CN106411438A - Shallow water time-varying multi-path underwater acoustic channel modeling method - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
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- H—ELECTRICITY
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- H04B17/0082—Monitoring; Testing using service channels; using auxiliary channels
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Abstract
The present invention discloses a shallow water time-varying multi-path underwater acoustic channel modeling method. According to the method, modeling is carried out for an underwater acoustic channel through adopting a theoretical analysis and experimental verification-combined method; underwater acoustic channel fading is modeled as large-scale fading and small-scale fading, namely, the underwater acoustic channel can be expressed as a plurality of clusters of paths with different amplitudes, delay and phases; large-scale fading parameters are obtained through calculation and by means of ray theory model-based BELLHOP software; amplitudes in small-scale fading parameters are modeled as Rician distribution, delay in the small-scale fading parameters is modeled as an AR (p) model, phases in the small-scale fading parameters are modeled as uniform distribution from 0 to 2Pi, and Doppler of the small-scale fading parameters is modeled as deterministic Doppler and stochastic Doppler; the model is greatly matched with an actually measured channel; and the model can provide support for underwater communication receiver design, network performance evaluation, optimal configuration and the like.
Description
Technical field
The invention belongs to Wireless Channel Modeling field, it is related to a kind of shallow water time-varying more than way underwater acoustic channel modeling method.
Background technology
The complex characteristics of underwater acoustic channel propose very big choosing to the design of underwater sound communication system and underwater sound communication network
War.In order to preferably design underwater acoustic receiver and realize distributing rationally of Internet resources, the interference that antagonism underwater acoustic channel introduces,
Grasp to underwater acoustic channel characteristic is very necessary.Underwater sound communication is a subject focusing on very much testing, and underwater sound field trial
Condition is very arduous, often will expend substantial amounts of human and material resources and financial resources, and have non-repeated.Therefore how
Set up a kind of channel model that can simulate true underwater acoustic channel environment, the design for underwater sound communication system and network and performance
Assessment etc. has important Research Significance.
At present underwater acoustic channel is modeled mainly from two aspects：One is to provide channel difference physics by theory analysis
The statistical model of parameter, such as amplitude, the distribution character of time delay, the time of parameters, spatial correlation characteristic etc., then pass through examination
Test data to be verified；Two is the statistical model by analyzing the parameters that measured data obtains, then according to this result pair
Channel is modeled.Underwater acoustic channel is extremely complex, causes the factor of underwater acoustic channel structure and composition very many, by theory analysis
Go modeling underwater acoustic channel extremely difficult, but still can provide the principal element of impact channel architecture by theory analysis.Logical
The result crossing measured data analysis carries out Channel Modeling, closer to actual underwater acoustic channel, but can have great limitation
Property.Underwater acoustic channel characteristic is affected by very many factors such as time, geographical position, sound source/receiver location, distances, and surveys
The result of examination is also affected by test signal and signal processing method, such as finite bandwidth, finite time/frequency resolution
Deng, but the method still can play certain directive function to Channel Modeling.
List of references 1 (B.Tomasi, G.Zappa, K.McCoy, P.Casari, and M.Zorzi.Experimental
study of the space-time properties of acoustic channels for underwater
communications[C].in Proc.IEEE OCEANS Conference.Sydney,NSW,2010,pp:1-9) basis
The environmental model of known test site rerun BELLHOP model produce a series of channel impulse responses, then according to should
Result carries out estimating the statistical property of channel, and the change such as temperature and salinity etc. of environment takes into account in this model, yet with only
Consider component environment parameter, without considering the factors such as water surface fluctuating, lead to simulation result and actual measured results presence poor
Different.List of references 2 (P.Qarabaqi, M.Stojanovic.Statistical Characterization and
Computationally Efficient Modeling of a Class of Underwater Acoustic
Communication Channels[J].IEEE Journal of Oceanic Eng.2013,38(4),pp:701-717)
Propose a kind of underwater acoustic channel modeling method it is contemplated that the motion that causes of the relative motion of emittor/receiver, water surface stormy waves with
And the Doppler frequency deviation that causes of factor such as floating, and consider multipath fading model, but by multipath fading parameter time delay
It is modeled as AR (1) model, fitting result experimental result deviation is larger.The application adopts the method for theory analysis Binding experiment to shallow
Water underwater acoustic channel is modeled, and modeling result is preferable with experimental result matching.
