CN109459745A - A method of moving acoustic sources speed is estimated using radiated noise - Google Patents
A method of moving acoustic sources speed is estimated using radiated noise Download PDFInfo
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The present invention provides a kind of methods using radiated noise estimation moving acoustic sources speed, noise signal is obtained using sensor and is recorded, pretreatment is filtered to the signal of record, undetermined parameter is substituted into, the time-frequency distributions of signal are obtained by Doppler-CT method, Instantaneous frequency variations curve is extracted from time-frequency distributions, undetermined parameter estimated value is obtained based on criterion of least squares, continuous iteration, until Doppler-CT iteration convergence, can be obtained accurate velocity estimation value.The beneficial effects of the invention are as follows when being fitted Instantaneous frequency variations curve caused by Doppler effect, estimation up to 10 multinomial coefficients are generally required compared to PCT, present invention only requires 4 parameters such as estimating speed, thus effectively improve computational efficiency.
Description
Technical field
The present invention relates to signal processings and joint time frequency analysis field, especially a kind of to realize fortune using Time-Frequency Analysis Method
The speed estimation method in moving noise source.
Background technique
One kind moving target such as automobile, aircraft can regard radiated noise source as, when it is relative to reception system motion
When, the amplitude and frequency for receiving system output signal can generate corresponding variation because of Doppler effect, and this doppler phenomenon is
The foundation of passive acoustics speed-measuring method.The radiated noise power spectrum of usual this kind of noise source is related in harmonic wave by broadband continuous spectrum
A plurality of line spectrum constitute, wherein line spectrum multicomponent energy is stronger thus be more easily detected.It is passed through when target remains a constant speed to move along a straight line
When crossing the receiving sensor of fixed Mr. Yu's point, the instantaneous frequency of line spectrum is extracted from reception signal using joint time frequency analysis method
After rate change curve, estimation can be made to the speed of moving acoustic sources accordingly.
Ferguson establishes target line spectrum instantaneous frequency and speed under the conditions of linear uniform motion according to Doppler effect first
Relationship (the subsequent referred to as frequency displacement model of the present invention) between the parameters such as degree, then passes through Short Time Fourier Transform (Short
Time Fourier Transform, STFT) from receive signal in extract Instantaneous frequency variations curve, finally combine frequency displacement mould
The parameters such as type estimating speed.Based on this method, Ferguson has successfully estimated the flight speed of linear uniform motion aircraft
Spend (Ferguson B G, Quinn B G.Application of the short-time Fourier transform and
the Wigner–Ville distribution to the acoustic localization of aircraft[J]
.Journal of the Acoustical Society of America,1994,96(2):821-827.).The above method
In, obtaining accurate Instantaneous frequency variations curve is the key that accurate estimating speed.STFT is extracted since time-frequency concentration class is lower
Instantaneous frequency variations curve precision it is limited, influence the performance of velocity estimation.Xu Lingji et al. is proposed using time-frequency concentration class more
Excellent PCT (Polynomial Chirplet Transform) method extracts Instantaneous frequency variations curve, in pair of measured data
Than analysis in discovery using PCT method compared with using STFT method obtain more accurate velocity estimation result (Xu L, Yang Y,
Yu S.Analysis of moving source characteristics using polynomial chirplet
transform[J].Journal of the Acoustical Society of America,2015,137(4):EL320-
EL326.).But the calculating process of PCT method takes a long time.It is instantaneous using fitting of a polynomial target line spectrum in PCT method
Frequency variation curve.To obtain preferable fitting effect, polynomial order, which generally requires, is taken as 10 ranks or so, that is, needs to estimate phase
With the multinomial coefficient of number, calculating is complex, this is to cause to estimate that the method for motion artifacts source speed calculates effect based on PCT
The main reason for rate is low.The present invention uses frequency displacement models fitting Instantaneous frequency variations curve, it is only necessary to estimating speed etc. 4 ginsengs
Number, thus effectively improve computational efficiency.
Summary of the invention
For overcome the deficiencies in the prior art, the present invention, which provides, a kind of utilizes new Time-Frequency Analysis Method --- Doppler's tune
Frequency wavelet transformation (Doppler Chirplet Transform, Doppler-CT) extracts Instantaneous frequency variations curve, and real
The estimation of existing sound source velocity.
