CN107707324B - A kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation - Google Patents
A kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04J—MULTIPLEX COMMUNICATION
- H04J3/00—Time-division multiplex systems
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- H04J3/06—Synchronising arrangements
- H04J3/0635—Clock or time synchronisation in a network
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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
- G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
- G01S11/14—Systems for determining distance or velocity not using reflection or reradiation using ultrasonic, sonic, or infrasonic waves
Abstract
The invention belongs to wireless monitoring technology fields, disclose a kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, under noise background, signal is acquired using acoustic sensor array and is pre-processed to obtain frequency-region signal by cross-correlation function and Short Time Fourier Transform；Calculate the relative phase of two-way acoustical signal than and combine the principle of maximum- likelihood estimation to obtain the probability of all possible time delay estimated value；Under conditions of not depending on signal and noise priori knowledge, using time delay value corresponding to maximum probability peak value as final time delay estimated value.The present invention can accurately estimate the reaching time-difference TDOA of sound source；Taking 10 groups of length is the data of 1024 sampled points, and to delay 0.0029s, 0.0059s, 0.0088s, 0.0118s calculates separately its mean square error, by Tables 1 and 2 it can be seen that the present invention has very big accuracy.
Description
Technical field
The invention belongs to wireless monitoring technology field more particularly to it is a kind of based on the sound of phase difference and maximal possibility estimation believe
Number delay time estimation method.
Background technique
Target Passive Positioning technology is always the hot issue of wireless monitor area research and supervises in military affairs supervision, environment
Survey, rescue and relief work etc. are used widely.And passive target itself will not emit electromagnetic wave, concealment with higher,
Therefore, it is very necessary for studying accurate passive target locating scheme.It has developed both at home and abroad at present excellent based on geometric parameter
The location technology of change can be mainly divided into based on arrival time TOA, reaching time-difference TDOA, angle of arrival AOA, received signal strength
Tetra- class of RSS.Arrival time TOA location technology reaches the absolute time between node by measurement sound source and estimates to target position
Meter, although TOA location algorithm is capable of providing accurate location estimation, it is required that accurate synchronised clock, increases system
Complexity.AOA location technology pass through determine target to node direction of arrival line so that it is determined that sound source position, this method need
The array antenna for estimating direction of arrival degree is disposed, the cost of system is increased.Received signal strength RSS location technology
The intensity of sound-source signal is received by measuring node to estimate the position of target, however between the performance number measured and true value
Due to the presence of obstacle, the reception power conversion measured it is electromagnetic propagation path simply by model, can makes to position
Precision causes biggish error.However be compared with other methods, TDOA has hardware requirement few, and the high advantage of positioning accuracy arrives
Absolute time between measurement echo signal and node is not needed up to time difference TDOA, it only need to be by between the different nodes of measurement target arrival
Reaching time-difference realize positioning.The above method is the common method for carrying out passive target positioning, is based on wireless sensing
The key of the TDOA location technology of device network is high-precision time delay estimation.One kind is reached based on non-linear maximum likelihood
TDOA estimation, the method for realizing sound source position estimation, but the computation complexity of the method is higher.A kind of recurrence based on tree is maximum
Likelihood algorithm positions sound source, in the case that two microphones distance farther out, time delay is carried out by phase difference between time-frequency and is estimated
Meter realizes the determination to multi-acoustical number and position, however this method only accounts for the processing of static sound source, for movement
Target can not real-time estimation target position and realize target following, can be connect by a frame frame processing and tracker realize
The detection and positioning of moving target.
In conclusion problem of the existing technology is: current target Passive Location there are computation complexity compared with
Height, for the target of movement can not real-time estimation target position and realize target following.
Summary of the invention
In view of the problems of the existing technology, believed the present invention provides a kind of based on the sound of phase difference and maximal possibility estimation
Number delay time estimation method.