Content of the invention
Present invention aim at providing a kind of shallow water time-varying more than way underwater acoustic channel modeling method, can reduce by testing handss
Section carries out the consumption of human and material resources and the financial resources that Performance Evaluation brings etc. to the communication of algorithms, thus effectively improving algorithm development effect
Rate.
Realize the object of the invention technical scheme：
Step 1：Setting simulated environment parameter, calculates large scale fading parameter αp,0And τp,0, αp,0For complex magnitude, wherein imitative
True parameter includes Larger water depths, sends and receives node and lay depth, send and receive the distance between node, and sound velocity gradient divides
Cloth, water-bed water-surface reflection coefficient, transmitting transducer angle of release etc., arrange different simulation frequency, run BELLHOP and are calculated not
Transfer function H (f) under same frequency, H (f) is carried out inversefouriertransform, obtains channel impulse response, and this result is certain a period of time
The large scale fading parameter carved；
Step 2：Setting multipath fading parameter, sets scattering path number Sp, each scattering path amplitude alphapVarianceDelay, τpVarianceTime delay obeys the exponent number p of AR model, the parameters of AR (p) model；
Step 3：Setting Doppler parameter, arranges definitiveness Doppler factor ap,0Or the uniform motion speed of equivalence
vp,0, random Doppler factor a is setp,iVariance
The device have the advantages that：
The present invention is verified by theory analysis Binding experiment, has modeled a kind of shallow water time-varying more than way underwater acoustic channel model, should
Model can be very good to simulate multi-path effect, time-varying characteristics of shallow water underwater acoustic channel etc., can be used for analyzing underwater acoustic channel to letter
Number introduce interference, thus being estimated to the performance of underwater sound communication and network algorithm and predicting, and appropriate design receiver calculate
Method and optimization of network performance, can effectively reduce the damage of the human and material resources bringing by outfield experiments checking, financial resources etc.
Consumption, is simultaneously available for the emulation of substantial amounts of repetition, solves the nonrepeatability in outfield experiments and non-repeated.
Brief description
Fig. 1 is time-varying more than way underwater acoustic channel modeling procedure；
Fig. 2 is Lake Lianhuahu testing position figure；
Fig. 3 is distributed for Lake Lianhuahu sound velocity gradient；
Fig. 4 is actual measurement time varying channel system function (a) impulse response；(b) transfer function；(c) spread function；(d) double frequency
Function；
Fig. 5 is probability density distribution and L-S distribution fitting result (a) the first paths gain of each path gain；
(b) Article 2 path gain；The gain of (c) third path；(d) Article 4 path gain；
Fig. 6 is that time coherence coefficient (a) of channel impulse response removes the coherence factor before definitiveness Doppler；(b)
Remove the coherence factor after definitiveness Doppler；
Fig. 7 be 0～20s time in, before not removing definitiveness Doppler, when p takes different value, AR (p) data matching with
Fitting result during experimental data comparing result (a) p=1；Fitting result during (b) p=2；Fitting result during (c) p=4；
Fitting result during (d) p=8；
Specific embodiment
With reference to specific embodiment, further describe shallow water time-varying more than way underwater acoustic channel modeling method and its beneficial
Effect.
