CN114142948A - Acoustic wave communication method, apparatus and storage medium - Google Patents
Acoustic wave communication method, apparatus and storage medium Download PDFInfo
- Publication number
- CN114142948A CN114142948A CN202111474131.XA CN202111474131A CN114142948A CN 114142948 A CN114142948 A CN 114142948A CN 202111474131 A CN202111474131 A CN 202111474131A CN 114142948 A CN114142948 A CN 114142948A
- Authority
- CN
- China
- Prior art keywords
- signal
- time
- frequency
- sound wave
- pulse signal
- 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
- 238000000034 method Methods 0.000 title claims abstract description 69
- 238000004891 communication Methods 0.000 title claims abstract description 61
- 238000003860 storage Methods 0.000 title claims abstract description 13
- 238000001914 filtration Methods 0.000 claims abstract description 45
- 238000005070 sampling Methods 0.000 claims description 47
- 230000006870 function Effects 0.000 claims description 23
- 230000008859 change Effects 0.000 claims description 14
- 238000012545 processing Methods 0.000 abstract description 18
- 230000005540 biological transmission Effects 0.000 abstract description 15
- 230000009467 reduction Effects 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 7
- 230000002093 peripheral effect Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 230000007423 decrease Effects 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 4
- 230000009466 transformation Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 3
- 238000007476 Maximum Likelihood Methods 0.000 description 2
- 238000012952 Resampling Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000013139 quantization Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000005562 fading Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
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
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0056—Systems characterized by the type of code used
- H04L1/0061—Error detection codes
Abstract
The application relates to a sound wave communication method, equipment and a storage medium, belonging to the technical field of communication, wherein the method comprises the following steps: obtaining a target sound wave signal; carrying out fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal; filtering the pulse signal by using a preset filter to obtain a filtered pulse signal; performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal; determining information data based on the time-frequency signal; the problem that the conventional sound wave communication mode is short in sound wave signal identification distance can be solved, and due to the fact that noise reduction processing is conducted on the target sound wave signal in the fractional Fourier domain, noise signals generated due to multipath attenuation in the transmission process of the sound wave signal can be effectively eliminated, the influence of noise generated by multipath attenuation on sound wave signal identification can be reduced, and therefore the identification distance of the sound wave signal is increased.
Description
[ technical field ] A method for producing a semiconductor device
The application relates to a sound wave communication method, equipment and a storage medium, belonging to the technical field of communication.
[ background of the invention ]
With the development of electronic science and technology, more and more intelligent devices are equipped with audio interfaces, which widens the application scenarios of sound wave communication. The acoustic wave communication means: information data is embedded into the sound wave signal, and the sound wave signal is played and received by using the audio interface to transmit the information data.
The traditional sound wave communication mode comprises the following steps: the sending end modulates information data to be transmitted to obtain a target sound wave signal and plays the target sound wave signal; and the receiving end preprocesses the received target sound wave signal and demodulates the preprocessed signal to obtain information data.
However, as the longer the acoustic wave transmission distance is, the more noise is generated due to multipath attenuation, and the conventional acoustic wave communication method cannot effectively eliminate the noise generated due to multipath attenuation in the process of preprocessing the acoustic wave signal, which results in a problem that the conventional acoustic wave communication method has a short identification distance for the acoustic wave signal.
[ summary of the invention ]
The application provides an acoustic wave communication method, acoustic wave communication equipment and a storage medium, which can solve the problem that the traditional acoustic wave communication mode is short in acoustic wave signal identification distance. The application provides the following technical scheme:
in a first aspect, a method of acoustic wave communication is provided, the method comprising:
acquiring a target sound wave signal, wherein the target sound wave signal is obtained by linear frequency modulation;
performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time bandwidth product of the pulse signal is smaller than a preset threshold value;
filtering the pulse signal by using a preset filter to obtain a filtered pulse signal;
performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal so as to reflect the change condition of the frequency of the time-frequency signal along with time;
information data is determined based on the time-frequency signal.
Optionally, the pulse signal comprises a first pulse signal and a second pulse signal;
the first pulse signal is obtained by performing fractional Fourier transform on the target sound wave signal at a first rotation angle; the first rotation angle is determined according to the signal slope of a first sound wave signal of which the frequency linearly increases in each signal period in the target sound wave signal;
the second pulse signal is obtained by performing fractional Fourier transform on the target sound wave signal at a second rotation angle; the second rotation angle is determined according to the signal slope of the second sound wave signal with the linearly reduced frequency in each signal period in the target sound wave signal.
Optionally, the determining information data based on the time-frequency signal includes:
superposing the time-frequency signal corresponding to the first pulse signal and the time-frequency signal corresponding to the second pulse signal to obtain a superposed time-frequency signal;
and demodulating the superposed time-frequency signal to obtain the information data.
Optionally, the demodulating the superimposed time-frequency signal to obtain the information data includes:
filtering the superposed time-frequency signals by using a preset high-pass filter and a preset low-pass filter to obtain a first superposed time-frequency signal processed by the preset high-pass filter and a second superposed time-frequency signal processed by the preset low-pass filter;
calculating the signal intensity difference between the first superposed time-frequency signal and the second superposed time-frequency signal at different moments;
and determining the information data according to the change condition of the signal intensity difference value in each signal period.
Optionally, before filtering the superimposed time-frequency signal by using a preset high-pass filter and a preset low-pass filter, the method further includes:
down-sampling the superposed time-frequency signal to obtain a down-sampled time-frequency signal;
and determining the initial position of the time-frequency signal after the down-sampling so as to demodulate the time-frequency signal after the down-sampling from the initial position.
Optionally, the filtering the pulse signal by using a preset filter to obtain the noise-reduced pulse signal includes:
filtering the pulse signal by using a preset two-dimensional band-pass filter to obtain a filtered pulse signal, wherein the band-pass width of the two-dimensional band-pass filter is determined according to the bandwidth of the target sound wave signal; and the moving step length of the two-dimensional band-pass filter is determined according to the signal period of the target sound wave signal.
Optionally, the moving step of the two-dimensional band-pass filter is calculated by the following formula:
wherein ,
is the moving step length of the two-dimensional band-pass filter; t issymbolIs the signal period of the target acoustic signal; oc is a rotation angle at the time of fractional Fourier transform;
the band-pass width of the two-dimensional band-pass filter is calculated by the following formula:
Bequivalent＝csc(∝)(FH-FL)+cot(∝)cos(∝)Fs
wherein ,BequivalentIs the band-pass width of the two-dimensional band-pass filter; oc is a rotation angle at the time of fractional Fourier transform; fHIs the maximum frequency of the target acoustic signal; fLIs the minimum frequency of the target acoustic signal; fSIs the sampling rate of the target acoustic signal.
