CN107728109A - A kind of noncooperative target radiated noise measurement and positioning technology - Google Patents
A kind of noncooperative target radiated noise measurement and positioning technology Download PDFInfo
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- CN107728109A CN107728109A CN201710837758.4A CN201710837758A CN107728109A CN 107728109 A CN107728109 A CN 107728109A CN 201710837758 A CN201710837758 A CN 201710837758A CN 107728109 A CN107728109 A CN 107728109A
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
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Abstract
The invention discloses a kind of noncooperative target radiated noise measurement and positioning technology, based on vector hydrophone e measurement technology, acoustic pressure, the vibration velocity reception model of vector hydrophone are constructed, utilizes the acoustic pressure vibration velocity joint processing technology of vector hydrophone, using cross-spectrum sound intensity technique, the measurement azimuth of baseline is obtained；Target location coordinate information measured by every group of baseline is resolved by triangle Convergence method.Positioning for more vector hydrophones, the combination of two of vector hydrophone is can be considered, then again by Data Fusion technology, the measurement result of comprehensive all baselines, determine the position of each measurement point of moving target.Postpositive disposal finally is carried out using Kalman filtering algorithm, the track of moving target is further optimized.Data fusion technique combination Kalman filtering algorithm can improve positioning precision, and the movement locus of target is fast, accurately oriented in a small range, solve the problems, such as that two hydrophone positioning precisions are poor, tracking velocity is slower.
Description
Technical field
The present invention relates to noise testing technical field, and in particular to a kind of noncooperative target radiated noise measurement and positioning skill
Art.
Background technology
Noise testing technology (noise measuring technique) noise testing includes various noise sources and noise field
The measurement of fundamental characteristics parameter；The sound absorption used in Noise measarement and sound insulating material, the acoustical behavior measure of damping material；
Technology efficiency evaluation measurement of the control measure such as sound absorption, sound insulation, Amortization ＆＆ Damping, vibration isolation etc..In addition, research noise on human body
The subjective assessment for influenceing and endangering, being carried out to noise, formulate the work such as various Standards of Environmental Noise and noise testing offer is provided
The foundation of science.It is accurately finished these measurement needs of work and uses various technological means.
Noise testing technology can receive the radiated noise of target, obtain its acoustic information, can provide and refer to for vibration and noise reducing
Lead suggestion.And between submarine target and measurement point distance accurate measurement, be target sound source level calculate key.Passive sonar
Target ship-radiated noise is broadband, and the noise intensity on different frequency is different.Reflect sound source radiation noise intensity pair
The amount of frequency dependence, referred to as sound source spectrum level, be at 1 meter away from sound source radiated noise near certain single-frequency in 1HZ bandwidth
The sound intensity relative to the decibels of reference sound intensity, represented with SLs.Due to the complicated mechanism of ship-radiated noise, SLs is difficult to lead to
Theoretical calculation is crossed to obtain, it is necessary to carry out actual measurement.In conventional noise measuring system, it is to utilize cooperation beacon, obtains same pacing
Away from information.But it can not be realized for noncooperative target, this method.Because vector hydrophone simultaneous can obtain the scalar sum arrow of target
Information is measured, measurement capability can be lifted, used in noise measurement system.Therefore herein based on vector hydrophone measurement skill
Art, utilize vector hydrophone orientation estimated result, using data fusion method, the data message for obtaining more vector hydrophones
It is fully utilized, quickly and accurately orients the movement locus of target in a small range, solve domestic noise testing at present
The problem of noncooperative target can not being accurately positioned in system.
Deng Xiu China et al. have studied method (the Deng Xiu China self-conductance canister missdistances measurement side that synchronic distance accurately measures
Method research marine electronic engineerings, 2012, Vol.32No.10), it is provided with synchronous acoustic marker in target, can not realize to non-
The measurement of cooperative moving targets；Wu Yan group et al. have studied vector hydrophone bearings-only target motion analysis method (Wu Yanqun,
Waterborne target motion analysis acoustic techniques of the Hu Yongming based on single vector hydrophone, 2010,1000-3630 (2010) -04-
0361-04), it can carry out orientation estimation using single vector hydrophone to target, a wide range of interior to moving target progress
Tracking measurement, but this method tracking velocity is slower, positioning precision can not meet measurement request.
