A filtering method for sampling signals

Abstract

The present invention provides a filtering method for sampling signals. First, a pseudo-high-frequency transformation is performed on the sampling signal to obtain a pseudo-high-frequency signal. Secondly, a jitter step size n or a frequency Δf is given to the sampling signal after the pseudo-high-frequency transformation, and a jitter filtering calculation is performed on the sampling signal after the pseudo-high-frequency transformation to achieve high-pass filtering, suppress low-frequency signals, and retain high-frequency signals. The present invention can simply and effectively filter out interference signals to accurately identify target signals or extract boundary information; it can also discard the limitations of the technical field and be conveniently applied to multiple fields.

Description

Technical Field

[0001] The present invention relates to the field of signal filtering, and particularly to a filtering method for sampled signals or signal sampling. Background Art

[0002] For the identification of sampled signals in many daily life or high-tech fields, due to the interference or mutual interference of different signals, it is difficult to identify the target signal or extract the boundary. For example, the extraction of reflected waves and scattered waves in ultrasonic non-destructive testing and seismic exploration, and the boundary detection based on graphic image processing when extracting license plate numbers, etc., are widely present in the engineering field and are a thorny problem.

[0003] In different application fields, in many scenarios, technicians often care more about the judgment or identification of the sampling positions where the boundaries or abnormal signals are located, while ignoring the true amplitude of the signals. At this time, filtering algorithms, especially high-pass filtering algorithms, are often the first choice for processing methods. Existing general filtering methods include time, space or frequency domain filtering, Kalman filtering, and wavelet transform and other algorithms, which are widely used in all walks of life; Sampled signals obtained from special industries or observation systems may also be separated from interference signals and target signals through specific processing modes or algorithm improvements. Although such algorithms are supported by systematic theoretical principles and the calculation methods are complete, there are often disadvantages such as aliasing, oscillation, boundary effects, and large computational amounts in the actual operation process. A set of algorithms in one field is difficult to be applicable to other engineering fields, and it is very inconvenient for professional technicians who are not familiar with this field to understand and use.

[0004] Therefore, there is an urgent need for a filtering method for sampled signals that can simply and effectively filter out interference signals to accurately identify target signals or extract boundary information; and can also discard the limitations of the technical field and be conveniently applied to multiple fields. Summary of the Invention

[0005] The main purpose of the present invention is to provide a filtering method, system and storage medium for sampled signals, aiming to solve the technical problems of low resolution of the existing filtering method for sampled signals for target signals and limitations of the technical field.

[0006] To achieve the above object, the present invention provides a filtering method for sampled signals, and the method includes the following steps:

[0007] S1: Assign a jitter step size n or a frequency Δf to the sampled signal; Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, perform jitter filtering calculation on the sampled signal to achieve high-pass filtering, suppress low-frequency signals, and retain high-frequency signals to improve the resolution of the sampled signal.

[0008] As a further improvement of the above solution, before performing jitter filtering calculation on the sampled signal, it further includes:

[0009] S0: Perform pseudo-high-frequency transformation on the sampled signal to obtain a pseudo-high-frequency signal;

[0010] Step S1 performs jitter filtering calculation on the sampled signal that has undergone pseudo-high-frequency transformation in step S0.

[0011] As a further improvement of the above solution, the jitter filtering calculation is performed through formula (2):

[0012] newy(i) = y(i) - y(i - n), (i - n) > 0

[0013] or newy(i - n) = y(i - n) - y(i), (i - n) > 0 (2)

[0014] Wherein, newy(i) is the sequence signal after jitter filtering; y(i) is the sampled signal or the pseudo-high-frequency signal; i is the sequence number; n is the jitter step length, which is an integer multiple of 1; the jitter frequency Δf = 1 / n.

[0015] As a further improvement of the above solution, when performing jitter filtering calculation on the sampled signal:

[0016] If the given jitter step length n achieves the expected signal processing effect through the processing of formula (2), the calculation is terminated, and subsequent analysis and interpretation are performed with reference to the high-resolution signal;

[0017] If the given jitter step length n does not achieve the expected signal processing effect through the processing of formula (2), the jitter step length n is adjusted and the calculation continues until the expected signal processing effect is achieved.