Optionally, the fractional fourier transform is performed on the target acoustic wave signal to obtain a pulse signal corresponding to the target acoustic wave signal, and the pulse signal is represented by the following formula:
wherein s is an object function of discrete fractional Fourier transform; k is a sampling point corresponding to the pulse signal and is also a y-axis component on a discrete fractional Fourier transform domain; oc is a rotation angle at the time of fractional Fourier transform; j is an imaginary number; fsIs the sampling rate of the target acoustic signal; m, calculating the size of the adopted window in each summation; s [ n ]]Sampling the target sound wave signal to obtain a discrete function; n is the number of sample points.
In a second aspect, an electronic device is provided, the device comprising a processor and a memory; the memory has stored therein a program that is loaded and executed by the processor to implement the acoustic wave communication method provided by the first aspect.
In a third aspect, a computer-readable storage medium is provided, in which a program is stored, which when executed by a processor, is configured to implement the acoustic wave communication method provided in the first aspect.
The beneficial effects of this application include at least: obtaining a target sound wave signal; performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time-bandwidth product of the pulse signal is smaller than a preset threshold value; filtering the pulse signal by using a preset filter to obtain a filtered pulse signal; performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal, and obtaining the change condition of the frequency of the time-frequency signal along with time; determining information data based on the time-frequency signal; the problem that the conventional sound wave communication mode is short in sound wave signal identification distance can be solved, and due to the fact that noise reduction processing is conducted on the target sound wave signal in the fractional Fourier domain, noise signals generated due to multipath attenuation in the transmission process of the sound wave signal can be effectively eliminated, the influence of noise generated by multipath attenuation on sound wave signal identification can be reduced, and therefore the identification distance of the sound wave signal is increased.
In addition, because the pulse signals comprise the first pulse signals and the second pulse signals, the first pulse signals and the second pulse signals can be conveniently filtered respectively, the first pulse signals after being filtered mainly comprise the pulse signals corresponding to the first sound wave signals, and the second pulse signals after being filtered mainly comprise the pulse signals corresponding to the second sound wave signals, so that the effect of filtering the pulse signals can be further improved, noise signals generated due to multipath attenuation in the transmission process of the sound wave signals are effectively eliminated, and the identification distance of the sound wave signals is further improved.
In addition, because the information data is determined according to the change condition of the signal intensity difference value in each signal period, the signal type corresponding to the signal in each period can be judged according to a small number of signals in each period, so that the information data is determined, and the identification distance of the sound wave signal is increased.
In addition, the acoustic wave communication method provided by the application can be realized only by improving the software level, and does not involve improving the hardware of the sending end and the receiving end, so that the applicability of the acoustic wave communication method can be improved, and the deployment and the use are convenient.
The foregoing description is only an overview of the technical solutions of the present application, and in order to make the technical solutions of the present application more clear and clear, and to implement the technical solutions according to the content of the description, the following detailed description is made with reference to the preferred embodiments of the present application and the accompanying drawings.
[ description of the drawings ]
Fig. 1 is a schematic structural diagram of an acoustic wave communication system provided in an embodiment of the present application;
FIG. 2 is a flow chart of an acoustic wave communication method provided by one embodiment of the present application;
FIG. 3 is a schematic illustration of a target acoustic signal provided by one embodiment of the present application;
FIG. 4 is a schematic diagram of a pulse signal provided by an embodiment of the present application;
FIG. 5 is a schematic diagram of a two-dimensional bandpass filter provided by an embodiment of the present application;
FIG. 6 is a diagram illustrating a variation of signal strength difference according to an embodiment of the present application;
FIG. 7 is a diagram illustrating a process for calculating a variation of a signal strength difference according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a two-dimensional bandpass filter provided by another embodiment of the present application;
FIG. 9 is a schematic illustration of a sonic communication scenario provided by an embodiment of the present application;
FIG. 10 is a flow chart of an acoustic wave communication method provided by another embodiment of the present application;
FIG. 11 is a block diagram of an acoustic wave communication device provided by one embodiment of the present application;
fig. 12 is a block diagram of an electronic device provided by an embodiment of the application.
[ detailed description ] embodiments
The following detailed description of embodiments of the present application will be made with reference to the accompanying drawings and examples. The following examples are intended to illustrate the present application but are not intended to limit the scope of the present application.
First, a number of terms related to embodiments of the present application will be described.
Chirp, also known as chirp, refers to: a signal whose signal frequency varies linearly in one signal period; the signal with linearly increased frequency in the signal period is positive chirp, and the signal with linearly decreased frequency in the signal period is negative chirp.
Fractional Fourier transform, which means: and rotating the coordinate axis of the time-frequency surface at the angle of the viewing time-frequency surface, and analyzing information from the angle of the viewing frequency domain, wherein the Fourier transform is performed when the rotation angle of the coordinate axis of the time-frequency surface is 90 degrees.
Fig. 1 is an acoustic wave communication system provided in an embodiment of the present application, and the system includes a transmitting end 110 and a receiving end 120.
Optionally, the transmitting end 110 may be a device with a sound wave broadcasting function, such as a mobile phone and a sound device, and the type of the transmitting end 110 is not limited in this embodiment.
In this embodiment, the transmitting end 110 has a function of broadcasting a sound wave signal according to audio data.
Optionally, the audio data may be generated by the sending end 110 according to the information data to be sent, or may also be generated by other devices according to the information data to be sent and transmitted to the sending end 110, and the embodiment does not limit the manner of obtaining the audio data.
In one example, the audio data generated by the audio data transmitting end 110, at this time, the audio data is generated according to the information data, and the method includes: coding the information data to obtain coded information; modulating the coded information to obtain modulated information data; and carrying out quantization resampling and coding on the modulated information data to obtain audio data.
Optionally, the information data may be encoded by a hamming code or a convolutional code, and the method of encoding the information data is not limited in this embodiment.
In this embodiment, modulating the encoded information includes: and modulating the data with the bit of 0 in the coded information into audio data with linearly increased frequency in the signal period, and modulating the data with the bit of 1 into audio data with linearly decreased frequency in the signal period.
