CN111384983A - Signal processing method and device - Google Patents
Signal processing method and device Download PDFInfo
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- CN111384983A CN111384983A CN201811642421.9A CN201811642421A CN111384983A CN 111384983 A CN111384983 A CN 111384983A CN 201811642421 A CN201811642421 A CN 201811642421A CN 111384983 A CN111384983 A CN 111384983A
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Abstract
The embodiment of the invention provides a signal processing method and a device, wherein the method comprises the following steps: receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal; acquiring the at least one data signal from the signal to be processed; and filtering the at least one data signal by a Gaussian filter, wherein the Gaussian filter is a band-pass filter. The method is used for improving the accuracy of the decoding result.
Description
Technical Field
The embodiment of the invention relates to the field of signal processing, in particular to a signal processing method and device.
Background
An Electronic Toll Collection (ETC) system is a system capable of realizing Electronic Toll Collection (ETC) of vehicles. The ETC system includes an On Board Unit (OBU) generally provided in a vehicle and a Road Side Unit (RSU) generally provided in a Road.
In practical applications, an OBU in a vehicle may send a Bi-Phase space coding (FM 0) modulation signal to an RSU, after the RSU receives an FM0 modulation signal, perform analog/digital processing and modulus operation on an FM0 modulation signal in sequence to obtain an FM0 baseband signal, then use a low-pass filter to perform filtering processing on the FM0 baseband signal to eliminate high-frequency interference, then determine the FM0 baseband signal without the high-frequency interference according to a selected determination time and a preset determination threshold to obtain a determined FM0 baseband signal, and finally perform decoding processing on the determined FM0 baseband signal.
In the process, the baseband FM0 signal is filtered by the low-pass filter, so that the low-frequency interference cannot be eliminated, and therefore, when the baseband FM0 signal without the high-frequency interference is judged according to the selected judgment time and the preset judgment threshold, a judgment error occurs, and the accuracy of decoding the FM0 baseband signal is poor.
Disclosure of Invention
The embodiment of the invention provides a signal processing method and a signal processing device, which are used for improving the accuracy of a decoding result.
In a first aspect, an embodiment of the present invention provides a signal processing method, including:
receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal;
acquiring the at least one data signal from the signal to be processed;
and filtering the at least one data signal by a Gaussian filter, wherein the Gaussian filter is a band-pass filter.
In a possible implementation, before the filtering processing of the at least one data signal by the gaussian filter, the method includes:
determining a first set of coefficients and a second set of coefficients, wherein the number of coefficients in the first set of coefficients is different from the number of coefficients in the second set of coefficients, and the first set of coefficients and the second set of coefficients are Yang-Hue-Delta coefficients;
determining coefficients of the Gaussian filter based on the first set of coefficients and the second set of coefficients.
In another possible implementation, the number of coefficients in the first set of coefficients is smaller than the number of coefficients in the second set of coefficients; said determining coefficients of said gaussian filter based on said first set of coefficients and said second set of coefficients comprises:
carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients;
carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients;
adding the same number of zeros at the initial position and the end position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients;
determining coefficients of the Gaussian filter according to the fourth set of coefficients and the fifth set of coefficients.
In another possible embodiment, the determining the coefficients of the gaussian filter according to the fourth set of coefficients and the fifth set of coefficients includes:
and respectively subtracting a second coefficient in the fourth set of coefficients from a first coefficient in the fifth set of coefficients to obtain the coefficients of the Gaussian filter, wherein the position of the first coefficient in the fifth set of coefficients is the same as the position of the second coefficient in the fourth set of coefficients.
In another possible embodiment, the filtering the at least one data signal by a gaussian filter includes:
and performing convolution operation on the coefficient of the Gaussian filter and the at least one datum respectively to realize filtering processing on the at least one datum signal.
In a second aspect, an embodiment of the present invention provides a signal processing apparatus, which includes a first receiving module, a first obtaining module, and a first filtering module, wherein,
the first receiving module is used for receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal;
the first obtaining module is configured to obtain the at least one data signal from the signal to be processed;
the first filtering module is used for filtering the at least one data signal, and the first filtering module is a band-pass filter.
In one possible implementation, the apparatus further includes a first determining module, a second determining module, wherein,
the first determining module is configured to determine a first group of coefficients and a second group of coefficients, where the number of coefficients in the first group of coefficients is different from the number of coefficients in the second group of coefficients, and the first group of coefficients and the second group of coefficients are yang-delta coefficients;
the second determining module is configured to determine the coefficients of the first filtering module according to the first set of coefficients and the second set of coefficients.
