CN115291162B - Method for estimating azimuth angle of aerial sound source by unattended single three-component detector - Google Patents
Method for estimating azimuth angle of aerial sound source by unattended single three-component detector Download PDFInfo
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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
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
- G01S3/802—Systems for determining direction or deviation from predetermined direction
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/16—Receiving elements for seismic signals; Arrangements or adaptations of receiving elements
- G01V1/18—Receiving elements, e.g. seismometer, geophone or torque detectors, for localised single point measurements
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Abstract
The invention relates to a method for estimating an azimuth angle of an aerial sound source by an unattended single three-component detector, which mainly aims at gunshot, aerial explosion, fireworks and crackers and the like. Aiming at the problems of multipath acoustic shock coupling and low effective Rayleigh wave content in acoustic shock coupling waves, the invention aims to estimate the azimuth information of the sound source in the air by detecting the Rayleigh waves by utilizing the polarization characteristics and the frequency domain characteristics of the acoustic shock coupling waves. Firstly, preprocessing a time domain and a frequency domain according to time-frequency characteristics of signals, then solving a plurality of characteristic parameters under each frequency band, setting a threshold value to calculate a weight value, finding out the frequency band most likely to exist Rayleigh waves through a nonlinear weight value algorithm, and finally estimating an azimuth angle according to three component data obtained through band-pass filtering. The method of the invention realizes that the azimuth angle of the sound source in the air can be estimated by utilizing a single three-component detector, improves the robustness of estimating the azimuth angle of the unmanned sensor network, and is also suitable for scenes with few-point arrangement requirements.
Description
Technical field:
the invention relates to the field of acoustic shock coupling application, in particular to a method for estimating an azimuth angle of an aerial sound source by an unattended single three-component detector.
The background technology is as follows:
the unattended ground sensor has the advantages of all-weather monitoring, no interference of light and the like, and is widely applied to monitoring of an invading air sound source in a key area. For example, in the vicinity of critical structures (border lines, power plants, dams, etc.) and life lines (electric power, natural gas, petroleum transmission lines, etc.), it is necessary to monitor airborne explosives (chemicals), gunwaves, etc. to ensure personal safety; the inflammable object zones in mountain areas, warehouses and the like need to monitor all-weather and illegal setting off of fireworks and crackers so as to reduce fire accidents. The acquisition of the azimuth information (azimuth angle) of the sound source is beneficial to helping a security system to quickly find the position of the sound source, and reduces life and property loss. Currently, the dominant method of estimating the azimuth of an aerial sound source is to use acoustic sensor array monitoring (e.g., comparative document 1 (CN 201410503647.6)), however, the acoustic sensor is easily found and destroyed when exposed to the outside, and itself is also easily disturbed by weather and environment, resulting in poor data quality and unreliability. Based on the acoustic-vibration coupling principle, the geophone can sense an air sound source, is relatively not easy to be influenced by severe weather, and is hidden. Thus, geophones may be utilized instead when acoustic sensors are not available.
At present, an aerial sound source azimuth angle is estimated mainly by using a geophone array, arrival time information of the geophone is extracted, and then the azimuth angle is deduced according to the relationship between arrival time difference and azimuth angle in the array. However, the array is effective if all detectors in the array can extract time of day information. When the sound source is weaker, the detectors at the farther positions in the array cannot extract time information due to low signal-to-noise ratio, so that the azimuth angle cannot be estimated by the whole array. In fact, the polarization characteristics of the seismic signals can reflect the azimuth information of the target, and according to the propagation characteristics of different seismic phases, a single three-component detector can theoretically estimate the azimuth angle of an air sound source, so that the method is more suitable for scenes with few-point arrangement requirements.
The conventional method for estimating the azimuth angle of the ground source by using polarization characteristics (for example, comparative document 2 (CN 113093093A)) cannot be directly used for estimating the azimuth angle of an aerial sound source, because the propagation path of a seismic wave excited by the ground source is relatively clear, various seismic phases are compatible and easy to distinguish, and Rayleigh waves are easy to find; the air sound source propagates simultaneously in the underground medium due to the acoustic-vibration coupling effect and has complex multipath seismic waves, the Rayleigh waves and the multiple vibration phases are mixed together, so that data are unreliable due to strong interference, and the error of estimating the azimuth angle of the air sound source by adopting the method of the comparison document 2 is large, so that the estimation result is unreliable. Therefore, the characteristics of the Rayleigh waves in the acoustic shock coupled waves in a plurality of domains are combined to detect the Rayleigh waves, and then the azimuth angle of the sound source in the air is estimated according to the particle motion rule of the Rayleigh waves.