[0018] As a further improvement of the above solution, the method of the pseudo-high-frequency transformation is to perform a constant rational power operation on the sampled signal, so that the original signal presents a pseudo-high-frequency signal with a frequency that is a multiple of the original signal frequency.

[0019] As a further improvement of the above solution, the pseudo-high-frequency signal is obtained through the calculation of formula (1),

[0020]

[0021] Wherein, Y(i) is the signal after performing pseudo-high-frequency processing; y(i) is the sampled signal; i is the sampled signal sequence number; M is the total number of data; e is the power function operation factor, a constant rational number, which is flexibly set according to the expected signal processing effect; sign() is the sign function; abs() is the absolute value function.

[0022] As a further improvement of the above solution, when performing pseudo-high-frequency transformation on the sampled signal, according to the expected processing effect, a power function operation factor e is given in advance.

[0023] If the given power function operation factor e achieves the expected signal processing effect through the processing of Equation (1), then perform dither filtering calculation.

[0024] If the given power function operation factor e does not achieve the expected signal processing effect through the processing of Equation (1), then adjust the power function operation factor e and continue the processing until the expected signal processing effect is achieved.

[0025] As a further improvement of the above solution, when performing dither filtering processing on the sampled signal:

[0026] If the given dither step size n achieves the expected signal processing effect through the processing of Equation (2), then end the calculation and perform subsequent analysis and interpretation with reference to the high-resolution signal.

[0027] If the given dither step size n does not achieve the expected signal processing effect through the processing of Equation (2), then adjust the dither step size n and continue the calculation.

[0028] If adjusting the dither step size n still does not achieve the expected signal processing effect, then return to adjust the power function operation factor e until the expected signal processing effect is achieved.

[0029] It should be noted that during the pseudo-high-frequency transformation described in the present invention, the expected signal processing effect can macroscopically show obvious enhanced high-frequency signal characteristics. Specifically, for different fields, it appears corresponding to the sampled signals in the corresponding fields; for the field of seismic exploration data processing, it means the appearance of high-frequency signals or target reflection event signals.

[0030] For the dither filtering calculation described above, the expected signal processing effect can be analyzed and compared through the amplitude spectrum or power spectrum, and it can be found that the low frequency is suppressed and the high frequency is relatively enhanced; or, the user preliminarily predicts the interval where effective signals should appear based on existing data, and obvious enhanced effective signals appear in this interval after processing; or, for the field of image boundary recognition, the expected signal processing effect is to clearly present the target boundary or contour.

[0031] In addition, to achieve the above object, the present invention also provides a filtering system for sampled signals, including a memory, a processor, and a filtering program for sampled signals stored on the memory and executable on the processor. When the filtering program for sampled signals is executed by the processor, it implements the steps of a filtering method for sampled signals as described above.

[0032] In addition, to achieve the above object, the present invention further provides a storage medium, on which a filtering method program for sampling signals is stored. When the filtering program for sampling signals is executed by a processor, the steps of a filtering method for sampling signals as described in any one of the above are implemented.

[0033] Since the present invention adopts the above technical solutions, the beneficial effects of the present application are as follows:

[0034] 1. The present invention provides a filtering method for sampling signals. First, a jitter step size n or frequency Δf is assigned to the sampling signal. Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, jitter filtering calculation is performed on the sampling signal to achieve high-pass filtering, suppressing low-frequency signals and retaining high-frequency signals to improve the resolution of the sampling signal. This filtering method for sampling signals only needs to preset the jitter step size n or frequency Δf in advance. Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, it can suppress low-frequency signals and retain high-frequency signals, thereby improving the resolution of the sampling signal. Therefore, the calculation amount of the entire filtering method for sampling signals is small, no boundary effect will be generated, and no false signal will be generated in the section without signals. Moreover, the principle is easy to understand and the operation is flexible.