The length of the signal period is a preset value, and is pre-stored in the transmitting end 110.
Illustratively, the linear increase in frequency within a signal period refers to: the frequency in the signal period is linearly increased from a first preset frequency to a second preset frequency. The linear reduction of the frequency in the signal period means that: the frequency in the signal period is linearly reduced from the second preset frequency to the first preset frequency.
The first preset frequency and the second preset frequency are preset values, and the first preset frequency is smaller than the second preset frequency.
In other embodiments, the encoded information is modulated, including: the data with bit 0 in the encoded information is modulated into audio data with linearly decreasing frequency in a preset signal period, and the data with bit 1 is modulated into audio data with linearly increasing frequency in the signal period.
In order to raise the frequency of the audio data to the preset frequency range, in this embodiment, after modulating the encoded information, the method further includes: and multiplying the modulated coded information by a preset chord function, and carrying out carrier modulation on the coded information so as to enable the frequency range of the modulated coded information to be a preset frequency range.
Wherein the preset chord function has a stable initial phase.
Optionally, the preset frequency range is a preset value and is stored in the transmitting end 110 in advance. The predetermined frequency range may be greater than or equal to 20kHz, or may be less than 20kHz, and the predetermined frequency range is not limited in this embodiment.
In one example, the predetermined frequency range is a frequency less than 20 kHz.
Optionally, the preset chord function may be a sine function or a cosine function, and the embodiment does not limit the type of the preset chord function.
Optionally, performing quantization resampling and coding on the modulated information data to obtain audio data, including: filtering the modulated information data by using a digital non-recursive (FIR) band-pass filter to obtain filtered information data; and quantizing the filtered audio information by using a preset audio format, sampling and encoding to obtain audio data.
Optionally, the preset audio format is a lossless audio format, where the lossless audio format may be a FLAC format, or may also be a WAV format, and the embodiment does not limit the type of the lossless audio format.
In this embodiment, the receiving end 120 may be a device with sound wave collecting and processing functions, such as a mobile phone, a computer, and an intelligent sound device, and the type of the receiving end 120 is not limited in this embodiment.
In this embodiment, the receiving end 120 is used for acquiring an acoustic wave signal.
Optionally, the acoustic wave signal may be generated by the transmitting end 110, or may be generated by other devices, or may also be a noise signal generated during transmission of the acoustic wave signal, and the embodiment does not limit the type of the acoustic wave signal.
In this embodiment, the receiving end 120 is configured to obtain a target sound wave signal; performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time-bandwidth product of the pulse signal is smaller than a preset threshold value; filtering the pulse signal by using a preset filter to obtain a filtered pulse signal; performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal so as to reflect the change condition of the frequency of the time-frequency signal along with time; information data is determined based on the time-frequency signal.
Wherein, the target sound wave signal is obtained by linear frequency modulation.
Optionally, the receiving end 120 is further configured to perform carrier demodulation on the target acoustic wave signal based on a preset chord function, so as to perform fractional fourier transform on the acoustic wave signal after carrier demodulation.
Wherein, the preset chord function is generated by an oscillator algorithm with a receiving end.
Optionally, determining the information data based on the time-frequency signal comprises: and decoding the time-frequency signal according to the coding mode of the sending end to obtain information data.
In summary, in the acoustic wave communication system provided in this embodiment, the receiving end acquires a target acoustic wave signal; performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time-bandwidth product of the pulse signal is smaller than a preset threshold value; filtering the pulse signal by using a preset filter to obtain a filtered pulse signal; performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal so as to reflect the change condition of the frequency of the time-frequency signal along with time; determining information data based on the time-frequency signal; the problem that the conventional sound wave communication mode is short in sound wave signal identification distance can be solved, and due to the fact that noise reduction processing is conducted on the target sound wave signal in the fractional Fourier domain, noise signals generated due to multipath attenuation in the transmission process of the sound wave signal can be effectively eliminated, the influence of noise generated by multipath attenuation on sound wave signal identification can be reduced, and therefore the identification distance of the sound wave signal is increased.
The following describes the acoustic wave communication method provided in the present application in detail.
Fig. 2 is an acoustic wave communication method according to an embodiment of the present application, and this embodiment takes the application of the method to a receiving end in the acoustic wave communication system shown in fig. 1 as an example for description. The method comprises the following steps:
The target sound wave signal is obtained through linear frequency modulation, and the frequency of the target sound wave signal changes linearly in each signal period.
Optionally, the signal period is a preset value, and is pre-stored in the receiving end.
Optionally, the target acoustic signal is obtained by sampling the acoustic signal in the environment at a preset sampling rate by the receiving end.
The preset sampling rate is a preset value and is stored in the receiving end in advance.
In practical implementation, the sampling rate may be 44.1kHz, 48kHz, 96kHz or 192kHz, and the value of the sampling rate is not limited in this embodiment.
In the present embodiment, the target acoustic wave signal includes at least one signal period, and the frequency of the target acoustic wave signal linearly increases or linearly decreases in each signal period. That is, the target acoustic wave signal includes: a first acoustic signal in which the frequency increases linearly during the signal period, and a second acoustic signal in which the frequency decreases linearly during the signal period.
Referring to FIG. 3, the target acoustic signal includes 0T1、T1～T2 and T2～T3Three signal periods; at 0 to T1 and T2～T3In the two signal periods, the frequency of the target sound wave signal is linearly increased to be a first sound wave signal; at T1～T2This signal period, the frequency of the target acoustic wave signal decreases linearly, being the second acoustic wave signal.
Optionally, the signal slopes of the first acoustic signal are the same, and the signal slopes of the second acoustic signal are the same.
Step 202, performing fractional order fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time bandwidth product of the pulse signal is smaller than a preset threshold value.
The preset threshold is a preset value and is pre-stored in the receiving end.
For better elimination of the noise signal in the target sound wave signal during the filtering process, optionally, the preset threshold is close to 0, so that the pulse signal has small variation in the time dimension.
Because the signal slopes of the first acoustic wave signal and the second acoustic wave signal are different, in order to make the time-bandwidth product of the pulse signal smaller than a preset threshold, fractional order fourier transform needs to be performed on the target acoustic wave signal at different rotation angles respectively when the fractional order fourier transform is performed on the target acoustic wave signal, so as to obtain a corresponding pulse signal.
