CN107123431A - A kind of underwater sound signal noise-reduction method - Google Patents
A kind of underwater sound signal noise-reduction method Download PDFInfo
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- CN107123431A CN107123431A CN201710300367.9A CN201710300367A CN107123431A CN 107123431 A CN107123431 A CN 107123431A CN 201710300367 A CN201710300367 A CN 201710300367A CN 107123431 A CN107123431 A CN 107123431A
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L21/0216—Noise filtering characterised by the method used for estimating noise
- G10L21/0232—Processing in the frequency domain
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- 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
Abstract
The present invention proposes a kind of underwater sound signal noise-reduction method, and input underwater sound signal is decomposed into each modal components first；Secondly each modal components decomposition obtained transform to frequency domain and handled；Further according to the distribution character of noise in underwater sound signal, design threshold function filters out noise；Then each modal components after processing are transformed into time domain；Underwater sound signal after last reconstructed reduced noise.The present invention compared with prior art, effectively eliminates noise contribution, by the way that underwater sound signal is decomposed into a series of mode, is conducive to noise in identification mode, facilitates subsequent treatment.Compared to general spectrum-subtraction, there is some superiority on processing non-stationary signal, can more show the physical significance of signal in itself.Simultaneously by design threshold function, processing will be filtered in modal transformation to frequency domain, takes full advantage of the energy statisticses characteristic of noise and signal, the more commonly used wavelet de-noising method, this method shows higher anti-acoustic capability.
Description
Technical field
The invention belongs to acoustics signal processing field, it is related to underwater sound signal noise reduction technology, and in particular to a kind of threshold deniosing
Method.
Background technology
When underwater sound signal is propagated in the seawater, due to by other targets, marine environment interference complicated and changeable and instrument
The influence of device, what reception sensor was received is the low-down non-stationary signal of signal to noise ratio.Therefore underwater sound signal receiving terminal will be to mesh
Mark feature is extracted and classified, and primarily must be filtered processing to the primary signal collected.
The underwater sound signal of superposition seanoise is time-varying non-stationary signal, ununified waveform, it is difficult to design suitable
Matched filter.Traditional has some such as spectrum-subtractions of the noise-reduction method based on Fourier transformation, can cut down to a certain extent
Noise component(s).But because Fourier transformation is in process signal, signal is transformed to frequency domain from whole time domain, it is impossible to reflect signal
Commutation instants, therefore be not suitable for the processing of unstable state underwater sound signal.Wavelet transformation is relative to Fourier transformation, its conversion
Window is variable during processing non-stationary signal, has higher frequency discrimination ability to the low frequency part of signal, and right
The HFS of signal has higher time domain resolution capability, can be efficiently used for the processing of non-stationary signal.So small echo becomes
Change is that he is carried out many by flexible shift operations to signal with one of widest nonparametric technique in acoustical signal Denoising Algorithm
Yardstick is refined, and segments frequency at high-band frequency rough segmentation, low frequency, reaches the automatic requirement for adapting to time frequency signal analysis.But it is small
There is Gibbs effects and the low shortcoming of reconstruction accuracy in ripple noise reduction, and because wavelet basis is set in advance, therefore can not be fine
Expression reality in actual signal.Independent component analysis (Independent Component Analysis, ICA) is in recent years
Come a kind of signal processing technology risen, if being independent between each source signal, ICA can decompose the mixed signal received
For separate composition, each composition as source signal isolated, but be that each independent element must be there is also restrictive condition
Non-gaussian distribution.
The content of the invention
In order to avoid the shortcomings of the prior art, the present invention proposes a kind of new underwater sound signal noise-reduction method, by inciting somebody to action
Input underwater sound signal and carry out new mode decomposition, frequency domain is transformed to therewith and carries out threshold value screening filtering process, then contravariant is changed to
Time domain reconstruction underwater sound signal, finally exports the underwater sound signal after noise reduction.Can largely it be lifted by the method for the present invention
Input signal signal to noise ratio.
