Method and system for accurately measuring eigen parameters of high-frequency signal at ultra-low sampling rate

Abstract

A method and system for accurately measuring eigen parameters of a signal, which can perform synchronous sampling on a high-frequency signal and a differential / integral signal thereof at an ultra-low sampling rate, and accurately measure frequency, amplitude and initial phase parameters of all components in the high-frequency signal, thereby accurately reconstructing the high-frequency signal. Moreover, the measurement method and system can perform sampling at any sampling rate lower than or / and higher than the highest or lowest frequency of a measured signal, accurately measure frequency, amplitude and initial phase parameters of components in a multi-frequency signal distributed at any frequency, can accurately reconstruct the signal, and are not only suitable for measurement and reconstruction of eigen parameters of a real signal, but also suitable for measurement and reconstruction of eigen parameters of a complex signal. For a noise-containing signal, the measurement method and system can achieve high-precision measurement and reconstruction of eigen parameters of the signal.

Description

A method and system for accurately measuring characteristic parameters of high-frequency signals at ultra-low sampling rates Technical Field

[0001] The present invention relates to a method and system for accurately measuring characteristic parameters of a high-frequency signal, such as frequency, amplitude, and initial phase, and relates to the field of signal processing technology. The method can be widely used in signal analysis and processing in the fields of electronics, communications, acoustics, optics, video, imaging, mechanics, biology, medicine, etc. Background Art

[0002] Sampling bridges the analog and digital worlds, fueling the rapid development of digital signal processing technology and playing a vital role in contemporary science, communications, national defense, and everyday life. With the continued maturity and application of 5G and 6G communication technologies, as well as deep space exploration, lidar, and terahertz technologies, the requirements for signal sampling are becoming increasingly stringent. The hardware cost for sampling is rapidly increasing, and achieving high-rate sampling of high-frequency signals has become a bottleneck restricting the development of signal processing technology.

[0003] Measuring and reconstructing the characteristic parameters of higher-frequency signals at the lowest possible sampling rate has long been a goal pursued by scientists and engineers both domestically and internationally. In 1928, Nyquist proposed the sampling theorem for baseband signals, stating that a sampling rate of at least twice the signal's highest effective frequency is required for accurate reconstruction of the original signal. In 1948, Shannon further proposed the Shannon-Nyquist sampling theorem for band-limited signals, stating that a sampling rate of at least twice the signal's maximum effective bandwidth can also accurately reconstruct the original signal, significantly reducing the sampling rate requirement.

[0004] Since then, scientists and engineers at home and abroad have proposed numerous theories, methods, and techniques for reducing sampling rates based on the diverse characteristics of signals. For example, compressed sampling technology based on compressed sensing for sparse signals employs a sampling-while-compression technique, reducing the sampling rate while also compressing the data dimensionality. However, this technique requires the establishment of a dictionary tailored to the specific signal, and currently, there is no universal, effective method for establishing a sparse decomposition dictionary. Undersampling technology for signals with a finite update rate uses a sampling rate determined by the signal's update rate and can be significantly lower than the signal's Shannon-Nyquist sampling rate. However, this technique requires that the signal in the time domain be determined by a finite number of pulses, and that prior information about the pulses be known. Furthermore, there are X-sampling techniques, non-uniformly spaced random sampling techniques, and so on.

[0005] Although the above-mentioned technology can significantly break through the limitation of Shannon-Nyquist sampling rate and greatly reduce the hardware cost of sampling, the following problems still exist: 1. It puts forward more stringent requirements on the signal, and at the same time greatly increases the difficulty and cost of signal reconstruction, and even makes it difficult to achieve online reconstruction of the signal; 2. Although the sampling rate is greatly reduced, when the frequency of the signal is very high (such as terahertz signal), the hardware cost of sampling is still very high, or even difficult to achieve; 3. The sampling technology is closely related to the characteristics and prior knowledge of the signal, which limits the versatility of the sampling technology; 4. Insufficient attention is paid to the measurement and extraction technology of the amplitude and phase of the signal, which cannot meet the needs of engineering measurement. For example, the magnitude of signal energy is proportional to the square of the amplitude. Accurately measuring the amplitude of the signal component is the key to obtaining the signal energy distribution. The phase parameter is an important parameter for lidar measurement. When using lidar to measure the distance and speed of a target, the maximum accuracy of measuring the distance using only the frequency parameter can only reach half the radar wavelength. To achieve higher-precision measurement, the phase parameter must be used. The higher the accuracy of the phase parameter, the higher the distance measurement accuracy. When using the Doppler effect to measure the speed or even acceleration of a target, the phase parameter is the most critical parameter.

[0006] Summary of the Invention

[0007] The present invention provides a method and system for accurately measuring characteristic parameters of high-frequency signals at an ultra-low sampling rate, which is used for ultra-low rate sampling of high-frequency signals and accurate measurement of frequency, amplitude and initial phase parameters and signal reconstruction.

[0008] A method for accurately measuring signal characteristic parameters uses the original digital discrete signal of a multi-frequency high-frequency signal and its differential / integral digital discrete signal to accurately measure the frequency, amplitude, and initial phase parameters of all components of the multi-frequency high-frequency signal, including the following steps:

[0009] S101, constructing an original signal matrix, using the original digital discrete signal of the multi-frequency high-frequency signal obtained at an ultra-low sampling rate to construct the original signal matrix;

[0010] S102, constructing a differential / integral signal matrix, using the differential / integral digital discrete signals of the multi-frequency high-frequency signal obtained at an ultra-low sampling rate to construct the differential / integral signal matrix;

[0011] The sampling point distribution of the differential / integral digital discrete signal is the same as that of the original digital discrete signal, and the elements in the differential / integral signal matrix are in one-to-one correspondence with the elements in the original signal matrix;

[0012] S103, constructing a signal generalized eigenvalue equation, using the original signal matrix and the differential / integral signal matrix to construct a signal generalized eigenvalue equation, uB=λuA, Bv=λAv,

[0013] Wherein, A is the original signal matrix, B is the differential / integral signal matrix, λ is the generalized eigenvalue of the signal generalized eigenvalue equation, and v and v are the left and right generalized eigenvectors of the signal generalized eigenvalue equation, respectively;

[0014] S104, solving the signal generalized eigenvalue equation by reducing the order, performing singular value decomposition on the original signal matrix or the differential / integral signal matrix, using only non-zero singular values ​​and their corresponding singular vectors, reducing the signal generalized eigenvalue equation from a high-order generalized eigenvalue problem to a low-order generalized eigenvalue problem, and obtaining the generalized eigenvalues ​​and their corresponding generalized eigenvectors of the signal generalized eigenvalue equation;

[0015] S105 , calculating the component signal frequencies of the multi-frequency high-frequency signal, and calculating the component signal amplitudes and initial phases of the multi-frequency high-frequency signal.