Optionally, the pulse signal comprises a first pulse signal and a second pulse signal; the first pulse signal is obtained by performing fractional Fourier transform on a target sound wave signal at a first rotation angle; the second pulse signal is obtained by performing fractional Fourier transform on the target sound wave signal at a second rotation angle.
The first rotation angle is determined according to the signal slope of a first sound wave signal of which the frequency linearly increases in each signal period in the target sound wave signal; the second rotation angle is determined according to the signal slope of the second acoustic signal in which the frequency linearly decreases in each signal period in the target acoustic signal.
Optionally, the first rotation angle is an inclination angle corresponding to a slope of the first acoustic wave signal.
In one example, determining the first angle of rotation from the slope of the first acoustic signal is represented by:
A＝arctan(k1)
wherein A is a first rotation angle, k1Is the slope of the first acoustic signal.
Optionally, the slope of the first acoustic wave signal is a preset value, and is stored in the receiving end in advance.
Optionally, the second rotation angle is an inclination angle corresponding to a slope of the second acoustic signal.
In one example, determining the second rotation angle from the slope of the second acoustic signal is represented by:
B＝arctan(k2)
wherein B is a second rotation angle, k2Is the slope of the second acoustic signal.
Optionally, the slope of the second acoustic signal is a preset value, and is pre-stored in the receiving end
Since the first rotation angle is determined according to the slope of the first sound wave signal, in the first pulse signal, the time-bandwidth product of the pulse signal corresponding to the first sound wave signal is smaller than a preset threshold; since the second rotation angle is determined according to the slope of the second acoustic signal, in the second pulse signal, the time-bandwidth product of the pulse signal corresponding to the second acoustic signal is smaller than the preset threshold.
Referring to fig. 4, the left graph in fig. 4 is a first pulse signal, and the right graph in fig. 4 is a second pulse signal.
In one example, the target sound wave signal is subjected to fractional fourier transform to obtain a signal corresponding to the target sound wave information, which is represented by the following formula:
wherein f is an object function of fractional Fourier transform ^ is a y-axis component in a fractional Fourier transform domain; oc is a rotation angle at the time of fractional Fourier transform; t is the time in the fractional Fourier transform domain; f (t) refers to a function in the time domain, i.e., an object that is fractional Fourier transformed; j is an imaginary number.
In another example, the target acoustic wave signal is subjected to fractional fourier transform to obtain a pulse signal corresponding to the target acoustic wave signal, which is represented by the following formula:
wherein s is an object function of discrete fractional Fourier transform; k is a sampling point corresponding to the pulse signal and is a y-axis component on a discrete fractional Fourier transform domain; oc is a rotation angle at the time of fractional Fourier transform; j is an imaginary number; fsIs the sampling rate of the target acoustic signal; m, calculating the size of the adopted window in each summation; s [ n ]]Is a discrete function after sampling of the target acoustic signal; n is the number of sample points.
And 203, filtering the pulse signal by using a preset filter to obtain a filtered pulse signal.
Because the length of the pulse signal on the x-axis component is extremely short, the noise on the x-axis component is not easy to be eliminated by adopting the conventional band-pass filter, and therefore, the pulse signal is not suitable for being filtered by using the conventional band-pass filter. For the characteristic, the method adopts a two-dimensional band-pass filtering method for processing.
Optionally, the filtering the pulse signal by using a preset filter to obtain the noise-reduced pulse signal includes: and filtering the pulse signal by using a preset two-dimensional band-pass filter to obtain the pulse signal subjected to noise reduction.
The band-pass width of the two-dimensional band-pass filter is determined according to the bandwidth of the target sound wave signal; the moving step length of the two-dimensional band-pass filter is determined according to the signal period of the target sound wave signal.
Wherein, the moving step length of the two-dimensional band-pass filter is as follows: the distance a two-dimensional band-pass filter moves at one time during the filtering process. Since the pulse signal is filtered using the two-dimensional band-pass filter in the fractional fourier domain, the moving step of the two-dimensional band-pass filter is equal to the signal spacing in the fractional fourier domain.
Referring to the two-dimensional band-pass filter shown in fig. 5, a white portion is a band-pass portion, and a black portion is a band-stop portion; the width of the white part in the vertical direction is the band-pass width of the two-dimensional band-pass filter; the length of the white portion in the horizontal direction is a preset empirical value.
Alternatively, the step size of the two-dimensional band-pass filter is calculated by the following formula:
wherein ,
the moving step length of the two-dimensional band-pass filter is obtained; t issymbolIs the signal period of the target acoustic signal; oc is a rotation angle at the time of fractional fourier transform.
Alternatively, the band-pass width of the two-dimensional band-pass filter is calculated by:
Bequivalent＝csc(∝)(FH-FL)+cot(∝)cos(∝)Fs
wherein ,BeguivalentIs the bandpass width of the two-dimensional bandpass filter; oc is a rotation angle at the time of fractional Fourier transform; fHIs the maximum frequency of the target acoustic signal; fLIs the minimum frequency of the target acoustic signal; fsIs the sampling rate of the target acoustic signal.
Alternatively, the maximum frequency and the minimum frequency of the target acoustic wave signal are preset values and are stored in the receiving end in advance.
In one example, the maximum frequency and the minimum frequency of the target acoustic wave signal are determined according to a preset frequency range.
Optionally, the preset two-dimensional band-pass filter is obtained by raised cosine function shaping.
In one example, the filtering processing is performed on the pulse signal by using a preset two-dimensional band-pass filter, so as to obtain a noise-reduced pulse signal, including: determining an initial filtering position; the pulse signal is filtered starting from the initial filtering position.
Optionally, determining an initial filtering position comprises: and sliding a two-dimensional band-pass filter on a time axis for a preset time length, calculating the signal intensity of the two-dimensional band-pass filter at different moments in the preset time length, and determining the position with the strongest filtered signal intensity as an initial filtering position.
In one example, the preset duration is equal to one signal period.
To avoid errors caused by sampling, in another example, the preset duration is equal to the sum of the signal period and an error parameter, and the error parameter is determined according to the sampling rate.
Optionally, the filtering the pulse signal from the initial filtering position includes: starting from the initial position, the signals which do not pass through the two-dimensional band-pass filter are filtered out by sliding in the time axis direction by a moving step.
Because the pulse signal includes the first pulse signal and the second pulse signal, correspondingly, use the predetermined filter to carry out filtering processing to the pulse signal, obtain the pulse signal after the filtration, include: filtering the first pulse signal by using a preset filter to obtain a filtered first pulse signal; and processing the second pulse signal by using a preset filter to obtain a filtered second pulse signal.