The invention comprises the following steps:
the invention aims to overcome the defects in the prior art, and provides a method for estimating the azimuth angle of an aerial sound source by using an unattended single three-component detector.
The invention is characterized in that a small amount of available Rayleigh waves are contained in the acoustic shock coupling process, the characteristic that the polarization direction of the Rayleigh waves corresponds to the direction of a sound source is taken as the basis, meanwhile, the multipath effect, the environmental interference and the multi-order phenomenon of the Rayleigh waves of the acoustic shock coupling are considered, aiming at the problem of low signal to noise ratio, 4 polarization characteristics and 1 frequency domain characteristic are utilized to jointly detect the relatively ideal Rayleigh waves based on a nonlinear weight method, acceleration and speed signals of three components are obtained through calculus transformation, and the azimuth angle is estimated by utilizing a relation formula of the polarization characteristics and the azimuth angle.
The invention aims at realizing the following technical scheme:
a method for estimating an azimuth angle of an airborne sound source by an unattended single three-component detector, comprising the steps of:
a. preprocessing an original horizontal component signal X, Y and a vertical component signal Z, making a time-frequency diagram of Z, and preliminarily judging a rough frequency interval [ F ] where Rayleigh waves are located according to the duration time of an actual signal and the low-frequency interference frequency range 1 ，F 2 ]Hz, and requires F 2 Not more than the frequency corresponding to the strongest energy part of the signal in the time-frequency diagram;
b. in [ F ] 1 ，F 2 ]In the method, a zero phase shift filter is selected to carry out band-pass filtering on three component signals for a plurality of times, the frequency bandwidth and the moving step length are WHz, and the filtering frequency band interval pi (n) is [ F ] in sequence 1 ，F 1 +W]Hz，[F 1 +W，F 1 +2W]Hz，[F 1 +2W，F 1 +3W]Hz, …, N is the number of filter bands, n=1, 2, N is the total number of filter bands;
c. solving the characteristic parameters of each frequency band, taking the J-th filtering frequency band in pi (n) as an example, wherein three components after pi (J) filtering are X J 、Y J And Z J Let the matrix ζ= [ Z ] J ，X J ，Y J ] T Find 3×3 synergy variance matrix xi T And decomposing the characteristic value lambda 1 ＞λ 2 ＞λ 3 Corresponding feature vectorA plurality of characteristic parameters are obtained, and the characteristic parameters are calculated,
1) Reciprocal ellipticity
2) Coefficient of flatness
3) The phase difference is a function of the phase difference,
obtaining R 1 ，Z J Phase difference between(angle making);
4) V-solving 3 Included angle with horizontal plane
5)X J 、Y J And Z J E (J);
then, ρ (n), c (n), p (n) are obtained for all the frequency bands,θ (N) and e (N), 5 features each contain N elements, find out the frequency bands corresponding to all maximum points on the dispersion curve of e (N), and form a set H;
d. calculating absolute error values of 4 polarization characteristic parameters
E Δ (n)＝|Δ(n)-L Δ | (6)
Wherein delta refers to ρ, c,θ, L ρ 、L c 、/>And L θ Equal to 0, 1, 90 degrees and 0 degree, respectively, and for each polarization characteristic parameter, an error threshold T Δ =std (Δ (n)), where std () represents the double standard deviation of the one-dimensional array in brackets;
e. calculating the weight sum of 4 polarization characteristic parameters corresponding to each frequency band in H, wherein the weight calculation method of each characteristic parameter is the same to calculate the weight of characteristic delta in II (J)In the case of an example of this,
where min () represents the minimum value of the one-dimensional array in brackets, then the sum of weights W of the 4 polarization feature parameters on n (J) J Is calculated by the formula of (2)
The weight sum of each frequency band in H is calculated, the frequency band with the maximum weight sum value is found, the corresponding frequency band serial number is K, we consider that the relatively ideal Rayleigh wave exists in Pi (K),the extracted horizontal component X K 、Y K And a vertical component Z K ；
f. X is integrated by calculus K 、Y K And Z K Conversion to S x 、S y And V z Wherein S is x 、S y And V z Acceleration signals in the x and y directions and velocity signals in the z direction, respectively;
g. the azimuth angle of the aerial sound source is calculated,
where Θ is the angle system, ".
The beneficial effects are that:
the method can be applied to environments with large noise interference in cities and fields, has strong applicability, and can still accurately estimate the azimuth angle of the aerial sound source under the condition that useful signals are nearly submerged. The method is mainly suitable for estimating the azimuth angle of low-altitude static sound sources such as gunshot, aerial explosives, fireworks and crackers, and has important reference value for high-altitude sound sources such as thunder, sonic boom, and dynamic sound sources such as airliners and helicopters.