The technical solution adopted by the present invention to solve the technical problems specifically includes the following steps:
Step 1: obtaining noise signal using sensor and record；
Fixed reception sensor, target remain a constant speed linear motion by sensor, and sensor persistently receives the spoke of target
It penetrates noise and is converted into electric signal, electric signal is recorded after filter and amplification with data acquisition instrument, is denoted as sr(t)；
Step 2: to the signal s of recordr(t) it is filtered pretreatment
The frequency range where spectral line to be analyzed is determined according to STFT, using bandpass filter to signal sr(t) located
Reason, filters out the interference other than the band limits, the signal s (t) after being pre-processed；
Step 3: setting the initial value of undetermined parameter.
Frequency f in initial undetermined parameter0 0It is set as the centre frequency of bandpass filtering in step 2, speed v0, CPA time instant τc 0
With CPA distance Rc 0It is set greater than 0 value according to priori knowledge, such as without priori knowledge, is set greater than 0 arbitrary value；
Step 4: substituting into undetermined parameter, the time-frequency distributions of s (t) are obtained by Doppler-CT method；
The definition converted according to Doppler's chirpletThe when frequency division of signal s (t) after being pre-processed
Cloth, wherein τ indicates window function wσ(t) time shift amount, ω indicate signal frequency, wσ(t) indicate that standard deviation is the Gaussian window of σ,It is signal s (t) through rotation operatorWith frequency displacement operatorTreated signal, D=(f0,
v,τc,Rc) represent 4 undetermined parameters constantly updated in iterative process, f0For the actual frequency of spectral line, do not became at any time originally
The constant frequency f of change0Frequency is shown as at any time from large to small in receiving signal, and v is moving acoustic sources linear uniform motion
Movement velocity；In sound source motion profile with sensor it is more immediate be known as CPA (theclosest point of
Approach), τcAt the time of meaning sound source by CPA, referred to as CPA moment；RcMean sensor at a distance from CPA, referred to as CPA
Distance；
Step 5: Instantaneous frequency variations curve is extracted from time-frequency distributions；
Spectral peak is extracted from s (t) time-frequency distributions that step 4 obtains, obtains the spectrum peak frequency under one group of different moments, i.e. wink
When frequency variation curve, it is contemplated that choose N there are truncation effect in the both ends of signalw/ 2 arrive N-NwInstantaneous frequency between/2 becomes
Change, wherein N indicates discrete signal length, NwIndicate adding window length；
Step 6: undetermined parameter estimated value is obtained based on criterion of least squares；
It is calculated using frequency displacement models fitting Instantaneous frequency variations curve using Gaussian weighting marks based on criterion of least squares
Method solves undetermined parameter phase, i.e. solution D=(f0,v,τc,Rc) in four parameters, when Gaussian weighting marks convergence after obtain to
Determine the estimated value of parameter；
Step 7: the undetermined parameter estimated value that step 6 is solved as the undetermined parameter of next iteration, repeat step 4~
Step 6, until Doppler-CT iteration convergence, the condition of convergence are as follows:
Wherein, δ is threshold value, and threshold value value range is ten a ten thousandths to accurate speed between a ten thousandth, can be obtained
Spend estimated value.
The beneficial effects of the invention are as follows when being fitted Instantaneous frequency variations curve caused by Doppler effect, PCT mono- is compared
As need estimate up to 10 multinomial coefficients, present invention only requires 4 parameters such as estimating speed, thus effectively improve meter
Calculate efficiency.
Detailed description of the invention
Fig. 1 is that sound issues the communication process schematic diagram for reaching sensor from sound source.
Fig. 2 is the flow chart that signal estimation motion artifacts source speed is received using sensor.
Fig. 3 is Doppler-CT method iterative process figure.
Fig. 4 is the processing result of certain signal STFT in embodiment.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.
Step 1: obtaining noise signal using sensor and record；
Fixed reception sensor, target remain a constant speed linear motion by sensor, in this process (such as Fig. 1 institute
Show), sensor persistently receives the radiated noise of target and is converted into electric signal, and electric signal is acquired after filter and amplification with data
Instrument record is denoted as sr(t)；
Step 2: to the signal s of recordr(t) it is filtered pretreatment
The frequency range where spectral line to be analyzed is determined according to STFT, using bandpass filter to signal sr(t) located
Reason, filters out the interference other than the band limits, the signal s (t) after being pre-processed；
Step 3: setting the initial value of undetermined parameter.