And 204, performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal so as to reflect the change condition of the frequency of the time-frequency signal along with time.
Because the pulse signal includes the first pulse signal and the second pulse signal, correspondingly, the inverse fractional order fourier transform is performed on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal, including: performing inverse fractional Fourier transform on the filtered first pulse signal to obtain a time-frequency signal corresponding to the filtered first pulse signal; and performing inverse fractional Fourier transform on the filtered second pulse signal to obtain a time-frequency signal corresponding to the filtered second pulse signal.
Optionally, performing inverse fractional fourier transform on the filtered first pulse signal to obtain a time-frequency signal corresponding to the filtered first pulse signal, including: and performing inverse fractional Fourier transform on the filtered first pulse signal by a third rotation angle to obtain a time-frequency signal corresponding to the filtered first pulse signal.
Wherein the third rotation angle is opposite to the first rotation angle.
Optionally, performing inverse fractional fourier transform on the filtered second pulse signal to obtain a time-frequency signal corresponding to the filtered second pulse signal, including: to the filtered second pulse signal by0A time-frequency signal.
Wherein the fourth rotation angle is opposite to the second rotation angle.
Optionally, determining the information data based on the time-frequency signal includes: superposing the time-frequency signal corresponding to the first pulse signal and the time-frequency signal corresponding to the second pulse signal to obtain a superposed time-frequency signal; and demodulating the superposed time-frequency signal to obtain information data.
Optionally, demodulating the superimposed time-frequency signal to obtain information data, including: filtering the superposed time-frequency signals by using a preset high-pass filter and a preset low-pass filter to obtain a first superposed time-frequency signal processed by the preset high-pass filter and a second superposed time-frequency signal processed by the preset low-pass filter; calculating the signal intensity difference between the first superposed time-frequency signal and the second superposed time-frequency signal at different moments; and determining the information data according to the change condition of the signal intensity difference in each signal period.
In order to ensure phase synchronization of the outputs of the high-pass filter and the low-pass filter, the high-pass filter and the low-pass filter use the same window function and the same order.
Referring to fig. 6, in one example, the signal strength is represented in a logarithmic form, and the variation of the signal strength difference in each signal period is as shown in fig. 6.
Optionally, determining the information data according to a variation of the signal strength difference in each signal period includes: and dividing the signal period into three parts, wherein the time length of the first part is equal to the time length of the last part, and judging the signal type of each period according to the difference between the average value of the energy intensity difference values at all times in the first part of the signal period and the average value of the energy intensity difference values at all times in the last part of the signal period to obtain information data.
Wherein the signal type is a first sound wave signal or a second sound wave signal.
Referring to FIG. 7, in one example, θ [ n ]]For superimposed time-frequency signals, Hn]Is theta [ n ]]The signal filtered by the predetermined high-pass filter, i.e. the first superimposed time-frequency signal, Ln]Is theta [ n ]]The signal filtered by the predetermined low-pass filter, i.e. the second superimposed time-frequency signal, E { H [ n: n + epsilon]Is the energy of the sampled fraction in the high-pass filtered signal, E { L [ n: n + ε }]And is the energy of the sampled segment in the low-pass filtered signal, where ε is the length of the sampled segment. DM [ p ]i]For the variation of the signal strength difference in the ith signal period, in which p is inputiIs the initial position of the i-th signal period. η is the offset of the start position of the last part relative to the start position of the first part after dividing a signal period into three parts.
Optionally, the length epsilon of the sampling segment is less than the duration of the last portion.
In one example, the length of a sampling segment is one twentieth of the signal period.
In one example, the initial position of the ith signal period is calculated by:
pi＝p0+Tsymbol
wherein ,piThe initial position of the ith signal period; p is a radical of0The initial position of the superposed time frequency signal is obtained; t issymbolIs the signal period of the target acoustic signal.
In one example, after dividing a signal cycle into three parts, the offset of the starting position of the last part relative to the starting position of the first part is calculated by the following formula:
wherein, eta is the offset of the initial position of the last part relative to the initial position of the first part after dividing a signal period into three parts; f. ofHSetting the cut-off frequency of the high-pass filter; b is the bandwidth of the target sound wave signal; t issymbolIs the signal period of the target acoustic signal.
In one example, the bandwidth of the pre-set low-pass filter is calculated by:
fL＝B-fH
wherein ,fLA cutoff frequency of a low-pass filter is preset; b is the bandwidth of the target sound wave signal; f. ofHThe high pass filter cut-off frequency is preset.
In one example, the variation of the signal strength difference over the ith signal period is calculated by:
wherein, DM [ pi]The variation condition of the signal intensity difference value in the ith signal period is obtained; i is the signal periodicity in the superposed time-frequency signal; p is a radical ofiThe starting position of each signal period; eta is the offset of the initial position of the last part relative to the initial position of the first part after a signal period is divided into three parts; e is the length of the sampling segment; h is the signal after high-pass filtering; l is the signal after low-pass filtering; theta is the time-frequency signal after superposition; h isHAn equation for presetting a high-pass filter; h isLAn equation for presetting a low-pass filter; e {. for computing signalsThe intensity of the energy.
In order to ensure the accuracy of the demodulated information data, the method for judging the signal type of each period according to the difference between the average value of the energy intensity difference values of all the moments in the first part and the average value of the energy intensity difference values of all the moments in the last part of the signal period comprises the following steps: calculating the absolute value of the difference between the average value of the energy intensity difference values at all times in the first part of the signal period and the average value of the energy intensity difference values at all times in the last part of the signal period, and judging the type of the signal according to the difference between the average value of the energy intensity difference values at all times in the first part of the signal period and the average value of the energy intensity difference values at all times in the last part of the signal period under the condition that the absolute value is greater than or equal to a preset difference threshold; and in the case that the absolute value is smaller than the preset difference threshold value, abandoning the signal data.
Optionally, the manner of determining the signal type of each period may be soft decision, or may also be hard decision, and this embodiment does not limit the determination manner of the signal type.
In one example, a decoder using a Maximum Likelihood (MLE) algorithm determines the signal type for each period.
Optionally, before filtering the superimposed time-frequency signal by using a preset high-pass filter and a preset low-pass filter, the method further includes: down-sampling the superposed time-frequency signals to obtain down-sampled time-frequency signals; and determining the initial position of the time-frequency signal after the down-sampling so as to demodulate the time-frequency signal after the down-sampling from the initial position.