[0035] 2. The present invention provides a filtering method for sampling signals. Before performing jitter filtering calculation on the sampling signal, it further includes: S0: performing pseudo-high-frequency transformation on the sampling signal to obtain a pseudo-high-frequency signal; step S1 performing jitter filtering calculation on the sampling signal that has undergone pseudo-high-frequency transformation in step S0. With such a setting, first, pseudo-high-frequency transformation is performed on the sampling signal to obtain a pseudo-high-frequency signal. However, this seemingly "distorted" signal does not deviate from the real sampling signal, laying a certain foundation for the subsequent jitter filtering algorithm. Then, in order to extract high-frequency signals, based on the principle that synchronous jitter of harmonic signals with different frequencies can produce a filtering effect, by performing jitter calculation on the sampling signal with a certain step size (or frequency), the effect of suppressing low-frequency signals is quickly achieved. The combination of the pseudo-high-frequency signal and jitter filtering has a better filtering effect, can more effectively improve the resolution of the sampling signal, and will not generate boundary effects or false signals in the section without signals. It is convenient to be widely applied to one-dimensional, two-dimensional or multi-dimensional sampling signals or data such as time-based, space-based, frequency domain, and wavenumber domain. Description of the Drawings

[0036] Figure 1 is a schematic flowchart of a filtering method for sampling signals according to Embodiment 1 of the present invention;

[0037] Figure 2 is a schematic flowchart of a filtering method for sampling signals according to Embodiment 2 of the present invention Figure 1 ;

[0038] Figure 3 Schematic diagram of the process of a filtering method for sampling signals involved in Embodiment 2 of the present invention Figure 2 ;

[0039] Figure 4 Harmonic signals of different frequencies with an amplitude of 1;

[0040] Figure 5 Amplitude change characteristics of different frequency harmonic signals after being jittered with different step sizes;

[0041] Figure 6 A grayscale image;

[0042] Figure 7 The image processed by the sampling signal filtering method based on Embodiment 1;

[0043] Figure 8 Comparison of the jitter filtering calculation results between the harmonics after implementing pseudo-high frequency based on Embodiment 2 and the original harmonics;

[0044] Figure 9 The original harmonic signal based on Embodiment 2 and the signal after its sixth power change;

[0045] Figure 10 The spectrum of the original harmonic signal based on Embodiment 2 and the spectrum of the signal after its sixth power change;

[0046] Figure 11 The original seismic record section of 169 unprocessed record traces;

[0047] Figure 12 is Figure 11 the seismic sampling signal at a recording point in

[0048] Figure 13 is Figure 12 the seismic sampling signal after the sampling signal in

[0049] Figure 14 is Figure 13 the seismic sampling signal after the signal in

[0050] Figure 15 is the seismic section of 169 recording points after filtering processing. Specific implementation manner

[0051] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] It should be noted that all directional indications in the embodiments of the present invention, such as first, second, up, down, left, right, front, back... are only used to explain the relative positional relationship and movement conditions between components in a specific posture as shown in the accompanying drawings. If the specific posture changes, the directional indications will also change accordingly.

[0053] In addition, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0054] The present invention will be further described below with reference to the accompanying drawings:

[0055] Embodiment 1:

[0056] Referring to Figure 1 , a flowchart of the first embodiment of a method for filtering a sampling signal according to the present invention is provided. The method includes the following steps:

[0057] S1: Assign a jitter step size n or a frequency Δf to the sampling signal. Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, perform jitter filtering calculation on the sampling signal to achieve high-pass filtering, suppress low-frequency signals, and retain high-frequency signals to improve the resolution of the sampling signal.

[0058] Specifically, the jitter filtering calculation is performed through Equation (2):

[0059] newy(i) = y(i) - y(i - n), (i - n) > 0

[0060] or newy(i - n) = y(i - n) - y(i), (i - n) > 0 (2)

[0061] where newy(i) is the sequence signal after jitter filtering; y(i) is the sampling signal; i is the sequence number; n is the jitter step size, which is an integer multiple of 1; the jitter frequency Δf = 1 / n;

[0062] When performing jitter filtering calculation on the sampling signal:

[0063] If the given jitter step size n achieves the expected signal processing effect through the processing of Equation (2), the calculation ends, and subsequent analysis and interpretation are carried out with reference to the high-resolution signal;

[0064] If the given jitter step size n does not achieve the expected signal processing effect through the processing of Equation (2), the jitter step size n is adjusted and the calculation continues until the expected signal processing effect is achieved; for this filtering method of sampled signals, only the jitter step size n or the frequency Δf needs to be set in advance. Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, it is possible to suppress low-frequency signals and retain high-frequency signals, thereby improving the resolution of sampled signals; therefore, the entire filtering method of sampled signals has a small amount of calculation, will not produce boundary effects, and will not generate false signals in sections without signals; moreover, the principle is easy to understand and the operation is flexible.