Frequency f in initial undetermined parameter0 0It is set as the centre frequency of bandpass filtering in step 2, speed v0, CPA time instant τc 0
With CPA distance Rc 0It is set greater than 0 value according to priori knowledge, such as without priori knowledge, is set greater than 0 arbitrary value；
Step 4: substituting into undetermined parameter, the time-frequency distributions of s (t) are obtained by Doppler-CT method；
The definition converted according to Doppler's chirpletThe when frequency division of signal s (t) after being pre-processed
Cloth, wherein τ indicates window function wσ(t) time shift amount, ω indicate signal frequency, wσ(t) indicate that standard deviation is the Gaussian window of σ,It is signal s (t) through rotation operatorWith frequency displacement operatorTreated signal, D=(f0,
v,τc,Rc) represent 4 undetermined parameters constantly updated in iterative process, f0For the actual frequency of spectral line, due to Doppler effect,
Originally the constant frequency f not changed over time0Frequency is shown as at any time from large to small in receiving signal, as shown in Figure 1；v
For the movement velocity of moving acoustic sources linear uniform motion；In sound source motion profile with sensor it is more immediate be known as CPA
(the closest point of approach), τcAt the time of meaning sound source by CPA, referred to as CPA moment；RcMean sensing
Device is at a distance from CPA, referred to as CPA distance；
Step 5: Instantaneous frequency variations curve is extracted from time-frequency distributions；
Spectral peak is extracted from s (t) time-frequency distributions that step 4 obtains, obtains the spectrum peak frequency under one group of different moments, i.e. wink
When frequency variation curve, it is contemplated that choose N there are truncation effect in the both ends of signalw/ 2 arrive N-NwInstantaneous frequency between/2 becomes
Change, wherein N indicates discrete signal length, NwIndicate adding window length；
Step 6: undetermined parameter estimated value is obtained based on criterion of least squares；
It is calculated using frequency displacement models fitting Instantaneous frequency variations curve using Gaussian weighting marks based on criterion of least squares
Method solves undetermined parameter phase, i.e. solution D=(f0,v,τc,Rc) in four parameters, when Gaussian weighting marks convergence after obtain to
Determine the estimated value of parameter；
Step 7: the undetermined parameter estimated value that step 6 is solved as the undetermined parameter of next iteration, repeat step 4~
Step 6, until Doppler-CT iteration convergence, the condition of convergence are as follows:
Wherein, δ is threshold value, and threshold value value range is ten a ten thousandths to accurate speed between a ten thousandth, can be obtained
Spend estimated value.
As shown in Figure 1, moving acoustic sources and the immediate point of receiving sensor are known as CPA, the CPA moment refers to sound source by CPA
At the time of, CPA distance refers to the distance between CPA and receiving sensor.Undetermined parameter shares 4, is the frequency of original line spectrum respectively
Rate f0, noise source speed v, CPA time instant τcWith CPA distance Rc.Doppler-CT method sets the initial of undetermined parameter first
Then value obtains receiving the time-frequency distributions of signal using Doppler-CT method, therefrom extract Instantaneous frequency variations curve, be based on
After criterion of least squares obtains the estimated value of the above-mentioned undetermined parameter in motion artifacts source, lay equal stress on as the updated value of undetermined parameter
Above-mentioned steps are carried out again until iteration convergence, obtains the speed in motion artifacts source.
The overall procedure of technical solution of the present invention is as shown in Fig. 2, be segmented into following steps:
1) noise signal is obtained using sensor and recorded, be denoted as sr(t)。
2) to the signal s of recordr(t) it is filtered pretreatment and obtains s (t).
3) initial value of undetermined parameter is set.
4) undetermined parameter is substituted into, the time-frequency distributions of s (t) are obtained by Doppler-CT method.
5) Instantaneous frequency variations curve is extracted from time-frequency distributions.
6) undetermined parameter estimated value is obtained based on criterion of least squares.
7) step 4)~6 are repeated) until until convergence, obtains the speed in motion artifacts source.