Based on this, the present invention combines vector hydrophone e measurement technology with data fusion method, obtains to a greater degree
Target and the information content of environment must be tested, the target information that comprehensive more set measuring systems obtain, effectively improves system
Performance, improve positioning precision.On the other hand combine Kalman filtering algorithm is filtered processing to target motion conditions again,
Optimized the movement locus of target, it is met the needs of noise testing uses.Method proposed by the present invention make use of
Data fusion technique has handled the data message that more vector hydrophones measure, and the data for making to measure have played the work of maximum
With being adapted to a small range is quick, the high-precision movement locus for orienting target, improve the efficiency of experiment, in engineering
It is easier to realize.
The content of the invention
The present invention proposes a kind of noncooperative target radiated noise measurement and positioning technology, combines vector data fusion and card
Kalman Filtering algorithm, effectively non-cooperative moving targets can be tracked with measurement, obtain kinematic parameter, preferably improve vector
The positioning precision of hydrophone and the stability of measuring system.
The technical solution adopted for the present invention to solve the technical problems comprises the following steps：
(1) the line measurement battle array model being made up of four array elements, square measurement battle array model, four array elements composition six are established respectively
Bar baseline, they with six triangles of target configuration, form 12 azimuths respectively；
(2) receipt signal model of vector hydrophone is established, obtains the acoustic pressure data P (t) that vector hydrophone receives, X side
To vibration velocity Vx(t), Y-direction vibration velocity Vy(t), by the acoustic pressure vibration velocity joint processing technology of vector hydrophone, using cross-spectrum sound intensity technique
Carry out orientation estimation；
(3) spectrum analysis is carried out to reception signal, extraction envelope obtains effective band, and frequency domain is carried out in narrow bandwidth range and is melted
Conjunction is handled；
(4) 6 baselines and 12 obtained azimuths are combined, is crossed method by triangle, is resolved every baseline and surveyed
The target location obtained；The target location calculated to multigroup vector hydrophone carries out data and merged again；
(5) to the moving object measurement track of generation in (4), it is optimized using Kalman filtering algorithm.
The acoustic pressure vibration velocity joint processing technology of the vector hydrophone of described step (2) specifically includes：
Target is combined with six baselines respectively, obtaining the reception signal at i-th of array element is：
Wherein subscript s represents semaphore, and subscript n represents noisiness；pi(t) the acoustic pressure letter that i-th of array element receives is represented
Number, vxi(t) the vibration velocity signal in the horizontal direction that i-th of array element of expression receives, vyi(t) represent what i-th of array element received
Vibration velocity signal in vertical direction, θ are the horizontal azimuth of incident acoustic wave.
The cross-spectrum sound intensity technique of described step (2) specifically includes：
The acoustic pressure amount p that will be obtainedi(r, t), vibration velocity amount vxi(r,t)、vyi(r, t) makees Fourier transformation, is carried out in frequency domain
Signal transacting can obtain frequency domain sound intensity information：
The horizontal azimuth for estimating each frequency using cross-spectrum sound intensity technique is：
Wherein ω is angular frequency,For the average sound intensity in x directions,For the average sound intensity in y directions,
For the estimate of horizontal azimuth.
Described step (3) specifically includes：
Power Spectral Estimation is carried out to whole frequency domain with FFT first, the line spectrum of signal is found by analysis, to extraction of line spectrum
Envelope, to a narrow bandwidth range (f where envelope1,f2,f3,…,fn) do Frequence zooming analysis；For same echo signal,
A series of azimuth estimation value of targets is obtained using cross-spectrum sound intensity technique；The target location then calculated to multigroup vector hydrophone
Carry out data to merge again, to the weighted comprehensive for being accurately positioned result and should be all baseline positioning results of target location
Weight selected is variance counting backward technique, wherein DiRepresent the variance of i-th group of measurement data：
Described step (4) specifically includes：
The distance between array element i and array element j：
Bi_hydrophone cross bearing schematic diagram as shown in figure 1, solve measurement battle array coordinate system in R andFor：
Described step (5) specifically includes：
The recurrence formula of Kalman filtering algorithm is as follows：
P (k+1 | k)=Φ P (k | k) Φ '+Γ Q (k) Γ '；
K (k+1)=P (k+1 | k) H ' (k+1 | k) S-1(k+1)；
S (k+1)=H (k+1) P (k+1 | k) H ' (k+1)+R (k+1)；
P (k+1 | k+1)=[I-K (k+1) H (k+1)] P (k+1 | k)；
Wherein, Q (k) δkl=E [g (k) .g'(l)], R (k) δkl=E [w (k) .w'(l)].