In another possible implementation, the number of coefficients in the first set of coefficients is smaller than the number of coefficients in the second set of coefficients; the second determining module is specifically configured to:
carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients;
carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients;
adding the same number of zeros at the initial position and the end position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients;
determining coefficients of the first filtering module based on the fourth set of coefficients and the fifth set of coefficients.
In another possible implementation manner, the second determining module is specifically configured to:
and respectively subtracting a second coefficient in the fourth set of coefficients from a first coefficient in the fifth set of coefficients to obtain the coefficients of the Gaussian filter, wherein the position of the first coefficient in the fifth set of coefficients is the same as the position of the second coefficient in the fourth set of coefficients.
In another possible implementation manner, the first filtering module is specifically configured to:
and performing convolution operation on the coefficient of the first filtering module and the at least one data respectively to realize filtering processing on the at least one data signal.
In a third aspect, an embodiment of the present invention provides a signal processing apparatus, including: a processor coupled with a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the signal processing apparatus to perform the method of any of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a readable storage medium, which includes a program or instructions, and when the program or instructions are run on a computer, the method according to any one of the first aspect is performed.
In the method, a signal to be processed is received, wherein the signal to be processed comprises an interference signal and at least one data signal; acquiring the at least one data signal from the signal to be processed; and filtering the at least one data signal by a Gaussian filter, wherein the Gaussian filter is a band-pass filter. In the above process, the signal to be processed includes an interference signal, and when the gaussian filter is used to perform filtering processing on at least one data signal including the interference signal, low-frequency interference and high-frequency interference of the interference signal in each data signal can be eliminated, so that accuracy of decoding the data signal can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of a signal processing method according to an embodiment of the present invention;
fig. 2 is a first schematic flowchart of a signal processing method according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a signal processing method according to an embodiment of the present invention;
FIG. 4 is a first time domain waveform of a data signal provided by an implementation of the present invention;
FIG. 5 is a first spectrum diagram of a data signal provided by an implementation of the present invention;
FIG. 6 is a second time domain waveform diagram of a data signal according to an embodiment of the present invention;
fig. 7 is a spectrum diagram ii of a data signal according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of the coefficient distribution of a Gaussian filter provided in accordance with an embodiment of the present invention;
FIG. 9 is a spectrum diagram of a Gaussian filter provided in accordance with an embodiment of the present invention;
fig. 10 is a time domain waveform diagram of a data signal subjected to decision provided by an embodiment of the present invention;
fig. 11 is a first schematic structural diagram of a signal processing apparatus according to an embodiment of the present invention;
fig. 12 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic view of an application scenario of a signal processing method according to an embodiment of the present invention. Referring to fig. 1, in the electronic toll collection system 10, an on-board unit 12 is provided in a vehicle 11, an on-board unit 22 is provided in a vehicle 21, a toll collection device 4 is provided in a road on which the vehicle 11 and the vehicle 12 travel, and a roadside unit 3 is provided in the toll collection device 4.
In practical applications, when the vehicle 11 and the vehicle 12 pass through the toll collection device 4, the on-board unit 12 transmits a first FM0 modulated signal to the roadside unit 3, the on-board unit 12 transmits a second FM0 modulated signal to the roadside unit 3, and the roadside unit 3 may receive a superimposed signal of the first FM0 modulated signal, the second FM0 modulated signal, and the interference signal. After the roadside unit 3 receives the superimposed signal, firstly, performing power spectrum estimation processing on the superimposed signal to obtain a first FM0 modulated signal containing an interference signal and a second FM0 modulated signal containing an interference signal; secondly, analog/digital processing and modulus operation are sequentially carried out on the first FM0 modulation signal containing the interference signal, and a first FM0 baseband signal containing the interference signal is obtained; thirdly, filtering the first FM0 baseband signal containing the interference signal by adopting a band-pass Gaussian filter; then, the filtered first FM0 baseband signal is judged according to the selected judgment time and a preset judgment threshold, and a judged first FM0 baseband signal is obtained; and finally, decoding the judged first FM0 baseband signal to acquire first code element information.
The processing procedure of the roadside unit 3 on the second FM0 baseband signal including the interference signal is the same as the processing procedure on the first FM0 baseband signal including the interference signal. After the rsu 3 processes the second FM0 baseband signal containing the interference signal, the second symbol information may be obtained.