It elaborates below to each step of the invention:
The step 1) is implemented as follows:
Fixed reception sensor, target remain a constant speed linear motion by sensor, and in this process, sensor is lasting
It receives the radiated noise of target and is converted into electric signal, electric signal is recorded after filter and amplification with data acquisition instrument.
The schematic diagram of motion process is as shown in Figure 1.
The step 2) is implemented as follows:
The frequency range where spectral line to be analyzed is determined according to STFT, using bandpass filter to signal sr(t) located
Reason, filters out the interference other than the band limits, the signal s (t) after being pre-processed.
The step 3) is implemented as follows:
As shown in Figure 1, moving acoustic sources and the immediate point of receiving sensor are known as CPA, the CPA moment refers to sound source by CPA
At the time of, CPA distance refers to the distance between CPA and receiving sensor.Undetermined parameter shares 4, is the frequency of original line spectrum respectively
Rate f0, noise source speed v, CPA time instant τcWith CPA distance Rc.Under normal circumstances, frequency f in initial undetermined parameter0 0It can set
For the centre frequency of bandpass filtering in step 2), speed v0, CPA time instant τc 0With CPA distance Rc 0It can be set as according to priori knowledge
Some desired value greater than 0 also may be set to the arbitrary value greater than 0 such as without priori knowledge.
The step 4) is implemented as follows:
Define fDIt is as follows
Wherein, fDRepresent the transformation kernel function of Doppler-CT, the frequency displacement model under the conditions of substantially known velocity of sound c, then
Doppler-CT can be expressed as following form:
Wherein
τ indicates window function w in formula (2) and formula (3)σ(t) time shift amount, ω indicate signal frequency, wσ(t) standard deviation is indicated
For the Gaussian window of σ, discrete form wσ(n)=exp (- 0.5 (n/ σ)2), wherein-(Nw-1)/2≤n≤(Nw- 1)/2, σ=
(Nw- 1)/5, NwIndicate adding window length,It is signal s (t) through rotation operatorWith frequency displacement operatorTreated signal, D
=(f0,v,τc,Rc) represent the kernel function f constantly updated in iterative processD4 parameters.
After setting initial undetermined parameter, the time-frequency distributions of signal s (t) after being pre-processed according to formula (2).Subsequent
In iteration, undetermined parameter will be provided by the estimated result based on criterion of least squares, as shown in Figure 3.
The step 5) is implemented as follows:
Spectral peak is extracted from s (t) time-frequency distributions that step 4) obtains obtains the spectrum peak frequency under one group of different moments, i.e. wink
When frequency variation curve fi.In view of the both ends of signal are there are truncation effect, so practical only choose Nw/ 2 arrive N-NwBetween/2
Instantaneous frequency variations, wherein N indicates discrete signal length, NwIndicate adding window length.
The step 6) is implemented as follows:
It can be returned based on criterion of least squares using the Instantaneous frequency variations curve observation of frequency displacement models fitting step 5)
It receives to solve the minimization problem of following form
Wherein fD(τi) it is τiThe match value of moment Instantaneous frequency variations curve, fiRepresent τiThe sight of moment Instantaneous frequency variations
Measured value is provided by step 5).
The problem of formula (4), can be solved using Gaussian weighting marks method, and iterative formula is as follows
Wherein behalf the number of iterations,Represent Jacobian matrix.
(generally requiring 200 times or more iteration) after Gaussian weighting marks convergence can be obtained undetermined parameter estimated value.
The step 7) is implemented as follows:
The estimates of parameters in the motion artifacts source that step 6) is solved as the updated value of undetermined parameter, repeat step 4)~
6), until D-C-CZT iteration convergence, can be obtained accurate velocity estimation value.The decision condition of termination iteration can set as follows:
Wherein, δ is threshold value, and threshold value value range is ten a ten thousandths between a ten thousandth.