The beneficial effects of the present invention are：This method sufficiently make use of the data message that vector hydrophone obtains, and will swear
Amount hydrophone acoustic pressure vibration velocity joint processing technology and Data fusion technique are effectively combined together with.And employ Kalman's filter
Ripple algorithm, the track of moving target is optimized so that the positioning precision of moving target is significantly improved, can
To meet the measurement request to noncooperative target, there is stronger engineering practicability.
Brief description of the drawings
Fig. 1 is flow chart of the present invention；
Fig. 2 is double vector hydrophone cross bearing schematic diagrames；
Fig. 3 is square cloth station schematic diagram；
Fig. 4 is target trajectory simulation analysis result；
Fig. 5 is X-direction velocity measuring simulation analysis result；
Fig. 6 is Y-direction velocity measuring simulation analysis result；
Fig. 7 is X-axis position detection error simulation analysis result；
Fig. 8 is Y-axis position detection error simulation analysis result.
Embodiment
The present invention is further described with example below in conjunction with the accompanying drawings.
(1) measurement model of four-vector hydrophone is established, four array element combination of two form six measurement baselines, and they divide
Not with six triangles of target configuration, azimuths are measured so as to obtain 12.
So that square measures battle array as an example, square array is respectively positioned in xoy planes with moving target, four-vector hydrophone
[1,2,3,4] is distributed on square four summit that the length of side is a, is arranged counterclockwise, and coordinate is respectively (xi,yi),
I=1,2,3,4.Array element 1 and array element 2 are located in x-axis, and equidistantly distributed is in origin O both sides.Array element 3 and array element 4 are located at respectively
The surface of array element 2, array element 3.The initial position of target is located at array element 1 and the midpoint of the intersection of array element 4, as shown in Figure 3.
(2) receipt signal model of vector hydrophone is established, obtains the acoustic pressure data P (t) that vector hydrophone receives, X side
To vibration velocity Vx(t), Y-direction vibration velocity Vy(t).Make target be combined respectively with six baselines, then can obtain at i-th of array element
Reception signal is：
Subscript s represents semaphore, and subscript n represents noisiness.Wherein pi(t) the acoustic pressure letter that i-th of array element receives is represented
Number, vxi(t) the vibration velocity signal in the horizontal direction that i-th of array element of expression receives, vyi(t) represent what i-th of array element received
Vibration velocity signal in vertical direction.θ is the horizontal azimuth of incident acoustic wave.
The acoustic pressure amount p that will be obtainedi(r, t), vibration velocity amount vxi(r,t)、vyi(r, t) makees Fourier transformation, is carried out in frequency domain
Signal transacting can obtain frequency domain sound intensity information：
The horizontal azimuth for estimating each frequency using cross-spectrum sound intensity technique is：
ω is angular frequency in formula,For the average sound intensity in x directions,For the average sound intensity in y directions,
For the estimate of horizontal azimuth.
(3) to improve positioning precision, spectrum analysis need to be carried out to reception signal, effective band is obtained, in narrow bandwidth range
Frequency domain fusion treatment is carried out, carrys out positioning result of all baselines of composite measurement battle array to target.
Power Spectral Estimation is carried out to whole frequency domain with FFT first, the line spectrum of signal is found by analysis, to extraction of line spectrum
Envelope, to a narrow bandwidth range (f where envelope1,f2,f3,…,fn) do Frequence zooming analysis.
Vector hydrophone carries out direction finding using cross-spectrum sound intensity technique, corresponding to each frequency f of reception signal1,f2,
f3,…,fn, an azimuth information can be estimated according to formula (2.4)Therefore, for same echo signal, utilize
Cross-spectrum sound intensity technique can obtain a series of azimuth estimation value of targetsFor each group of vector
Hydrophone, corresponding to each frequency of reception signal, one group of target location coordinate data S can be calculated according to formula (8)1
(x,y),S2(x,y),S3(x,y),…,Sn(x, y), utilize the size of each frequency sound intensityIt is each to integrate
The target location result of frequency.