In one example, the down-sampling process takes one sample from every 20 samples, and correspondingly, the sampling rate is decreased from 48kHz to 2.4 kHz.
Optionally, the start position of the down-sampled time-frequency signal is represented by an order of occurrence of the first acoustic signal and/or the second acoustic signal in the down-sampled time-frequency signal.
For example, two consecutive first target acoustic signals are used as the start positions of the time-frequency signals to be sampled.
Optionally, determining a start position of the down-sampled time-frequency signal includes: performing fractional Fourier transform on the time frequency signal subjected to the down sampling to obtain a pulse signal subjected to the down sampling corresponding to the time frequency signal subjected to the down sampling; sliding along a time axis by using a preset two-dimensional band-pass filter to determine the initial position of the pulse signal after down sampling; and determining the initial position of the time-frequency signal after the down-sampling according to the initial position of the pulse signal after the down-sampling.
For example, taking two consecutive first target acoustic signals as the start positions of the time-frequency signals to be sampled, and determining the start positions of the time-frequency signals to be down-sampled at this time includes: carrying out fractional Fourier transform on the time frequency signal subjected to the down sampling according to a first rotation angle to obtain a first pulse signal subjected to the down sampling corresponding to the time frequency signal subjected to the down sampling; sliding along a time axis by using a preset two-dimensional band-pass filter to determine the positions of pulse signals corresponding to two continuous first target sound signals in the first pulse signals after down sampling; and determining the positions of the two continuous first target sound wave signals in the down-sampled time-frequency signals according to the positions of the pulse signals corresponding to the two continuous first target sound wave signals in the down-sampled first pulse signals.
Meanwhile, in order to facilitate finding the positions of the pulse signals corresponding to the two continuous first target sound wave signals, the preset two-dimensional band-pass filter is shown in fig. 8, the white area is a band-pass area, the interval between the two band-pass areas is the signal interval in the fractional order fourier domain, that is, the moving step length of the two-dimensional band-pass filter, and whether the current position is the signal head position or not can be judged by calculating the energy intensity of the signals passing through the two band-pass areas.
In order to better explain the acoustic wave communication method provided by the present invention, an example is given below for explanation.
Referring to the sound wave communication scenario shown in fig. 9, the receiving end is respectively placed at positions 15 meters, 35 meters, 40 meters, 50 meters, 60 meters and 70 meters away from the transmitting end to receive the sound wave signals broadcast by the transmitting end, and the sound wave communication method provided by the present application is used to process the sound wave signals to obtain information data, where the test conditions and results are shown in table 1 below:
table 1 transmission success rate under different conditions
The first receiving end and the second receiving end are different receiving ends; 10bps and 20bps indicate transmission speeds of information data.
According to the test results, the sound wave communication method can realize long-distance information transmission, can still have high transmission success rate when the distance between the transmitting end and the receiving end is 70 meters, and particularly has good long-distance communication effect when the transmission speed is low.
Meanwhile, if the convolutional code is used for coding the information data at the sending end, the soft decision is used for demodulating the target sound wave signal at the receiving end, and the transmission success rate in long-distance communication can be further improved.
Experiments prove that the sound wave communication method provided by the application has the obvious effect of resisting the multipath fading channel interference by carrying out noise reduction on the target sound wave signal in the fractional Fourier domain and demodulating the noise-reduced sound wave signal by adopting matched signal demodulation. In practical tests, the sound wave communication of the invention has robustness on Doppler frequency shift of signals generated by low-speed moving targets such as pedestrians, carts and the like.
In summary, the acoustic wave communication method provided by the present embodiment obtains the target acoustic wave signal; performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time-bandwidth product of the pulse signal is smaller than a preset threshold value; filtering the pulse signal by using a preset filter to obtain a filtered pulse signal; performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal, and obtaining the change condition of the frequency of the time-frequency signal along with time; determining information data based on the time-frequency signal; the problem that the conventional sound wave communication mode is short in sound wave signal identification distance can be solved, and due to the fact that noise reduction processing is conducted on the target sound wave signal in the fractional Fourier domain, noise signals generated due to multipath attenuation in the transmission process of the sound wave signal can be effectively eliminated, the influence of noise generated by multipath attenuation on sound wave signal identification can be reduced, and therefore the identification distance of the sound wave signal is increased.
In addition, because the pulse signals comprise the first pulse signals and the second pulse signals, the first pulse signals and the second pulse signals can be conveniently filtered respectively, the first pulse signals after being filtered mainly comprise the pulse signals corresponding to the first sound wave signals, and the second pulse signals after being filtered mainly comprise the pulse signals corresponding to the second sound wave signals, so that the effect of filtering the pulse signals can be further improved, noise signals generated due to multipath attenuation in the transmission process of the sound wave signals are effectively eliminated, and the identification distance of the sound wave signals is further improved.
In addition, because the information data is determined according to the change condition of the signal intensity difference value in each signal period, the signal type corresponding to the signal in each period can be judged according to a small number of signals in each period, so that the information data is determined, and the identification distance of the sound wave signal is increased.
In addition, the acoustic wave communication method provided by the application can be realized only by improving the software level, and does not involve improving the hardware of the sending end and the receiving end, so that the applicability of the acoustic wave communication method can be improved, and the deployment and the use are convenient.
In order to more clearly understand the acoustic wave communication method provided in the present application, the following description will be given taking an example of the method. As shown in fig. 10. This embodiment will be described by taking as an example the case where this method is used in the receiving end in the acoustic wave communication system shown in fig. 1. The method at least comprises the following steps:
step 1002, performing fractional Fourier transform on the target sound wave signal at a first rotation angle to obtain a first pulse signal;
1004, performing inverse fractional Fourier transform on the filtered first pulse signal by a third rotation angle to obtain a time-frequency signal corresponding to the filtered first pulse signal, and executing step 1008;
step 1008, overlapping the time frequency signal corresponding to the first pulse signal and the time frequency signal corresponding to the second pulse signal to obtain an overlapped time frequency signal;
and 1013, determining the information data according to the change situation of the signal strength difference in each signal period.
Optionally, step 1002 may be executed before step 1005, or may also be executed after step 1005, or may also be executed simultaneously with step 1005, and the execution order between step 1002 and step 1005 is not limited in this embodiment.