(1) basic model
The time-domain expression of conventional time-varying more than way underwater acoustic channel is shown below：
Wherein, (pth paths complex gain is α to channel h for τ, t) common P pathspT (), time delay is τp(t).Consider that presence is many
It is assumed that there is not acceleration in the situation of general Le, if the Doppler factor of pth paths is ap, then formula (1) can be expressed as
Wherein, Doppler factor is defined as ap=vp/ c, vpFor pth paths movement velocity in the horizontal direction, and define
Move toward one another is that just relative motion is negative, and c is the velocity of sound in water.Due to scattering process, every paths all expand to cluster path,
If comprising I single sub path in every cluster path, then formula (2) can be expressed as again
Wherein, αp,i(t)、τp,i(t) and ap,i(t) be respectively the complex gain of the i-th paths in pth cluster path, time delay and
Doppler factor.Here, τp,iT () refers to propagate, by signal, the time delay causing, the time delay in total path also includes Doppler and draws
Time delay a risingp,i(t)t.Channel impulse response is really a series of superposition of intrinsic sound rays, and due to scattering process, every intrinsic
Sound ray expands to cluster path, and therefore every cluster path can be expressed as the superposition of main path and its scattering path, then path increases again
Benefit and time delay can be expressed as again
Wherein, αp,0And τp,0It is defined as large scale fading parameter, for the more stable path parameter in this cluster path, can
To be calculated by running BELLHOP.δαp,iWith δ τp,iIt is defined as multipath fading parameter, this parameter can be by theoretical point
The method of analysis binding tests data analysiss obtains.
Channel delay one side is propagated due to signal and is caused, and is on the one hand because Doppler frequency deviation introduces.Equally
It is considered to scattering process, Doppler frequency deviation can also represent
Wherein, average ap,0Definitiveness Doppler, δ a can be regarded asp,iCan be regarded as random Doppler.Assume to determine
Property Doppler caused by uniform motion, causes the main cause of uniform motion to include the active exercise of sending and receiving end and stormy waves causes
Relative motion etc., only considers constant speed part therein, and the Doppler that nonuniform motion causes is classified as in random Doppler, causes
Motion heterogeneous also includes interior ripple, turbulent flow etc..Therefore, Doppler can be modeled as definitiveness Doppler and random Doppler two
Part, definitiveness Doppler can be calculated by setting speed of related movement of equal value, and random Doppler assumes to obey height
This distribution.
(2) large scale decline
Uncertainty due to geographical position and the velocity of sound will cause the change of channel gain and time delay, and this uncertainty is general
It is modeled as change at random.At short notice it is considered that channel large scale fading parameter is constant, therefore this parameter can pass through ripple
Bundle tracer tools BELLHOP is calculated.Through after a period of time, need again to calculate large scale decline ginseng according to ambient parameter
Number, thus obtain a series of time dependent large scale fading parameters.It is described in detail below how using BELLHOP meter
Calculate large scale fading parameter.
BELLHOP ray model is M.Porter by USN's marine acoustics et al. exploitation, by inputting the velocity of sound
Gradient, sound source and the parameter such as receiver depth, the depth of water, receiving range, seafloor density and sea water absorption coefficient, can be calculated
The information such as intrinsic sound ray, propagation loss, the amplitude receiving sound ray and time delay.But BELLHOP is the channel propagated based on arrowband
Model, and actual underwater sound communication channel is often a broad-band channel.For channel impulse response, the path delay of time mainly takes
Certainly in path and the velocity of sound, path gain is affected by propagation loss and absorptance.Propagation loss and distance dependent, with
Frequency is unrelated, and absorptance is relevant with frequency, and therefore different frequencies mainly affects absorptance and increases thus affecting its path
Benefit.Frequency is the signal propagation distance of f is that during l, gain of received signal can be expressed as
A (l, f)=A0lka(f)l(7)
Wherein, A0It is a constant, k is spreading factor, and a (f) is absorptance, according to the every km of Thorp empirical equation
Absorption decibels can be expressed as：
Because shallow water underwater acoustic channel is broad-band channel it is therefore desirable to calculate the absorptance under different frequency, thus calculating
Large scale fading parameter under different frequency.If a width of B of underwater acoustic channel band, whole bandwidth is divided into N part it is assumed that each subband
Wide BiAbsorptance approximately equal in=B/N, the absorptance calculating respectively in each frequency band obtains a (f), thus obtaining a certain
Channel transfer function H (f) in moment, transfer function is carried out inversefouriertransform, you can to obtain the channel impulse in this moment
Response, is shown below：
Wherein P is total path number, αp,0And τp,0It is respectively and complex gain and time delay.Because scattering etc. acts on, one
Intrinsic sound ray path often expands to cluster sound ray, and the channel fading now causing is referred to as multipath fading, is situated between in detail below
Continue the modeling of multipath fading.
