Sample signal processing method and device for digital filtering, digital oscilloscope

Abstract

The application discloses a sampling signal processing method and device for digital filtering, and a digital oscilloscope. Firstly, a sampling signal is filtered to obtain a to-be-processed signal; then, N-stage continuous decimation filtering processing is performed on the to-be-processed signal to obtain a decimation filtering signal; then, M-time continuous interpolation filtering processing is performed on the decimation filtering signal obtained after the N-stage continuous decimation filtering processing to obtain a complementary value filtering signal; finally, the complementary value filtering signal obtained after the M-time continuous interpolation filtering processing is output as a sampling signal filtered from a preset low-frequency component. Since the low-pass filtered sampling signal is subjected to multi-stage decimation filtering to perform down-sampling processing, and then the decimation filtering signal obtained after the down-sampling processing is subjected to multi-time interpolation processing to restore the frequency to the frequency of the sampling signal, low-pass filtering of a very low cut-off frequency can be realized in a high sampling rate and large data flow scene by using a small amount of computing resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal filtering, in particular to a sampling signal processing method and device for digital filtering and a digital oscilloscope. BACKGROUND

[0002] Digital filtering is a technology of processing discrete-time signals (digital signals) by algorithms to enhance useful information or suppress noise. Unlike analog filtering (processing continuous signals), digital filtering is based on mathematical calculations and is suitable for digital systems such as computers, DSPs (digital signal processors) or FPGAs. In the field of signal filtering technology, different cutoff frequencies need to be filtered. Since the sampling frequency needs to be at least twice the highest frequency of the signal to be sampled (sampling law), a direct filtering method is generally used for filtering. However, in the case of high sampling rate (such as MHz to GHz level) and large data flow (continuous high-speed input), it is very difficult to implement direct filtering for very low cutoff frequency (sampling frequency is more than 100 times, 1000 times or more than the sampled frequency).

[0003] It is usually not feasible or even impossible to design a FIR or IIR filter with very low cutoff frequency directly at high sampling rate. The main reason is that the computational complexity is too high. For example, the order N of the FIR filter is approximately equal to the quotient of the filtering band coefficient and the normalized transition bandwidth, normalized transition bandwidth = (actual width of transition band) / f s When f s is very high (such as 100MHz) and the cutoff frequency f c is very low (such as 1kHz) and requires a narrow transition band, (f s / f c ) is very large (10 5 000 order), resulting in a very high N (tens of thousands or even millions of orders). Each sample requires N times of multiplication and addition operation, and the computing power (GOPS or TOPS) required for real-time processing of large data flow is far beyond the capacity of ordinary processors. If an IIR filter is used, although the order is usually much lower than that of the FIR filter, it is also very difficult to implement a stable IIR filter with very low cutoff frequency at high sampling rate. The requirement of very low cutoff frequency requires that the poles be very close to z=1 in the z-plane unit circle, which will cause serious quantization effect, long transient response and numerical precision problems, increasing hardware complexity and power consumption. SUMMARY

[0004] The technical problem to be solved by the present application is the obvious defect in the low cutoff frequency filtering of high sampling rate and large data flow.

[0005] In a first aspect, a sampling signal processing method for digital filtering is provided in an embodiment, comprising:

[0006] low-pass filter or band-pass filter the sampling signal of the first sampling frequency to obtain a to-be-processed signal which is processed by anti-sampling aliasing;

[0007] perform N-order continuous decimation filtering on the to-be-processed signal to obtain a decimation filtering signal, where N is a natural number not less than 2;

[0008] the decimation filtering process of each order includes:

[0009] sample and decimate the to-be-processed signal or the decimation filtering signal after the decimation filtering of the previous order according to a preset sampling decimation mode, so that the frequency value of the to-be-processed signal or the decimation filtering signal after the decimation filtering of the previous order is attenuated;

[0010] low-pass filter the to-be-processed signal or the decimation filtering signal after the decimation filtering of the previous order whose frequency value is attenuated to obtain the decimation filtering signal after the decimation filtering of the current order;

[0011] perform M-order continuous interpolation filtering on the decimation filtering signal obtained after the N-order continuous decimation filtering to obtain a value-added filtering signal, where M is a natural number not less than 2; and the value-added filtering signal obtained after the M-order interpolation filtering has the same frequency as the sampling signal;