Optionally, the superimposed signal is subjected to a power spectrum estimation process, and a first FM0 modulated signal containing an interference signal and a second FM0 modulated signal containing an interference signal may be separated from the superimposed signal.
Optionally, the first FM0 baseband signal containing the interference signal is filtered, so as to obtain a first FM0 baseband signal with high frequency interference and low frequency interference eliminated.
Optionally, the roadside unit 3 may calculate the required road passing fee of the vehicle 11 according to the first code element information, and calculate the required road passing fee of the vehicle 12 according to the second code element information.
Alternatively, the first symbol information generally includes the frame number and the travel information of the vehicle 11, the user information to which the vehicle 11 belongs, and the like.
Alternatively, the second symbol information generally includes the frame number and the travel information of the vehicle 12, the user information to which the vehicle 12 belongs, and the like.
Alternatively, the travel information may include a current road number (e.g., x008), a continuous driving time period, a vehicle travel distance, and the like.
Optionally, the user information may include an identification number, a mobile phone number, and the like of the user.
The signal processing method provided by the implementation of the invention is applied to an electronic charging system, and in the method, as the band-pass Gaussian filter is adopted to filter the FM0 baseband signal of the interference signal, the FM0 baseband signal for eliminating low-frequency interference and high-frequency interference can be obtained, and the FM0 baseband signal for eliminating low-frequency interference and high-frequency interference is judged and decoded in sequence, so that the accuracy of decoding information can be improved.
Furthermore, the accuracy of the decoded information is improved, so that the electronic toll collection system can more accurately calculate the required road passing fee of each vehicle in the process of executing toll collection calculation.
The technical means shown in the present application will be described in detail below with reference to specific examples. It should be noted that the following embodiments may be combined with each other, and the description of the same or similar contents in different embodiments is not repeated.
Fig. 2 is a first flowchart of a signal processing method according to an embodiment of the present invention. Referring to fig. 2, the method includes:
s201: and receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal.
Optionally, the execution main body in the embodiment of the present invention may be a road side unit, and may also be a signal processing device disposed in the road side unit. Alternatively, the signal processing means may be implemented by a combination of software and hardware.
Optionally, the signal processing device includes a high-gain directional beam-steering read-write antenna.
Optionally, the high-gain directional beam-steering read-write antenna in the signal processing apparatus may receive a signal to be processed.
Optionally, the signal to be processed further includes an interference signal.
Optionally, the signal to be processed is a superimposed signal of the interference signal and the at least one data signal.
Optionally, the interference signal is a noise signal, a wireless signal transmitted by other wireless communication devices (such as a mobile phone) and a wireless communication base station, and the like.
Optionally, the data signal is an FMO modulated signal sent by an on-board unit of the vehicle.
S202: at least one data signal is acquired in the signal to be processed.
In practical application, before acquiring at least one data signal from the signal to be processed, the method further comprises performing analog-to-digital conversion processing on the signal to be processed.
Optionally, the signal to be processed after the analog/digital conversion processing is subjected to power spectrum estimation processing based on a super-resolution space of feature decomposition, so as to obtain at least one data signal from the signal to be processed.
It should be noted that each acquired data signal still contains an interference signal.
Alternatively, the waveform of the data signal is typically a square wave.
Alternatively, the data signal usually has "glitches" in its waveform because the data signal contains interference signals. In particular, reference may be made to a time domain waveform diagram of a data signal as shown in the implementation of fig. 4 and a spectral diagram of a data signal as shown in the implementation of fig. 5.
S203: at least one data signal is filtered by a gaussian filter, which is a band-pass filter.
Alternatively, a gaussian filter may be preset according to the bandwidth of the data signal.
Alternatively, the gaussian filter usually has parameters such as bandwidth and filter coefficient.
Optionally, after filtering each data signal including the interference signal by using a gaussian filter, each data signal from which the low-frequency interference and the high-frequency interference are removed may be obtained. Specifically, after the filtering process, a time domain waveform diagram of the data signal including the interference signal can be seen in fig. 6. After the filtering process, the spectrogram of the data signal, which contains the interference signal, can be seen in fig. 7.
Optionally, after each data signal for eliminating the low frequency interference and the high frequency interference is obtained, each data signal may be further subjected to demodulation, decision, and decoding.