(2) multipath fading
Formula (4) and (5) give multipath fading parameter δ αp,iWith δ τp,iIt is considered to wherein one paths, because scattering is made
With paths are dispersed into many little paths, if every cluster path scattering path number is Sp, each scattering path is independent same
Distribution, according to central limit theorem, when scattering path number is sufficiently large, path gain δ αp,iObey multiple Gauss to divide
Cloth, large scale fading parameter αp,0It is considered as the average of this cluster path complex gain, therefore δ αp,iBeing considered as average is 0 variance
ForComplex variable.If scattering coefficient δ αp,iReal part imaginary part there is the variance of equal (or approximately equal), then envelope clothes
From L-S distribution.
Equally, the time delay in every cluster path is considered as average and for 0 variance isGauss distribution, underwater acoustic channel is part
Coherent channel although due to scattering process lead to channel coherency time decline, but within the observing time of coherence time length
Scattering component still can regard relevant as, and the channel impulse response phase place in therefore former and later two moment has relatively-stationary
Phase contrast, namely relatively-stationary time delay.So now multipath fading parameter time delay δ τp,iOne group can be expressed as and have one
The data of phased relationship number.Assume time-delay series δ τp,iObey AR (p) (p>1) model is that is to say, that the channel shape of current time
State is not only relevant with the channel status of previous moment, also relevant with the state in several moment front.In order to distinguish in AR (p) model
P and pth paths in p, AR (p) to represent with AR (q), then δ τp,iCan be expressed as with AR (q) model
δτp,i(t)=μ1δτp,i(t-1)+μ2δτp,i(t-2)+...+μqδτp,i(t-q)+ε(t) (10)
μ1,μ2,...,μqIt is unable to identically vanishing.δτp,iAutocorrelation coefficient can be expressed as
ρ (k)=μ1ρ(k-1)+μ2ρ(k-2)+...+μqρ (k-q) k ＞ 0 (11)
Autocorrelation coefficient can be further represented as
Wherein,It is characterized equationRoot, L be k hysteresis factors.For ensure with
The stationarity of machine process it is desirable to | Gi| ＜ 1.
According to above-mentioned introduction, time-varying more than way underwater acoustic channel modeling procedure can be summarized as shown in Figure 1.
(3) experimental verification
This channel test is tested and is carried out in Heilongjiang Province Hailin City Lake Lianhuahu region in October, 2012.Average water at test
Deep 18m, receives and transmitting node hangs depth and is 4 meters, and transmitting-receiving ship is in state of freely drifting.Communication distance is initially about
2km, due to the impact of stormy waves, there is relative motion in two ships, and two ship relative distances are also gradually changing, two accommodation during test
Put schematic diagram as shown in Figure 2.
In experiment, estimate channel, each two LFM using multiple continuous linear frequency modulation (LFM) signals as detectable signal
Protection interval between signal is 100ms.A length of 20～150ms during LFM signal, signal bandwidth is 4k-8kHz, every 150 LFM
Signal continuously transmits for one group, and every group of signal duration is about 20s, and between every group of signal, time interval is about 500ms, letter
Number continuously transmit 10 minutes.The sound velocity gradient that records in process of the test is as shown in figure 3, the surface depth velocity of sound that is less than 4 meters about
It is distributed in negative gradient, when depth is more than 4 meters about, the velocity of sound is in faint positive gradient, and generally, sonic velocity change is little.
The LFM train of pulse receiving is carried out with copy related, channel impulse response not in the same time can be obtained.Before test
In 20s, as shown in figure 4, Fig. 4 (a) is channel impulse response, there are 4 clusters in this in figure to the four systemses function of channel more obvious
Path, as shown in figure p1～p4, the five, the six cluster path p5, p6 energy comparisons are faint, are not very stable, can ignore.From figure
4 (b) transfer function can be seen, the frequency selective fading of channel is obvious, and declines and uneven, and band segment is in deep
Degree decline.
