information is avoided, and the frequency resolution of the FFT algorithm is improved. The application also discloses a frequency estimation device, a system and a computer readable storage medium, which have the same beneficial effects as the frequency estimation method.
Description
Technical Field
The present disclosure relates to the field of surface acoustic wave sensor data processing technologies, and in particular, to a frequency estimation method, apparatus, system, and computer readable storage medium.
Background
The surface acoustic wave sensor is a sensor which directly outputs an echo signal corresponding to the temperature of a measured object, and the processor obtains parameters such as the temperature of the measured object according to a curve of the pre-calibrated frequency and the temperature by extracting the frequency of the echo signal. It can be seen that frequency estimation is a key element in achieving parameter detection using a surface acoustic wave sensor.
At present, in the field of signal processing, a plurality of algorithms for frequency estimation exist, and the FFT (Fast Fourier Transformation, fast Fourier transform) has the advantages of high operation speed, few parameters, insensitivity of the algorithms to the parameters and wide use.
However, when the FFT algorithm processes a finite N-point time sequence, only N/2 independent spectral lines are obtained and can be used for effectively estimating the signal frequency, and the redundancy of calculation information wastes calculation amount, reduces the operation speed of the FFT algorithm and reduces the frequency resolution capability due to interference of invalid information.
Therefore, how to provide a solution to the above technical problem is a problem that a person skilled in the art needs to solve at present.
Disclosure of Invention
The frequency estimation method reduces the operation amount, improves the operation speed of the FFT algorithm, avoids the interference of invalid information, and improves the frequency resolution of the FFT algorithm; it is another object of the present application to provide a frequency estimation device, system and computer readable storage medium having the same advantageous effects as the above frequency estimation method.
In order to solve the above technical problems, the present application provides a frequency estimation method, including:
sampling echo signals of the surface acoustic wave sensor to obtain an information matrix;
reconstructing the information matrix to obtain a reconstructed matrix;
carrying out noise reduction treatment on the reconstruction matrix to obtain a noise reduction matrix;
and carrying out Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result.
Preferably, the noise reduction processing is performed on the reconstructed matrix, and the process of obtaining the noise reduction matrix specifically includes:
and carrying out noise reduction processing on the information matrix by utilizing Singular Value Decomposition (SVD) to obtain a noise reduction matrix.
Preferably, the process of reconstructing the information matrix to obtain a reconstructed matrix specifically includes:
reconstructing the attractor trajectory matrix by using the information matrix by using a time sequence;
and obtaining a reconstruction matrix according to the attractor trajectory matrix.
Preferably, after the obtaining the noise reduction matrix, before performing fast fourier transform FFT on the noise reduction matrix, the method further includes:
and carrying out zero padding treatment on the noise reduction matrix.
Preferably, after the calculating the frequency of the echo signal according to the result of the FFT transformation, the method further comprises:
and correcting the frequency.
Preferably, the process of correcting the frequency specifically includes:
the frequencies are corrected using a gaussian fitting algorithm.
In order to solve the above technical problem, the present application further provides a frequency estimation device, including:
the acquisition unit is used for sampling echo signals of the surface acoustic wave sensor to obtain an information matrix;
a reconstruction unit, configured to reconstruct the information matrix to obtain a reconstructed matrix;
the noise reduction unit is used for carrying out noise reduction treatment on the reconstruction matrix to obtain a noise reduction matrix;
and the calculation unit is used for carrying out Fast Fourier Transform (FFT) on the noise reduction matrix and calculating the frequency of the echo signal according to the FFT result.
Preferably, the noise reduction unit is specifically configured to perform noise reduction processing on the reconstructed matrix by using singular value decomposition SVD to obtain a noise reduction matrix.
In order to solve the above technical problem, the present application further provides a frequency estimation system, including:
a memory for storing a computer program;
a processor for implementing the steps of the frequency estimation method according to any one of the preceding claims when executing the computer program.
To solve the above technical problem, the present application further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the frequency estimation method according to any one of the above.