[0065] For the jitter filtering calculation described above, for the expected signal processing effect, it can be found through amplitude spectrum or power spectrum analysis and comparison that low frequencies are suppressed and high frequencies are relatively enhanced; or, the user preliminarily predicts the interval where effective signals should appear based on existing data, and obvious enhanced effective signals appear in this interval after processing; or, for the field of image boundary recognition, the expected signal processing effect is that the target boundary or contour is clearly presented.

[0066] The following conducts jitter filtering processing on a time-domain signal with a certain step size to illustrate the jitter filtering principle of the present invention, specifically as follows:

[0067] The jitter filtering effect of a time-domain signal with a certain step size is reflected in its different suppression capabilities for harmonic signals of different frequencies. The basic law is that the jitter operation will suppress low-frequency signals and relatively retain high-frequency signals, presenting a high-pass characteristic.

[0068] Arbitrarily given a time-domain signal [y(1), y(2), y(3) …… y(i) …… y(N)], where i is the signal serial number or the sampling time point serial number, and N is the total number of sampling points. Let n be the jitter step size, and n < N, and n is an integer multiple of serial number 1; when it is converted to a time parameter, it is equal to n multiplied by the sampling interval, and let the product be △t, and the corresponding jitter frequency is converted to △f = 1 / △t. n being a positive or negative number corresponds to jittering forward or backward respectively.

[0069] Ignoring the signals at the endpoints when (i - n) <= 0, the jittered sequence signal is:

[0070] newy(i) = y(i) - y(i - n)

[0071] In particular, when n = 1, the calculation result is similar to the traditional horizontal gradient calculation value.

[0072] Similarly, take the trigonometric function: y = sin(2*pi*f*t), where five frequency harmonics are set from high to low as f = 4000Hz, 2000Hz, 1000Hz, 500Hz, and 250Hz respectively. The time sampling interval is 0.000025 seconds.

[0073] Set the amplitude of all harmonics to be "1", and the intercepted parts of harmonic signals with different frequencies are as attached Figure 4 shown.

[0074] The jitter step size n is set to 1 to 10 respectively, and the corresponding times are Δt(j) = j * 0.000025 seconds, where j = 1, 2,..., 10; when n = 1, it is converted to the time Δt = 0.000025 seconds, and the corresponding jitter frequency Δf = 40KHz. Obtain the maximum value Amax after jitter of different frequency harmonics, and the obtained signal amplitude change is as attached Figure 5 shown.

[0075] From the attachment Figure 5 it can be seen that overall, for signals with lower frequencies, the amplitude attenuation after jitter is greater, indicating that they are more sensitive to jitter, while for signals with higher frequencies, the amplitude attenuation is relatively weaker; as the jitter step size (abscissa) increases, the amplitude of the jittered signal shows different change characteristics, but generally conforms to the aforementioned law.

[0076] To illustrate the use effect of the filtering method for sampling signals in Example 1, the filtering method for sampling signals provided in Example 1 of the present invention is applied to the field of image boundary recognition. Specifically, select Figure 6 a grayscale image as shown, with the vertical and horizontal coordinates both being pixel points, a total of 60 * 4000. The boundaries of different targets on the image are very blurred, and it is difficult to determine the target boundaries from this original image, which affects the development of subsequent processing work. Therefore, the jitter filtering calculation in the present invention is used to improve the boundary determination. Taking the grayscale value at the pixel point as the parameter y, two independent jitter filtering calculations are performed in the horizontal direction with a jitter step size of 2 (pixel points) and in the vertical direction with a jitter step size of 20 (pixel points), and the results of the two jitter filtering calculations are superimposed to obtain a grayscale image as Figure 7 shown. From Figure 7 it can be seen that different target boundaries can be clearly recognized from the jittered image, improving the resolution ability of the image signal.