In order to verify the validity for the method estimation noise source movement velocity that the present invention provides, design and simulation experiment is as follows:
Setup parameter (f0,v,τc,Rc, c)=(88,25,5,50,340), that is, assume the line spectrum radiated noise frequency f of noise source0=
88Hz does the linear uniform motion of speed v=25m/s, beam time instant τc=5s, the distance abeam of noise source to receiving sensor
Rc=50m, THE VELOCITY OF SOUND IN AIR c=340m/s.Observing time is set as 10s, sample rate fs=1024Hz, the number of iterations are 3 times,
Gaussian window length is taken as 1024, and signal-to-noise ratio is taken as SNR=0dB, indicate signal and noise in observation time gross energy it is opposite
Size, noise are white Gaussian noise.Emulation signal is handled using the method that the present invention provides, can be obtained as shown in Figure 4
The processing result of signal STFT, spectral line is as shown in Figure 4, frequency range substantially 116Hz~121Hz in 30 seconds.In Fig. 4
Light tone lines can be seen, be the filter range that can determine bandpass filter according to light tone lines.Gained velocity estimation such as 1 institute of table
Show.The ginsengs such as the speed of aerial sports sound source can be accurately estimated using the method that the present invention provides as can be seen from Table 1
Number, it was demonstrated that the validity of this method.
The parameter estimation result of 1 Doppler-CT method of table
Claims (1)
1. a kind of method using radiated noise estimation moving acoustic sources speed, it is characterised in that include the following steps:
Step 1: obtaining noise signal using sensor and record；
Fixed reception sensor, target remain a constant speed linear motion by sensor, and the radiation that sensor persistently receives target is made an uproar
Sound is simultaneously converted into electric signal, and electric signal is recorded after filter and amplification with data acquisition instrument, is denoted as sr(t)；
Step 2: to the signal s of recordr(t) it is filtered pretreatment
The frequency range where spectral line to be analyzed is determined according to STFT, using bandpass filter to signal sr(t) it is handled, is filtered
Interference in addition to the band limits, the signal s (t) after being pre-processed；
Step 3: setting the initial value of undetermined parameter；
Frequency f in initial undetermined parameter0 0It is set as the centre frequency of bandpass filtering in step 2, speed v0, CPA time instant τc 0And CPA
Distance Rc 0It is set greater than 0 value according to priori knowledge, such as without priori knowledge, is set greater than 0 arbitrary value；
Step 4: substituting into undetermined parameter, the time-frequency distributions of s (t) are obtained by Doppler-CT method；
The definition converted according to Doppler's chirpletThe when frequency division of signal s (t) after being pre-processed
Cloth, wherein τ indicates window function wσ(t) time shift amount, ω indicate signal frequency, wσ(t) indicate that standard deviation is the Gaussian window of σ,It is signal s (t) through rotation operatorWith frequency displacement operatorTreated signal, D=(f0,
v,τc,Rc) represent 4 undetermined parameters constantly updated in iterative process, f0For the actual frequency of spectral line, do not became at any time originally
The constant frequency f of change0Frequency is shown as at any time from large to small in receiving signal, and v is moving acoustic sources linear uniform motion
Movement velocity；In sound source motion profile with sensor it is more immediate be known as CPA, τcAt the time of sound source is meant by CPA, claim
For the CPA moment；RcMean sensor at a distance from CPA, referred to as CPA distance；
Step 5: Instantaneous frequency variations curve is extracted from time-frequency distributions；
It extracts spectral peak from s (t) time-frequency distributions that step 4 obtains, obtains the spectrum peak frequency under one group of different moments, i.e., instantaneous frequency
Rate change curve, it is contemplated that there are truncation effects at the both ends of signal, choose Nw/ 2 arrive N-NwInstantaneous frequency variations between/2,
In, N indicates discrete signal length, NwIndicate adding window length；
Step 6: undetermined parameter estimated value is obtained based on criterion of least squares；
It is asked using frequency displacement models fitting Instantaneous frequency variations curve using Gaussian weighting marks algorithm based on criterion of least squares
Undetermined parameter phase is solved, i.e. solution D=(f0,v,τc,Rc) in four parameters, when Gaussian weighting marks convergence after obtain ginseng undetermined
Several estimated values；
Step 7: the undetermined parameter estimated value that step 6 is solved repeats step 4~step as the undetermined parameter of next iteration
6, until Doppler-CT iteration convergence, the condition of convergence are as follows:
Wherein, δ is threshold value, and threshold value value range is that ten a ten thousandths are estimated to accurate speed between a ten thousandth, can be obtained
Evaluation.
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