The application provides a frequency estimation method, which comprises the steps of sampling echo signals of a surface acoustic wave sensor to obtain an information matrix; reconstructing the information matrix to obtain a reconstructed matrix; performing noise reduction on the reconstruction matrix to obtain a noise reduction matrix; and carrying out Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result.
In the method, the information matrix obtained by sampling the echo signals is reconstructed, the noise reduction processing is carried out on the reconstructed matrix to obtain the noise reduction matrix, then the frequency of the echo signals is estimated by utilizing the FFT algorithm, the redundant parts of the information are filtered through noise reduction, the operation amount is reduced, the operation speed of the FFT algorithm is improved, meanwhile, the interference of invalid information is avoided, and the frequency resolution of the FFT algorithm is improved.
The application also provides a frequency estimation device, a system and a computer readable storage medium, which have the same beneficial effects as the frequency estimation method.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly explain the drawings needed in the prior art and embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a frequency estimation method provided in the present application;
fig. 2 is a schematic structural diagram of a frequency estimation device provided in the present application;
fig. 3 is a schematic structural diagram of a frequency estimation system provided in the present application.
Detailed Description
The core of the application is to provide a frequency estimation method, which reduces the operation amount, improves the operation speed of the FFT algorithm, simultaneously avoids the interference of invalid information and improves the frequency resolution of the FFT algorithm; another core of the present application is to provide a frequency estimation device, a system and a computer readable storage medium, which have the same advantageous effects as the above frequency estimation method.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Referring to fig. 1, fig. 1 is a flow chart of a frequency estimation method provided in the present application, including:
step S11: and sampling echo signals of the surface acoustic wave sensor to obtain an information matrix.
Specifically, the echo signal here is a signal returned from a resonator in the surface acoustic wave sensor, and this signal is related to the temperature of the object to be measured. The data obtained by a single sample can be represented by the following information matrix a:
A＝[x 1 x 2 x 3 ... x k ]wherein k=1, 2, … N, x k Is the frequency value of the echo signal.
Step S12: and reconstructing the information matrix to obtain a reconstructed matrix.
In particular, the reconstruction matrix obtained by reconstructing the information matrix is to facilitate removing redundant information, and the attractor trajectory matrix may be reconstructed by using a time sequence to construct the attractor trajectory matrix into the reconstruction matrix.
In addition to the above, the reconstruction matrix may be obtained in other ways, which are not particularly limited herein.
Step S13: and carrying out noise reduction treatment on the reconstruction matrix to obtain a noise reduction matrix.
Specifically, the step aims at filtering redundant information, filtering out components with small information quantity and little meaning, so that on one hand, the calculated quantity can be reduced, and on the other hand, the interference of invalid information can be avoided.
Accordingly, the noise reduction processing may be an SVD (Singular Value Decomposition ) method, or may be another method, which is not particularly limited herein.
Step S14: and carrying out Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result.
Specifically, when the FFT is adopted for frequency estimation, the inherent defect of poor frequency estimation variance performance (severe fluctuation of results) exists in the FFT method, so that the resolution of a variable to be measured by a measurement system is limited. In addition, when the FFT algorithm processes a finite-length N-point real sequence, only N/2 independent spectral lines are obtained and can be used for effectively estimating the signal frequency. This redundancy of calculation result information wastes calculation amount on the one hand and reduces the frequency resolution capability on the other hand. At present, the resolution of frequency estimation is usually improved by using secondary interpolation, namely, after FFT conversion, spectrum peak points and three points adjacent to each other are fitted by a quadratic function, a final frequency estimation value is obtained, but when a three-point frequency curve near the peak is dissimilar to the quadratic function, the frequency estimation performance of the method is poor. Therefore, the method and the device can effectively solve the problems by firstly carrying out noise reduction on the information matrix and then estimating the frequency of the echo signal by utilizing the FFT algorithm.
It should be noted that, because the performance of the FFT method in estimating the variance of the frequency is poor, a bias compensation method may be adopted at present, however, when the FFT method estimates the frequency of the sinusoidal signal truncated in the non-whole period, the result is biased estimation, and the bias is not obvious, so that the compensation effect is not ideal.