For the related description of the present embodiment, reference is made to the above system and method embodiments, which are not described herein again.
In summary, in the acoustic wave communication method provided in this embodiment, because the pulse signal includes the first pulse signal and the second pulse signal, it may be convenient to filter the first pulse signal and the second pulse signal respectively, so that the filtered first pulse signal mainly includes the pulse signal corresponding to the first acoustic wave signal, and the filtered second pulse signal mainly includes the pulse signal corresponding to the second acoustic wave signal, which may improve the effect of filtering the pulse signals, effectively eliminate the noise signal generated by multipath attenuation during the transmission process of the acoustic wave signal, and thus improve the identification distance of the acoustic wave signal.
Fig. 11 is a block diagram of an acoustic wave communication apparatus provided in an embodiment of the present application, which is applied to a receiving end in the acoustic wave communication system shown in fig. 1, and the apparatus includes at least the following modules: a signal acquisition module 1110, a first transformation module 1120, a signal filtering module 1130, a second transformation module 1140, and an information determination module 1150.
The signal acquiring module 1110 is configured to acquire a target acoustic wave signal, where the target acoustic wave signal is obtained through linear frequency modulation;
the first transformation module 1120 is configured to perform fractional fourier transformation on the target acoustic wave signal to obtain a pulse signal corresponding to the target acoustic wave signal, so that a time-bandwidth product of the pulse signal is smaller than a preset threshold;
a signal filtering module 1130, configured to perform filtering processing on the pulse signal by using a preset filter, so as to obtain a filtered pulse signal;
a second transform module 1140, configured to perform inverse fractional fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal, so as to reflect a change condition of a frequency of the time-frequency signal along with time;
an information determining module 1150 is configured to determine information data based on the time-frequency signal.
For further details, reference is made to the above-described system and method embodiments.
It should be noted that: the acoustic wave communication device provided in the above embodiment performs acoustic wave communication, which is only illustrated by dividing the functional modules, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the acoustic wave communication device is divided into different functional modules, so as to perform all or part of the above described functions. In addition, the sound wave communication device and the sound wave communication method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.
Fig. 12 is a block diagram of an electronic device provided by an embodiment of the application. The electronic device may be a receiving end in the acoustic wave communication system shown in fig. 1. The electronic device comprises at least a processor 1201 and a memory 1202.
Processor 1201 may include one or more processing cores such as: 4 core processors, 8 core processors, etc. The processor 1201 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1201 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 1201 may be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing content that the display screen needs to display. In some embodiments, the processor 1201 may further include an AI (Artificial Intelligence) processor for processing a computing operation related to machine learning.
Memory 1202 may include one or more computer-readable storage media, which may be non-transitory. Memory 1202 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 1202 is used to store at least one instruction for execution by processor 1201 to implement the acoustic wave communication methods provided by method embodiments herein.
In some embodiments, the electronic device may further include: a peripheral interface and at least one peripheral. The processor 1201, memory 1202, and peripheral interface may be connected by bus or signal lines. Each peripheral may be connected to the peripheral interface via a bus, signal line, or circuit board. Illustratively, peripheral devices include, but are not limited to: radio frequency circuit, touch display screen, audio circuit, power supply, etc.
Of course, the electronic device may include fewer or more components, which is not limited by the embodiment.
Optionally, the present application also provides a computer-readable storage medium, in which a program is stored, the program being loaded and executed by a processor to implement the acoustic wave communication method of the above-described method embodiment.
Optionally, the present application further provides a computer product including a computer-readable storage medium, in which a program is stored, the program being loaded and executed by a processor to implement the acoustic wave communication method of the above-mentioned method embodiment.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of acoustic wave communication, the method comprising:
acquiring a target sound wave signal, wherein the target sound wave signal is obtained by linear frequency modulation;
performing fractional Fourier transform on the target sound wave signal to obtain a pulse signal corresponding to the target sound wave signal, so that the time bandwidth product of the pulse signal is smaller than a preset threshold value;
filtering the pulse signal by using a preset filter to obtain a filtered pulse signal;
performing inverse fractional Fourier transform on the filtered pulse signal to obtain a time-frequency signal corresponding to the filtered pulse signal so as to reflect the change condition of the frequency of the time-frequency signal along with time;
information data is determined based on the time-frequency signal.
2. The method of claim 1, wherein the pulse signal comprises a first pulse signal and a second pulse signal;
the first pulse signal is obtained by performing fractional Fourier transform on the target sound wave signal at a first rotation angle; the first rotation angle is determined according to the signal slope of a first sound wave signal of which the frequency linearly increases in each signal period in the target sound wave signal;
the second pulse signal is obtained by performing fractional Fourier transform on the target sound wave signal at a second rotation angle; the second rotation angle is determined according to the signal slope of the second sound wave signal with the linearly reduced frequency in each signal period in the target sound wave signal.
3. The method of claim 2, wherein determining information data based on the time-frequency signal comprises:
superposing the time-frequency signal corresponding to the first pulse signal and the time-frequency signal corresponding to the second pulse signal to obtain a superposed time-frequency signal;
and demodulating the superposed time-frequency signal to obtain the information data.
4. The method according to claim 3, wherein the demodulating the superimposed time-frequency signal to obtain the information data comprises:
filtering the superposed time-frequency signals by using a preset high-pass filter and a preset low-pass filter to obtain a first superposed time-frequency signal processed by the preset high-pass filter and a second superposed time-frequency signal processed by the preset low-pass filter;
calculating the signal intensity difference between the first superposed time-frequency signal and the second superposed time-frequency signal at different moments;
and determining the information data according to the change condition of the signal intensity difference value in each signal period.
5. The method according to claim 4, wherein before filtering the superimposed time-frequency signal by using a preset high-pass filter and a preset low-pass filter, the method further comprises:
down-sampling the superposed time-frequency signal to obtain a down-sampled time-frequency signal;
and determining the initial position of the time-frequency signal after the down-sampling so as to demodulate the time-frequency signal after the down-sampling from the initial position.
6. The method according to claim 1, wherein the filtering the pulse signal by using a preset filter to obtain a noise-reduced pulse signal comprises:
filtering the pulse signal by using a preset two-dimensional band-pass filter to obtain a filtered pulse signal, wherein the band-pass width of the two-dimensional band-pass filter is determined according to the bandwidth of the target sound wave signal; and the moving step length of the two-dimensional band-pass filter is determined according to the signal period of the target sound wave signal.