The invention is realized in this way a kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation,
The acoustical signal delay time estimation method based on phase difference and maximal possibility estimation utilizes acoustic sensor array under noise background
Acquisition signal simultaneously is pre-processed to obtain frequency-region signal by cross-correlation function and Short Time Fourier Transform；Calculate two-way acoustical signal
Relative phase than and combine the principle of maximum- likelihood estimation to obtain the probability of all possible time delay estimated value；It is disobeying
Under conditions of relying signal and noise priori knowledge, using time delay value corresponding to maximum probability peak value as final time delay estimated value.
Further, the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation the following steps are included:
Step 1, in t moment, by the signal of acquisitionWithIt is related to carry out sliding, obtaining can between this two paths of signals
Time delay section [(1-N)/f of energys,(N-1)/fs]；
Step 2, time-frequency domain conversation, by signalWithIts frequency domain presentation is obtained using Short Time Fourier TransformWith
Step 3 calculates relative phase ratio, calculates the relative phase ratio φ between t moment two signals of each frequency pointm(t,
k)；
Step 4 calculates relative phase than set, calculates the relative phase ratio of each possibility each frequency point of time delay d, and
Summarized and constitutes relative phase than set
Step 5, estimated probability initialization carry out equality initialization to the probability parameter of each possible time delay value
Step 6, calculation delay estimated probability calculate the averaged power spectrum probability of each possible time delay value of t moment
Step 7 obtains time delay value, using time delay value corresponding to the maximum value in resulting averaged power spectrum probability as letter
NumberWithReaching time-difference；
Step 8, recursive estimation parameter estimate the probability parameter of next frame based on the resulting estimation parameter of previous frame
Meter
Further, the acoustical signal delay time estimation method reaching time-difference TDOA based on phase difference and maximal possibility estimation
Estimate model, wherein t=1 ..., T are the time index of signal time domain, and k=0 ..., K are frequency index, share M to sensing
Device node, the then signal model that i-th of node acquires are as follows:
WhereinV (t, k),Respectively i-th of sonic transducer node to sound source sound transfer function,
Additive noise of the m to i-th of microphone acquisition signal of node.
Further, in the step 3:
φm(t, k) is the phase difference that m acquires signal to node,The each time-frequency of signal is acquired for i-th of node
Point signal amplitude,The mould of each time frequency point signal of signal is acquired for i-th of node.
Further, in the step 4:
For the phase difference set of all time delay values, TsFor the sampling time, k=0 ..., K are frequency index, and d is time delay
Value.
Further, the average probability of d-th of time delay value of t moment is estimated in the step 6 are as follows:
For the averaged power spectrum probability of each possibility TDOA value of t moment,It is d-th at each frequency point of t moment
The probabilistic estimated value of time delay, K are frequency point sum.
Further, in the step 8:
For the probabilistic estimated value of all possible time delay value of t moment,For the flat of all possible time delay values of t moment
Equal estimated probability, γtIndicate recursive smoothing parameter, value range is (0,1).
Advantages of the present invention and good effect are as follows: Fig. 5 and Fig. 6 can be seen that in the lower situation of signal-to-noise ratio, postpone
In 720 sampled points, the present invention may occur in which apparent peak value, can accurately estimate the reaching time-difference TDOA of sound source.Fig. 7
As can be seen that when data length is 1024 sampled points, when data length is increased to 1300 sampled points, in delay 720
When sampled point, time delay estimated value still can be accurately obtained.Taking 10 groups of length is the data of 1024 sampled points, to delay
0.0029s, 0.0059s, 0.0088s, 0.0118s calculate separately its mean square error, by Tables 1 and 2 it can be seen that the present invention
With very big accuracy.