[0012] the interpolation filtering process of each order includes:

[0013] sample and interpolate the decimation filtering signal obtained after the N-order continuous decimation filtering or the value-added filtering signal obtained after the interpolation filtering of the previous order according to a preset sampling interpolation mode, so that the frequency value of the value-added filtering signal obtained after the sampling interpolation is increased;

[0014] low-pass filter the decimation filtering signal or the value-added filtering signal obtained after the interpolation filtering of the previous order whose frequency value is increased to obtain the value-added filtering signal after the interpolation filtering of the current order;

[0015] output the value-added filtering signal obtained after the M-order continuous interpolation filtering as the sampling signal filtered of preset low-frequency components.

[0016] In an embodiment, the sampling signal processing method further includes:

[0017] in the decimation filtering process of each order, the frequency value is attenuated by an even number of times;

[0018] in the interpolation filtering process of each order, the frequency value is increased by an even number of times.

[0019] In an embodiment, the sampling signal processing method further includes:

[0020] The order N of the continuous decimation filtering process is the same as the number M of the continuous interpolation filtering process;

[0021] The frequency value attenuation multiple in each decimation filtering process is the same as the frequency value increase multiple in each interpolation filtering process.

[0022] In an embodiment, the sampling signal processing method further comprises:

[0023] In each interpolation filtering process, the sampling interpolation inserted value is the same preset constant.

[0024] In an embodiment, the sampling signal processing method further comprises:

[0025] The value of the preset constant is 0.

[0026] In an embodiment, the sampling signal processing method further comprises:

[0027] The sampling decimation mode is equal-interval sampling decimation of a fixed number of sampling points, and the sampling interpolation mode is equal-interval interpolation of a fixed number and value of sampling points.

[0028] Or, the sampling decimation mode is linear-interval sampling decimation, and the sampling interpolation mode is linear-interval sampling interpolation.

[0029] Or, the sampling decimation mode is sinusoidal-interval sampling decimation, and the sampling interpolation mode is sinusoidal-interval sampling interpolation.

[0030] In a second aspect, an embodiment provides a sampling signal processing device for digital filtering, which is used to apply the sampling signal processing method as described in the first aspect, and the sampling signal processing device comprises:

[0031] A preprocessing module is configured to perform low-pass filtering or band-pass filtering on a sampling signal at a first sampling frequency to obtain a to-be-processed signal for anti-sampling aliasing processing;

[0032] A decimation filtering module is configured to perform N-order continuous decimation filtering on the to-be-processed signal to obtain a decimation filtering signal, where N is a natural number not less than 2;

[0033] An interpolation filtering module is configured to perform M-time continuous interpolation filtering on the decimation filtering signal obtained after the N-order continuous decimation filtering to obtain a complement value filtering signal, where M is a natural number not less than 2; and the complement value filtering signal obtained after the M-time interpolation filtering has the same frequency as the sampling signal.

[0034] An output module is configured to output the interpolated filtered signal obtained after the M times of continuous interpolation filtering as a sampling signal filtered to remove preset low frequency components.

[0035] In a third aspect, a digital oscilloscope is provided in an embodiment, comprising the sampling signal processing apparatus according to the second aspect.

[0036] In a fourth aspect, a computer program product is provided in an embodiment, comprising computer programs and / or instructions executable by a processor to implement the sampling signal processing method according to the first aspect.

[0037] In a fifth aspect, a computer readable storage medium is provided in an embodiment, the medium storing programs executable by a processor to implement the sampling signal processing method according to the first aspect.