[0016] Preferably, in step S101,

[0017] (1) The rank of the original signal matrix is ​​closely related to the number of frequency components of the multi-frequency high-frequency signal, that is, when the original digital discrete signal is a real number, the rank of the original signal matrix is ​​twice the number of frequency components of the multi-frequency high-frequency signal; when the original digital discrete signal is a complex number, the rank of the original signal matrix is ​​1 times the number of frequency components of the multi-frequency high-frequency signal;

[0018] (2) When the sampling intervals of the original digital discrete signals are equal, the Hankel matrix and the Toeplitz matrix constructed by the original digital discrete signals can be used as the original signal matrix; when the sampling intervals of the original digital discrete signals are semi-randomly distributed, the sampling intervals of the original digital discrete signals in the same row / column of the original signal matrix are randomly distributed, and the sampling intervals of the original digital discrete signals in different rows / columns are equal to the sampling intervals of the original digital discrete signals in the previous column / row.

[0019] Furthermore, in step S104, after reduction, when the original digital discrete signal is a real number, the order of the low-order generalized eigenvalue equation is twice the number of frequency components of the multi-frequency high-frequency signal; when the original digital discrete signal is a complex number, the order of the low-order generalized eigenvalue equation is 1 times the number of frequency components of the multi-frequency high-frequency signal.

[0020] Furthermore, in step S105,

[0021] (1) using the generalized eigenvalue of the signal generalized eigenvalue equation to accurately calculate the frequencies of the component signals of the multi-frequency high-frequency signal,

[0022] Among them, abs(λ i ) is the modulus of the i-th non-zero generalized eigenvalue, p is the order / degree of the differential / integral signal used when constructing the differential / integral signal matrix B, and c takes ±1 corresponding to the differential / integral signal matrix respectively;

[0023] and / or, (2) using the generalized eigenvector of the signal generalized eigenvalue equation and the original signal matrix, accurately calculating the amplitude and initial phase of the component signal of the real multi-frequency high-frequency signal, the calculation steps comprising:

[0024] S1051A, using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix, calculate the following matrix elements, e i11 =v i1 A i1 v i1 , e i12 =v i1 A i2 v i1 , e i21 =u i2 A i1 v i2 , e i22 =u i2 A i2 v i2 ,

[0025] Among them, u i1 and v i1 are the left and right generalized eigenvectors corresponding to the i-th generalized eigenvalue, u i2 and v i2 are the left and right generalized eigenvectors corresponding to the conjugate generalized eigenvalue of the i-th generalized eigenvalue, A i1 The amplitude is 1, the initial phase is zero, and the frequency is the calculated f i The cosine signal corresponds to the cosine component signal matrix of the sampling point of the original signal matrix A, A i2 The amplitude is 1, the initial phase is zero, and the frequency is the calculated f i The sinusoidal signal corresponds to the sinusoidal component signal matrix of the sampling points of the original signal matrix A;

[0026] S1052A, using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix, calculate the following vector element, g i1 =u i1 Avi1 , g i2 =u i2 Av i2 ;

[0027] S1053A, using the matrix element e i11 、e i12 、e i21 、e i22 and the vector element g i1 、g i2 Construct a system of linear equations in two variables,

[0028] S1054A, solve the system of linear equations of two variables to obtain the parameter h i1 and h i2 ;

[0029] S1055A, calculate the amplitude and phase of the i-th component of the multi-frequency high-frequency signal, the calculation formulas are:

[0030] And / or, (3) using the generalized eigenvector of the signal generalized eigenvalue equation and the original signal matrix, the amplitude and initial phase of the component signal of the complex multi-frequency high-frequency signal can be accurately calculated, and the calculation steps include:

[0031] S1051B, using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix, calculate the Rayleigh quotient w as follows: i , w i =u i Av i / v i A i v i

[0032] Among them, u i and v i are the generalized eigenvalues ​​λ i The corresponding left and right generalized eigenvectors, A i The amplitude is 1, the initial phase is zero, and the frequency is the calculated f i The complex signal corresponds to the complex component signal matrix of the sampling points of the original signal matrix A;

[0033] S1052B, using the Rayleigh quotient to calculate the amplitude and phase of the i-th component of the multi-frequency high-frequency signal, the calculation formulas are: a i =abs(w i ),

[0034] Among them, abs(wi ) is w i The modulus, imag(w i ) is w i The imaginary part, real(w i ) is w i The real part of .

[0035] Preferably, the sampling rates of the original digital discrete signal and the differential / integral digital discrete signal can be arbitrarily lower and / or arbitrarily higher than the highest or lowest frequency of the multi-frequency high-frequency signal; the original digital discrete signal and the differential / integral digital discrete signal can be obtained by any means.

[0036] The present invention also discloses a signal characteristic parameter precise measurement system that adopts the above-mentioned signal characteristic parameter precise measurement method. It uses a digital discrete signal obtained at a sampling rate arbitrarily lower than and / or arbitrarily higher than the highest or lowest frequency of the measured signal, and can accurately analyze and measure the frequency, amplitude and initial phase parameters of all components of the measured signal, and accurately reconstruct the measured signal.

[0037] The signal characteristic parameter precise measurement system includes: a signal preprocessing unit, a signal delay unit, an original signal A / D conversion unit, a differential / integral signal A / D conversion unit, and a signal measurement and analysis unit.

[0038] (1) The signal preprocessing unit receives the measured signal, conditions and filters the measured signal so that the measured signal meets the requirements of the post-processing software and hardware configuration, and divides the preprocessed signal into two signals and outputs them in parallel;

[0039] (2) The signal delay unit receives the two signals output in parallel by the signal preprocessing unit, applies different delays to the two signals, and outputs them separately;

[0040] (3) The original signal A / D conversion unit receives one of the signals output by the signal delay unit, performs an A / D conversion operation, and obtains the original digital discrete signal of the measured signal;

[0041] (4) The differential / integral signal A / D conversion unit receives the other signal output by the signal delay unit, performs a differential / integral operation on the other signal, obtains a differential / integral signal of the measured signal, and then conditions the differential / integral signal so that the differential / integral signal meets the requirements of the post-related software and hardware configuration, and then performs an A / D conversion operation to obtain a differential / integral digital discrete signal of the measured signal;

[0042] (5) The signal measurement and analysis unit receives and stores the original digital discrete signal obtained by the original signal A / D conversion unit and the differential / integral digital discrete signal obtained by the differential / integral signal A / D conversion unit, and then uses the original digital discrete signal and the differential / integral digital discrete signal to calculate and analyze the frequency, amplitude and initial phase parameters of the components of the measured signal using the signal characteristic parameter precise measurement method according to claim 1, and accurately reconstructs the measured signal.