By MATLAB experiment simulation, the feasibility and validity of algorithm are demonstrated, has carried out three groups of emulation experiments respectively,
Different Gaussian noises is added on the basis of testing one in experiment two, obtains this method situation lower in signal-to-noise ratio by comparison
Under, Time delay Estimation Accuracy still with higher.Experiment three increases data length on the basis of testing two, is obtained at that time by comparison
The precision for prolonging estimation is also influenced by data length, and data length determines the model for the time delay value that the algorithm can accurately be estimated
It encloses.Therefore, the present invention does not depend on the priori knowledge of signal and noise, and it is long that suitable data are chosen in the case of signal-to-noise ratio is lower
Degree can accurately estimate the value of reaching time-difference.
Detailed description of the invention
Fig. 1 is the acoustical signal delay time estimation method stream provided in an embodiment of the present invention based on phase difference and maximal possibility estimation
Cheng Tu.
Fig. 2 is time delay estimation model structure schematic diagram provided in an embodiment of the present invention.
Fig. 3 is that PRP provided in an embodiment of the present invention extracts preprocessing process schematic diagram.
Fig. 4 is TDOA algorithm for estimating block diagram provided in an embodiment of the present invention.
Fig. 5 is 1 time delay schematic diagram of emulation experiment provided in an embodiment of the present invention；
In figure: (a) postponing the estimation of 0.0029s time delay；(b) delay 0.0059s time delay estimation；(c) postpone 0.0088s time delay
Estimation.
Fig. 6 is 2 time delay schematic diagram of emulation experiment provided in an embodiment of the present invention；
In figure: (a) postponing the estimation of 0.0029s time delay；(b) delay 0.0059s time delay estimation；(c) postpone
The estimation of 0.0088s time delay.
Fig. 7 is 3 time delay schematic diagram of emulation experiment provided in an embodiment of the present invention；
In figure: (a) 1024 sampled point delay 0.0118s time delay estimations；(b) when 1300 sampled point delay 0.0118s
Prolong estimation.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
Application principle of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, provided in an embodiment of the present invention estimated based on the acoustical signal time delay of phase difference and maximal possibility estimation
Method the following steps are included:
S101: under noise background, signal is acquired using acoustic sensor array and by cross-correlation function and in short-term in Fu
Leaf transformation is pre-processed to obtain frequency-region signal；
S102: calculate two-way acoustical signal relative phase than and combine maximum- likelihood estimation principle obtain it is all can
The probability of the time delay estimated value of energy；
S103: under conditions of not depending on signal and noise priori knowledge, by time delay value corresponding to maximum probability peak value
As final time delay estimated value.
Application principle of the invention is further described with reference to the accompanying drawing.
1 model structure
Using acoustic sensor array, reaching time-difference TDOA that estimated sensor is collected mail number indirectly.Reaching time-difference TDOA
Estimate model structure as shown in Fig. 2, wherein t=1 ..., T are the time index of signal time domain, and k=0 ..., K are under frequency
Mark, shared M is to sensor node, then the signal model that i-th of node acquires are as follows:
WhereinV (t, k),Sound transfer function of respectively i-th of the sonic transducer node to sound source, m
To the additive noise of i-th of microphone acquisition signal of node.