[0038] According to the sampling signal processing method of the above embodiments, since the low-pass filtered sampling signal is first subjected to multi-order decimation filtering for down-sampling processing, and then the decimated filtered signal obtained after the down-sampling processing is subjected to multiple interpolation processing to restore the frequency to the frequency of the sampling signal, only a small amount of computing resources is required to implement low-pass filtering of a very low cut-off frequency in a high sampling rate, large data flow scenario. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A flowchart of a sampling signal processing method according to an embodiment;

[0040] Figure 2 A flowchart of a decimation filtering process according to an embodiment;

[0041] Figure 3 A flowchart of an interpolation filtering process according to an embodiment;

[0042] Figure 4 A block diagram of a sampling signal processing apparatus according to an embodiment;

[0043] Figure 5 A flowchart of a sampling signal processing method according to another embodiment;

[0044] Figure 6 A filter waveform diagram of an anti-aliasing process of a low-pass filter according to an embodiment;

[0045] Figure 7 An example diagram of sampling decimation in a decimation filtering process according to an embodiment;

[0046] Figure 8 An example diagram of sampling interpolation in an interpolation filtering process according to an embodiment;

[0047] Figure 9 This is a waveform diagram of low-pass filter filtering in interpolation filtering process in one embodiment. Detailed Implementation

[0048] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0049] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0050] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0051] Preprocessing the sampled signal involves computationally intensive filtering operations, while anti-aliasing and anti-mirror filtering are also necessary to ensure signal quality. Specific steps include:

[0052] First, anti-aliasing filtering (decimation of the starting point) is performed. The sampling rate of the input sampled signal is f. s1 In order to ensure safe extraction (downsampling) to f s2 = f s1 / 2, anti-aliasing filtering is necessary, and a low-pass filter (LPF) is used. The filter must strongly attenuate all frequency components above f. s2 / 2=f s1 / 4 part (f s2 (This refers to the downsampled frequency). The ultimate goal is to satisfy the Nyquist sampling theorem. When the sampling rate is reduced to f...s2 At this time, the new Nyquist frequency is f s2 / 2 = f s1 / 4. Any frequency component higher than f s1 / 4 will alias back into the band 0 to f s1 / 4 after decimation, polluting the valid signal. An anti-aliasing filter is used to prevent this aliasing from occurring.

[0053] Then the decimation filtering process is performed. After anti-aliasing filtering, the signal is decimated (down-sampled). The simplest decimation is to take every other sample. After decimation, the sampling rate is reduced from f s1 to f s2 = f s1 / 2. After filtering, a low-pass filtering is performed again.

[0054] A multi-stage decimation filtering process (iterative filtering and decimation) is performed, i.e. the above decimation filtering process (low-pass filtering + decimation) is repeated multiple times. At each stage (f s_k ), a low-pass filter is designed, whose cut-off frequency needs to satisfy the anti-aliasing requirement of the next stage decimation (f s_{k+1} = f s_k / 2) (i.e. the cut-off frequency is about f s_k / 4.

[0055] In the above multi-stage decimation filtering process, as the sampling rate is halved at each stage, the number of data points of the signal is also halved. The number of multiply-accumulate operations required for filtering operations (especially those low cut-off frequency filters which require high computation) at low sampling rates is significantly reduced. A filter of length N running at f s_k , its computation is (f s1 / f s_k )*(the ratio of the number of data points) times of the same length filter running at f s1 . At low sampling rates, the same relative bandwidth (e.g. 0 to -f c ) corresponds to a narrower absolute bandwidth (f c ). It is usually easier to design a filter with a lower cut-off frequency f c at a lower sampling rate than to design a filter with the same absolute cut-off frequency f c at the original high sampling rate (the transition band requirement is relatively relaxed, and the filter order can be lower). However, the multi-stage decimation filtering structure has obvious disadvantages in scenarios with high sampling rates and large data streams, including non-flat passband (Sinc-shaped roll-off), insufficient stopband attenuation, and the existence of side lobes after "notch", and the need for a post-compensation filter to correct the passband notch and further improve the stopband attenuation.

[0056] In the embodiment of the present application, the low-pass filtered sampling signal is subjected to multi-stage decimation filtering for down-sampling processing, and then the decimation filtered signal obtained after the down-sampling processing is subjected to multiple interpolation processing to restore the frequency to the frequency of the sampling signal. Only a small amount of computing resources is needed to perform low-pass filtering on a very low cutoff frequency in a high sampling rate and large data flow scenario.

[0057] Embodiment one

[0058] Please refer to Figure 1 The sampling signal processing method is used for filtering a very low cutoff frequency (the sampling frequency is more than 100 times or 1000 times of the sampled frequency) in a high sampling rate (such as MHz to GHz level) and large data flow scenario (continuous high-speed input). The sampling signal processing method includes the following steps.