From Fig. 4 (c) spread function it is clear that channel all has a certain degree of broadening in time domain and frequency domain, when
The broadening in domain is caused by scattering, and the broadening of frequency domain is caused by Doppler, Doppler frequency shift probable ranges be 0.6Hz～
1.2Hz, this point in Fig. 4 (d) it can also be seen that.Because communication channel is broad-band channel, different frequencies has different
Doppler frequency shift, therefore Doppler frequency shift are not single-frequencies, and test channel width is 4kHz～8kHz, is launched by contrast
The time span of signal and the time span of receipt signal, it is estimated that Doppler factor is 1.5e-4, can be calculated
Doppler frequency shift scope is 0.6Hz～1.2Hz, identical with actual test result.
Fig. 4 (d) gives the dual-frequency function of channel, and what this figure was apparent indicates Doppler frequency shift with becoming that frequency changes
Gesture, with the increase of frequency, Doppler frequency shift increases.Simultaneously for a certain frequency, this Doppler frequency shift is not single
, but there is certain width in value, namely in addition to there is a stable Doppler frequency shift, also exist one random many
Pu Le, that this random Doppler may be caused by interior ripple, turbulent flow etc. or (and) transmitter and receiver that caused by stormy waves
Random floating causes.
We analyze the statistical property of each path gain below.Remove definitiveness Doppler first, then find
All paths at every cluster path maximum of points and decline 3dB, root-mean-square (rms) value counting this cluster path is as this cluster path
Gain.Fig. 5 gives the probability density distribution of 4 cluster path gains and the result of Rice chart matching, and in figure black I shape line is given
Go out the value that each bar shaped rod confidence interval of rectangular histogram is 95%.From the figure, it can be seen that this fitting result major part of Lay all falls
In confidence interval.Table 1 gives parameter A, σ of the L-S distribution of matching2Estimated result and fitting result and actual measurement with K
The root-mean-square error (RMSE) of result, the probability density function of wherein L-S distribution is
Wherein, A is the peak value of main signal amplitude, σ2It is the power of multi-path signal-component, I0() is 0 rank first revised
Class Bessel function, Rice factor K is defined as power and the multipath component power ratio of main signal, that is,
Can see from table 1, the mean square error of each cluster path fitting is all smaller, and fitting result is relatively good, with theory
The path of analysis is obeyed L-S distribution result and is matched.The Rice factor in the 2nd cluster path is maximum, next to that the 1st, 3,4 cluster paths,
Rice factor is bigger, represents that the main footpath in this path is more powerful, path is more stable, matches with Fig. 5 (a) result.
This data matching average of table 1 Lay and the root-mean-square error of variance and estimation
Observe the time dependent characteristic of a lower channel below.First, defining channel time coherent function is
Wherein, h (t) is the channel impulse response in t,*Represent the conjugation of signal, after h (t+ τ) is the time delay τ time
Channel impulse response.Remove in 0～120s and determine that the channel coherence factor before and after Doppler is as shown in Figure 6.0～
The determination Doppler factor estimated in six time periods of 120s be respectively 1.5e-4,1.35e-4,1.0e-4,0.65e-4,
0.2e-4 and -0.51e-4, Doppler factor is gradually reduced, and then inversely increases, and can see from Fig. 6 (a), from overall next
Say, increase over time, channel coherence factor is gradually reduced, the different channel coherence factor of different movement velocity correspondences.
With the reduction of Doppler factor, channel coherence factor is gradually increased, and between 80～100s, Doppler factor is minimum, is concerned with
Coefficient is maximum, is all higher than 0.7, then speed of related movement reversely increases in observation time, and Doppler factor increases, phase responsibility
Number declines again therewith.
Can see from Fig. 6 (b), after removing determination Doppler, in the time range of 20s, channel coherence factor is equal
Maintain more than 0.8, partially coherent coefficient maintains more than 0.9.The channel more tranquil for the water surface is described, removes determination many
After Pu Le, channel changes over and yet suffers from very high coherence.After removing determination Doppler, channel coherence factor is still deposited
In certain decline and fluctuation.