The application provides a frequency estimation method, which comprises the steps of sampling echo signals of a surface acoustic wave sensor to obtain an information matrix; reconstructing the information matrix to obtain a reconstructed matrix; performing noise reduction on the reconstruction matrix to obtain a noise reduction matrix; and carrying out Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result.
In the method, the information matrix obtained by sampling the echo signals is reconstructed, the noise reduction processing is carried out on the reconstructed matrix to obtain the noise reduction matrix, then the frequency of the echo signals is estimated by utilizing the FFT algorithm, the redundant parts of the information are filtered through noise reduction, the operation amount is reduced, the operation speed of the FFT algorithm is improved, meanwhile, the interference of invalid information is avoided, and the frequency resolution of the FFT algorithm is improved.
Based on the above embodiments:
as a preferred embodiment, the process of reconstructing the information matrix to obtain the reconstructed matrix specifically includes:
reconstructing the information matrix into an attractor trajectory matrix by using a time sequence;
and obtaining a reconstruction matrix according to the attractor trajectory matrix.
Specifically, the matrix A is reconstructed into a matrix B form by matrix reconstruction, namely, the information matrix is reconstructed into an attractor track matrix by using time sequence, and the reconstructed matrix B form is as follows:
the reconstruction matrix SVD technology based on the signals is an energy analysis method, namely, the signals with larger energy correspond to larger singular values, and the signals with smaller energy correspond to smaller singular values. The echo signal has higher signal-to-noise ratio and is a damped oscillation sine signal, so that a singular value with larger energy and a singular vector corresponding to the singular value can be extracted to achieve the effect of noise reduction.
As a preferred embodiment, the noise reduction processing is performed on the reconstruction matrix, and the process of obtaining the noise reduction matrix specifically includes:
and carrying out noise reduction treatment on the information matrix by utilizing Singular Value Decomposition (SVD) to obtain a noise reduction matrix.
Specifically, unlike conventional signal analysis concepts, SVD techniques decompose a reconstruction matrix containing signal information into a series of singular values and signal subspaces corresponding to the singular value vectors, with the different subspaces reflecting the different components and features of the signal.
Accordingly, the separation effect of SVD is greatly different due to different values of m and n in the reconstruction matrix, so that the selection of m and n is a key problem. The method for determining the information quantity of SVD is used for determining the values of m and n, namely determining the noise reduction matrix, and the specific method is as follows: a series of different rows m are taken to construct a matrix according to the following formula
η i ＝λ i /(λ 1 +λ 2 +…+λ p ),i＝1,2,…p；
Calculating the information quantity of each component signal by using singular values of construction matrix, wherein lambda i For the corresponding singular value, η i Is the information amount of the singular value. If m takes any value, from a certain information quantity eta i The initial subsequent information amounts all tend to 0, which indicates that the other components after the i-th component are not significant, where the number of rows m=i of the noise reduction matrix can be determined, and n=int (N/m), where N is the time series point. According to experience, the first two singular values can be selected as the signal part, the rest singular values are filtered as the noise part, so that a noise reduction matrix is obtained, and then the noise reduction matrix can be restored into a time sequence, so that the effect of noise reduction of echo signals is achieved.
Accordingly, after the time series is restored, the FFT conversion formula is utilized to carry out N-point FFT on the time series signal after the noise reduction treatment, and the N-point FFT can be represented by the following formula:
It should be noted that, in addition to the manner described in this embodiment, the noise reduction matrix may be determined in other manners, which are not particularly limited herein.
As a preferred embodiment, after obtaining the noise reduction matrix and before subjecting the noise reduction matrix to the fast fourier transform FFT, the method further comprises:
and carrying out zero padding treatment on the noise reduction matrix.