[0077] Example 2:

[0078] Referring to Figure 2 and Figure 3 , the flow schematic diagram of the second embodiment is provided for a filtering method of a sampling signal of the present invention, and the method includes the following steps:

[0079] S0: Perform a pseudo-high-frequency transformation on the sampled signal to obtain a pseudo-high-frequency signal;

[0080] Specifically, the method of the pseudo-high-frequency transformation is to perform a constant rational power operation on the sampled signal, so that the original signal presents a pseudo-high-frequency signal with a frequency that is a multiple of the original signal frequency;

[0081] The pseudo-high-frequency signal is obtained by calculating according to Equation (1),

[0082]

[0083] where Y(i) is the signal after performing pseudo-high-frequency processing; y(i) is the sampled signal; i is the sampled signal sequence number; M is the total number of data; e is the power function operation factor, a constant rational number, which is flexibly set according to the expected effect of signal processing; sign() is the sign function; abs() is the absolute value function.

[0084] When performing a pseudo-high-frequency transformation on the sampled signal, according to the expected processing effect, a power function operation factor e is given in advance,

[0085] If the given power function operation factor e achieves the expected effect of signal processing through the processing of Equation (1), then perform dither filtering calculation;

[0086] If the given power function operation factor e does not achieve the expected effect of signal processing through the processing of Equation (1), then adjust the power function operation factor e and continue the processing until the expected effect of signal processing is achieved.

[0087] To better illustrate the principle of the pseudo-high-frequency transformation, without loss of generality, a time-varying sinusoidal harmonic signal y = sin(2*pi*f*t) is taken for illustration, where:

[0088] pi is the pi; f is the signal frequency; t is the time variable.

[0089] Expand the time-varying sinusoidal harmonic signal y = sin(2*pi*f*t) according to the exponential expression of trigonometric functions:

[0090]

[0091] After the power function operation with n being a constant, a frequency-doubled signal based on the effective frequency of the original signal will appear in the signal, which is called a pseudo-high-frequency signal. This pseudo-high-frequency signal is based on the original signal but has a large change to the original signal. When f = 100 Hz, its signal is as shown in the appendix Figure 9 shown. If the sixth power calculation is adopted, the calculation expression is:

[0092]

[0093] Appendix Figure 10As the amplitude spectra of two signals, it can be seen that originally there was only a harmonic wave with a frequency of 100 Hz, and after power operation, pseudo-high frequencies such as 300 Hz, 500 Hz... appear.

[0094] Usually when it is desired to improve the signal or boundary resolution, it is often hoped to increase the frequency of the signal. Based on the exploration of the transformation law of ordinary harmonic signals, the present invention can obtain pseudo-high frequency signals based on simple power operation. This seemingly "distorted" signal does not deviate from the real sampled signal, laying a certain foundation for the subsequent jitter filtering algorithm.

[0095] S1: Assign a jitter step size n or frequency Δf to the sampled signal after pseudo-high frequency transformation. Based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, perform jitter filtering calculation on the sampled signal to achieve high-pass filtering, suppress low-frequency signals, and retain high-frequency signals to improve the resolution of the sampled signal;

[0096] Specifically, the jitter filtering calculation is performed through Equation (3):

[0097] newy(i) = Y(i) - Y(i - n), (i - n) > 0

[0098] or newy(i - n) = Y(i - n) - Y(i), (i - n) > 0 (3)

[0099] Among them, newy(i) is the sequence signal after jitter filtering; y(i) is the signal after pseudo-high frequency processing; i is the serial number; n is the jitter step size, which is an integer multiple of 1; the jitter frequency Δf = 1 / n;

[0100] When performing jitter filtering calculation on the signal after pseudo-high frequency processing:

[0101] If the given jitter step size n reaches the expected signal processing effect through Equation (3), the calculation is ended, and subsequent analysis and interpretation are carried out with reference to the high-resolution signal;

[0102] If the given jitter step size n does not reach the expected signal processing effect through Equation (3), adjust the jitter step size n and continue the calculation until the expected signal processing effect is achieved.

[0103] As a preferred embodiment, when performing jitter filtering processing on the signal after pseudo-high frequency processing:

[0104] If the given jitter step size n reaches the expected signal processing effect through Equation (3), the calculation is ended, and subsequent analysis and interpretation are carried out with reference to the high-resolution signal;

[0105] If the given jitter step size n does not reach the expected signal processing effect through Equation (3), adjust the jitter step size n and continue the calculation;

[0106] If adjusting the dither step size n still fails to achieve the expected signal processing effect, then return to adjust the power function operation factor e until the expected signal processing effect is achieved.

