CN112929096A - Sound signal processing method and device and electronic equipment - Google Patents
Sound signal processing method and device and electronic equipment Download PDFInfo
- Publication number
- CN112929096A CN112929096A CN202110107866.2A CN202110107866A CN112929096A CN 112929096 A CN112929096 A CN 112929096A CN 202110107866 A CN202110107866 A CN 202110107866A CN 112929096 A CN112929096 A CN 112929096A
- Authority
- CN
- China
- Prior art keywords
- signal
- determining
- communication signal
- communication
- sound
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B11/00—Transmission systems employing sonic, ultrasonic or infrasonic waves
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
- H04B13/02—Transmission systems in which the medium consists of the earth or a large mass of water thereon, e.g. earth telegraphy
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0012—Modulated-carrier systems arrangements for identifying the type of modulation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
The application provides a processing method, a processing device and electronic equipment of a sound signal, which are used for acquiring the sound signal and converting the sound signal into a corresponding digital signal; judging whether a communication signal exists in the digital signal, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal; identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity; the communication signals are stored according to the signal modulation mode, and by adopting the mode, the communication signals with effective information can be identified from the sound signals, so that the processing efficiency of the sound signals can be improved.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for processing a sound signal, and an electronic device.
Background
With the rise of ocean exploration, in the process of ocean information monitoring, a self-contained submersible buoy system is taken as a main environmental monitoring device at present, has the capability of continuously acquiring hydrological information such as ocean environment, ocean sound and the like in severe sea areas under the condition of unmanned operation, becomes an extension of space and time of an observation station, an investigation ship and an airplane, and is an important means for offshore monitoring. The self-contained submerged buoy can carry various detection devices, such as an acoustic detector and the like, can complete short-term or long-term marine sound signal acquisition tasks, stores acquired data, opens a releaser device after acquisition is completed, sinks heavy objects such as lead blocks, floats out of the water through a fixed floating ball group, is salvaged and recovered by an experimental scientific investigation ship, and reads acquired sound signal data and observation results.
However, a lot of noise exists in the marine environment, at present, after the self-contained submersible buoy system starts to work, some useless marine noise information can be collected and stored in the storage system, because the self-contained submersible buoy system has limited storage capacity and underwater portable energy, the occupation of the invalid information on the storage capacity and the equipment power consumption seriously influences the collection and storage work of effective information, the underwater operation time of the equipment is reduced, and the collected sound signals need to be manually analyzed, so that the processing efficiency is low.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method, a device and an electronic device for processing an audio signal, wherein the method comprises determining a collected audio signal, retaining the audio signal including a valid communication signal, determining a communication signal from the audio signal, automatically identifying the communication signal, obtaining a modulation scheme corresponding to the communication signal, and further classifying and storing the communication signal according to the modulation scheme. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
The embodiment of the application provides a processing method of a sound signal, which comprises the following steps:
acquiring a sound signal, and converting the sound signal into a corresponding digital signal;
judging whether a communication signal exists in the digital signal, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal;
identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity;
and storing the communication signal according to the signal modulation mode.
Further, after the determining whether a communication signal exists in the digital signal and determining the communication signal and a first signal characteristic quantity corresponding to the communication signal if the communication signal exists in the digital signal, the processing method further includes:
if the communication signal does not exist in the digital signal, determining the digital signal as a noise signal;
the noise signal is deleted.
Further, whether the communication signal exists in the digital signal is judged based on the following method:
determining a plurality of sampled data points in the digital signal;
analyzing each sampling data point, and determining a second signal characteristic quantity corresponding to the digital signal;
determining the existence probability of the communication signal according to the second signal characteristic quantity;
if the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal;
and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
Further, a signal modulation scheme corresponding to the communication signal is identified based on:
determining a time domain characteristic parameter and a frequency domain characteristic parameter corresponding to the communication signal;
determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal;
determining a high-order cumulant corresponding to the communication signal;
and determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
Further, the acquiring a sound signal and converting the sound signal into a corresponding digital signal includes:
converting the sound signal into an electrical signal;
amplifying the electric signal, and filtering the amplified electric signal to obtain an analog signal corresponding to the electric signal;
converting an analog signal corresponding to the electrical signal into the digital signal.