2 Time Delay Estimation Algorithms
2.1 extracting relative phase ratio
In many auditory localization algorithms, it only used the amplitude for receiving signal, have ignored phase information.However it is based on phase
The reaching time-difference estimation mechanism of potential difference can show higher precision.It needs that signal progress will be received before carrying out time delay estimation
Pretreatment, to extract the frequency domain information of signal, detailed process is as shown in Figure 3.Opposite signal collected to sensor node of m
Phase ratio PRP are as follows:
2.2 relative phases are than collection
By two paths of signalsWithIt is related that sliding is carried out in the time domain, and signal length N has 2N-1 after carrying out cross-correlation
A time delay value, D are all possible TDOA set, TsFor the sampling time.Assuming that be that W- is separated orthogonal for the acoustical signal of acquisition, this
The each time frequency point of sample is relevant, predefined relative phase collection to each time delay valueAre as follows:
2.3 recurrence maximal possibility estimation RDEM
By to the above relative phase than set analysis, the relative phase ratio PRP of each sensor node and each time frequency point
Can be used to lower statistical model indicates, it may be assumed that
Wherein ψdFor in the estimated probability of d-th of time delay value of time frequency point (t, k), Nc(.；.；) indicate that variance is σ2Complexity
Gaussian probability, it may be assumed that
Wherein
Recurrence maximum likelihood estimate is being derived, and grid coordinate search on two-dimensional space is converted in the one-dimensional space
The search of step-out time can derive its probability density function are as follows:
By asking a series of derivation such as local derviation to find out probability density function maximum value, when can finally obtain t moment d-th
Prolong the probability Estimation of value are as follows:
The average probability of d-th of time delay value of t moment is estimated are as follows:
It is realized by the processing that mono- frame of recurrence maximal possibility estimation RDEM connects a frame and the TDOA of moving target is estimated.It is passed
Return parameterEquality initialization is carried out in t=0, the parameter Estimation of each frame passes through Recursive Implementation later, it may be assumed that
Wherein: φm(t, k) is the phase difference that m acquires signal to node,It is every that signal is acquired for i-th of node
A time frequency point signal amplitude,The mould of each time frequency point signal of signal is acquired for i-th of node；For all time delays
The phase difference set of value, TsFor the sampling time, k=0 ..., K are frequency index, and d is time delay value；For each possibility of t moment
The averaged power spectrum probability of TDOA value,For the probabilistic estimated value of d-th of time delay at each frequency point of t moment, K is that frequency point is total
Number；For the probabilistic estimated value of all possible time delay value of t moment,Estimate for all possible being averaged for time delay value of t moment
Count probability, γtIndicate recursive smoothing parameter, value range is (0,1).
2.4 algorithms are realized
Estimation in the present invention based on relative phase than carrying out step-out time with recursive maximum likelihood algorithm, each frame signal
Data length be N, sample rate fs, the algorithm flow block diagram is as shown in Figure 4.The specific implementation steps are as follows:
Step 1: in t moment, by the signal of acquisitionWithIt is related to carry out sliding, obtains possibility between this two paths of signals
Time delay section [(1-N)/fs,(N-1)/fs]；
Step 2: time-frequency domain conversation.By signalWithIts frequency domain presentation is obtained using Short Time Fourier TransformWith
Step 3: calculating relative phase ratio.The opposite phase between t moment two signals of each frequency point is calculated using formula (2)
Compare φ in positionm(t,k)；
Step 4: calculating relative phase than set.The opposite of each possibility each frequency point of time delay d is calculated using formula (3)
Phase ratio, and summarized and constitute relative phase than set
Step 5: estimated probability initialization.Equality initialization is carried out to the probability parameter of each possible time delay value
Step 6: calculation delay estimated probability.Using formula (5) and formula (7), each possible time delay value of t moment is calculated
Averaged power spectrum probability
Step 7: obtaining time delay value.Time delay value corresponding to maximum value in the resulting averaged power spectrum probability of previous step is made
For signalWithReaching time-difference；
Step 8: recursive estimation parameter.Using formula (9) based on the resulting estimation parameter of previous frame to the probability of next frame
Parameter is estimated
Application effect of the invention is explained in detail below with reference to emulation.
1 simulation analysis
Assuming that there are two sensors 1 and 2 to form acoustic sensor array, z1(t) signal received for sensor 1 is energy
It is enough to obtain accurate theoretical time delay value, two groups of emulation experiments are carried out respectively, and experiment is first is that two paths of signals data length is 1024
Sampled point, by signal z1(t) signal z is obtained after postponing different sampled points2(t), z is used2(t) the received letter of analog sensor 2
Number.Experiment is second is that add different Gaussian noises for two signals, data length is 1024 sampled points.In order to verify difference
Influence of the data length to experimental result precision, carry out third group emulation experiment, test third is that data length is set to
1024 sampled points and 1300 sampled points, by signal z1(t) signal z is obtained after postponing 720 sampled points2(t), z is used2(t) mould
Quasi- 2 received signal of sensor, compares influence of the different data lengths to Time delay Estimation Accuracy.Sample frequency is 61kHz, it is assumed that
Sound-source signal is incoherent with noise.Using being combined using relative phase ratio and recurrence maximal possibility estimation for above-mentioned introduction
TDOA algorithm for estimating carry out simulating, verifying.