[0043] Furthermore, after the signal preprocessing unit conditions and filters the measured signal, the maximum frequency of the two signals output in parallel is not limited by the maximum A / D conversion rate of the subsequent original signal A / D conversion unit and the differential / integral signal A / D conversion unit;

[0044] and / or applying different time delays to the two signals output in parallel by the signal preprocessing unit, respectively, to ensure that the original digital discrete signal obtained by the original signal A / D conversion unit and the differential / integral digital discrete signal obtained by the differential / integral signal A / D conversion unit are synchronized;

[0045] And / or, the sampling rate of the A / D conversion module of the original signal A / D conversion unit can be configured as a constant rate or a variable rate, and the sampling rate can be arbitrarily lower than or / and arbitrarily higher than the highest or lowest frequency of the measured signal; when the sampling rate is configured as a variable rate, the sampling interval should be semi-randomly distributed.

[0046] Furthermore, the differential / integral signal A / D conversion unit includes:

[0047] a differential module configured to: receive the other signal output by the signal delay unit, perform first-order or / and multi-order differentials, and obtain first-order or / and multi-order differential signals of the measured signal; and

[0048] A differential signal conditioning module is configured to condition and amplify the first-order and / or multi-order differential signals to meet the requirements of subsequent related software and hardware configurations; and

[0049] an integration module configured to: receive the other signal output by the signal delay unit, perform one or / and multiple integrations, and obtain one or / and multiple integration signals of the measured signal; and

[0050] An integral signal conditioning module is configured to condition and amplify the primary and / or multiple integral signals to meet the requirements of subsequent related software and hardware configurations; and

[0051] The differential / integral signal A / D conversion module is configured to: perform an A / D conversion operation to obtain the differential / integral digital discrete signal of the measured signal.

[0052] Preferably, the differential / integral signal A / D conversion unit can also be configured to: only include the differential module, the differential signal conditioning module and the differential / integral signal A / D conversion module; or, only include the integration module, the integration signal conditioning module and the differential / integral signal A / D conversion module.

[0053] Preferably, a first-order differential, or multi-order differential, or single-integral, or multi-integral digital discrete signal of the measured signal can be selectively obtained; the sampling rate and sampling interval configuration of the differential / integral signal A / D conversion module are the same as the sampling rate and sampling interval configuration of the A / D conversion module of the original signal A / D conversion unit.

[0054] The signal characteristic parameter precise measurement system adopting the above-mentioned signal characteristic parameter precise measurement method uses a digital discrete signal obtained at a sampling rate arbitrarily lower than and / or arbitrarily higher than the highest or lowest frequency of the measured signal, and can accurately analyze and measure the frequency, amplitude and initial phase parameters of all components of the measured signal, and accurately reconstruct the measured signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] FIG1 is a schematic diagram showing the principles of various methods for accurately measuring signal characteristic parameters according to various implementation schemes.

[0056] FIG2 is a schematic diagram showing the principles of a system for accurately measuring signal characteristic parameters according to various embodiments.

[0057] FIG3 is a schematic diagram showing the principle of a differential / integral signal A / D conversion unit according to various embodiments.

[0058] FIG4 is a flow chart of the signal characteristic parameter accurate measurement method and steps and signal data according to various embodiments.

[0059] FIG5 shows the positional relationship between equally spaced sampling points of a complex signal and the signal during low-rate sampling.

[0060] FIG6 shows the positional relationship between randomly spaced sampling points of a complex signal and the signal during low-rate sampling.

[0061] FIG7 shows the positional relationship between equally spaced sampling points of a real signal and the signal during low-rate sampling. DETAILED DESCRIPTION

[0062] Below, various embodiments are described in conjunction with the accompanying drawings, which will help to better understand the details disclosed herein. With respect to the functional block diagrams of the various embodiments shown in the drawings, the functional blocks do not necessarily indicate the division between hardware circuits. For example, one or more functional blocks (e.g., memory or A / D converter) can be implemented in a single piece of hardware (e.g., random access memory, hard disk or general signal processor) or multiple pieces of hardware. Similarly, a program can be a stand-alone program, can be incorporated into an operating system as a subroutine, can be a function in an installed software package, can also be implemented in hardware or firmware, and so on. It should be understood that the various embodiments are not limited to the arrangements shown in the drawings, and these descriptions are merely exemplary and are not intended to limit the scope of the disclosure herein.

[0063] The terms used herein are only for describing specific embodiments and are not intended to limit the disclosure herein. As used herein, the term "high-frequency signal" is relative to the sampling rate, which means that when the signal characteristic parameter measurement method and system disclosed herein are used to measure and analyze the measured signal, the sampling rate of the digital discrete signal used can accurately calculate and analyze the frequency, amplitude and initial phase parameters of the component signal even when it is far lower than the highest frequency of the measured signal. During implementation, it is not required that the sampling rate must be far lower than the highest frequency of the measured signal. High-frequency signal does not specifically refer to a measured signal greater than or equal to a certain frequency. The measured signal is not limited to time domain signals, but also includes spatial signals and all other forms of signals.

[0064] The term "ultra-low sampling rate" means that the sampling rate of a digital discrete signal is much lower than the sampling rate of a traditional signal measurement and analysis method (such as a signal analysis method based on Fourier theory).

[0065] The terms "system", "unit" and "module" mean hardware or / and software systems that operate to perform one or more functions. For example, a system, unit or module may include an electronic circuit that includes or / and is coupled to one or more computer processors, controllers, or other logic-based devices that perform operations based on instructions stored on tangible and non-transient computer-readable storage media. The systems, units or modules shown in the accompanying drawings may represent hardware that operates based on software or hard-wired instructions, software that instructs hardware to perform operations, or a combination thereof. A "system", "unit" or "module" may include or represent hardware and related instructions (for example, software stored on tangible and non-transient computer-readable storage media) that perform one or more operations described herein. Hardware may include an electronic circuit that includes or / and is connected to one or more logic-based devices, such as microprocessors, processors, controllers, etc. In addition, a "system", "unit" or "module" may be configured to execute one or more algorithms to perform the functions or operations described herein. One or more algorithms may include aspects of the embodiments disclosed herein, whether explicitly identified in a flow chart or as steps of a method.