The target location then calculated to multigroup vector hydrophone carries out data and merged again, to the accurate fixed of target location
Position result should be the weighted comprehensive of all baseline positioning results, i.e.,：
Weight selected is variance counting backward technique, wherein DiRepresent the variance of i-th group of measurement data：
(4) six baselines are combined into by four array elements, respectively with six triangles of target configuration, form 12 azimuths.Profit
With the distance between obtained level orientation value θ and baseline, the position coordinates where target is determined by triangle Convergence method.
Specially：
The distance between array element i and array element j：
Bi_hydrophone cross bearing schematic diagram as shown in figure 1, solve measurement battle array coordinate system in R andFor：
(5) processing is filtered to target motion conditions using Kalman filtering.Kalman filtering algorithm (recurrence formula)
It is as follows：
P (k+1 | k)=Φ P (k | k) Φ '+Γ Q (k) Γ '
K (k+1)=P (k+1 | k) H'(k+1 | k) S-1(k+1)
S (k+1)=H (k+1) P (k+1 | k) H'(k+1)+R (k+1)
P (k+1 | k+1)=[I-K (k+1) H (k+1)] P (k+1 | k)
Wherein：Q(k).δkl=E [g (k) .g'(l)], R (k) δkl=E [w (k) .w'(l)].
The embodiment of content of the invention each several part is illustrated above, combines Data fusion technique and karr
More vector hydrophones joint track and localization technology of graceful filtering algorithm, it can effectively improve the positioning precision of system.Below with just
Exemplified by square cloth station, simulation result is analyzed.
Instance parameter sets as follows：Quaternary square array is laid as shown in Figure 2.The horizontal position that No.1 vector hydrophone is laid
It is set to (- 100,0)；The horizontal level that No. two vector hydrophones are laid is (100,0), the horizontal position that No. three vector hydrophones are laid
It is set to (100,200)；The horizontal level that No. four vector hydrophones are laid is (- 100,200).Assuming that target is simple signal, letter
Number frequency is 150Hz, sample rate 4096, and initial time signal to noise ratio is 20dB, the initial position of target in the horizontal plane for (-
100,100), the initial velocity of X-direction is Vx=1m/s, Y-direction initial velocity are Vy=0.
Fig. 3 is target trajectory simulation analysis result, and Fig. 4 is velocity measuring simulation analysis result, and Fig. 5 detects for position
Errors simulation analysis result.
The simulation result of complex chart 3, Fig. 4 and Fig. 5 is understood：
(1) multivariate vector hydrophone Passive Positioning computation, the movement locus of target can be relatively accurately depicted,
Demonstrate the reliability of the algorithm and the validity of localization method.More vector hydrophone combination Kalman filtering algorithms, can enter one
Step improves positioning precision.
(2) the distance between target and hydrophone can be accurately obtained using azimuth information, carries out the calculating of Acoustic Wave Propagation,
So as to accurately obtain the radiated noise level of target.
Claims (6)
1. a kind of noncooperative target radiated noise measurement and positioning technology, it is characterised in that specifically comprise the following steps：
(1) the line measurement battle array model being made up of four array elements, square measurement battle array model are established respectively, and four array elements form six bases
Line, they with six triangles of target configuration, form 12 azimuths respectively；
(2) receipt signal model of vector hydrophone is established, obtains the acoustic pressure data P (t) that vector hydrophone receives, X-direction is shaken
Fast Vx(t), Y-direction vibration velocity Vy(t), by the acoustic pressure vibration velocity joint processing technology of vector hydrophone, carried out using cross-spectrum sound intensity technique
Estimate in orientation；
(3) spectrum analysis is carried out to reception signal, extraction envelope obtains effective band, carried out in narrow bandwidth range at frequency domain fusion
Reason；
(4) 6 baselines and 12 obtained azimuths are combined, is crossed method, is resolved measured by every baseline by triangle
Target location；The target location calculated to multigroup vector hydrophone carries out data and merged again；
(5) to the moving object measurement track of generation in (4), it is optimized using Kalman filtering algorithm.