Description of the drawings:
fig. 1 is a graph of the absolute error of azimuth angles of 20 drum signals estimated using the covariance matrix method and the method of the present invention.
The method for estimating the azimuth angle of the aerial sound source by using the unattended single three-component detector is further described in detail below with reference to the accompanying drawings and the embodiment.
The embodiment is performed in a brick-and-tile space, and a velocity-type three-component geophone is deployed on the ground. The air sound source adopts the traditional cowhide drum in China, the drum body is wooden, and the drum is continuously beaten 20 times in one point position.
A method for estimating an azimuth angle of an airborne sound source by an unattended single three-component detector, comprising the steps of:
a. preprocessing an original horizontal component signal X, Y and a vertical component signal Z, and making a time-frequency diagram of Z, wherein the low-frequency interference frequency range is mainly below 20Hz, and the frequency corresponding to the strongest energy part of the signal in the time-frequency diagram is 90Hz although the whole signal frequency range is between 20 and 400 Hz, so that the rough frequency range 20 and 90Hz of the Rayleigh wave is primarily judged;
b. in the interval [20, 90], selecting a zero phase shift filter to carry out band-pass filtering on three component signals for a plurality of times, wherein the frequency bandwidth and the moving step length are 3Hz, the filtering frequency band interval pi (N) is sequentially [20, 23] Hz, [23, 26] Hz, [26, 29] Hz, [29, 32] Hz, …, N is the serial number of the filtering frequency band, n=1, 2, and N, N is the total number of the filtering frequency band;
c. solving the characteristic parameters of each frequency band, taking the J-th filtering frequency band in pi (n) as an example, wherein three components after pi (J) filtering are X J 、Y J And Z J Let the matrix ζ= [ Z ] J ，X J ，Y J ] T Find 3×3 synergy variance matrix xi T And decomposing the characteristic value lambda 1 ＞λ 2 ＞λ 3 Corresponding feature vectorA plurality of characteristic parameters are obtained, and the characteristic parameters are calculated,
1) Reciprocal ellipticity
2) Coefficient of flatness
3) The phase difference is a function of the phase difference,
obtaining R 1 ，Z J Phase difference between(angle making);
4) V-solving 3 Included angle with horizontal plane
5)X J 、Y J And Z J E (J);
then, ρ (n), c (n), p (n) are obtained for all the frequency bands,θ (N) and e (N), 5 features each contain N elements, find out the frequency bands corresponding to all maximum points on the dispersion curve of e (N), and form a set H;
d. calculating absolute error values of 4 polarization characteristic parameters
E Δ (n)＝|Δ(n)-L Δ | (6)
Wherein delta refers to ρ, c,θ, L ρ 、L c 、/>And L θ Equal to 0, 1, 90 degrees and 0 degree, respectively, and for each polarization characteristic parameter, an error threshold T Δ =std (Δ (n)), where std () represents the double standard deviation of the one-dimensional array in brackets;
e. calculating the weight sum of 4 polarization characteristic parameters corresponding to each frequency band in H, wherein the weight calculation method of each characteristic parameter is the same to calculate the weight of characteristic delta in II (J)In the case of an example of this,
where min () represents the minimum value of the one-dimensional array in brackets, then the sum of weights W of the 4 polarization feature parameters on n (J) J Is calculated by the formula of (2)
Solving the weight sum of each frequency band in H and finding the frequency band with the largest weight sum value, wherein the corresponding frequency band serial number is K, and the relative ideal Rayleigh wave exists in pi (K), and the extracted horizontal component X K 、Y K And a vertical component Z K ；
f. X is integrated by calculus K 、Y K And Z K Conversion to S x 、S y And V z Wherein S is x 、S y And V z Acceleration signals in the x and y directions and velocity signals in the z direction, respectively;
g. the azimuth angle of the aerial sound source is calculated,
where Θ is the angle system, ".
Comparing fig. 1 with the covariance matrix method and the method of the invention to estimate the absolute error of the drum azimuth, it can be seen that the covariance matrix method has very large error, the average error is about 60 degrees, and is almost unusable, while the azimuth estimation accuracy obtained by the method of the invention has obvious improvement, and the average absolute error can still be less than 10 degrees under the condition of low signal-to-noise ratio, which indicates that the method of the invention has ideal effectiveness.