7. The method of claim 6, wherein the step size of the two-dimensional band-pass filter is calculated by:
wherein ,
is the moving step length of the two-dimensional band-pass filter; t issymbolIs the signal period of the target acoustic signal; oc is a rotation angle at the time of fractional Fourier transform;
the band-pass width of the two-dimensional band-pass filter is calculated by the following formula:
Bequivalent＝csc(∝)(FH-FL)+cot(∝)cos(∝)Fs
wherein ,BequivalentIs the band-pass width of the two-dimensional band-pass filter; oc is a rotation angle at the time of fractional Fourier transform; fHIs the maximum frequency of the target acoustic signal; fLIs the minimum frequency of the target acoustic signal; fsIs the sampling rate of the target acoustic signal.
8. The method according to claim 1, wherein the fractional fourier transform is performed on the target acoustic wave signal to obtain a pulse signal corresponding to the target acoustic wave signal, and the pulse signal is represented by the following formula:
wherein s is a discrete fractional order Fourier transformAn object function of the inner leaf transform; k is a sampling point corresponding to the pulse signal and is also a y-axis component on a discrete fractional Fourier transform domain; oc is a rotation angle at the time of fractional Fourier transform; j is an imaginary number; fsIs the sampling rate of the target acoustic signal; m, calculating the size of the adopted window in each summation; s [ n ]]Sampling the target sound wave signal to obtain a discrete function; n is the number of sample points.
9. An electronic device, characterized in that the device comprises a processor and a memory; the memory has stored therein a program that is loaded and executed by the processor to implement the acoustic wave communication method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that a program is stored in the storage medium, which when executed by a processor, is configured to implement the acoustic wave communication method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111474131.XA CN114142948B (en) | 2021-12-03 | 2021-12-03 | Modulation and noise reduction method for long-distance acoustic wave communication and communication system thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111474131.XA CN114142948B (en) | 2021-12-03 | 2021-12-03 | Modulation and noise reduction method for long-distance acoustic wave communication and communication system thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114142948A true CN114142948A (en) | 2022-03-04 |
| CN114142948B CN114142948B (en) | 2023-09-22 |
Family
ID=80383781
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111474131.XA Active CN114142948B (en) | 2021-12-03 | 2021-12-03 | Modulation and noise reduction method for long-distance acoustic wave communication and communication system thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114142948B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305945A (en) * | 2011-06-20 | 2012-01-04 | 电子科技大学 | Linear noise eliminating method |
| US20140269193A1 (en) * | 2013-03-13 | 2014-09-18 | Martin Junkar | Sonic-assisted localization of wireless devices |
| CN109405954A (en) * | 2018-10-23 | 2019-03-01 | 哈尔滨工程大学 | A kind of UUV mobile underwater sound communication technology based on vector hydrophone arrays |
| CN111323784A (en) * | 2020-03-25 | 2020-06-23 | 哈尔滨工程大学 | Near-field distributed sound source positioning method |
| CN113030861A (en) * | 2021-03-07 | 2021-06-25 | 西北工业大学 | Underwater acoustic signal detection method based on time reversal and fractional order wavelet transformation |
-
2021
- 2021-12-03 CN CN202111474131.XA patent/CN114142948B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305945A (en) * | 2011-06-20 | 2012-01-04 | 电子科技大学 | Linear noise eliminating method |
| US20140269193A1 (en) * | 2013-03-13 | 2014-09-18 | Martin Junkar | Sonic-assisted localization of wireless devices |
| CN109405954A (en) * | 2018-10-23 | 2019-03-01 | 哈尔滨工程大学 | A kind of UUV mobile underwater sound communication technology based on vector hydrophone arrays |
| CN111323784A (en) * | 2020-03-25 | 2020-06-23 | 哈尔滨工程大学 | Near-field distributed sound source positioning method |
| CN113030861A (en) * | 2021-03-07 | 2021-06-25 | 西北工业大学 | Underwater acoustic signal detection method based on time reversal and fractional order wavelet transformation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114142948B (en) | 2023-09-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108764077B (en) | Digital signal modulation classification method based on convolutional neural network | |
| CN102832908B (en) | Wavelet transform and variable-step-size LMS (least mean square) adaptive filtering based signal denoising method | |
| CN112101245A (en) | Short-time Fourier transform mechanical impact feature extraction method based on frequency domain window function | |
| CN106249208B (en) | Signal detecting method under amplitude modulated jamming based on Fourier Transform of Fractional Order | |
| CN101949977B (en) | Railway frequency shift signal anti-interference method based on blind source separation | |
| CN115359771B (en) | Underwater sound signal noise reduction method, system, equipment and storage medium | |
| CN109359633B (en) | Signal joint classification method based on Hilbert-Huang transform and wavelet ridge line | |
| CN109286457B (en) | TWACS uplink signal detection method based on wavelet analysis | |
| CN114142948B (en) | Modulation and noise reduction method for long-distance acoustic wave communication and communication system thereof | |
| CN102629879B (en) | Underwater acoustic communication method based on mode frequency modulation | |
| CN112800863B (en) | Time-frequency feature extraction method and system for communication signal modulation pattern recognition | |
| CN115347978B (en) | Method, device and storage medium for identifying AIS frame header data | |
| CN111611686A (en) | Detection method for communication signal time-frequency domain | |
| CN107330462B (en) | Gesture recognition method and device based on time-frequency analysis | |
| CN115293219B (en) | Pulse signal denoising method integrating wavelet and kurtosis | |
| CN109167650A (en) | Bluetooth receiver and bluetooth encode frame detection method | |
| CN113096260B (en) | Detection method and device of ETC system, storage medium and terminal | |
| CN115985333A (en) | Audio signal alignment method and device, storage medium and electronic equipment | |
| CN111384983B (en) | Signal processing method and device | |
| CN106568421A (en) | New method for deep-sea oceanpack expendable profiler long-distance linear time-varying transmission channel modeling | |
| Lijun et al. | A signal demodulation algorithm based on generative adversarial networks | |
| CN111766444A (en) | Multi-component linear frequency modulation signal parameter estimation method and system based on comprehensive algorithm | |
| CN115754433B (en) | Characteristic current code identification method, device and network topology identification method | |
| CN115347979B (en) | Method, device and storage medium for identifying AIS frame header data | |
| He et al. | A Novel Approach Based on Generative Adversarial Network for Signal Enhancement in Wireless Communications |
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 |