[0107] The dither filtering principle in the second embodiment is the same as that in the first embodiment, and will not be elaborated here.

[0108] Refer to Figure 8 , the harmonic signal with a frequency of 250 Hz is processed by pseudo-high-frequency transformation, and then the dither filtering algorithm is used to obtain the comparison result as shown in the appendix Figure 8 . In the figure, the dotted line is the result after the original harmonic signal is dithered, and the solid line is the effect after pseudo-high-frequency processing and then dither filtering.

[0109] From the appendix Figure 8 , it can be seen that for the signal after pseudo-high-frequency transformation processing, when performing dither filtering calculation, it can more sensitively grasp the extreme points of the signal, and there is no phase shift in the position of the original extreme points.

[0110] From the above discussion, through the pseudo-high-frequency transformation operation, higher-frequency potential feature signals can be obtained based on the original signal, providing support for subsequent dither filtering; in this embodiment, the pseudo-high-frequency transformation processing and the dither filtering calculation are combined and used together to comprehensively achieve the effect of improving the signal resolution.

[0111] It should be noted that when performing the pseudo-high-frequency transformation of the present invention, the expected signal processing effect, macroscopically, is that the enhanced high-frequency signal characteristics can be clearly seen. Specifically, for different fields, it appears corresponding to the sampling signals in the corresponding fields; for the field of seismic exploration data processing, it means that the high-frequency signals or the target reflection in-phase axis signals appear;

[0112] For the dither filtering calculation, the expected signal processing effect can be analyzed and compared through the amplitude spectrum or power spectrum, and it can be found that the low frequency is suppressed and the high frequency is relatively enhanced; or, the user preliminarily judges the interval where the effective signal should appear according to the existing data, and obvious enhanced effective signals appear in this interval after processing; or, for the field of image boundary recognition, the expected signal processing effect is to see the target boundary or contour clearly presented.

[0113] In order to illustrate the use effect of first performing pseudo-high-frequency transformation processing on the sampling signal and then performing dither filtering calculation on the sampling signal after pseudo-high-frequency transformation in the second embodiment, the filtering method of the sampling signal provided in the second embodiment of the present invention is applied to the one-dimensional data processing in the field of seismic exploration. Specifically, 169 seismic data are collected, and the original seismic trace records are as shown in Figure 11 .

[0114] Take the seismic record of the 55th trace as shown inFigure 12 As shown, the abscissa is the time sequence number, the time sampling interval is 50 us, and the ordinate is the amplitude of the sampling signal. In order to better obtain high-resolution seismic signals, a 1 / 4 power function is used to perform pseudo-high-frequency processing on the original recorded data. The processed signal is as shown in Figure 13 shown. Compared with Figure 12 the original signal in, the pseudo-high-frequency signal is clearly reflected in the signals of each different time period. On the basis of this pseudo-high-frequency signal processing, a dither filtering process with a step size of 9 can be used to obtain a high-frequency signal as shown in Figure 14 shown. It can be seen from this signal that the boundaries of the signals in different time periods after pseudo-high-frequency processing can be well reflected. Using the processing strategy provided in Embodiment 2, similar processing is performed on all 169-channel records of the full profile. The processed profile is as shown in Figure 15 shown. Comparing Figure 11 and Figure 15 , it can be clearly seen that the detailed information that was not shown on the original profile is perfectly presented in Figure 15 .

[0115] For the filtering process of the sampling signal provided in Embodiment 2, first, a pseudo-high-frequency signal is obtained based on a simple power operation. This seemingly "distorted" signal does not deviate from the real sampling signal, laying a certain foundation for the subsequent dither filtering algorithm;

[0116] Secondly, in order to extract the pseudo-high-frequency signal, based on the principle that "synchronous dithering of harmonic signals with different frequencies can produce a filtering effect", a dither filtering calculation with a certain step size (or frequency) is performed on the sampling signal that has undergone pseudo-high-frequency processing, quickly achieving the effect of suppressing low-frequency signals. Combining the pseudo-high-frequency transformation processing and the dither filtering calculation can be applied in many engineering fields. From engineering cases, the use effect is obvious.