The distribution characteristicss of lower surface analysis once time coherence coefficient.It is assumed above that time coherence coefficient obeys AR (p) distribution,
, when Fig. 7 gives p and takes different value taking channel in 0～20s as a example, the contrast of experimental data and fitting result, the RMSE of matching is such as
Shown in table 2.Can see from Fig. 7 and Biao 2, as p=1, fitting result error is very big.Within a period of time starting, phase
Responsibility number assumes more obvious exponential damping, but increases over time, and decay assumes the form of concussion, and AR (1) is no
Method describes the decay of this form well.It can be seen that error of fitting is less and less after AR matching using high-order.Below with
Another group of example proves the reasonability of high-order AR matching proposed by the present invention further.
When table 2p takes different value, the root-mean-square error of AR (p) matching
Claims (5)
1. a kind of shallow water time-varying more than way underwater acoustic channel modeling method it is characterised in that：
Step 1：Setting simulated environment parameter, calculates large scale fading parameter αp,0And τp,0, αp,0For complex magnitude, wherein emulation ginseng
Number includes Larger water depths, sends and receives node and lay depth, send and receive the distance between node, sound velocity gradient is distributed,
Water-bed water-surface reflection coefficient, transmitting transducer angle of release etc., arrange different simulation frequency, run BELLHOP and are calculated difference
Transfer function H (f) under frequency, H (f) is carried out inversefouriertransform, obtains channel impulse response, and this result is a certain moment
Large scale fading parameter；
Step 2：Setting multipath fading parameter, sets scattering path number Sp, each scattering path amplitude alphapVariance
Delay, τpVarianceTime delay obeys the exponent number p of AR model, the parameters of AR (p) model；
Step 3：Setting Doppler parameter, arranges definitiveness Doppler factor ap,0Or uniform motion speed v of equivalencep,0If,
Put random Doppler factor ap,iVariance.
2. the large scale fading parameter computational methods according to described in claim 1 step 1 it is characterised in that：In the short time
Inside think that large scale fading parameter is constant, according to ambient parameter, run and obtained based on the theoretical BELLHOP computed in software of geometrical acoustics
To the large scale fading parameter in a certain moment, As time goes on, ambient parameter such as transmitting-receiving node distance, Larger water depths etc.
Changing, again new large scale fading parameter being calculated according to new ambient parameter, thus obtaining a series of changing over
Large scale decline channel impulse response.
3. the setting multipath fading parameter according to described in claim 1 step 2 it is characterised in that：Multipath fading by
The factors such as scattering cause, and the paths showing as channel impulse response expand to cluster path, if every cluster path scattering path
Number is Sp, each scattering path is independent identically distributed, according to central limit theorem, when scattering path number is sufficiently large
When, path gain δ αp,iObey multiple Gauss distribution, large scale fading parameter αp,0It is considered as the average of this cluster path complex gain,
Therefore δ αp,iBeing considered as average for 0 variance isComplex variable, if scattering coefficient δ αp,iReal part imaginary part have equal
The variance of (or approximately equal), then envelope obedience L-S distribution.
4. the setting multipath fading parameter according to described in claim 1 step 2 it is characterised in that：Every cluster path when
Prolong and be considered as average and for 0 variance beGauss distribution it is considered to the coherence of underwater acoustic channel, the i.e. letter in former and later two moment
Channel shock response has relatively-stationary phase contrast, in other words relatively-stationary delay inequality, therefore models multipath fading parameter
Time delay obeys AR (p) model, represents that current channel parameters are relevant with the channel parameter in front p moment, the value of p and AR model
Parameter is relevant with channel coherency time.
5. the setting Doppler factor according to claim 1 step 3 it is characterised in that：Doppler is modeled as two classes, one
Plant being to determine property Doppler, can be calculated by arranging the movement velocity of Doppler factor or equivalence；One kind is random
Doppler, can obtain its probability-distribution function by the method for statistics, be modeled as the Gauss distribution of zero-mean.
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