The technical scheme is that：
A kind of underwater sound signal noise-reduction method, it is characterised in that：Comprise the following steps：
Step 1：The underwater sound signal of input is decomposed into modal components, wherein underwater sound signal is s (n), n=1,2 ... N, N
For signal length；
Step 1.1：Produce I white noise fragment wi, i ∈ 1,2 ... I；The I white noise fragment to generation is carried out respectively
Mode decomposition, obtains the intrinsic mode signals of K ranks of I white noise fragment；K is equal to the iterations in step 1.2；
Step 1.2：Decomposition is iterated using procedure below, until meeting stopping criterion for iteration；
Wherein：
Decompose for the first time：
The underwater sound signal of input is superimposed I white noise fragment respectively, I is obtained and decomposes required input letter for the first time
Number；Input signal needed for being decomposed for the first time to described I carries out first time mode decomposition, and calculates I first time mode point
The average value of the respective intrinsic mode signals of first rank of result is solved, the intrinsic mode signals of the first rank of underwater sound signal are obtained；
The underwater sound signal of input is subtracted to the intrinsic mode signals of the first rank of underwater sound signal, underwater sound signal is obtained and divides for the first time
Residual error after solution；
Residual error is superimposed the intrinsic mode signals of the first rank of I white noise fragment respectively after underwater sound signal is decomposed for the first time,
Obtain the input signal needed for I second of decomposition；
Second of decomposition：
Second of mode decomposition is carried out to the input signal needed for I second of decomposition, and calculates I second of mode point
The average value of the respective intrinsic mode signals of first rank of result is solved, the intrinsic mode signals of second-order of underwater sound signal are obtained；
Residual error subtracts the intrinsic mode signals of second-order of underwater sound signal after underwater sound signal is decomposed for the first time, obtains underwater sound letter
Residual error after number second decomposing；
Kth time is decomposed：
Input signal needed for being decomposed to I kth time carries out kth time mode decomposition, and calculates I kth time mode decomposition
As a result the average value of the respective intrinsic mode signals of first rank, obtains the intrinsic mode signals of kth rank of underwater sound signal
Residual error after -1 decomposition of underwater sound signal kth is subtracted to the intrinsic mode signals of kth rank of underwater sound signal, underwater sound letter is obtained
Residual error after number kth time is decomposed；
In decomposable process, judge whether the extreme value number that residual error possesses after each decomposition of underwater sound signal is less than two, if so,
Then iteration terminates, and the underwater sound signal residual error now obtained is final residual error R (n)；
Step 2：The intrinsic mode signals of each rank of underwater sound signal that step 1 is obtainedFrom time domain to frequency domain, frequency is obtained
Domain mode signals
Step 3：According to formula
Calculate the threshold value T of kth rankk, wherein c1To represent the constant of signal type, σ2For the noise energy size of estimation,
ENH(k) noise energy contained for the intrinsic mode signals of underwater sound signal kth rank：
WhereinβH=0.719, ENH(1) water intaking acoustical signal
The intrinsic mode signal energy of 1st rank
The value of each rank mode signals of underwater sound signal is compared with the threshold value of corresponding rank in the frequency domain that step 2 is obtained, such as
ReallyIt is then that corresponding frequency amplitude is scaled；
Step 4：By the state simulation of frequency region signal after step 3 is handledContravariant gains time domain, obtains Time-Domain Modal
Signal
Step 5：Each mode and residual error R (n) in time domain is overlapped
Obtain reconstructing the underwater sound signal come after noise reduction.
Beneficial effect
The present invention proposes a kind of new underwater sound signal noise-reduction method, and compared with prior art, this method is effectively eliminated
Noise contribution, by the way that underwater sound signal is decomposed into a series of mode, is conducive to noise in identification mode, facilitates subsequent treatment.
Compared to general spectrum-subtraction, there is some superiority on processing non-stationary signal, can more show the physical significance of signal in itself.Together
When by design threshold function, processing will be filtered in modal transformation to frequency domain, the energy of noise and signal is taken full advantage of
Statistical property, the more commonly used wavelet de-noising method, this method shows higher anti-acoustic capability.
Experiment proves that this method can effectively improve the signal to noise ratio of input underwater sound signal, and more now widely used spectrum subtracts
Method, wavelet de-noising method are more effective, and the present invention takes full advantage of the useful information of underwater sound signal, largely reduces noise and contains
Amount, can obtain good noise reduction.
The additional aspect and advantage of the present invention will be set forth in part in the description, and will partly become from the following description
Obtain substantially, or recognized by the practice of the present invention.
Brief description of the drawings
The above-mentioned and/or additional aspect and advantage of the present invention will become from description of the accompanying drawings below to embodiment is combined
Substantially and be readily appreciated that, wherein：
Fig. 1 is a kind of theory diagram of new underwater sound signal noise-reduction method of the present invention.
Embodiment
Embodiments of the invention are described below in detail, the embodiment is exemplary, it is intended to for explaining the present invention, and
It is not considered as limiting the invention.
It is new by the way that underwater sound signal progress will be inputted the purpose of the present invention is to propose to a kind of new underwater sound signal noise-reduction method
Mode decomposition, transforms to frequency domain and carries out threshold value screening filtering process, then inverse transformation is to time domain reconstruction underwater sound signal, finally therewith
Export the underwater sound signal after noise reduction.
The present invention basic step thinking be：
Step one：Input underwater sound signal is decomposed into each modal components；
Step 2：Each modal components that decomposition is obtained transform to frequency domain and handled；
Step 3：According to the distribution character of noise in underwater sound signal, design threshold function filters out noise；
Step 4：Each modal components after processing are transformed into time domain；
Step 5：Underwater sound signal after reconstructed reduced noise.
As shown in figure 1, below using MATLAB as operating platform, describing the implementation steps and computational methods of the present invention in detail.
Step 1：The underwater sound signal of input is decomposed into modal components, wherein underwater sound signal is s (n), n=1,2 ... N, N
For signal length；
Step 1.1：Produce the I white noise fragment w for obeying N (0,1)i, i ∈ 1,2 ... I；To I white noise of generation
Fragment carries out mode decomposition respectively, obtains the intrinsic mode signals of K ranks of I white noise fragment；K is equal to the iteration in step 1.2
Number of times；White noise variance is ε=0.2 in the present embodiment, and white noise number of samples is I=100.
Step 1.2：Decomposition is iterated using procedure below, until meeting stopping criterion for iteration；
Wherein：
Decompose for the first time：
The underwater sound signal of input is superimposed I white noise fragment respectively, I is obtained and decomposes required input letter for the first time
Number；Input signal needed for being decomposed for the first time to described I carries out first time mode decomposition, and calculates I first time mode point
The average value of the respective intrinsic mode signals of first rank of result is solved, the intrinsic mode signals of the first rank of underwater sound signal are obtained；
The underwater sound signal of input is subtracted to the intrinsic mode signals of the first rank of underwater sound signal, underwater sound signal is obtained and divides for the first time
Residual error after solution；
Residual error is superimposed the intrinsic mode signals of the first rank of I white noise fragment respectively after underwater sound signal is decomposed for the first time,
Obtain the input signal needed for I second of decomposition；
Second of decomposition：
Second of mode decomposition is carried out to the input signal needed for I second of decomposition, and calculates I second of mode point
The average value of the respective intrinsic mode signals of first rank of result is solved, the intrinsic mode signals of second-order of underwater sound signal are obtained；
Residual error subtracts the intrinsic mode signals of second-order of underwater sound signal after underwater sound signal is decomposed for the first time, obtains underwater sound letter
Residual error after number second decomposing；
Kth time is decomposed：
Input signal needed for being decomposed to I kth time carries out kth time mode decomposition, and calculates I kth time mode decomposition
As a result the average value of the respective intrinsic mode signals of first rank, obtains the intrinsic mode signals of kth rank of underwater sound signal
Residual error after -1 decomposition of underwater sound signal kth is subtracted to the intrinsic mode signals of kth rank of underwater sound signal, underwater sound letter is obtained
Residual error after number kth time is decomposed；
In decomposable process, judge whether the extreme value number that residual error possesses after each decomposition of underwater sound signal is less than two, if so,
Then iteration terminates, and the underwater sound signal residual error now obtained is final residual error R (n)；
Therefore underwater sound signal decomposition result can be expressed as：
Step 2：The intrinsic mode signals of each rank of underwater sound signal for being obtained step 1 using Fourier transformationFrom time domain
To frequency domain, state simulation of frequency region signal is obtained
Step 3：According to formula
Calculate the threshold value T of kth rankk, band makes an uproar in underwater sound signal, and noise content is higher, and threshold value is bigger；Wherein c1To represent letter
The constant of number type, this experiment takes c using actual measurement underwater sound signal1=53, σ2For the noise energy size of estimation, by defeated
The sound signal analysis estimation entered can obtain；
ENH(k) noise energy contained for the intrinsic mode signals of underwater sound signal kth rank：
WhereinIt is different according to Noise Characteristic, different H values are taken, this
It is white Gaussian noise in invention, therefore takesβH=0.719, ENH(1) the water intaking intrinsic mode signal energy of the rank of acoustical signal the 1st
The value of each rank mode signals of underwater sound signal is compared with the threshold value of corresponding rank in the frequency domain that step 2 is obtained, such as
ReallyThen that corresponding frequency amplitude is scaled, diminution ratio is c2, can be according to actual conditions by this parameter
Control to take in diminution ratio, the present embodiment
Step 4：After being screened by threshold value, by the state simulation of frequency region signal after step 3 is handledUsing in anti-Fu
Leaf transformation contravariant gains time domain, obtains Time-Domain Modal signal
Step 5：Each mode and residual error R (n) in time domain is overlapped
Obtain reconstructing the underwater sound signal come after noise reduction.
As if it is determined that in underwater sound signal the frequency band range with noise, can also carry out similar threshold to the mode in respective bandwidth
Value filtering, now noise reduction is better than overall filter effect.
Although embodiments of the invention have been shown and described above, it is to be understood that above-described embodiment is example
Property, it is impossible to limitation of the present invention is interpreted as, one of ordinary skill in the art is not departing from the principle and objective of the present invention
In the case of above-described embodiment can be changed within the scope of the invention, change, replace and modification.
Claims (1)
1. a kind of underwater sound signal noise-reduction method, it is characterised in that：Comprise the following steps：
Step 1：The underwater sound signal of input is decomposed into modal components, wherein underwater sound signal is that s (n), n=1,2 ... N, N are letter
Number length；
Step 1.1：Produce I white noise fragment wi, i ∈ 1,2 ... I；The I white noise fragment to generation carries out mode respectively
Decompose, obtain the intrinsic mode signals of K ranks of I white noise fragment；K is equal to the iterations in step 1.2；
Step 1.2：Decomposition is iterated using procedure below, until meeting stopping criterion for iteration；
Wherein：
Decompose for the first time：
The underwater sound signal of input is superimposed I white noise fragment respectively, I is obtained and decomposes required input signal for the first time；It is right
Described I is decomposed required input signal and carries out first time mode decomposition, and calculate I first time mode decomposition result for the first time
The average value of the respective intrinsic mode signals of first rank, obtains the intrinsic mode signals of the first rank of underwater sound signal；
The underwater sound signal of input is subtracted to the intrinsic mode signals of the first rank of underwater sound signal, obtained after underwater sound signal decomposition for the first time
Residual error；
Residual error is superimposed the intrinsic mode signals of the first rank of I white noise fragment respectively after underwater sound signal is decomposed for the first time, obtains I
Input signal needed for individual second of decomposition；
Second of decomposition：
Second of mode decomposition is carried out to the input signal needed for I second of decomposition, and calculates I second of mode decomposition knots
The average value of the really respective intrinsic mode signals of first rank, obtains the intrinsic mode signals of second-order of underwater sound signal；
Residual error subtracts the intrinsic mode signals of second-order of underwater sound signal after underwater sound signal is decomposed for the first time, obtains underwater sound signal the
Residual error after twice decomposition；
Kth time is decomposed：
Input signal needed for being decomposed to I kth time carries out kth time mode decomposition, and calculates I kth time mode decomposition result
The average value of the respective intrinsic mode signals of first rank, obtains the intrinsic mode signals of kth rank of underwater sound signal
Residual error subtracts the intrinsic mode signals of kth rank of underwater sound signal after underwater sound signal kth -1 time is decomposed, and obtains underwater sound signal the
Residual error after k decomposition；
In decomposable process, judge whether the extreme value number that residual error possesses after each decomposition of underwater sound signal is less than two, if so, then changing
In generation, terminates, and the underwater sound signal residual error now obtained is final residual error R (n)；
Step 2：The intrinsic mode signals of each rank of underwater sound signal that step 1 is obtainedFrom time domain to frequency domain, state simulation of frequency region is obtained
SignalK=1,2 ... K；
Step 3：According to formula
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Calculate the threshold value T of kth rankk, wherein c1To represent the constant of signal type, σ2For the noise energy size of estimation, ENH(k)
The noise energy contained for the intrinsic mode signals of underwater sound signal kth rank：
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Step 4：By the state simulation of frequency region signal after step 3 is handledContravariant gains time domain, obtains Time-Domain Modal signal
Step 5：Each mode and residual error R (n) in time domain is overlapped
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Obtain reconstructing the underwater sound signal come after noise reduction.
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| CN108387887A (en) * | 2018-05-22 | 2018-08-10 | 西安邮电大学 | A kind of mixing noise-reduction method of underwater sound signal |
| CN108490494A (en) * | 2018-03-12 | 2018-09-04 | 中国科学院电子学研究所 | Marine magnetic survey noise suppressing method based on spectrum-subtraction and wavelet analysis |
| CN108875706A (en) * | 2018-07-18 | 2018-11-23 | 中国海洋大学 | The ocean structure Time-Frequency Analysis Method collected based on sliding average and energy |
| CN111401236A (en) * | 2020-03-16 | 2020-07-10 | 西北工业大学 | Underwater sound signal denoising method based on self-coding neural network |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108490494A (en) * | 2018-03-12 | 2018-09-04 | 中国科学院电子学研究所 | Marine magnetic survey noise suppressing method based on spectrum-subtraction and wavelet analysis |
| CN108387887A (en) * | 2018-05-22 | 2018-08-10 | 西安邮电大学 | A kind of mixing noise-reduction method of underwater sound signal |
| CN108875706A (en) * | 2018-07-18 | 2018-11-23 | 中国海洋大学 | The ocean structure Time-Frequency Analysis Method collected based on sliding average and energy |
| CN108875706B (en) * | 2018-07-18 | 2021-08-17 | 中国海洋大学 | Ocean structure time-frequency analysis method based on moving average and energy collection |
| CN111401236A (en) * | 2020-03-16 | 2020-07-10 | 西北工业大学 | Underwater sound signal denoising method based on self-coding neural network |
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