An embodiment of the present application further provides a processing apparatus for a sound signal, where the processing apparatus includes:
the acquisition module is used for acquiring a sound signal and converting the sound signal into a corresponding digital signal;
the judging module is used for judging whether a communication signal exists in the digital signal or not, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal;
the identification module is used for identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity;
and the storage module is used for storing the communication signal according to the signal modulation mode.
Further, the determining module is further configured to:
determining a plurality of sampled data points in the digital signal;
analyzing each sampling data point, and determining a second signal characteristic quantity corresponding to the digital signal;
determining the existence probability of the communication signal according to the second signal characteristic quantity;
if the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal;
and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
Further, the identification module is further configured to:
determining a time domain characteristic parameter and a frequency domain characteristic parameter corresponding to the communication signal;
determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal;
determining a high-order cumulant corresponding to the communication signal;
and determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
An embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of the method of processing sound signals as described above.
Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the steps of the sound signal processing method as described above.
The present application provides a processing method, a processing device, and an electronic device for processing a voice signal, wherein the method comprises determining a collected voice signal, retaining the voice signal including an effective communication signal, determining a communication signal from the voice signal, automatically identifying the communication signal, obtaining a modulation scheme corresponding to the communication signal, and further classifying and storing the communication signal according to the modulation scheme. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart illustrating a method for processing a sound signal according to an embodiment of the present application;
fig. 2 is a flowchart illustrating another sound signal processing method provided by an embodiment of the present application;
fig. 3 is a flowchart illustrating another sound signal processing method provided by an embodiment of the present application;
fig. 4 is a flowchart illustrating another sound signal processing method provided by an embodiment of the present application;
fig. 5 is a schematic structural diagram illustrating an apparatus for processing an acoustic signal according to an embodiment of the present application;
fig. 6 shows a second schematic structural diagram of an apparatus for processing an audio signal according to an embodiment of the present application;
fig. 7 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.
First, an application scenario to which the present application is applicable will be described. The method and the device can be applied to the technical field of data processing.
Research shows that at present, after a self-contained submerged buoy system starts to work, some useless ocean noise information can be collected and stored in a storage system, the storage capacity of the self-contained submerged buoy system and underwater portable energy are limited, the occupation of the invalid information on the storage capacity and the equipment power consumption seriously influences the collection and storage work of the valid information, the underwater operation time of the equipment is shortened, collected sound signals need manual analysis, and the processing efficiency is low.
Based on this, an embodiment of the present application provides a processing method, a processing apparatus, and an electronic device for a sound signal, by determining a collected sound signal, retaining the sound signal including an effective communication signal, determining a communication signal from the sound signal, then automatically identifying the communication signal, obtaining a modulation method corresponding to the communication signal, and further classifying and storing the communication signal according to the modulation method. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for processing an audio signal according to an embodiment of the present disclosure. As shown in fig. 1, a method for processing a sound signal provided in an embodiment of the present application is applied to processing a sound signal in a marine environment, and includes:
s101, acquiring a sound signal, and converting the sound signal into a corresponding digital signal.
In the step, sound signals in the marine environment are collected and converted into digital signals which can be analyzed, processed and stored.
Here, in a natural marine environment, the collected sound signals include a marine environment noise signal and an underwater sound signal.
As one possible embodiment, a hydrophone is used to receive acoustic signals in a marine environment. The marine environmental noise is an interference background field in an underwater acoustic channel, and is all noises except self noise received by hydrophones in the sea, including marine noise, biological noise, seismic noise, rain noise, artificial noise (noise of navigation, industry, drilling and the like) and the like. In marine environmental noise, the noise source is wide, and the noise source has both a natural sound source and an artificial sound source; different sound source fields produce noise of different frequencies and levels, and noise of the same frequency range may be produced by one or more sound sources.