[0059] Step 100, performing initial filtering.

[0060] The sampling signal of the first sampling frequency is subjected to low-pass filtering or band-pass filtering to obtain a to-be-processed signal subjected to anti-sampling aliasing processing.

[0061] Step 200, multi-stage decimation filtering processing.

[0062] The to-be-processed signal is subjected to N-stage continuous decimation filtering processing to obtain a decimation filtered signal, where N is a natural number not less than 2.

[0063] Step 300, multiple interpolation filtering processing.

[0064] The decimation filtered signal obtained after the N-stage continuous decimation filtering processing is subjected to M-stage continuous interpolation filtering processing to obtain a complementary filtered signal, where M is a natural number not less than 2. The complementary filtered signal obtained after the M-stage interpolation filtering processing has the same frequency as the sampling signal.

[0065] Step 400, outputting a filtered result signal.

[0066] The complementary filtered signal obtained after the M-stage continuous interpolation filtering processing is output as a sampling signal filtered of preset low-frequency components.

[0067] Please refer to Figure 2 The flowchart of the decimation filtering processing process in an embodiment includes the following steps.

[0068] Step 201, performing sampling decimation.

[0069] The sampling decimation is performed on the to-be-processed signal or the decimation filtered signal after the previous-stage decimation filtering according to a preset sampling decimation mode, so that the frequency value of the to-be-processed signal or the decimation filtered signal after the previous-stage decimation filtering is attenuated. In an embodiment, the frequency value is attenuated by an even multiple during the decimation filtering of each stage. In an embodiment, the sampling decimation mode is equal-interval sampling decimation of a fixed number of sampling points.

[0070] In step 202, low-pass filtering is performed.

[0071] The to-be-processed signal or the decimation filtered signal after the previous-stage decimation filtering is subjected to low-pass filtering to obtain the decimation filtered signal after the current-stage decimation filtering.

[0072] Please refer to Figure 3 FIG. 1 is a flowchart of an embodiment of the interpolation filtering process. Each interpolation filtering process includes the following steps:

[0073] In step 301, sampling interpolation is performed.

[0074] The decimation filtered signal obtained after the N-stage continuous decimation filtering or the interpolated filtered signal obtained after the previous-stage interpolation filtering is subjected to sampling interpolation according to a preset sampling interpolation mode, so that the frequency value of the interpolated filtered signal obtained after the sampling interpolation is increased. In an embodiment, the frequency value is increased by an even multiple during each interpolation filtering process. In an embodiment, the number N of stages of continuous decimation filtering is the same as the number M of times of continuous interpolation filtering. In an embodiment, the frequency value is attenuated by the same multiple during each stage of decimation filtering as the frequency value is increased during each interpolation filtering process. In an embodiment, the same preset constant is inserted as the value during sampling interpolation during each interpolation filtering process. In an embodiment, the value of the preset constant is 0.

[0075] In an embodiment, the sampling interpolation mode is equal-interval insertion of a fixed number and value of sampling points. In an embodiment, the sampling decimation mode is linear-interval sampling decimation, and the corresponding sampling interpolation mode is linear-interval sampling interpolation. In an embodiment, the sampling decimation mode is sinusoidal-interval sampling decimation, and the corresponding sampling interpolation mode is sinusoidal-interval sampling interpolation.

[0076] In step 302, low-pass filtering is performed.

[0077] The decimation filtered signal after the frequency value is increased or the interpolated filtered signal obtained after the previous-stage interpolation filtering is subjected to low-pass filtering to obtain the interpolated filtered signal after the current-stage interpolation filtering.

[0078] Please refer to Figure 4As shown in Fig. 1, a structure block diagram of a sampling signal processing device in an embodiment is shown. In an embodiment of the present application, a sampling signal processing device is disclosed for applying the sampling signal processing method as described above. The sampling signal processing device comprises a preprocessing module 10, an decimation filtering module 20, an interpolation filtering module 30 and an output module 40. The preprocessing module 10 is configured to perform low-pass filtering or band-pass filtering on the sampling signal of the first sampling frequency to obtain a to-be-processed signal for anti-sampling aliasing processing. The decimation filtering module 20 is configured to perform N-order continuous decimation filtering on the to-be-processed signal to obtain a decimation filtering signal, where N is a natural number not less than 2. The interpolation filtering module 30 is configured to perform M-order continuous interpolation filtering on the decimation filtering signal obtained after the N-order continuous decimation filtering to obtain a interpolation filtering signal, where M is a natural number not less than 2. The interpolation filtering signal obtained after the M-order interpolation filtering has the same frequency as the sampling signal. The output module 40 is configured to output the interpolation filtering signal obtained after the M-order continuous interpolation filtering as the sampling signal with the preset low-frequency components filtered out.