The signal processing method provided by the embodiment of the invention receives a signal to be processed, wherein the signal to be processed comprises an interference signal and at least one data signal; acquiring the at least one data signal from the signal to be processed; and filtering the at least one data signal by a Gaussian filter, wherein the Gaussian filter is a band-pass filter. In the above process, the signal to be processed includes an interference signal, and when the gaussian filter is used to perform filtering processing on at least one data signal including the interference signal, low-frequency interference and high-frequency interference of the interference signal in each data signal can be eliminated, so that accuracy of decoding the data signal can be improved.
On the basis of any of the above embodiments, the following describes the solution of the present invention in further detail with reference to fig. 3, specifically, refer to fig. 3.
Fig. 3 is a schematic flowchart of a signal processing method according to an embodiment of the present invention. Referring to fig. 3, the method includes:
s301: and receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal.
S302: at least one data signal is acquired in the signal to be processed.
Optionally, S301 corresponds to S201 identically, and S302 corresponds to S202 identically, and here, the contents of S301 and S302 are not described again, specifically, refer to S201 and S202.
S303: and determining a first group of coefficients and a second group of coefficients, wherein the number of coefficients in the first group of coefficients is different from that of coefficients in the second group of coefficients, and the first group of coefficients and the second group of coefficients are the Yankee triangle coefficients.
Optionally, the first group of coefficients and the second group of coefficients are the pope triangle coefficients in any two rows of the pope triangle.
For example, the first set of coefficients may be the pope triangle coefficients in line 48 of the pope triangle. When the first set of coefficients is the popcornian coefficient in row 48, the number of coefficients in the first set of coefficients is 48.
For example, the second set of coefficients may be the pope triangle coefficients in line 60 of the pope triangle. When the second set of coefficients is the Yankee triangle coefficient in the 60 th row, the number of coefficients in the first set of coefficients is 60.
For convenience of understanding, the following describes details of S303 to S306, taking the first set of coefficients as the popcorne coefficients in the 6 th row of the popcorne and the second set of coefficients as the popcorne coefficients in the 8 th row of the popcorne.
S304: and carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients.
For example, the first set of coefficients includes 1, 5, 10, 5, and 1, and the normalization process is performed by dividing each coefficient in the first set of coefficients by 2 to the power of 6 to obtain a third set of coefficients 0.0156, 0.0781, 0.1563, 0.1563, 0.0781, 0.0156.
S305: and carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients.
For example, the second set of coefficients includes 1, 7, 21, 35, 21, 7, and 1, and the normalization process is performed by dividing each coefficient in the second set of coefficients by 2 to the power of 8 to obtain a fourth set of coefficients 0.0039, 0.027, 0.082, 0.1367, 0.1367, 0.082, 0.027, 0.0039.
S306: and adding the same number of zeros at the starting position and the ending position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients.
For example, the same number of zeros are added to the start and end positions of the third set of coefficients, resulting in fifth set of coefficients of 0, 0.0156, 0.0781, 0.1563, 0.1563, 0.0781, 0.0156, 0. The number of coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients, and the number of coefficients is 8.
S307: and respectively subtracting the second coefficient in the fourth group of coefficients from the first coefficient in the fifth group of coefficients to obtain the coefficient of the Gaussian filter, wherein the position of the first coefficient in the fifth group of coefficients is the same as the position of the second coefficient in the fourth group of coefficients.
Optionally, the coefficients-0.0039, -0.0117, -0.0039, 0.0195, -0.0039, -0.0117, and-0.0039 of the gaussian filter are obtained by subtracting the second coefficient of the fourth set of coefficients from the first coefficient of the fifth set of coefficients, i.e., 0-0.0039, 0.0156-0.027-0.0117, 0.0781-0.082-0.0039, 0.1563-0.1367-0.0195, 0.1563-0.1367-0.0195, 0.0781-0.082-0.0039, 0.0156-0.027-0.0117, and 0-0.0039.
S308: and performing convolution operation on the coefficient of the Gaussian filter and at least one datum respectively to realize filtering processing on at least one datum signal.
Alternatively, see the schematic coefficient distribution diagram of the gaussian filter in fig. 8.
Fig. 4 is a first time domain waveform diagram of a data signal provided by the implementation of the present invention. Referring to fig. 4, in a time domain waveform diagram of a data signal obtained after power spectrum estimation is performed on a signal to be processed, an x axis represents the number of sampling points of the data signal, and a y axis represents an amplitude value of the sampling points of the data signal.
It should be noted that the sampling points of the data signal on the x-axis correspond to time, that is, the time corresponding to the sampling point position is different.
Alternatively, due to the interference information included in the data signal, a spike (i.e., a "spur") may occur in the time domain waveform shown in fig. 4.