Therefore, the collected sound signals in the marine environment comprise the marine environment noise signals and the underwater sound signals, and the collected sound signals are converted into digital signals after being processed, so that the subsequent processing and storage are facilitated.
S102, judging whether a communication signal exists in the digital signal, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal.
In the step, whether a communication signal required by a researcher exists in the digital signal converted from the sound signal is judged, if the judgment result is that the communication signal exists in the digital signal, the fact that the communication signal required by the researcher exists in the sound signal corresponding to the sound signal is indicated, the sound model needs to be reserved, the communication signal is extracted from the digital signal, and the communication signal is analyzed and processed to obtain a first signal characteristic quantity corresponding to the communication signal.
Here, the first signal characteristic amount includes a time domain characteristic parameter, a frequency domain characteristic parameter, and a high-order cumulative amount corresponding to the communication signal. In one possible implementation, the time domain characteristic parameters corresponding to the communication signal include dimensional characteristic parameters and dimensionless characteristic parameters, where the dimensional characteristic parameters include: peak, mean, root mean square or significant, variance, etc.; the dimensionless feature parameters include: peak factor, kurtosis index, form factor, pulse index, margin coefficient, skewness, and the like. The frequency domain characteristic parameters corresponding to the communication signals are obtained by performing Fourier series and Fourier transform calculation on the time domain signals, and preferably performing Fast Fourier Transform (FFT) calculation.
Thus, by acquiring the time domain characteristic parameters and the frequency domain characteristic parameters of the communication signals, the communication signals can be first classified between classes according to different Modulation classes, and the communication signals can be identified to obtain a plurality of Modulation signal classes such as Frequency Shift Keying (FSK) signals, Quadrature Amplitude Modulation (QAM) signals, Phase Shift Keying (PSK) signals, and the like.
And S103, identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity.
In this step, the communication signal is specifically identified within the modulation category according to the first signal characteristic quantity corresponding to the communication signal determined in step S102, so as to obtain a specific communication signal modulation scheme.
Here, the specific communication signal modulation method includes: a plurality of specific modulation methods such as Binary frequency Shift Keying (2 FSK), quaternary frequency Shift Keying (4 FSK), octal frequency Shift Keying (8 FSK), Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), and octal Phase Shift Keying (8 PSK).
The identification Process may be performed by a Digital Signal Processing (DSP) circuit.
Therefore, the communication signal is accurately identified, the specific modulation mode of the communication signal can be automatically determined, the manual analysis of researchers after the communication signal is obtained is avoided, and the efficiency of sound signal processing is improved.
And S104, storing the communication signal according to the signal modulation mode.
In this step, the communication signal identified in step S103 is stored in accordance with the modulation scheme corresponding thereto.
Wherein the communication signal is optionally stored in a secure digital card.
In one possible implementation, the communication signal stored in the secure digital card may be output through a Universal Serial Bus (USB) interface circuit.
Therefore, the communication signals are stored according to the corresponding debugging mode, and the communication signals can be conveniently read by researchers.
According to the processing method of the sound signal, the collected sound signal is judged, the sound signal containing the effective communication signal is reserved, the communication signal is determined from the sound signal, then the communication signal is automatically identified, the modulation mode corresponding to the communication signal is obtained, and the communication signal is further classified and stored according to the modulation mode. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
Referring to fig. 2, fig. 2 is a flowchart illustrating another sound signal processing method according to an embodiment of the present application. As shown in fig. 2, a method for processing a sound signal provided in an embodiment of the present application includes:
s201, acquiring a sound signal, and converting the sound signal into a corresponding digital signal.
S202, judging whether a communication signal exists in the digital signal or not, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal.
S203, if the communication signal does not exist in the digital signal, determining that the digital signal is a noise signal.