[0079] In an embodiment of the present application, a digital oscilloscope is disclosed, which comprises the sampling signal processing device as described above. When performing signal sampling, the digital oscilloscope needs to perform low-frequency cutoff filtering, which mainly functions to suppress high-frequency noise (the low-frequency cutoff filter filters high-frequency signals, effectively suppresses random noise interference in measurement, and improves the signal-to-noise ratio of the signal), improve signal resolution (high-frequency noise can cause signal waveform burrs, and low-pass filtering can eliminate these interferences to make the waveform smoother, thereby improving the resolution), ensure measurement accuracy (by filtering out interference signals beyond the low-frequency range, the measurement result is ensured to be more accurate), and perform online real-time processing (signals can be processed in real time without additional equipment, and the waveform comparison effect before and after filtering can be displayed synchronously).

[0080] The sampling signal processing method disclosed in the embodiments of the present application first filters the sampling signal to obtain a to-be-processed signal, then performs N-order continuous decimation filtering on the to-be-processed signal to obtain a decimation filtering signal, then performs M-order continuous interpolation filtering on the decimation filtering signal obtained after the N-order continuous decimation filtering to obtain a interpolation filtering signal, and finally outputs the interpolation filtering signal obtained after the M-order continuous interpolation filtering as the sampling signal with the preset low-frequency components filtered out. Since the low-pass filtered sampling signal is first subjected to multi-order decimation filtering for down-sampling processing, and then the decimation filtering signal obtained after the down-sampling processing is subjected to interpolation processing multiple times to restore the frequency to the frequency of the sampling signal, low-pass filtering of a very low cutoff frequency in a high sampling rate and large data flow scenario can be realized with a small amount of computing resources.

[0081] For the convenience of understanding the specific application mode of the sampling signal processing method disclosed in the present application, the following will be described in detail through specific embodiments, which specifically include:

[0082] Please refer to Figure 5 , the flowchart of the sampling signal processing method in another embodiment, in which the pre-processing module performs low-pass filtering on the sampling signal of the first sampling frequency f s1 to obtain the to-be-processed signal for anti-sampling aliasing processing. The decimation filtering module is used to perform three consecutive decimation filtering processes on the to-be-processed signal to obtain the decimation filtered signal (the sampling frequency of the decimation filtered signal obtained after each decimation filtering process is 1 / 2f s1 , 1 / 4f s1 and 1 / 8f s1 ). The interpolation filtering module is used to perform three consecutive interpolation filtering processes on the decimation filtered signal obtained after the three consecutive decimation filtering processes to obtain the interpolation filtered signal (the sampling frequency of the interpolation filtered signal obtained after each interpolation filtering process is 1 / 4f s1 , 1 / 2f s1 and f s1 ), and the interpolation filtered signal obtained after the three interpolation filtering processes has the same frequency as the sampling signal. The output module is used to output the interpolation filtered signal obtained after the three consecutive interpolation filtering processes as the sampling signal filtered of the preset low-frequency components. In the sampling signal processing flow, the filtering is realized through a low-pass filter, the sampling decimation method adopts equal-interval sampling decimation of a fixed number of sampling points (data equal-interval selection), and the sampling interpolation method is equal-interval insertion of a fixed number and value of sampling points (the values inserted by the sampling interpolation are all 0), which specifically includes:

[0083] Step 501, obtaining a sampling signal. Reading the sampling signal data of the first sampling frequency f s1 , or performing real-time sampling at the first sampling frequency f s1 .