Fig. 5 is a first spectrum diagram of a data signal provided by the implementation of the present invention. Referring to fig. 5, the x-axis represents frequency points corresponding to the sampling points of the data signal, and the y-axis represents amplitude values corresponding to the frequency points.
Optionally, a data signal spectrum map 5 including the interference signal may be obtained by performing fourier transform (FFT) on a data signal including the interference signal.
As can be seen from fig. 5, due to the existence of the interference signal, an "interference frequency point" appears in the data signal spectrogram.
Fig. 6 is a time domain waveform diagram ii of a data signal according to an embodiment of the present invention. Referring to fig. 6, the x-axis represents the number of samples of the data signal, and the y-axis represents the amplitude values of the samples of the data signal, and it can be seen from the y-axis that the amplitude values of the data signal are floating between-8000- + 8000.
The data signal including the interference signal is subjected to filtering processing, and a time domain waveform diagram of the data signal shown in fig. 6 is obtained.
Fig. 7 is a spectrum diagram of a data signal according to an embodiment of the present invention. Referring to fig. 7, the x-axis represents frequency points corresponding to the sampling points of the data signal, and the y-axis represents amplitude values corresponding to the frequency points.
The data signal including the interference signal is sequentially subjected to filtering processing and FFT processing, and the spectrum diagram of the data signal shown in fig. 7 is obtained.
Alternatively, as can be seen from fig. 7 and 5, the frequency points from 5000 to the frequency point in the positive direction along the x-axis are filtered by the gaussian filter, and the amplitude value of the interference frequency point between 0 and 5000 is suppressed.
Fig. 8 is a schematic diagram of coefficient distribution of a gaussian filter according to an embodiment of the present invention. Referring to fig. 8, the x-axis represents the number of gaussian filter coefficients and the y-axis represents the magnitude of the coefficients.
The number of gaussian filter coefficients shown in fig. 8 is 60, and the coefficient distribution of the gaussian filter follows a gaussian probability distribution.
Fig. 9 is a spectrum diagram of a gaussian filter according to an embodiment of the present invention. Referring to FIG. 9, the x-axis represents the bandwidth of the Gaussian filter in rad/sample, where rad/sample represents the radian measure of each Yang point, and the y-axis represents the magnitude of the Gaussian filter in dB, where dB represents dB.
Alternatively, as can be seen from FIG. 9, the Gaussian filter bandwidth is 0.6 π rad/sample, where π is the natural circumference ratio.
Fig. 10 is a time domain waveform diagram of a data signal after being determined according to an embodiment of the present invention. Please refer to
In fig. 10, the x-axis represents samples of the data signal and the y-axis represents amplitude values of the samples of the data signal.
Optionally, as can be seen from fig. 10, the data signal after the decision processing has no influence of an interference signal, and a time domain waveform of the data signal exhibits a square wave shape.
Fig. 11 is a first schematic structural diagram of a signal processing apparatus according to an embodiment of the present invention. Referring to fig. 11, the apparatus includes a first receiving module 11, a first obtaining module 12, and a first filtering module 13, wherein,
the first receiving module 11 is configured to receive a signal to be processed, where the signal to be processed includes at least one data signal;
the first obtaining module 12 is configured to obtain the at least one data signal from the signal to be processed;
the first filtering module 13 is configured to perform filtering processing on the at least one data signal, and the first filtering module is a band-pass filter.
The takeaway order generating device provided by the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
In a possible implementation manner, the first filtering module 13 is specifically configured to:
and performing convolution operation on the coefficient of the first filtering module and the at least one data respectively to realize filtering processing on the at least one data signal.
Fig. 12 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present invention. Referring to fig. 12, the apparatus includes a first determining module 14 and a second determining module 15, where the first determining module 14 is configured to determine a first set of coefficients and a second set of coefficients, the number of coefficients in the first set of coefficients is different from the number of coefficients in the second set of coefficients, and the first set of coefficients and the second set of coefficients are yang-highlight coefficients;
the second determining module 15 is configured to determine the coefficients of the first filtering module according to the first set of coefficients and the second set of coefficients.
In one possible implementation, the number of coefficients in the first set of coefficients is smaller than the number of coefficients in the second set of coefficients; the second determining module 15 is specifically configured to:
carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients;
carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients;
adding the same number of zeros at the initial position and the end position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients;
determining coefficients of the first filtering module based on the fourth set of coefficients and the fifth set of coefficients.