2 emulation experiments
Emulation experiment 1
Signal z2(t) relative to signal z1(t) postpone 180,360,540 sampled points, i.e., corresponding delay time point respectively
Not Wei 0.0029s, 0.0059s, 0.0088s, shown in the time delay acquired respectively such as Fig. 5 (a), Fig. 5 (b), Fig. 5 (c).
Emulation experiment 2
Two signals are added into different Gaussian noises, signal z respectively2(t) relative to signal z1(t) postpone 180 respectively,
360,540 sampled points, i.e., corresponding delay time are respectively 0.0029s, 0.0059s, 0.0088s, the time acquired respectively
(a) of delay such as Fig. 6, shown in Fig. 6 (b), Fig. 6 (c).
Emulation experiment 3
By signal z1(t) signal z is obtained after postponing 720 sampled points2(t), data length is set to 1024 and 1300
When sampled point, shown in the time delay acquired such as Fig. 7 (a), Fig. 7 (b).
By observing above three groups of the simulation experiment results, experiment 1 and experiment 2 are compared, from Fig. 5 and Fig. 6
As can be seen that postponing in 720 sampled points, this method may occur in which apparent peak value, can in the lower situation of signal-to-noise ratio
Accurately estimate the reaching time-difference TDOA of sound source.In experiment three, adopted from figure 7 it can be seen that data length is 1024
When sampling point, 2 relative signal 1 of signal postpones do not have apparent peak value when 720 sampled points, has in this way to the precision of Delay Estima-tion
Very big influence, and when data length is increased to 1300 sampled points, when postponing 720 sampled points, still can be accurate
Time delay estimated value out.It can thus be seen that the precision that data length estimates time delay has a very big impact.
In order to verify the Time delay Estimation Accuracy of the algorithm, taking 10 groups of length is the data of 1024 sampled points, to delay
0.0029s, 0.0059s, 0.0088s, 0.0118s calculate separately its mean square error.
The mean square error of 1 1024 sampled point different delays of table
The mean square error of 2 1300 sampled point different delays of table
The present invention is based on relative phase ratio and maximal possibility estimation principles, with higher in the lower situation of signal-to-noise ratio
Time delay Estimation Accuracy, but the precision of its time delay estimation is also influenced by data length, and data length determines that algorithm institute can essence
The range for the time delay value really estimated demonstrates the validity of above-mentioned algorithm finally by emulation experiment.Major advantage is not depend on
The priori knowledge of signal and noise, step-out time value can accurately be estimated by choosing suitable data length.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (6)
1. a kind of acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, which is characterized in that described to be based on phase
The acoustical signal delay time estimation method of potential difference and maximal possibility estimation is under noise background, simultaneously using acoustic sensor array acquisition signal
It is pre-processed to obtain frequency-region signal by cross-correlation function and Short Time Fourier Transform；Calculate the relative phase of two-way acoustical signal
Than and combine the principle of maximum- likelihood estimation to obtain the probability of all possible time delay estimated value；It is not depending on signal and is making an uproar
Under conditions of sound priori knowledge, using time delay value corresponding to maximum probability peak value as final time delay estimated value；
It is described based on phase difference and maximal possibility estimation delay time estimation method the following steps are included:
Step 1, in t moment, by the signal of acquisitionWithIt is related to carry out sliding, obtains possible between this two paths of signals
Time delay section [(1-N)/fs,(N-1)/fs]；
Step 2, time-frequency domain conversation, by signalWithIts frequency domain presentation is obtained using Short Time Fourier Transform
With
Step 3 calculates relative phase ratio, calculates the relative phase ratio φ between t moment two signals of each frequency pointm(t,k)；