In this step, if the result obtained by the judgment is that no communication signal exists in the numerical signal, it is determined that the sound signal only contains a noise signal.
In one possible embodiment, the determination of whether the digital signal contains a communication signal is based on the following method:
a plurality of sampled data points in the digital signal is determined.
The position and the number of the sampling data points can be selected according to needs, and are not particularly limited herein, and 1024 sampling data points can be optionally collected.
And analyzing each sampling data point to determine a second signal characteristic quantity corresponding to the digital signal.
In this step, the acquired sampling data point is analyzed to obtain a second signal characteristic quantity corresponding to the digital signal.
Wherein the second signal characteristic quantity includes: main frequency band bandwidth, main frequency band signal-to-noise ratio, signal pulse width, and the like. The main frequency band bandwidth and the main frequency band signal-to-noise ratio are obtained through fast FFT calculation, and the signal pulse width is obtained through time domain analysis calculation of the digital signal.
And determining the existence probability of the communication signal according to the second signal characteristic quantity.
In the step, the existence probability of the communication signal is determined according to the corresponding relation among the existence probabilities of the communication signal based on the characteristic parameters of the digital signal such as the main frequency band bandwidth, the main frequency band signal-to-noise ratio and the signal pulse width.
If the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal; and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
In the step, the existence probability of the communication signal is compared with a preset probability threshold, if the existence probability value of the communication signal is smaller than the preset probability threshold, the probability that the communication signal exists in the digital signal is too small and can be ignored, and the digital signal can be determined as a noise signal only having marine environmental noise; conversely, if the probability value of the existence of the communication signal is greater than the preset probability threshold, the existence of the communication signal in the digital signal is indicated.
The size of the preset probability threshold may be set according to needs, and is not limited specifically here.
Therefore, the collected sound signals are judged, the sound information which does not contain the communication information required by the researcher is screened out, the sound information is determined as the noise information and is not stored, the storage space of the equipment is saved, and meanwhile, the efficiency of processing the sound signals is improved.
And S204, deleting the noise signal.
And S205, identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity.
And S206, storing the communication signal according to the signal modulation mode.
The descriptions of S201 to S202 and S205 to S206 may refer to the descriptions of S102 to S104, and the same technical effects can be achieved, which are not described in detail herein.
Referring to fig. 3, fig. 3 is a flowchart illustrating another sound signal processing method according to an embodiment of the present application. As shown in fig. 3, a method for processing a sound signal provided in an embodiment of the present application includes:
s301, determining time domain characteristic parameters and frequency domain characteristic parameters corresponding to the communication signals.
In the step, frequency domain characteristic parameters of the communication signals are extracted through a fast FFT method, and time domain characteristic analysis is carried out on the communication signals to obtain time domain characteristic parameters of the communication signals.
Optionally, the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal include: signal spectral characteristics, signal instantaneous amplitude, phase, frequency, etc.
S302, determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal.
In this step, inter-class identification is performed on the communication signal between signal modulation classes according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal.
Here, the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal are used as a classification basis, before the classification operation is started, a sample training parameter set is constructed, the sample training parameter set is trained to generate a decision threshold value, so as to construct a modulation class classifier, and the modulation class of the communication information is classified.
In another possible implementation manner, the time domain characteristic parameters and the frequency domain characteristic parameters corresponding to the acquired communication information are compared with the corresponding characteristic parameters of the modulation templates in the preset modulation type set, so as to determine the modulation type corresponding to the communication information.
Wherein the modulation categories include: ASK signals, FSK signals, PSK signals, QAM signals, and the like.
And S303, determining the high-order cumulant corresponding to the communication signal.
In this step, in order to specifically identify the modulation type corresponding to the communication information in the class, that is, to identify the modulation order, it is first necessary to determine a high-order cumulative amount corresponding to the communication signal.