In a possible implementation manner, the second determining module 15 is specifically configured to:
and respectively subtracting a second coefficient in the fourth set of coefficients from a first coefficient in the fifth set of coefficients to obtain the coefficients of the Gaussian filter, wherein the position of the first coefficient in the fifth set of coefficients is the same as the position of the second coefficient in the fourth set of coefficients.
The takeaway order generating device provided by the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
An embodiment of the present invention provides a signal processing apparatus, including: a processor coupled with a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the signal processing device to perform the method according to any of the method embodiments described above.
Embodiments of the invention provide a readable storage medium comprising a program or instructions for performing a method as described in any of the method embodiments above when the program or instructions are run on a computer.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention, and are not limited thereto; although embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the embodiments of the present invention.
Claims (10)
1. A signal processing method, comprising:
receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal;
acquiring the at least one data signal from the signal to be processed;
and filtering the at least one data signal by a Gaussian filter, wherein the Gaussian filter is a band-pass filter.
2. The method of claim 1, wherein prior to said filtering said at least one data signal with a gaussian filter, comprising:
determining a first set of coefficients and a second set of coefficients, wherein the number of coefficients in the first set of coefficients is different from the number of coefficients in the second set of coefficients, and the first set of coefficients and the second set of coefficients are Yang-Hue-Delta coefficients;
determining coefficients of the Gaussian filter based on the first set of coefficients and the second set of coefficients.
3. The method of claim 2, wherein the number of coefficients in the first set of coefficients is less than the number of coefficients in the second set of coefficients; said determining coefficients of said gaussian filter based on said first set of coefficients and said second set of coefficients comprises:
carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients;
carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients;
adding the same number of zeros at the initial position and the end position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients;
determining coefficients of the Gaussian filter according to the fourth set of coefficients and the fifth set of coefficients.
4. The method of claim 3, wherein determining the coefficients of the Gaussian filter based on the fourth set of coefficients and the fifth set of coefficients comprises:
and respectively subtracting a second coefficient in the fourth set of coefficients from a first coefficient in the fifth set of coefficients to obtain the coefficients of the Gaussian filter, wherein the position of the first coefficient in the fifth set of coefficients is the same as the position of the second coefficient in the fourth set of coefficients.
5. The method according to any one of claims 2-4, wherein said filtering said at least one data signal by a Gaussian filter comprises:
and performing convolution operation on the coefficient of the Gaussian filter and the at least one datum respectively to realize filtering processing on the at least one datum signal.
6. A signal processing device, comprising a first receiving module, a first obtaining module, and a first filtering module, wherein,
the first receiving module is used for receiving a signal to be processed, wherein the signal to be processed comprises at least one data signal;
the first obtaining module is configured to obtain the at least one data signal from the signal to be processed;
the first filtering module is used for filtering the at least one data signal, and the first filtering module is a band-pass filter.
7. The apparatus of claim 6, further comprising a first determination module, a second determination module, wherein,
the first determining module is configured to determine a first group of coefficients and a second group of coefficients, where the number of coefficients in the first group of coefficients is different from the number of coefficients in the second group of coefficients, and the first group of coefficients and the second group of coefficients are yang-delta coefficients;
the second determining module is configured to determine the coefficients of the first filtering module according to the first set of coefficients and the second set of coefficients.
8. The apparatus of claim 7, wherein the number of coefficients in the first set of coefficients is less than the number of coefficients in the second set of coefficients; the second determining module is specifically configured to:
carrying out normalization processing on the first group of coefficients to obtain a third group of coefficients;
carrying out normalization processing on the second group of coefficients to obtain a fourth group of coefficients;
adding the same number of zeros at the initial position and the end position of the third group of coefficients respectively to obtain a fifth group of coefficients, wherein the number of the coefficients in the fifth group of coefficients is the same as that of the coefficients in the fourth group of coefficients;
determining coefficients of the first filtering module based on the fourth set of coefficients and the fifth set of coefficients.
9. The apparatus of claim 8, wherein the second determining module is specifically configured to:
and respectively subtracting a second coefficient in the fourth set of coefficients from a first coefficient in the fifth set of coefficients to obtain the coefficients of the Gaussian filter, wherein the position of the first coefficient in the fifth set of coefficients is the same as the position of the second coefficient in the fourth set of coefficients.
10. The apparatus according to any one of claims 7 to 9, wherein the first filtering module is specifically configured to:
and performing convolution operation on the coefficient of the first filtering module and the at least one data respectively to realize filtering processing on the at least one data signal.
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