2. a kind of noncooperative target radiated noise measurement and positioning technology according to claim 1, it is characterised in that described
The acoustic pressure vibration velocity joint processing technology of the vector hydrophone of step (2) specifically includes：
Target is combined with six baselines respectively, obtaining the reception signal at i-th of array element is：
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Wherein subscript s represents semaphore, and subscript n represents noisiness；pi(t) sound pressure signal that i-th of array element receives, v are representedxi
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Upward vibration velocity signal, θ are the horizontal azimuth of incident acoustic wave.
3. a kind of noncooperative target radiated noise measurement and positioning technology according to claim 1, it is characterised in that described
The cross-spectrum sound intensity technique of step (2) specifically includes：
The acoustic pressure amount p that will be obtainedi(r, t), vibration velocity amount vxi(r,t)、vyi(r, t) makees Fourier transformation, and signal is carried out in frequency domain
Processing can obtain frequency domain sound intensity information：
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4. a kind of noncooperative target radiated noise measurement and positioning technology according to claim 1, it is characterised in that described
Step (3) specifically includes：
Power Spectral Estimation is carried out to whole frequency domain with FFT first, finds the line spectrum of signal by analysis, to extraction of line spectrum bag
Network, to a narrow bandwidth range (f where envelope1,f2,f3,…,fn) do Frequence zooming analysis；For same echo signal, profit
A series of azimuth estimation value of targets is obtained with cross-spectrum sound intensity technique；The target location then calculated to multigroup vector hydrophone is entered
Row data merge again, to the weighted comprehensive for being accurately positioned result and should be all baseline positioning results of target location
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</msub>
<msub>
<mi>x</mi>
<mrow>
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<mi>j</mi>
</mrow>
</msub>
</mrow>
<mrow>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>&NotEqual;</mo>
<mi>j</mi>
</mrow>
</munder>
<munder>
<mi>&Sigma;</mi>
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</munder>
<msub>
<mi>&omega;</mi>
<mrow>
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</mrow>
</msub>
</mrow>
</mfrac>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mfrac>
<mrow>
<munder>
<mi>&Sigma;</mi>
<mrow>
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<mo>&NotEqual;</mo>
<mi>j</mi>
</mrow>
</munder>
<munder>
<mi>&Sigma;</mi>
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</munder>
<msub>
<mi>&omega;</mi>
<mrow>
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</mrow>
</munder>
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</munder>
<msub>
<mi>&omega;</mi>
<mrow>
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</msub>
</mrow>
</mfrac>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>;</mo>
</mrow>
Weight selected is variance counting backward technique, wherein DiRepresent the variance of i-th group of measurement data：
<mrow>
<msub>
<mi>&omega;</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<msup>
<msub>
<mi>D</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>/</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
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<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
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<mi>i</mi>
</msub>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>.</mo>
</mrow>
5. a kind of noncooperative target radiated noise measurement and positioning technology according to claim 1, it is characterised in that described
Step (4) specifically includes：
The distance between array element i and array element j：
<mrow>
<msub>
<mi>d</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>=</mo>
<msqrt>
<mrow>
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<mrow>
<mo>(</mo>
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</mrow>
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<mo>,</mo>
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</mrow>
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</mrow>
Bi_hydrophone cross bearing schematic diagram as shown in figure 1, solve measurement battle array coordinate system in R andFor：
6. a kind of noncooperative target radiated noise measurement and positioning technology according to claim 1, it is characterised in that described
Step (5) specifically includes：
The recurrence formula of Kalman filtering algorithm is as follows：
P (k+1 | k)=Φ P (kk) Φ '+Γ Q (k) Γ '；
K (k+1)=P (k+1 | k) H'(k+1k) S-1(k+1)；
S (k+1)=H (k+1) P (k+1 | k) H'(k+1)+R (k+1)；
P (k+1 | k+1)=[I-K (k+1) H (k+1)] P (k+1 | k)；X (k+1 | k+1)=X (k+1 | k)+K (k+1 | k)+K
(k+1)·V(k+1)；
Wherein, Q (k) δkl=E [g (k) .g'(l)], R (k) δkl=E [w (k) .w'(l)].
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