Before calculating the high-order cumulant corresponding to the communication signal, calculating the high-order moment corresponding to the communication signal, and determining the high-order cumulant corresponding to the communication signal according to the high-order moment corresponding to the communication signal.
And S304, determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
In the step, the communication signals are subdivided by using the high-order cumulant corresponding to the communication signals, and a specific modulation mode corresponding to the communication signals in the signal modulation category is obtained.
Wherein, the modulation mode includes: 2FSK, 4FSK, 8FSK, BPSK, QPSK, 8PSK, 16QAM, 64QAM, etc.
Here, the specific calculation steps are: carrying out down-conversion processing on the communication signal to obtain a baseband modulation signal corresponding to the communication signal; determining high-order cumulant corresponding to the baseband modulation signal, and calculating characteristic parameters corresponding to a modulation mode; and determining a modulation mode corresponding to the baseband modulation signal based on different characteristic parameters corresponding to different modulation modes, and further determining a modulation mode corresponding to the communication information.
Therefore, the communication information is subdivided according to the specific modulation mode, the workload of researchers is reduced, and the processing efficiency of the sound signal is improved.
Referring to fig. 4, fig. 4 is a flowchart illustrating another sound signal processing method according to an embodiment of the present application. As shown in fig. 4, a method for processing a sound signal provided in an embodiment of the present application, for converting the sound signal into a corresponding digital signal, includes:
s401, converting the sound signal into an electric signal.
Here, the hydrophone is used to convert the collected marine sound information in the natural environment into electrical signals that can be processed and stored.
S402, amplifying the electric signal, and filtering the amplified electric signal to obtain an analog signal corresponding to the electric signal.
In this step, the electric signal determined in step S401 is amplified and filtered, and the electric signal is converted into an analog signal.
Here, since the electrical signal converted by the hydrophone is too weak to be directly processed by the electronic device, the electrical signal needs to be amplified so as to be normally processed by the electronic device, and the amplified point signal is filtered by a filter circuit as necessary to be adjusted to an analog signal having a specific frequency.
And S403, converting the analog signal corresponding to the electric signal into the digital signal.
In this step, optionally, an Analog to Digital Converter (ADC) is used to convert the Analog signal obtained after filtering into a Digital signal.
According to the processing method of the sound signal, the collected sound signal is judged, the sound signal containing the effective communication signal is reserved, the communication signal is determined from the sound signal, then the communication signal is automatically identified, the modulation mode corresponding to the communication signal is obtained, and the communication signal is further classified and stored according to the modulation mode. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
Referring to fig. 5 and 6, fig. 5 shows a first schematic structural diagram of a processing apparatus for audio signals according to an embodiment of the present application, and fig. 6 shows a second schematic structural diagram of the processing apparatus for audio signals according to the embodiment of the present application. As shown in fig. 5, the processing apparatus 500 of the sound signal includes:
the obtaining module 510 is configured to obtain a sound signal and convert the sound signal into a corresponding digital signal.
The determining module 520 is configured to determine whether a communication signal exists in the digital signal, and if the communication signal exists in the digital signal, determine the communication signal and a first signal characteristic quantity corresponding to the communication signal.
An identifying module 530, configured to identify, according to the first signal characteristic quantity, a signal modulation scheme corresponding to the communication signal.
A storage module 540, configured to store the communication signal according to the signal modulation scheme.
Further, the determining module 520 is further configured to:
determining a plurality of sampled data points in the digital signal;
analyzing each sampling data point, and determining a second signal characteristic quantity corresponding to the digital signal;
determining the existence probability of the communication signal according to the second signal characteristic quantity;
if the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal;
and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
Further, the identifying module 530 is further configured to:
determining a time domain characteristic parameter and a frequency domain characteristic parameter corresponding to the communication signal;
determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal;
determining a high-order cumulant corresponding to the communication signal;
and determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
Further, the obtaining module 510 is further configured to:
converting the sound signal into an electrical signal;
amplifying the electric signal, and filtering the amplified electric signal to obtain an analog signal corresponding to the electric signal;
converting an analog signal corresponding to the electrical signal into the digital signal.