Claims (1)
1. A method for estimating an azimuth angle of an airborne sound source by an unattended single three-component detector, comprising the steps of:
a. preprocessing an original horizontal component signal X, Y and a vertical component signal Z, making a time-frequency diagram of Z, and preliminarily judging a rough frequency interval [ F ] where Rayleigh waves are located according to the duration time of an actual signal and the low-frequency interference frequency range 1 ，F 2 ]Hz, and requires F 2 Not more than the frequency corresponding to the strongest energy part of the signal in the time-frequency diagram;
b. in [ F ] 1 ，F 2 ]In the method, a zero phase shift filter is selected to carry out band-pass filtering on three component signals for a plurality of times, the frequency bandwidth and the moving step length are WHz, and the filtering frequency band interval pi (n) is [ F ] in sequence 1 ，F 1 +W]Hz，[F 1 +W，F 1 +2W]Hz，[F 1 +2W，F 1 +3W]Hz, …, N is the number of filter bands, n=1, 2, N is the total number of filter bands;
c. solving the characteristic parameters of each frequency band, taking the J-th filtering frequency band in pi (n) as an example, wherein three components after pi (J) filtering are X J 、Y J And Z J Let the matrix ζ= [ Z ] J ，X J ，Y J ] T Find 3×3 synergy variance matrix xi T And decomposing the characteristic value lambda 1 ＞λ 2 ＞λ 3 Corresponding feature vectorA plurality of characteristic parameters are obtained, and the characteristic parameters are calculated,
1) Reciprocal ellipticity
2) Coefficient of flatness
3) The phase difference is a function of the phase difference,
obtaining R 1 ，Z J Angular phase difference between；
4) V-solving 3 Included angle with horizontal plane
5)X J 、Y J And Z J E (J);
then, ρ (n), c (n), p (n) are obtained for all the frequency bands,θ (N) and e (N), 5 features each contain N elements, find out the frequency bands corresponding to all maximum points on the dispersion curve of e (N), and form a set H;
d. calculating absolute error values of 4 polarization characteristic parameters
E Δ (n)＝|Δ(n)-L Δ | (6)
Wherein delta refers to ρ, c,θ, L ρ 、L c 、/>And L θ Equal to 0, 1, 90 degrees and 0 degree, respectively, and for each polarization characteristic parameter, an error threshold T Δ =std (Δ (n)), where std () represents the doubling of the one-dimensional array in bracketsThe accuracy is poor;
e. calculating the weight sum of 4 polarization characteristic parameters corresponding to each frequency band in H, wherein the weight calculation method of each characteristic parameter is the same to calculate the weight of characteristic delta in II (J)In the case of an example of this,
where min () represents the minimum value of the one-dimensional array in brackets, then the sum of weights W of the 4 polarization feature parameters on n (J) J Is calculated by the formula of (2)
Solving the weight sum of each frequency band in H and finding the frequency band with the largest weight sum value, wherein the corresponding frequency band serial number is K, and the relative ideal Rayleigh wave exists in pi (K), and the extracted horizontal component X K 、Y K And a vertical component Z K ；
f. X is integrated by calculus K 、Y K And Z K Conversion to S x 、S y And V z Wherein S is x 、S y And V z Acceleration signals in the x and y directions and velocity signals in the z direction, respectively;
g. the azimuth angle of the aerial sound source is calculated,
where Θ is the angle system, ".
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| CN1228182A (en) * | 1996-08-12 | 1999-09-08 | 埃罗接触系统公司 | Acoustic condition sensor employing plurality of mutually non-orthogonal waves |
| CN112698402A (en) * | 2020-12-18 | 2021-04-23 | 哈尔滨工程大学 | Sea ice sound velocity in-situ assessment method |
| CN112986902A (en) * | 2021-02-23 | 2021-06-18 | 自然资源部第三海洋研究所 | Method for estimating azimuth of underwater broadband sound source by single detector across ice layer |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1228182A (en) * | 1996-08-12 | 1999-09-08 | 埃罗接触系统公司 | Acoustic condition sensor employing plurality of mutually non-orthogonal waves |
| CN112698402A (en) * | 2020-12-18 | 2021-04-23 | 哈尔滨工程大学 | Sea ice sound velocity in-situ assessment method |
| CN112986902A (en) * | 2021-02-23 | 2021-06-18 | 自然资源部第三海洋研究所 | Method for estimating azimuth of underwater broadband sound source by single detector across ice layer |
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| Title |
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| 均匀振幅加权和余弦振幅加权定向地震波方法的对比;邹艳艳 等;地球物理学进展;20161231;第31卷(第06期);全文 * |
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