[0117] Overall, a filtering method for sampling signals provided in Embodiment 2 is based on engineering practice, with small algorithm calculation amount, flexible operation implementation, easy to change, no boundary effect, no false signal generated in the section without signal; the calculation principle is easy for technicians to master, and the implementation steps are easy for technicians to control; and it can be widely applied to one-dimensional, two-dimensional or multi-dimensional sampling signals or data such as time-based, space-based, frequency domain, and wavenumber domain.

[0118] Embodiment 3:

[0119] The present invention also provides a filtering system for sampling signals, including a memory, a processor, and a filtering program for sampling signals stored on the memory and executable on the processor. When the filtering program for sampling signals is executed by the processor, it implements the steps of a filtering method for sampling signals as described in any one of the above.

[0120] The specific embodiments of the storage medium of the present invention are basically the same as those of the above embodiments of the filtering method for sampling signals, and will not be elaborated here.

[0121] Embodiment 4:

[0122] In addition, to achieve the above object, the present invention also provides a storage medium, on which a program for the filtering method of sampling signals is stored. When the filtering program for sampling signals is executed by a processor, the steps of a filtering method for sampling signals as described in any of the above are implemented.

[0123] It should be noted that in this article, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or system including that element.

[0124] The serial numbers of the above embodiments of the present invention are only for description and do not represent the superiority or inferiority of the embodiments.

[0125] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware such as analog circuits or programmable logic devices (FPGA), but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium as described above (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0126] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the description of the present invention and the drawings, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A filtering method for a sampled signal, characterized in that the steps Including: S1: Assign a jitter step size n or a frequency Δf to the sampled signal, perform jitter filtering calculation on the sampled signal to achieve high-pass filtering, suppress low-frequency signals, and retain high-frequency signals; Before performing jitter filtering on the sampled signal, it further includes: S0: Perform pseudo-high-frequency transformation on the sampled signal to obtain a pseudo-high-frequency signal; Among them, step S1 performs jitter filtering calculation on the sampled signal that has undergone pseudo-high-frequency transformation in step S0; The pseudo-high-frequency signal is obtained through processing by formula (1), （1） where Y(i) is the signal after performing pseudo-high-frequency processing; y(i) is the sampled signal; i is the sampled signal serial number; M is the total number of data; e is the power function operation factor and is a constant rational number; sign( ) is the sign function; abs( ) is the absolute value function.

2. The filtering method for a sampled signal according to claim 1, wherein The jitter filtering process is calculated through formula (3): newy(i) = Y(i) - Y(i - n), (i - n) > 0 or newy(i - n) = Y(i - n) - Y(i), (i - n) > 0 (3) where newy(i) is the sequence signal after jitter filtering; Y(i) is the signal after performing pseudo-high-frequency processing; i is the serial number; n is the jitter step size and is an integer multiple of 1; the jitter frequency Δf = 1 / n.

3. A filtering method for a sampled signal according to claim 1 or 2, characterized in that, The method of the pseudo-high-frequency transformation is to perform a constant rational power operation on the sampled signal so that the original signal presents a pseudo-high-frequency signal with a frequency that is a multiple of the original signal frequency.

4. A filtering method for a sampled signal according to claim 1, characterized in that, When performing pseudo-high-frequency transformation on the sampled signal, if the given power function operation factor e achieves the expected signal processing effect through processing by formula (1), then perform jitter filtering calculation; if the given power function operation factor e does not achieve the expected signal processing effect through processing by formula (1), then adjust the power function operation factor e and continue to process until the expected signal processing effect is achieved.

5. A filtering method for a sampled signal according to claim 2, characterized in that When performing jitter filtering on the sampled signal: if the given jitter step size n achieves the expected signal processing effect through processing by formula (3), then end the calculation and perform subsequent analysis and interpretation with reference to the high-resolution signal; if the given jitter step size n does not achieve the expected signal processing effect through processing by formula (3), then adjust the jitter step size n and continue the calculation; if adjusting the jitter step size n still does not achieve the expected signal processing effect, then return to adjust the power function operation factor e until the expected signal processing effect is achieved.

6. A filtering method for a sampled signal according to claim 1, wherein, In step S1, based on the basic law that long-period low-frequency signals are relatively sensitive to jitter and short-period high-frequency signals are relatively insensitive to jitter, perform jitter filtering calculation on the sampled signal to achieve high-pass filtering.

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