Further, as shown in fig. 6, the processing apparatus 500 further includes a deleting module 550, where the deleting module 550 is configured to:
after judging whether a communication signal exists in the digital signal or not, if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal, and if the communication signal does not exist in the digital signal, determining that the digital signal is a noise signal; the noise signal is deleted.
According to the processing device for the sound signals, the collected sound signals are judged, the sound signals containing effective communication signals are reserved, the communication signals are determined from the sound signals, then the communication signals are automatically identified, the modulation modes corresponding to the communication signals are obtained, and the communication signals are further classified and stored according to the modulation modes. The stored data is guaranteed not to contain noise signals, and the processing efficiency of the sound signals is improved while the storage capacity resources are saved.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 7, the electronic device 700 includes a processor 710, a memory 720, and a bus 730.
The memory 720 stores machine-readable instructions executable by the processor 710, when the electronic device 700 runs, the processor 710 communicates with the memory 720 through the bus 730, and when the machine-readable instructions are executed by the processor 710, the steps of the method for processing a sound signal in the method embodiments shown in fig. 1 to 4 may be performed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for processing a sound signal in the method embodiments shown in fig. 1 to 4 may be executed.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for processing a sound signal, the method comprising:
acquiring a sound signal, and converting the sound signal into a corresponding digital signal;
judging whether a communication signal exists in the digital signal, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal;
identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity;
and storing the communication signal according to the signal modulation mode.
2. The method of claim 1, wherein after determining whether a communication signal is present in the digital signal and determining the communication signal and a first signal characteristic corresponding to the communication signal if the communication signal is present in the digital signal, the processing method further comprises:
if the communication signal does not exist in the digital signal, determining the digital signal as a noise signal;
the noise signal is deleted.
3. The processing method of claim 1, wherein determining whether the communication signal is present in the digital signal is based on:
determining a plurality of sampled data points in the digital signal;
analyzing each sampling data point, and determining a second signal characteristic quantity corresponding to the digital signal;
determining the existence probability of the communication signal according to the second signal characteristic quantity;
if the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal;
and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
4. The processing method of claim 1, wherein the signal modulation scheme corresponding to the communication signal is identified based on:
determining a time domain characteristic parameter and a frequency domain characteristic parameter corresponding to the communication signal;
determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal;
determining a high-order cumulant corresponding to the communication signal;
and determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
5. The processing method of claim 1, wherein the obtaining a sound signal and converting the sound signal into a corresponding digital signal comprises:
converting the sound signal into an electrical signal;
amplifying the electric signal, and filtering the amplified electric signal to obtain an analog signal corresponding to the electric signal;
converting an analog signal corresponding to the electrical signal into the digital signal.
6. A processing apparatus of a sound signal, characterized in that the processing apparatus comprises:
the acquisition module is used for acquiring a sound signal and converting the sound signal into a corresponding digital signal;
the judging module is used for judging whether a communication signal exists in the digital signal or not, and if the communication signal exists in the digital signal, determining the communication signal and a first signal characteristic quantity corresponding to the communication signal;
the identification module is used for identifying a signal modulation mode corresponding to the communication signal according to the first signal characteristic quantity;
and the storage module is used for storing the communication signal according to the signal modulation mode.
7. The processing apparatus as claimed in claim 6, wherein the determining module is further configured to:
determining a plurality of sampled data points in the digital signal;
analyzing each sampling data point, and determining a second signal characteristic quantity corresponding to the digital signal;
determining the existence probability of the communication signal according to the second signal characteristic quantity;
if the existence probability of the communication signal is greater than a preset probability threshold, determining that the communication signal exists in the digital signal;
and if the existence probability of the communication signal is smaller than a preset probability threshold, determining that the communication signal does not exist in the digital signal.