Step 4 calculates relative phase than set, calculates the relative phase ratio of each possibility each frequency point of time delay d, and by its
Summarize and constitutes relative phase than set
Step 5, estimated probability initialization carry out equality initialization to the probability parameter of each possible time delay value
Step 6, calculation delay estimated probability calculate the averaged power spectrum probability of each possible time delay value of t moment
Step 7 obtains time delay value, using time delay value corresponding to the maximum value in resulting averaged power spectrum probability as signalWithReaching time-difference；
Step 8, recursive estimation parameter estimate the probability parameter of next frame based on the resulting estimation parameter of previous frame
2. the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, feature exist as described in claim 1
In described to estimate model based on phase difference and maximal possibility estimation delay time estimation method reaching time-difference TDOA, wherein t=
1 ..., T are the time index of signal time domain, and k=0 ..., K are frequency index, share M to sensor node, then i-th of section
The signal model of point acquisition are as follows:
WhereinRespectively i-th of sonic transducer node to sound source sound transfer function, the m pairs
The additive noise of i-th of microphone acquisition signal of node.
3. the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, feature exist as described in claim 1
In in the step 3:
φm(t, k) is the phase difference that m acquires signal to node,The each time frequency point letter of signal is acquired for i-th of node
Number amplitude,The mould of each time frequency point signal of signal is acquired for i-th of node.
4. the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, feature exist as described in claim 1
In in the step 4:
TsFor the sampling time；For the phase difference set of all time delay values, TsFor the sampling time, k=0 ..., K are under frequency
Mark, d is time delay value.
5. the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, feature exist as described in claim 1
In the average probability estimation of d-th of time delay value of t moment in the step 6 are as follows:
For the averaged power spectrum probability of each possibility TDOA value of t moment,For d-th of time delay at each frequency point of t moment
Probabilistic estimated value, K be frequency point sum.
6. the acoustical signal delay time estimation method based on phase difference and maximal possibility estimation, feature exist as described in claim 1
In in the step 8:
For the probabilistic estimated value of all possible time delay value of t moment,Estimate for all possible being averaged for time delay value of t moment
Count probability, γtIndicate recursive smoothing parameter, value range is (0,1).
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| CN108957403B (en) * | 2018-06-09 | 2022-07-12 | 西安电子科技大学 | Gaussian fitting envelope time delay estimation method and system based on generalized cross correlation |
| CN109116301B (en) * | 2018-08-14 | 2023-02-28 | 中国电子科技集团公司第三十八研究所 | Time difference of arrival measuring method based on confidence degree estimation |
| CN109633554A (en) * | 2019-01-18 | 2019-04-16 | 浙江大学 | Moving sound based on probabilistic data association reaches delay time estimation method |
| CN109633538B (en) * | 2019-01-22 | 2022-12-02 | 西安电子科技大学 | Maximum likelihood time difference estimation method of non-uniform sampling system |
| CN110657864B (en) * | 2019-10-08 | 2020-12-18 | 三门核电有限公司 | Sensor response time measuring method |
| CN111832708B (en) * | 2020-07-31 | 2022-05-24 | 东南大学 | Narrow-band signal time difference estimation system based on long-term and short-term memory network |
| CN115118634B (en) * | 2021-03-19 | 2023-08-11 | 大唐移动通信设备有限公司 | Method, device, equipment and storage medium for measuring transmission delay |
| CN113766150B (en) * | 2021-08-31 | 2024-03-26 | 北京安酷智芯科技有限公司 | Noise reduction method, circuit system, electronic equipment and computer readable storage medium |
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