[0066] Various embodiments provide a method and system for accurately measuring characteristic parameters of high-frequency signals at an ultra-low sampling rate, used for ultra-low-rate sampling of high-frequency signals, precise measurement of characteristic parameters (frequency, amplitude, and initial phase), and signal reconstruction. The provided measurement method and system can synchronously sample the measured signal and its differential / integral signals at a sampling rate significantly lower than the measured signal frequency, obtaining the original digital discrete signal of the measured signal and its differential / integral digital discrete signals. Using these digital discrete signals obtained at the ultra-low sampling rate, the frequency, amplitude, and initial phase parameters of all components of the measured signal can be accurately calculated.

[0067] In various implementation schemes, the provided measurement method and system can also perform synchronous sampling on the measured signal and its differential / integral signal at a sampling rate arbitrarily lower than and / or arbitrarily higher than the highest or lowest frequency of the measured signal, thereby obtaining the original digital discrete signal of the multi-frequency signal with arbitrary frequency distribution and its differential / integral digital discrete signal, and then accurately calculate the frequency, amplitude and initial phase parameters of all components of the measured multi-frequency signal.

[0068] In various embodiments, the provided measurement method uses the original digital discrete signal of the measured signal and its differential / integral digital discrete signal to accurately calculate the frequency, amplitude and initial phase parameters of all components of the measured signal. The original digital discrete signal of the measured signal and its differential / integral digital discrete signal can be obtained using the measurement system disclosed in this article or by other methods. In the absence of noise interference and without considering digital discrete errors, the calculated frequency, amplitude and initial phase parameters of the component signals are all theoretically accurate values. For signals containing noise, the frequency, amplitude and initial phase parameters of the component signals measured using the provided measurement method also have extremely high accuracy.

[0069] Figure 1 is a schematic diagram of the principles of a method for accurately measuring signal characteristic parameters according to various embodiments. This measurement method uses the original digital discrete signal of a high-frequency signal obtained by synchronous sampling at an ultra-low sampling rate and its differential / integral digital discrete signal to accurately calculate the frequency, amplitude, and initial phase parameters of all components of a multi-frequency high-frequency signal with arbitrary frequency distribution.

[0070] (1) Constructing the original signal matrix using the original digital discrete signal of the multi-frequency high-frequency signal obtained at an ultra-low sampling rate;

[0071] (2) Constructing a differential / integral signal matrix using differential / integral digital discrete signals of multi-frequency high-frequency signals obtained at an ultra-low sampling rate;

[0072] (3) Construct the signal generalized eigenvalue equation using the original signal matrix and the differential / integral signal matrix;

[0073] (4) Perform singular value decomposition on the original signal matrix or differential / integral signal matrix, using only non-zero singular values ​​and their corresponding singular vectors, and reduce the signal generalized eigenvalue equation from a high-order generalized eigenvalue problem to a low-order generalized eigenvalue problem, and obtain the generalized eigenvalues ​​and their corresponding generalized eigenvectors of the signal generalized eigenvalue equation;

[0074] (5) Using the generalized eigenvalues ​​of the signal generalized eigenvalue equation; based on the real signal or complex signal, using the generalized eigenvectors corresponding to the generalized eigenvalues ​​and the original signal matrix, selectively calculate the amplitude and initial phase of the multi-frequency high-frequency real signal or complex signal.

[0075] In fact, this measurement method uses the original digital discrete signal of the signal obtained by synchronous sampling at any sampling rate and its differential / integral digital discrete signal to accurately calculate the frequency, amplitude and initial phase parameters of all components of the multi-frequency signal with arbitrary frequency distribution.

[0076] Figure 2 is a schematic diagram of a signal characteristic parameter precision measurement system according to various embodiments. The measurement system includes: a signal preprocessing unit, a signal delay unit, an original signal A / D conversion unit, a differential / integral signal A / D conversion unit, and a signal measurement and analysis unit.

[0077] In Figure 2, the signal preprocessing unit is configured to receive the measured signal, perform preprocessing such as amplification, isolation, and filtering on it so that the measured signal meets the requirements of the post-processing hardware and software configuration, and divide the preprocessed signal into two signals and output them in parallel to the post-processing signal delay unit.

[0078] Since the signal processing technology of the post-processing signal measurement and analysis unit is not based on Fourier transform theory, after pre-processing the measured signal, the maximum frequency of the two signals output in parallel to the post-processing signal delay unit may not be restricted by the maximum A / D conversion rate of the post-processing original signal A / D conversion unit and the post-processing differential / integral signal A / D conversion unit.

[0079] In Figure 2, the function of the signal delay unit is configured as follows: receiving two signals output in parallel by the signal preprocessing unit and applying different delays to the two signals, so that the original digital discrete signal generated by the measured signal after passing through the subsequent original signal A / D conversion unit and the differential / integral digital discrete signal generated after passing through the subsequent differential / integral signal A / D conversion unit remain synchronized.

[0080] In Figure 2, the original signal A / D conversion unit is configured to receive one of the signals output by the signal delay unit and perform an A / D conversion on it to obtain the original digital discrete signal of the measured signal. Depending on the requirements of the subsequent signal measurement and analysis unit, the sampling rate of the A / D conversion module of the original signal A / D conversion unit can be configured as either constant or variable, and the sampling rate can be arbitrarily higher and / or lower than the highest or lowest frequency of the measured signal. When the sampling rate is configured as variable, the sampling intervals should be semi-randomly distributed.

[0081] In Figure 2, the functional configuration of the differential / integral signal A / D conversion unit is as follows: receiving another signal output by the signal delay unit, and performing a differential / integral operation on it to obtain a differential / integral signal of the measured signal, and then conditioning the differential / integral signal so that the differential / integral signal meets the requirements of the subsequent differential / integral signal A / D conversion module, and then performing an A / D conversion operation to obtain a differential / integral digital discrete signal of the measured signal.