[0084] Step 502, performing initial filtering. Anti-aliasing filtering is performed through a low-pass filter, so that each stage of decimation is performed to half the rate of the last stage. For example, if the sampling frequency of the input sampling signal is the first sampling frequency f s1 , the frequencies above 1 / 4f s1 of the signal need to be attenuated through the low-pass filter, so that when decimation is performed to the rate of 1 / 2f s1 , the requirement of 1 / 2 sampling frequency of the Nyquist sampling theorem can be met.

[0085] The steps 503, 504, 505, 506, 507 and 508 are sequentially executed to sequentially perform first-order decimation, first-order filtering, second-order decimation, second-order filtering, third-order decimation and third-order filtering to complete three-order continuous decimation filtering processing of the sampling signal with the first sampling frequency f s1 , and the sampling frequency of the sequentially obtained decimation filtered signal after the processing is 1 / 2f s1 , 1 / 4f s1 and 1 / 8f s1 . In an embodiment, the frequency component remaining after the third-order filtering is f c . After the input sampling signal is filtered and decimated step by step, the rate is lower and lower, and the filtering with a low cutoff frequency can be performed at a low rate, and the required computing unit and computing capacity requirement are reduced.

[0086] The steps 509, 510, 511, 512, 513 and 514 are sequentially executed to sequentially perform first interpolation processing, first filtering processing, second interpolation processing, second filtering processing, third interpolation processing and third filtering processing to complete three-order continuous interpolation filtering processing, and the sampling frequency of the sequentially obtained interpolation filtered signal after the processing is 1 / 4f s1 , 1 / 2f s1 and f s1 . When the interpolation filtering processing is performed, the signal after the filtering processing will generate noise (noise frequency = 1 / 2* sampling rate ± input frequency) after the 0 interpolation, at this time, the signals with low frequencies remaining after the previous filtering are all concentrated near 1 / 2* sampling rate, and can be filtered out through a low-pass filter. The original sampling frequency f s1 can be restored through repeated interpolation and filtering.

[0087] Please refer to Figure 6 , Figure 7 , Figure 8 and Figure 9 , which are a filter waveform diagram (there is a great attenuation at 1 / 4 sampling frequency) of an embodiment of a low-pass filter for anti-aliasing processing, an example diagram of sampling decimation in decimation filtering processing (decimation is performed according to interval 1 sampling point data), an example diagram of sampling interpolation in interpolation filtering processing (the interpolation filling value is 0) and a waveform diagram of low-pass filtering of a low-pass filter in interpolation filtering processing (to filter out the noise signal caused by interpolation).

[0088] In step 515, the output sampling signal is output. Finally, the frequency component of 0 to f c can be obtained, and the frequency component of f c to 1 / 2f s1 is filtered out.

[0089] In the embodiment, the sampling rate is halved each time the filtering and decimation is performed, and can be adjusted according to actual requirements, but the corresponding interpolation and filtering also need to be adjusted accordingly, and the principle and mode are similar, and thus will not be described in detail. The sampling signal processing method disclosed in the embodiment of the application, on the one hand, firstly performs low-frequency filtering at a low sampling rate, and then restores the sampling rate through zero padding interpolation and low-pass filtering. The input sampling rate and the output sampling rate are kept consistent. On the other hand, the sampling rate is reduced through multi-stage decimation, the low-pass filtering operation at a very low frequency is realized, and the calculation resources are saved, and the number of calculation units is reduced.

[0090] Those skilled in the art can understand that all or part of the functions of the various methods in the above embodiments can be realized by hardware or by a computer program. When all or part of the functions in the above embodiments are realized by a computer program, the program can be stored in a computer readable storage medium, which can include read-only memory, random access memory, magnetic disk, optical disk, hard disk, etc. The above functions are realized by executing the program by a computer. For example, the program is stored in the memory of a device, and when the program in the memory is executed by a processor, the above functions are realized. In addition, when all or part of the functions in the above embodiments are realized by a computer program, the program can also be stored in a server, another computer, a storage medium such as a disk, an optical disk, a flash disk or a mobile hard disk, and is downloaded or copied into the memory of a local device, or the system of the local device is updated, and when the program in the memory is executed by a processor, the above functions are realized.

[0091] The above application of specific examples to the application is described, which is only used to help understand the application and does not limit the application. For those skilled in the art to which the application belongs, according to the idea of the application, several simple deductions, deformations or substitutions can be made.