Specifically, due to windowing truncation and the existence of a 'fence effect' during sampling, when the real frequency of a signal is not coincident with the FFT discrete frequency, the signal spectrum leaks, even if no noise is influenced, the real frequency of the signal still falls between 2 FFT spectral lines in a main lobe, so that the frequency estimation cannot meet the precision requirement. In order to further improve the frequency resolution, under the condition that the data length of the echo signal is short, zero is filled at the tail part of the noise reduction signal before the noise reduction matrix is restored to a time sequence, and then an FFT of N points is carried out, so that interpolation is carried out on the result of the FFT, and the fence effect is overcome.
As a preferred embodiment, after calculating the frequency of the echo signal from the result of the FFT transformation, the method further comprises:
the frequency is corrected.
Specifically, in order to further improve the frequency resolution, the frequency can be corrected after the frequency is obtained, so that the frequency accuracy is improved, and the frequency resolution is improved.
As a preferred embodiment, the process of correcting the frequency is specifically:
the frequency is corrected using a gaussian fitting algorithm.
Specifically, in correction, the frequency obtained by FFT conversion may be corrected by using a gaussian fitting algorithm to improve accuracy. In addition, correction may be performed in other ways besides gaussian fitting, and the present application is not particularly limited herein.
Therefore, the SVD is adopted to carry out noise reduction treatment on the sampling signal, then the FFT method is utilized to estimate the frequency of the sampling signal, the zero padding treatment is carried out on the sampling signal in the process of estimating the frequency by utilizing the FFT, the fence effect is overcome, and then the frequency value can be corrected by Gaussian curve fitting.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a frequency estimation device provided in the present application, including:
the acquisition unit 1 is used for sampling echo signals of the surface acoustic wave sensor to obtain an information matrix;
a reconstruction unit 2, configured to reconstruct the information matrix to obtain a reconstructed matrix;
the noise reduction unit 3 is used for carrying out noise reduction processing on the reconstruction matrix to obtain a noise reduction matrix;
a calculating unit 4, configured to perform fast fourier transform FFT on the noise reduction matrix, and calculate the frequency of the echo signal according to the result of FFT transformation.
As a preferred embodiment, the noise reduction unit 3 is specifically configured to perform noise reduction processing on the reconstruction matrix by using singular value decomposition SVD, so as to obtain a noise reduction matrix.
The application also provides a frequency estimation device, which has the same beneficial effects as the frequency estimation method.
For an introduction of a frequency estimation device provided in the present application, reference is made to the embodiment of the frequency estimation method described above, and the description thereof is omitted herein.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a frequency estimation system provided in the present application, including:
a memory 5 for storing a computer program;
a processor 6 for implementing the steps of the frequency estimation method as described in any of the embodiments above when executing a computer program.
The application also provides a frequency estimation system, which has the same beneficial effects as the frequency estimation method.
For an introduction of a frequency estimation system provided in the present application, reference is made to the embodiment of the frequency estimation method described above, and the description thereof is omitted herein.
The present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by the processor 6, implements the steps of the frequency estimation method as described in any of the embodiments above.
The present application also provides a computer-readable storage medium having the same advantageous effects as the above frequency estimation method.