8. The processing apparatus as in claim 6, wherein the identification module is further configured to:
determining a time domain characteristic parameter and a frequency domain characteristic parameter corresponding to the communication signal;
determining a signal modulation category corresponding to the communication signal according to the time domain characteristic parameter and the frequency domain characteristic parameter corresponding to the communication signal;
determining a high-order cumulant corresponding to the communication signal;
and determining a signal modulation mode corresponding to the signal modulation type according to the high-order cumulant.
9. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of the method of processing sound signals according to any one of claims 1 to 5.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, performs the steps of the method of processing a sound signal according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110107866.2A CN112929096B (en) | 2021-01-27 | 2021-01-27 | Sound signal processing method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110107866.2A CN112929096B (en) | 2021-01-27 | 2021-01-27 | Sound signal processing method and device and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112929096A true CN112929096A (en) | 2021-06-08 |
| CN112929096B CN112929096B (en) | 2022-07-12 |
Family
ID=76166634
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110107866.2A Active CN112929096B (en) | 2021-01-27 | 2021-01-27 | Sound signal processing method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112929096B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114089033A (en) * | 2022-01-24 | 2022-02-25 | 天津安力信通讯科技有限公司 | Abnormal signal detection method and system based on spectrum analysis |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4845707A (en) * | 1988-02-29 | 1989-07-04 | Motorola, Inc. | Frequency division multiplex/FM modulation recognition system |
| CN103067330A (en) * | 2012-12-14 | 2013-04-24 | 北京大学 | Dynamic reconfigurable under water acoustics modulator-demodulator and communication method thereof |
| WO2016180410A1 (en) * | 2015-05-13 | 2016-11-17 | Ls Telcom Ag | Method and device for automatic classification of the modulation format of a digitally modulated signal |
| CN107527615A (en) * | 2017-09-13 | 2017-12-29 | 联想(北京)有限公司 | Information processing method, device, equipment, system and server |
| CN108134753A (en) * | 2016-12-01 | 2018-06-08 | 南京理工大学 | The recognition methods of broadband signal modulation system |
| CN108243130A (en) * | 2018-01-10 | 2018-07-03 | 四川阵风科技有限公司 | Demodulation method, device, spectrum detector and computer readable storage medium |
| CN108257610A (en) * | 2016-12-27 | 2018-07-06 | 乐视汽车（北京）有限公司 | A kind of vehicle device and corresponding voice transmission method and system |
| CN109088611A (en) * | 2018-09-28 | 2018-12-25 | 咪付（广西）网络技术有限公司 | A kind of auto gain control method and device of acoustic communication system |
| CN109709851A (en) * | 2018-12-25 | 2019-05-03 | 北京无线电计量测试研究所 | A kind of complex modulated signal high speed generating means and method |
| CN109787929A (en) * | 2019-02-20 | 2019-05-21 | 深圳市宝链人工智能科技有限公司 | Signal modulate method, electronic device and computer readable storage medium |
| CN111800359A (en) * | 2020-09-07 | 2020-10-20 | 中国人民解放军国防科技大学 | Method, device, equipment and medium for identifying communication signal modulation mode |
-
2021
- 2021-01-27 CN CN202110107866.2A patent/CN112929096B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4845707A (en) * | 1988-02-29 | 1989-07-04 | Motorola, Inc. | Frequency division multiplex/FM modulation recognition system |
| CN103067330A (en) * | 2012-12-14 | 2013-04-24 | 北京大学 | Dynamic reconfigurable under water acoustics modulator-demodulator and communication method thereof |
| WO2016180410A1 (en) * | 2015-05-13 | 2016-11-17 | Ls Telcom Ag | Method and device for automatic classification of the modulation format of a digitally modulated signal |
| CN108134753A (en) * | 2016-12-01 | 2018-06-08 | 南京理工大学 | The recognition methods of broadband signal modulation system |