[0082] Figure 3 is a schematic diagram of a differential / integral signal A / D conversion unit formed according to various embodiments. The unit includes: a differential module, a differential signal conditioning module, an integral module, an integral signal conditioning module, and a differential / integral signal A / D conversion module.

[0083] In FIG3 , the differential module is configured to perform first-order or / and p-order differentials on the input signal to obtain first-order or / and p-order differential signals of the measured signal, where p is a positive integer.

[0084] In Figure 3, the functional configuration of the differential signal conditioning module is: receiving the differential signal of the measured signal output by the differential module, and performing pre-processing such as amplification and isolation on the differential signal so that the differential signal of the measured signal meets the requirements of the subsequent differential / integral signal A / D conversion module.

[0085] In FIG3 , the function of the integration module is configured as follows: performing one or / and p times integration on the input signal to obtain one or / and p times integrated signals of the measured signal, where p is a positive integer.

[0086] In Figure 3, the functional configuration of the integral signal conditioning module is: receiving the integral signal of the measured signal output by the integral module, and performing pre-processing such as amplification and isolation on the integral signal so that the integral signal of the measured signal meets the requirements of the subsequent differential / integral signal A / D conversion module.

[0087] In Figure 3, the functional configuration of the differential / integral signal A / D conversion module is: receiving the differential / integral signal of the measured signal output by the differential signal conditioning module and / or the integral signal conditioning module, applying an A / D conversion operation to it, and obtaining the differential / integral digital discrete signal of the measured signal.

[0088] The differential / integral signal A / D conversion unit shown in FIG3 can also be configured to include only a differential module, a differential signal conditioning module, and a differential / integral signal A / D conversion module; or to include only an integral module, an integral signal conditioning module, and a differential / integral signal A / D conversion module. The sampling rate and sampling interval configuration of the differential / integral signal A / D conversion module are the same as those of the A / D conversion module of the original signal A / D conversion unit.

[0089] In Figure 2, the functional configuration of the signal measurement and analysis unit is: receiving and saving the original digital discrete signal obtained by the original signal A / D conversion unit, and the differential / integral digital discrete signal obtained by the differential / integral signal A / D conversion unit, and based on these two sets of digital discrete signals, calculating and analyzing the frequency, amplitude and initial phase parameters of the components of the measured signal.

[0090] In the signal measurement and analysis unit of Figure 2, the signal characteristic parameter precise measurement method disclosed in this article is applied, and a digital discrete signal obtained at any sampling rate lower than and / or higher than the highest or lowest frequency of the measured signal is used to accurately calculate the frequency, amplitude and initial phase parameters of all components of the measured signal, and accurately reconstruct the measured signal.

[0091] FIG4 is a flow chart of a method and steps for accurately measuring signal characteristic parameters and signal data according to various embodiments. The method uses the original digital discrete signal of a multi-frequency high-frequency signal and its differential / integral digital discrete signal to accurately measure the frequency, amplitude and initial phase parameters of the component signals of the multi-frequency high-frequency signal. The sampling intervals of the original digital discrete signal and the differential / integral digital discrete signal can be equal or semi-randomly distributed; the sampling rate can be arbitrarily lower or / and higher than the highest or lowest frequency of the measured signal; the original digital discrete signal and the differential / integral digital discrete signal of the multi-frequency high-frequency signal can be obtained using the signal characteristic parameter accurate measurement system disclosed in this article, or can be obtained by other means.

[0092] The method for accurately measuring signal characteristic parameters includes: constructing the original signal matrix, constructing the differential / integral signal matrix, constructing the signal generalized eigenvalue equation, solving the signal generalized eigenvalue equation by reducing the order, calculating the component signal frequency, calculating the component signal amplitude and initial phase, and other methods and steps.

[0093] In FIG4 , the method for constructing the original signal matrix is ​​characterized in that: the method uses the original digital discrete signal of the multi-frequency high-frequency signal to construct the original signal matrix, and the rank of the matrix is ​​closely related to the number of frequency components of the multi-frequency high-frequency signal, that is, the rank of the real original signal matrix is ​​twice the number of frequency components of the multi-frequency high-frequency signal, and the rank of the complex original signal matrix is ​​1 times the number of frequency components of the multi-frequency high-frequency signal. The original signal matrix can be a square matrix with equal number of rows and columns, or a rectangular matrix with unequal number of rows and columns, and the number of rows and columns must not be less than the rank of the original signal matrix.

[0094] When the sampling intervals of the original digital discrete signals are equal, the Hankel matrix, Toeplitz matrix or other similar matrices constructed using the original digital discrete signals can be used as the original signal matrix; when the sampling intervals of the original digital discrete signals are semi-randomly distributed, the sampling intervals of the original digital discrete signals in the same row / column of the original signal matrix can be randomly distributed, and the sampling intervals of the original digital discrete signals in different rows / columns should be equal to the original digital discrete signals in the previous column / row.

[0095] In Figure 4, the method for constructing a differential / integral signal matrix is ​​characterized in that: the method uses differential / integral digital discrete signals of multi-frequency high-frequency signals to construct a differential / integral signal matrix, and the elements in the differential / integral signal matrix correspond one-to-one to the elements in the original signal matrix, that is, the sampling points of the original signal in the original signal matrix are the same as the sampling points of the differential / integral signal in the differential / integral signal matrix.

[0096] In FIG4 , the method for constructing a generalized eigenvalue equation of a signal is characterized in that: the method uses the original signal matrix of a multi-frequency high-frequency signal and its differential / integral signal matrix to construct a generalized eigenvalue equation of the signal, uB=λuA,Bv=λAv,

[0097] Where A is the original signal matrix, B is the differential / integrated signal matrix, λ is the generalized eigenvalue of the signal's generalized eigenvalue equation, and u and v are the left and right generalized eigenvectors of the signal's generalized eigenvalue equation, respectively. The generalized eigenvalue λ here corresponds one-to-one to the frequency of the component signals of the multi-frequency high-frequency signal.

[0098] In Figure 4, the method for reducing the order of solving the generalized eigenvalue equation of the signal is characterized in that: this method performs singular value decomposition or eigenspectrum decomposition on the original signal matrix or differential / integral signal matrix, and only uses non-zero singular values ​​and their corresponding singular vectors, or non-zero eigenspectra and their corresponding eigenvectors, to reduce the order of the generalized eigenvalue equation of the signal from a high-order generalized eigenvalue problem to a low-order generalized eigenvalue problem, and then converts it into a standard eigenvalue problem, thereby being able to efficiently and accurately calculate the non-zero generalized eigenvalues ​​and their corresponding generalized eigenvectors of the generalized eigenvalue equation of the signal.

[0099] Generally, when the original digital discrete signal is a real number, the order of the reduced low-order generalized eigenvalue equation is twice the number of frequency components of the multi-frequency high-frequency signal; when the original digital discrete signal is a complex number, the order of the reduced low-order generalized eigenvalue equation is 1 times the number of frequency components of the multi-frequency high-frequency signal.

[0100] In FIG4 , the method for calculating the component signal frequency is characterized in that the method uses the non-zero generalized eigenvalue of the generalized eigenvalue equation to accurately calculate the frequency of the component signal of the multi-frequency high-frequency signal.

[0101] Among them, abs(λ i ) is the modulus of the i-th non-zero generalized eigenvalue, p is the order / degree of the differential / integral signal used when constructing the differential / integral signal matrix B, and c is ±1 corresponding to the differential / integral signal matrix respectively.

[0102] In FIG4 , the method for calculating the amplitude and initial phase of the component signal is characterized in that the method uses the generalized eigenvalue vector of the generalized eigenvalue equation and the original signal matrix to accurately calculate the amplitude and initial phase of the component signal.

[0103] When the measured signal is a real signal, the steps for calculating the amplitude and initial phase of the component signal of the multi-frequency high-frequency signal are as follows:

[0104] Step 1: Use the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix to calculate the following parameters, e i11=u i1 A i1 v i1 , e i12 =u i1 A i2 v i1 , e i21 =u i2 A i1 v i2 , e i22 =u i2 A i2 v i2 ,

[0105] Among them, u i1 and v i1 are the left and right generalized eigenvectors corresponding to the i-th generalized eigenvalue, u i2 and v i2 are the left and right generalized eigenvectors corresponding to the conjugate generalized eigenvalue of the i-th generalized eigenvalue, respectively. i1 The amplitude is 1, the initial phase is zero, and the frequency is f i The cosine signal corresponds to the cosine component signal matrix of the sampling point of the original signal matrix A, A i2 The amplitude is 1, the initial phase is zero, and the frequency is f i The sinusoidal signal corresponds to the sinusoidal component signal matrix of the sampling points of the original signal matrix A;

[0106] Step 2: Use the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix to calculate the following parameters, g i1 =u i1 Av i1 , g i2 =u i2 Av i2 ;

[0107] Step 3, use parameter e i 11.e i12 、e i 21.e i 22 and g i1 、g i2 Construct a system of linear equations in two variables,

[0108] Step 4: Solve the above two-variable linear equations to obtain the parameter h i1 and h i2 ;

[0109] Step 5: Calculate the amplitude a of the i-th component of the multi-frequency high-frequency signal i and phase φ i , the calculation formulas are:

[0110] When the measured signal is a complex signal, the steps for calculating the amplitude and initial phase of the component signals of the multi-frequency high-frequency signal are as follows:

[0111] Step 1: Use the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix to calculate w as follows: i , w i =u i Av i / u i A i v i

[0112] Among them, u i and v i are the generalized eigenvalues ​​λ i The corresponding left and right generalized eigenvectors, A i The amplitude is 1, the initial phase is zero, and the frequency is f i The complex signal corresponds to the complex component signal matrix of the sampling points of the original signal matrix A;

[0113] Step 2: Calculate the amplitude a of the i-th component of the multi-frequency high-frequency signal i and phase The calculation formulas are: i =abs(w i ),

[0114] Among them, abs(w i ) is w i The modulus, imag(w i ) is w i The imaginary part, real(w i ) is w i The real part of .

[0115] Get the frequency f of the measured signal i , amplitude a i and phase After the parameters are calculated, the reconstruction formula of the real multi-frequency high-frequency signal is:

[0116] The reconstruction formula of complex multi-frequency high-frequency signal is:

[0117] Wherein, t is the independent variable of the measured signal, which can be a time variable, a space variable or other types of variables.

[0118] Taking a multi-frequency high-frequency signal containing 10 components as an example, the frequency parameters of the 10 components of the signal are: f i=0.9, 1.8, 1.9, 2.0, 2.2, 2.3, 2.6, 3.4, 3.5, 4.9 GHz; the amplitude parameters are: a i =1.5, 2.5, 1.7, 1.2, 1.5, 1.0, 0.8, 1.0, 1.2, 0.6; the initial phase parameters are: 240, 45, 144, 20, 0, 300, 0, 77, 0°. This signal has a frequency comparable to that of a 5G signal, with a maximum frequency of 4.9 GHz and a bandwidth of 4.0 GHz.

[0119] Using the test method and system disclosed in this article, even at extremely low sampling rates f s =0.97MHz, the frequency, amplitude, and initial phase parameters of all 10 signal components can still be accurately measured, thereby achieving accurate signal reconstruction. The sampling rate at this time is less than 0.0002 times the highest frequency of the signal and only about 0.00025 times the signal bandwidth, which is significantly lower than the sampling rate requirements of conventional sampling theory and technology for baseband and band-limited signals.

[0120] Ideally, using equally spaced sampling, a complex signal requires no more than 20 points of the original digital discrete signal and its corresponding differential / integral digital discrete signal to accurately measure the frequency, amplitude, and initial phase parameters of all 10 components and achieve precise signal reconstruction. A real signal, on the other hand, requires no more than 40 points of the original digital discrete signal and its corresponding differential / integral digital discrete signal to accurately measure the frequency, amplitude, and initial phase parameters of all 10 components and achieve precise signal reconstruction.

[0121] In the absence of errors and interference, using the test method and system disclosed in this article, using any low sampling rate, or any high sampling rate, or any variable rate sampling, as long as the sampling rate is greater than zero and is a finite value, it is possible to accurately measure the frequency, amplitude and initial phase parameters of all components of the measured signal containing finite components, thereby achieving accurate reconstruction of the signal. However, due to the interference of digital discrete errors, calculus errors, numerical calculation errors and noise, when the sampling rate is too high or too low, it will have a certain impact on the test accuracy. In practice, even in the presence of errors and interference, using the test method and system disclosed in this article can still significantly break through the limitations of conventional sampling theory and technology on the sampling rate of baseband signals and band-limited signals.

[0122] Figures 5, 6, and 7 illustrate the positional relationship between sampling points and the signal. Due to resolution limitations, this article only shows this positional relationship for low sampling rates. At ultra-low sampling rates, the spacing between sampling points and the number of peaks and troughs increase proportionally.

[0123] FIG5A shows a sampling rate f s =97MHz, the positional relationship between the equally spaced sampling points of the real part of a complex signal and the signal. Ideally, a complex high-frequency signal containing 10 components requires at least 19 points of the original digital discrete signal and its corresponding 19-point differential / integral digital discrete signals to accurately measure the frequency, amplitude, and initial phase parameters of all 10 components of the signal. In practical applications, considering the influence of digital discretization error and background noise, appropriately increasing the number of sampling points can effectively improve measurement accuracy.

[0124] Figure 5B is a partial enlarged view of Figure 5A, which can more clearly show the positional relationship between the sampling points and the signal peaks and valleys. s =0.97MHz, the time between sampling points will increase by a factor of 100, and the number of peaks and valleys between sampling points will also increase by approximately a factor of 100.

[0125] FIG6A shows the positional relationship between the randomly spaced sampling points of the real part of a complex signal and the signal. The average sampling rate in the figure is approximately f s =97MHz. Fig. 6B is a partial enlarged view of Fig. 6A.

[0126] FIG7A shows a sampling rate f s =97MHz, the positional relationship between equally spaced sampling points and the signal for a real-valued signal. Ideally, a real-valued high-frequency signal containing 10 components requires at least 39 points of the original digital discrete signal and its corresponding 39-point differential / integral digital discrete signals to accurately measure the frequency, amplitude, and initial phase parameters of all 10 components. Compared to complex-valued signals, accurate measurement and reconstruction of real-valued signals requires a greater number of sampling points and a longer sampling time.

[0127] Figure 7B is a partial enlarged view of Figure 7 A. When the sampling rate decreases, the time between sampling points and the number of peaks and valleys will increase proportionally.

Claims

1. A method for accurately measuring signal characteristic parameters, which uses the original digital discrete signal of a multi-frequency high-frequency signal and its differential / integral digital discrete signals to accurately measure the frequency, amplitude, and initial phase parameters of all components of the multi-frequency high-frequency signal. It is characterized in that: It includes the following steps: S101, constructing an original signal matrix, and constructing the original signal matrix with the original digital discrete signals of the multi-frequency high-frequency signals obtained at an ultra-low sampling rate; S102, constructing a differential / integral signal matrix, and constructing the differential / integral signal matrix with the differential / integral digital discrete signals of the multi-frequency high-frequency signals obtained at an ultra-low sampling rate; Wherein, the distribution of the sampling points of the differential / integral digital discrete signals is the same as that of the original digital discrete signals, and the elements in the differential / integral signal matrix and the elements in the original signal matrix are in one-to-one correspondence; S103, constructing a signal generalized eigenvalue equation, and constructing the signal generalized eigenvalue equation with the original signal matrix and the differential / integral signal matrix, uB = λuA, Bv = λAv, Wherein, A is the original signal matrix, B is the differential / integral signal matrix, λ is the generalized eigenvalue of the signal generalized eigenvalue equation, and u and v are the left and right generalized eigenvectors of the signal generalized eigenvalue equation respectively; S104, reducing the order to solve the signal generalized eigenvalue equation, performing singular value decomposition on the original signal matrix or the differential / integral signal matrix, only using non-zero singular values and their corresponding singular vectors, reducing the signal generalized eigenvalue equation from a high-order generalized eigenvalue problem to a low-order generalized eigenvalue problem, and obtaining the generalized eigenvalue of the signal generalized eigenvalue equation and its corresponding generalized eigenvector; S105, calculating the component signal frequencies of the multi-frequency high-frequency signals, calculating the component signal amplitudes and initial phases of the multi-frequency high-frequency signals.

2. The method for accurately measuring signal characteristic parameters according to claim 1, wherein: In step S101, (1) The rank of the original signal matrix is closely related to the number of frequency components of the multi-frequency high-frequency signals, that is, when the original digital discrete signal is real, the rank of the original signal matrix is twice the number of frequency components of the multi-frequency high-frequency signals; when the original digital discrete signal is complex, the rank of the original signal matrix is one time the number of frequency components of the multi-frequency high-frequency signals; (2) When the sampling intervals of the original digital discrete signals are equal, the Hankel matrix and Toeplitz matrix constructed with the original digital discrete signals can be used as the original signal matrix; when the sampling intervals of the original digital discrete signals are semi-randomly distributed, the sampling intervals of the original digital discrete signals in the same row / column of the original signal matrix are randomly distributed, and the sampling intervals of the original digital discrete signals in different rows / columns relative to the original digital discrete signals in the previous column / row are equal.

3. The method for accurately measuring signal characteristic parameters according to claim 1, characterized in that: In step S104, after reducing the order, when the original digital discrete signal is real, the order of the low-order generalized eigenvalue equation is twice the number of frequency components of the multi-frequency high-frequency signals; when the original digital discrete signal is complex, the order of the low-order generalized eigenvalue equation is one time the number of frequency components of the multi-frequency high-frequency signals.

4. The method for accurately measuring signal characteristic parameters according to claim 1, characterized in that: In step S105, (1) Using the generalized eigenvalues of the signal generalized eigenvalue equation, accurately calculate the frequencies of the component signals of the multi-frequency high-frequency signal, where abs(λ i ) is the modulus of the i-th non-zero generalized eigenvalue, p is the order / degree of the differential / integral signal used when constructing the differential / integral signal matrix B, and c takes ±1 corresponding to the differential / integral signal matrix respectively; And / or, (2) using the generalized eigenvector of the signal generalized eigenvalue equation and the original signal matrix, accurately calculate the amplitude and initial phase of the component signals of the real multi-frequency high-frequency signal. The calculation steps include: S1051A. Using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix, calculate the following matrix elements. e i11 = u i1 A i1 v i1 ,e i12 = u i1 A i2 v i1 , e i21 = u i2 A i1 v i2 ,e i22 = u i2 A i2 v i2 , wherein, u i1 and v i1 are respectively the left and right generalized eigenvectors corresponding to the i-th generalized eigenvalue, and u i2 and v i2 are respectively the left and right generalized eigenvectors corresponding to the conjugate generalized eigenvalue of the i-th generalized eigenvalue, A i1 is the cosine component signal matrix of the sampling points of the cosine signal with an amplitude of 1, an initial phase of zero, and a frequency of the calculated f i corresponding to the original signal matrix A, and A i2 is the sine component signal matrix of the sampling points of the sine signal with an amplitude of 1, an initial phase of zero, and a frequency of the calculated f i corresponding to the original signal matrix A; S1052A. Using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix, calculate the following vector elements. g i1 = u i1 Av i1 ,g i2 = u i2 Av i2 ; S1053A, using the matrix element e i11 、e i12 、e i21 、e i22 and the vector element g i1 、g i2 to construct a system of binary linear equations, Solve the system of binary linear equations to obtain the parameters □ i1 and □ i2 ; S1055A, calculate the amplitude and phase of the i-th component of the multi-frequency high-frequency signal, and the calculation formulas are respectively, And / or, (3) using the generalized eigenvector of the signal generalized eigenvalue equation and the original signal matrix, can accurately calculate the amplitude and initial phase of the component signals of the complex multi-frequency high-frequency signal. The calculation steps include: S1051B, calculate the Rayleigh quotient w according to the following formula using the generalized eigenvector corresponding to the generalized eigenvalue and the original signal matrix i , w i = u i Av i / u i A i v i wherein, u i and v i are respectively the left and right generalized eigenvectors corresponding to the generalized eigenvalue λ i , A i is a complex component signal matrix of the sampling points of the complex signal corresponding to the original signal matrix A, with an amplitude of 1, an initial phase of zero, and a frequency of the calculated f i ; S1052B. Using the Rayleigh quotient to calculate the amplitude and phase of the i-th component of the multi-frequency high-frequency signal. The calculation formulas are respectively: a i = abs(w i ), where, abs(w i ) is the modulus of w i , imag(w i ) is the imaginary part of w i , and real(w i ) is the real part of w i .

5. The method for accurately measuring signal characteristic parameters according to claim 1, characterized in that: The sampling rate of the original digital discrete signal and the differential / integral digital discrete signal can be arbitrarily lower than and / or arbitrarily higher than the highest or lowest frequency of the multi-frequency high-frequency signal; the original digital discrete signal and the differential / integral digital discrete signal can be obtained by any means.

6. A signal characteristic parameter precise measurement system adopting the signal characteristic parameter precise measurement method as described in claim 1, using a digital discrete signal obtained at a sampling rate that is arbitrarily lower than or / and arbitrarily higher than the highest or lowest frequency of the signal to be measured, precisely analyzing and measuring the frequency, amplitude, and initial phase parameters of all components of the signal to be measured, and precisely reconstructing the signal to be measured, characterized in that: The signal characteristic parameter accurate measurement system includes: a signal preprocessing unit, a signal time delay unit, an original signal A / D conversion unit, a differential / integral signal A / D conversion unit, and a signal measurement and analysis unit. (1) The signal preprocessing unit receives the measured signal, performs conditioning and filtering on the measured signal so that the measured signal meets the requirements of the subsequent software and hardware configuration, and divides the preprocessed signal into two signals for parallel output. (2) The signal time delay unit receives the two signals parallelly output by the signal preprocessing unit, applies different time delays to the two signals respectively, and outputs them respectively. (3) The original signal A / D conversion unit receives one of the signals output by the signal time delay unit and performs A / D conversion operation to obtain the original digital discrete signal of the measured signal. (4) The differential / integral signal A / D conversion unit receives the other signal output by the signal time delay unit, performs differential / integral operation on the other signal to obtain the differential / integral signal of the measured signal, then conditions the differential / integral signal so that the differential / integral signal meets the requirements of the subsequent relevant software and hardware configuration, and then performs A / D conversion operation to obtain the differential / integral digital discrete signal of the measured signal. (5) The signal measurement and analysis unit receives and stores the original digital discrete signal obtained by the original signal A / D conversion unit and the differential / integral digital discrete signal obtained by the differential / integral signal A / D conversion unit. Then, using the original digital discrete signal and the differential / integral digital discrete signal, adopt the signal characteristic parameter accurate measurement method described in claim 1 to calculate and analyze to obtain the frequency, amplitude and initial phase parameters of the components of the measured signal, and accurately reconstruct the measured signal.

7. The signal characteristic parameter precise measurement system according to claim 6, characterized in that: After conditioning and filtering the measured signal, the highest frequencies of the two signals output in parallel by the signal preprocessing unit are not limited by the highest A / D conversion rate of the subsequent original signal A / D conversion unit and the differential / integral signal A / D conversion unit; and / or, different time delays are applied to the two signals output in parallel by the signal preprocessing unit to ensure that the original digital discrete signal obtained by the original signal A / D conversion unit is synchronous with the differential / integral digital discrete signal obtained by the differential / integral signal A / D conversion unit; and / or, the sampling rate of the A / D conversion module of the original signal A / D conversion unit can be configured to be equal-rate or variable-rate, and the sampling rate can be arbitrarily lower than or / and arbitrarily higher than the highest or lowest frequency of the measured signal; when the sampling rate is configured to be variable-rate, the sampling intervals should be semi-randomly distributed.

8. The signal characteristic parameter precise measurement system according to claim 6, wherein: The differential / integral signal A / D conversion unit includes: a differential module configured to receive the other signal output by the signal delay unit, perform first-order or / and multi-order differentiation to obtain the first-order or / and multi-order differential signal of the measured signal; and a differential signal conditioning module configured to condition and amplify the first-order or / and multi-order differential signal to meet the requirements of the subsequent relevant software and hardware configurations; and an integration module configured to receive the other signal output by the signal delay unit, perform one-time or / and multiple integrations to obtain the one-time or / and multiple integral signals of the measured signal; and an integral signal conditioning module configured to condition and amplify the one-time or / and multiple integral signals to meet the requirements of the subsequent relevant software and hardware configurations; and a differential / integral signal A / D conversion module configured to perform A / D conversion operations to obtain the differential / integral digital discrete signal of the measured signal.

9. The signal feature parameter precise measurement system according to claim 6, wherein: The differential / integral signal A / D conversion unit can also be configured to include only the differential module, the differential signal conditioning module, and the differential / integral signal A / D conversion module; or, only include the integration module, the integral signal conditioning module, and the differential / integral signal A / D conversion module.

10. The signal feature parameter precise measurement system according to claim 6, wherein: Optionally obtain the first-order differential, or multi-order differential, or one-time integral, or multiple integral digital discrete signals of the measured signal; the configuration of the sampling rate and sampling interval of the differential / integral signal A / D conversion module is the same as that of the A / D conversion module of the original signal A / D conversion unit.

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