For an introduction to a computer readable storage medium provided in the present application, reference is made to the embodiment of the frequency estimation method described above, and the description thereof is omitted herein.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprises one" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A method of frequency estimation, comprising:
sampling echo signals of the surface acoustic wave sensor to obtain an information matrix; the echo signal is a signal returned by a resonator in the surface acoustic wave sensor, and the returned signal is related to the temperature of the measured object;
reconstructing the information matrix to obtain a reconstructed matrix;
carrying out noise reduction treatment on the reconstruction matrix to obtain a noise reduction matrix;
zero padding is carried out on the noise reduction matrix;
performing Fast Fourier Transform (FFT) on the noise reduction matrix, and calculating the frequency of the echo signal according to the FFT result;
the process of reconstructing the information matrix to obtain a reconstructed matrix specifically comprises the following steps:
reconstructing the attractor trajectory matrix by using the information matrix by using a time sequence;
obtaining a reconstruction matrix according to the attractor trajectory matrix;
the process of carrying out noise reduction treatment on the reconstruction matrix to obtain the noise reduction matrix specifically comprises the following steps:
carrying out noise reduction treatment on the information matrix by utilizing Singular Value Decomposition (SVD) to obtain a noise reduction matrix;
the process of obtaining the noise reduction matrix comprises the following steps:
the reconstruction matrix B is of the form:
taking a series of different rows m to construct a matrix according to the following formula:
η i ＝λ i /(λ 1 +λ 2 +…+λ p ),i＝1,2,…p
calculating the information quantity of each component signal by using the singular value of the reconstruction matrix, wherein lambda i For the corresponding singular value, η i Information amount for the singular value;
determining the line number m=i of the noise reduction matrix, and then n=int (N/m), wherein N is a time sequence point;
selecting the first two singular values as a signal part, and filtering the rest singular values as a noise part to obtain a noise reduction matrix;
the process of carrying out fast Fourier transform FFT on the noise reduction matrix and calculating the frequency of the echo signal according to the FFT result comprises the following steps:
the noise reduction matrix is restored into a time sequence, and the FFT conversion formula is utilized to carry out N-point FFT on the time sequence signal after noise reduction treatment, and the N-point FFT can be represented by the following formula:
wherein k=0, 1,2, …, N-1; e is an index, X k Is the frequency of the echo signal; x is x n N is the time sequence point, which is the nth information component;
obtain the command |X k The k value when the maximum value is taken is denoted as k max F=k max *f s /N；
Wherein f s The sampling frequency, f, is the required frequency.
2. The frequency estimation method according to claim 1, further comprising, after the calculating the frequency of the echo signal from the result of the FFT transformation:
and correcting the frequency.
3. The frequency estimation method according to claim 2, wherein the process of correcting the frequency is specifically:
the frequencies are corrected using a gaussian fitting algorithm.
4. A frequency estimation device, comprising:
the acquisition unit is used for sampling echo signals of the surface acoustic wave sensor to obtain an information matrix; the echo signal is a signal returned by a resonator in the surface acoustic wave sensor, and the returned signal is related to the temperature of the measured object;
a reconstruction unit, configured to reconstruct the information matrix to obtain a reconstructed matrix;
the noise reduction unit is used for carrying out noise reduction treatment on the reconstruction matrix to obtain a noise reduction matrix;
the computing unit is used for carrying out Fast Fourier Transform (FFT) on the noise reduction matrix and computing the frequency of the echo signal according to the FFT result;
the frequency estimation device is further configured to:
zero padding is carried out on the noise reduction matrix;
reconstructing the attractor trajectory matrix by using the information matrix by using a time sequence;
obtaining a reconstruction matrix according to the attractor trajectory matrix;
the frequency estimation device is further configured to:
carrying out noise reduction treatment on the information matrix by utilizing Singular Value Decomposition (SVD) to obtain a noise reduction matrix;
the reconstruction matrix B is of the form:
taking a series of different rows m to construct a matrix according to the following formula:
η i ＝λ i /(λ 1 +λ 2 +…+λ p ),i＝1,2,…p
calculating the information quantity of each component signal by using the singular value of the reconstruction matrix, wherein lambda i For the corresponding singular value, η i Information amount for the singular value;
determining the line number m=i of the noise reduction matrix, and then n=int (N/m), wherein N is a time sequence point;
selecting the first two singular values as a signal part, and filtering the rest singular values as a noise part to obtain a noise reduction matrix;
the noise reduction matrix is restored into a time sequence, and the FFT conversion formula is utilized to carry out N-point FFT on the time sequence signal after noise reduction treatment, and the N-point FFT can be represented by the following formula:
wherein,,k=0, 1,2, …, N-1; e is an index, X k Is the frequency of the echo signal; x is x n N is the time sequence point, which is the nth information component;
obtain the command |X k The k value when the maximum value is taken is denoted as k max F=k max *f s /N；
Wherein f s The sampling frequency, f, is the required frequency.
5. A frequency estimation system, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the frequency estimation method according to any one of claims 1 to 3 when executing said computer program.
6. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the frequency estimation method according to any of claims 1 to 3.
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