| CN108257610A (en) * | 2016-12-27 | 2018-07-06 | 乐视汽车（北京）有限公司 | A kind of vehicle device and corresponding voice transmission method and system |
| CN107527615A (en) * | 2017-09-13 | 2017-12-29 | 联想(北京)有限公司 | Information processing method, device, equipment, system and server |
| CN108243130A (en) * | 2018-01-10 | 2018-07-03 | 四川阵风科技有限公司 | Demodulation method, device, spectrum detector and computer readable storage medium |
| CN109088611A (en) * | 2018-09-28 | 2018-12-25 | 咪付（广西）网络技术有限公司 | A kind of auto gain control method and device of acoustic communication system |
| CN109709851A (en) * | 2018-12-25 | 2019-05-03 | 北京无线电计量测试研究所 | A kind of complex modulated signal high speed generating means and method |
| CN109787929A (en) * | 2019-02-20 | 2019-05-21 | 深圳市宝链人工智能科技有限公司 | Signal modulate method, electronic device and computer readable storage medium |
| CN111800359A (en) * | 2020-09-07 | 2020-10-20 | 中国人民解放军国防科技大学 | Method, device, equipment and medium for identifying communication signal modulation mode |
Non-Patent Citations (2)
| Title |
|---|
| 武玲娟等: "水下声学调制解调器动态可重构数字系统设计与实现", 《北京大学学报(自然科学版)》 * |
| 高文欢: "浅析无线电信号通用解调和调制识别技术", 《中国无线电》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114089033A (en) * | 2022-01-24 | 2022-02-25 | 天津安力信通讯科技有限公司 | Abnormal signal detection method and system based on spectrum analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112929096B (en) | 2022-07-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107068161B (en) | Speech noise reduction method and device based on artificial intelligence and computer equipment | |
| CN105448303B (en) | Voice signal processing method and device | |
| CN112929096B (en) | Sound signal processing method and device and electronic equipment | |
| CN111585662B (en) | Classification identification and parameter estimation method and system for phase modulation signal | |
| CN111222526A (en) | Fishing boat real-time fishing behavior recognition method, device, equipment and storage medium | |
| CN106357575A (en) | Multi-parameter jointly-estimated interference type identification method | |
| CN112069962B (en) | Method for identifying vibration spectrum under strong noise background based on image | |
| CN111967545A (en) | Text detection method and device, electronic equipment and computer storage medium | |
| CN111414832A (en) | Real-time online recognition and classification system based on whale dolphin low-frequency underwater acoustic signals | |
| CN113820333A (en) | Battery pole piece abnormity detection method and device, upper computer and detection system | |
| CN113674763B (en) | Method, system, device and storage medium for identifying whistle by utilizing line spectrum characteristics | |
| Moloney et al. | Autonomous multichannel acoustic recorders on the VENUS ocean observatory | |
| CN116907029A (en) | Method for detecting abnormality of fan in outdoor unit, control device and air conditioner outdoor unit | |
| CN114455042B (en) | Intelligent underwater sound detection system based on underwater glider | |
| Larsson Nordström et al. | Maximum likelihood separation of anthropogenic and wind-generated underwater noise | |
| CN114199305A (en) | Offshore area ecological environment risk monitoring method, device, equipment and storage medium | |
| CN114994650A (en) | Improved propeller rotating speed estimation method | |
| CN117033983B (en) | Unmanned ship self-noise detection and identification method and system | |
| Ambat | Performance evaluation of the DEMON processor for sonar | |
| CN114785414B (en) | Identification method and identification system for external acoustic interference of optical fiber composite submarine cable | |
| CN115329857B (en) | Inland navigation water area grade division method and device, electronic equipment and storage medium | |
| CN113011261B (en) | Sinusoidal signal detection method and device based on graph | |
| CN117992788A (en) | Training method, device and recognition method for intelligent recognition model of edge-end underwater target | |
| CN110850415A (en) | Method for searching for micro-plastic by using shipborne Doppler current meter | |
| CN116705055B (en) | Substation noise monitoring method, system, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |