CN105429720B - The Time Delay Estimation Based reconstructed based on EMD - Google Patents
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- 238000000034 method Methods 0.000 claims abstract description 23
- 230000006870 function Effects 0.000 claims abstract description 20
- 230000003595 spectral effect Effects 0.000 claims abstract description 15
- 238000001228 spectrum Methods 0.000 claims abstract description 14
- 230000002596 correlated effect Effects 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims abstract description 4
- 230000009466 transformation Effects 0.000 claims description 11
- 230000001186 cumulative effect Effects 0.000 claims description 6
- 238000000354 decomposition reaction Methods 0.000 claims description 6
- 230000004044 response Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000001360 synchronised effect Effects 0.000 claims description 3
- 230000003044 adaptive effect Effects 0.000 description 5
- 230000001934 delay Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000011664 signaling Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- SDIXRDNYIMOKSG-UHFFFAOYSA-L disodium methyl arsenate Chemical compound [Na+].[Na+].C[As]([O-])([O-])=O SDIXRDNYIMOKSG-UHFFFAOYSA-L 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
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- 230000004807 localization Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/24—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being the cepstrum
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/18—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/21—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being power information
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
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- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
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- Acoustics & Sound (AREA)
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Abstract
The invention discloses a kind of Time Delay Estimation Based reconstructed based on EMD, it is characterized in that, comprise the following steps：1) sample sequence y is obtained1(n)、y2(n) leading ambient noise sequence b, is extracted1(n)、b2(n)；2) sample sequence y is obtained1(n) cepstrum sequenceObtain leading ambient noise sequence b1(n) cepstrum sequence3) obtainSound channel responseWithSound channel responseObtainSpectral enveloping lineWithSpectral enveloping lineObtain spectral difference curve D1(ω), obtains normalizing spectral difference curve4) obtainAmplitude is higher than thresholding T1 ghz area；5) m Intrinsic mode functions are obtained；6) the Power Spectrum Distribution curve per group component, ratio calculated η are obtained1, obtain the reconstruction signal of echo signal；7) to the reconstruction signal C of echo signal1(n)、C2(n) secondary correlated seriesPeak value carries out detection and can obtain time delay estimateThis method improves the Stability and veracity of time delay estimated result in the case of low signal-to-noise ratio.
Description
Technical field
It is specific a kind of based on EMD (Empirical Mode the present invention relates to array signal process technique
Decomposition, empirical mode decomposition, abbreviation EMD) reconstruct Time Delay Estimation Based.
Background technology
As the key technology of auditory localization, the estimation of sodar time delay is always that the focus of array signal processing area research is asked
Topic, and it has been applied to a variety of occasions such as underwater target tracking and positioning, Satellite tool kit, intelligent robot.
Traditional delay time estimation method has：General cross correlation, the adaptive side filtering estimation technique, mean square deviation function method
Deng.
General cross correlation, refers to document：“C.H.Knapp and C.G.Carter.The generalized
correlation method for estimation of time delay[J].IEEE Trans,Acoustics,
Speech and Signal Processing, 1976,21 (2), pp.320-327. " can accurately estimate in high s/n ratio
Time delay, but the weighting function needed for it can not be predefined in the application of physical presence reverberation noise, can only with estimate come
Instead of so that measurement accuracy is poor and unstable under the actual low signal-to-noise ratio of general cross correlation.
Adaptively side filters the estimation technique, refers to document：“F.A.Reed,P.L.Feintuch and
N.J.Bershad.Time delay estimation using the LMS adaptive filter–behavior[J]
.IEEE Transactions on Acoustics,Speech and Signal Processing.1981,29(3),
Pp.561-571. ", by setting iterative initial value, parameter and adaptive learning come estimation time delay, but this method needs to assume logical
Ambient noise between road is incoherent white Gaussian noise, estimates that accuracy rate declines under actual noise environment.
Mean square deviation function method, refers to document：“G.Jacovitti and G.Scarano.Discrete Time
Techniques for Time Delay Estimation[J].IEEE Transactions on Signal
Processing, 1993,41 (2), pp.525-533. " can reach best estimate in no influence of noise, but ought exist
Estimate that accuracy is substantially reduced during actual noise, it is its greatest problem to resist changeable noise jamming ability.
For the situation of low signal-to-noise ratio, above method is in practical application at this stage, and effect is less desirable, actual to answer
In the urgent need to a kind of delay time estimation method that noiseproof feature is good, sane in.
The content of the invention
The purpose of the present invention be in view of the shortcomings of the prior art, and provide it is a kind of based on EMD reconstruct associated time delays estimation
Method.This method can improve the Stability and veracity of time delay estimated result in the case of low signal-to-noise ratio.
Realizing the technical scheme of the object of the invention is：
The Time Delay Estimation Based reconstructed based on EMD, is comprised the following steps：
1) two-way echo signal is gathered, the sample sequence y of two-way echo signal is obtained1(n)、y2(n), and two-way mesh is extracted
Mark the leading ambient noise sequence b of signaling channel1(n)、b2(n), because two-way echo signal exists when reaching two reception sensors
Time delay σ, therefore sample sequence y1And y (n)2(n) there is also time delay σ between；
2) to sample sequence y1(n) carry out discrete Fourier transform and obtain Y1(ω), by Y1The amplitude of (ω), which is taken the logarithm, to be obtainedIt is right againCarry out inverse Fourier transform and obtain sample sequence y1(n) cepstrum sequenceObtained by same mode
To echo signal channel leading ambient noise sequence b1(n) cepstrum sequence
3) willIt is filtered, respectively obtainsSound channel responseWithSound channel responseIt is rightFourier transformation is carried out respectively to obtainSpectral enveloping lineFrequency spectrum
EnvelopeIt is rightDo the difference of two squares and eliminate reciprocity noise, and divided by instantaneous background noise energy
Obtain spectral difference curve D1(ω), then to spectral difference curve D1(ω), which is normalized, to be obtained normalizing spectral difference curve
4) obtained with threshold methodAmplitude is higher than thresholding T1 ghz area, it is assumed that meeting the ghz area of condition has k
Individual, k numerical value is relevant with the distribution of signal spectrum energy, and the numerical value obtained under the conditions of varying environment is different, correspondence echo signal
In contained voice signal composition dominate frequency range and be designated as：[ωp11,ωq11]、......、[ωp1k,ωq1k]；
5) to sample sequence y1(n) EMD decomposition is carried out, m Intrinsic mode functions are obtained successively, are designated as：h11(n), h12
(n) ... ..., h1m(n), and one decompose after surplus r1(n), such y1(n) Intrinsic mode functions can be just expressed as and remaining
The sum of item, i.e.,It is adaptive, therefore m numerical value and sample sequence that EMD, which decomposes obtained component,
y1(n) the spectrum distribution situation of itself is relevant, sample sequence y1(n) frequency content is abundanter, and m numerical value is bigger；
6) calculated by Fourier transformation and obtain every group component h11(n)......h1m(n) Power Spectrum Distribution curve H11
(ω)......H1m(ω)；The Power Spectrum Distribution curve per group component is calculated in frequency range [ωp11,ωq11]、......、[ωp1k,
ωq1k] in the cumulative ratio η cumulative with global amplitude of amplitude1If respective components calculate obtained η1More than predetermined threshold value
TH, then the component be used as the composition of echo signal all the way reconstruction signal C1(n) one of component, otherwise abandons the component；
7) by another road sample sequence y2(n) according to step 2)-step 6) same operation is carried out, obtain another road target
Signal reconstruction signal C2(n), it is assumed that the signal after the reconstruct of two-way echo signal is expressed as C1And C (n)2(n), by C1(n) and
C2(n) carry out secondary correlation and obtain C1(n)、C2(n) secondary correlated seriesTo secondary correlated seriesPeak value carry out detection can obtain time delay estimate(refer to document：" Tang
Beautiful, row letter man of virtue and ability is based on secondary related delay time estimation method [J] computer engineering, 33 (21), pp.266- in 2007
267.”)。
The sample sequence y1(n)、y2(n) be two sensor synchronous acquisitions time sampling sequence, sample frequency is Fs
=8000Hz；
Described thresholding T1 is 0.7-0.9, and preferred value is 0.8.
Described predetermined threshold value TH is 0.5.
Described spectral difference curve D1(ω) is：
Described normalization spectral difference curveFor：
Described ratio η1For：Wherein H (ω) represents any
The Fourier transformation of Intrinsic mode functions function.
This method is directed to the time delay estimation in the case of low signal-to-noise ratio, and secondary associated time delays are estimated and empirical mode decomposition
Algorithm is combined, and is separated by cepstrum, Fourier transformation and frequency spectrum make poor method, realize useful signal dominant component after EMD is decomposed
Selection.This method improves the Stability and veracity of time delay estimated result in the case of low signal-to-noise ratio.
Brief description of the drawings
Fig. 1 is embodiment method flow schematic diagram.
Embodiment
Present disclosure is further elaborated with reference to the accompanying drawings and examples, but is not the limit to the present invention
It is fixed.
Embodiment：
Reference picture 1, the Time Delay Estimation Based reconstructed based on EMD, is comprised the following steps：
1) two-way echo signal is gathered, the sample sequence y of two-way echo signal is obtained1(n)、y2(n), and two-way mesh is extracted
Mark the leading ambient noise sequence b of signaling channel1(n)、b2(n), because two-way echo signal exists when reaching two reception sensors
Time delay σ, therefore sample sequence y1And y (n)2(n) there is also time delay σ between；
2) to sample sequence y1(n) carry out discrete Fourier transform and obtain Y1(ω), by Y1The amplitude of (ω), which is taken the logarithm, to be obtainedIt is right againCarry out inverse Fourier transform and obtain sample sequence y1(n) cepstrum sequencePass through same mode
Obtain echo signal channel leading ambient noise sequence b1(n) cepstrum sequence
3) willIt is filtered, respectively obtainsSound channel responseWithSound channel responseIt is rightFourier transformation is carried out respectively to obtainSpectral enveloping lineFrequency spectrum
EnvelopeIt is rightDo the difference of two squares and eliminate reciprocity noise, and divided by instantaneous background noise energy
Obtain spectral difference curve D1(ω), then to spectral difference curve D1(ω), which is normalized, to be obtained normalizing spectral difference curve
4) obtained with threshold methodAmplitude is higher than thresholding T1 ghz area, it is assumed that meeting the ghz area of condition has k
Individual, k numerical value is relevant with the distribution of signal spectrum energy, and the numerical value obtained under the conditions of varying environment is different, correspondence echo signal
In contained voice signal composition dominate frequency range and be designated as：[ωp11,ωq11]、......、[ωp1k,ωq1k]；
5) to sample sequence y1(n) EMD decomposition is carried out, m Intrinsic mode functions are obtained successively, are designated as：h11(n), h12
(n) ... ..., h1m(n), and one decompose after surplus r1(n), such y1(n) Intrinsic mode functions can be just expressed as and remaining
The sum of item, i.e.,It is adaptive, therefore m numerical value and sample sequence that EMD, which decomposes obtained component,
y1(n) the spectrum distribution situation of itself is relevant, sample sequence y1(n) frequency content is abundanter, and m numerical value is bigger；
6) calculated by Fourier transformation and obtain every group component h11(n)......h1m(n) Power Spectrum Distribution curve H11
(ω)......H1m(ω)；The Power Spectrum Distribution curve per group component is calculated in frequency range [ωp11,ωq11]、......、[ωp1k,
ωq1k] in the cumulative ratio η cumulative with global amplitude of amplitude1If respective components calculate obtained η1More than predetermined threshold value
TH, then the component be used as the composition of echo signal all the way reconstruction signal C1(n) one of component, otherwise abandons the component；
7) by another road sample sequence y2(n) according to step 2)-step 6) same operation is carried out, obtain another road target
Signal reconstruction signal C2(n), it is assumed that the signal after the reconstruct of two-way echo signal is expressed as C1And C (n)2(n), by C1(n) and
C2(n) carry out secondary correlation and obtain C1(n)、C2(n) secondary correlated seriesTo secondary correlated seriesPeak value carry out detection can obtain time delay estimate
The sample sequence y1(n)、y2(n) be two sensor synchronous acquisitions time sampling sequence, sample frequency is Fs
=8000Hz；
Described thresholding T1 values are 0.8.
Described predetermined threshold value TH is 0.5.
Step 3) middle acquisitionWithSound channel response includes below scheme：
Rectangular window function window (n), window width n are set on inverted frequency axle0, window function is expressed as：
The width of window function is relevant with the length of sample frequency and Fourier transformation, in order thatWithThrough in Fu
Envelope after leaf transformation is real function, and window function needs to meet symmetry；
WillIt is multiplied with window function, obtains sound channel response
Described spectral difference curve D1(ω) is：
Described normalization spectral difference curveFor：
Described ratio η1For：Wherein H (ω) represents any
The Fourier transformation of Intrinsic mode functions function.
Claims (6)
1. the Time Delay Estimation Based reconstructed based on EMD, it is characterized in that, comprise the following steps：
1) two-way echo signal is gathered, the sample sequence y of two-way echo signal is obtained1(n)、y2(n), and extract two-way target letter
The leading ambient noise sequence b of number channel1(n)、b2(n), because two-way echo signal has time delay when reaching two reception sensors
σ, therefore sample sequence y1And y (n)2(n) there is also time delay σ between；
2) to sample sequence y1(n) carry out discrete Fourier transform and obtain Y1(ω), by Y1The amplitude of (ω), which is taken the logarithm, to be obtainedIt is right againCarry out inverse Fourier transform and obtain sample sequence y1(n) cepstrum sequenceObtained by same mode
To echo signal channel leading ambient noise sequence b1(n) cepstrum sequence
3) willIt is filtered, respectively obtainsSound channel responseWithSound channel response
It is rightFourier transformation is carried out respectively to obtainSpectral enveloping lineSpectral enveloping lineIt is rightDo the difference of two squares and eliminate reciprocity noise, and divided by instantaneous background noise energyComposed
Poor curve D1(ω), then to spectral difference curve D1(ω), which is normalized, to be obtained normalizing spectral difference curve
4) obtained with threshold methodAmplitude is higher than thresholding T1 ghz area, it is assumed that meeting the ghz area of condition has k individual, right
The contained leading frequency range of voice signal composition in echo signal is answered to be designated as：[ωp11,ωq11]、......、[ωp1k,ωq1k]；
5) to sample sequence y1(n) EMD decomposition is carried out, m Intrinsic mode functions are obtained successively, are designated as：h11(n), h12
(n) ... ..., h1m(n), and one decompose after surplus r1(n), such y1(n) Intrinsic mode functions can be just expressed as and remaining
The sum of item, i.e.,
6) calculated by Fourier transformation and obtain every group component h11(n)......h1m(n) Power Spectrum Distribution curve H11
(ω)......H1m(ω)；The Power Spectrum Distribution curve per group component is calculated in frequency range [ωp11,ωq11]、......、[ωp1k,
ωq1k] in the cumulative ratio η cumulative with global amplitude of amplitude1If respective components calculate obtained η1More than predetermined threshold value
TH, then the component be used as the composition of echo signal all the way reconstruction signal C1(n) one of component, otherwise abandons the component；
7) by another road sample sequence y2(n) according to step 2)-step 6) same operation is carried out, obtain another road echo signal
Reconstruction signal C2(n), the signal after the reconstruct of two-way echo signal is expressed as C1And C (n)2(n), by C1And C (n)2(n) carry out
Secondary correlation obtains C1(n)、C2(n) secondary correlated seriesTo secondary correlated seriesPeak value enter
Row detection can obtain time delay estimate
2. the Time Delay Estimation Based according to claim 1 reconstructed based on EMD, it is characterized in that, the sample sequence y1
(n)、y2(n) be two sensor synchronous acquisitions time sampling sequence, sample frequency is Fs=8000Hz.
3. the Time Delay Estimation Based according to claim 1 reconstructed based on EMD, it is characterized in that, described thresholding T1
For 0.7-0.9.
4. the Time Delay Estimation Based according to claim 1 reconstructed based on EMD, it is characterized in that, described thresholding T1
For 0.8.
5. the Time Delay Estimation Based according to claim 1 reconstructed based on EMD, it is characterized in that：Described pre- gating
Limit value TH is 0.5.
6. the Time Delay Estimation Based according to claim 1 reconstructed based on EMD, it is characterized in that：Described spectral difference is bent
Line D1(ω) is：
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| CN109884893B (en) * | 2019-02-28 | 2021-09-10 | 西安理工大学 | Multi-process variable dynamic time lag estimation method |
| CN110514294A (en) * | 2019-08-30 | 2019-11-29 | 鞍钢矿业爆破有限公司 | A kind of blasting vibration signal noise-reduction method based on EMD and VMD |
| CN113395124B (en) * | 2021-08-17 | 2021-11-02 | 清华大学 | Time delay estimation method and device based on time shift variance |
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| CN103197318A (en) * | 2013-03-18 | 2013-07-10 | 中国科学院声学研究所 | Time delay estimation method based on the Pattern delay coding underwater acoustic positioning |
| CN103884862A (en) * | 2014-02-21 | 2014-06-25 | 国家电网公司 | Secondary correlation time delay estimation method for monitoring wind speed of supersonic wave of wind power station |
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| CN103197318A (en) * | 2013-03-18 | 2013-07-10 | 中国科学院声学研究所 | Time delay estimation method based on the Pattern delay coding underwater acoustic positioning |
| CN103884862A (en) * | 2014-02-21 | 2014-06-25 | 国家电网公司 | Secondary correlation time delay estimation method for monitoring wind speed of supersonic wave of wind power station |
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| 基于EMD分解重构的互相关时延估计方法;路晓妹等;《测控技术》;20131231;第32卷(第7期);第45-48,56页 * |
| 基于经验模式分解的广义互相关时延估计;孙书学等;《探测与控制学报》;20090430;第31卷(第2期);第5-9,13页 * |
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