Claims

1. A sampling signal processing method for digital filtering, characterized in that, include: The sampled signal at the first sampling frequency is subjected to low-pass or band-pass filtering to obtain the signal to be processed to prevent sampling aliasing. The signal to be processed is subjected to N-order continuous decimation filtering to obtain a decimation-filtered signal, where N is a natural number not less than 2. Each decimation filtering process includes: The signal to be processed or the decimated and filtered signal after the previous decimation and filtering process is sampled and extracted according to a preset sampling and extraction method, so that the frequency value of the signal to be processed or the decimated and filtered signal after the previous decimation and filtering process is attenuated. The signal to be processed after frequency attenuation or the decimated filter signal after the previous decimation filter is subjected to low-pass filtering to obtain the decimated filter signal after the current decimation filter. The decimated filter signal obtained after N-order continuous decimation filtering is subjected to M consecutive interpolation filtering processes to obtain a complemented filter signal, where M is a natural number not less than 2; wherein the complemented filter signal obtained after M interpolation filtering processes has the same frequency as the sampled signal. Each interpolation filtering process includes: The decimated filter signal obtained after N-order continuous decimation filtering or the complemented filter signal obtained after the previous interpolation filtering is sampled and interpolated according to a preset sampling and interpolation method, so that the frequency value of the complemented filter signal obtained after sampling and interpolation increases. The decimation filter signal after the frequency value is increased or the complement filter signal obtained after the previous interpolation filter processing is low-pass filtered to obtain the complement filter signal after the current interpolation filter processing. The complemented filtered signal obtained after M consecutive interpolation filtering is output as the sampling signal after filtering out the preset low-frequency components.

2. The sampling signal processing method as described in claim 1, characterized in that, Also includes: In each decimation filtering process, the frequency value attenuation factor is an even number; In each interpolation filtering process, the frequency value increases by an even multiple.

3. The sampling signal processing method as described in claim 1, characterized in that, Also includes: The order N of the continuous decimation filtering process is the same as the number M of the continuous interpolation filtering process. The frequency value attenuates by the same factor as the frequency value increases by the same factor in each interpolation filtering process.

4. The sampling signal processing method as described in claim 1, characterized in that, Also includes: In each interpolation filtering process, the sampled interpolation values ​​are the same preset constants.

5. The sampling signal processing method as described in claim 4, characterized in that, Also includes: The value of the preset constant is 0.

6. The sampling signal processing method as described in claim 1, characterized in that, Also includes: The sampling extraction method is to extract a fixed number of sampling points at equal intervals, and the sampling interpolation method is to insert a fixed number of sampling points with equal values ​​at equal intervals. Alternatively, the sampling extraction method is linear interval sampling extraction, and the sampling interpolation method is linear interval sampling interpolation; Alternatively, the sampling extraction method is sinusoidal interval sampling extraction, and the sampling interpolation method is sinusoidal interval sampling interpolation.

7. A sampling signal processing device for digital filtering, characterized in that, For applying the sampling signal processing method as described in any one of claims 1 to 6, the sampling signal processing apparatus comprises: The preprocessing module is used to perform low-pass filtering or band-pass filtering on the sampled signal at the first sampling frequency to obtain the signal to be processed to prevent sampling aliasing. The decimation filtering module is used to perform N-order continuous decimation filtering on the signal to be processed to obtain a decimated filtered signal, where N is a natural number not less than 2. The interpolation filtering module is used to perform M consecutive interpolation filtering processes on the decimated filtered signal obtained after N-order continuous decimation filtering to obtain a complemented filtered signal, where M is a natural number not less than 2; wherein the complemented filtered signal obtained after M interpolation filtering processes has the same frequency as the sampled signal. The output module is used to output the complemented filtered signal obtained after M consecutive interpolation filtering processes as a sampled signal with preset low-frequency components filtered out.

8. A digital oscilloscope, characterized in that, Includes the sampling signal processing apparatus as described in claim 7.

9. A computer program product, comprising a computer program and / or instructions, characterized in that, The computer program and / or instructions are executed by a processor to implement the sampling signal processing method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The medium stores a program that can be executed by a processor to implement the sampling signal processing method as described in any one of claims 1 to 6.

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