CN108919176B - Single-vector sensor increased-rank MUSIC direction finding technology - Google Patents

Single-vector sensor increased-rank MUSIC direction finding technology Download PDF

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CN108919176B
CN108919176B CN201810165467.XA CN201810165467A CN108919176B CN 108919176 B CN108919176 B CN 108919176B CN 201810165467 A CN201810165467 A CN 201810165467A CN 108919176 B CN108919176 B CN 108919176B
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CN108919176A (en
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柳艾飞
杨德森
时胜国
朱中锐
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Harbin Engineering University
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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
    • 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
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Abstract

The invention discloses a single-vector sensor rank-increasing MUSIC direction-finding technology, and belongs to the technical field of sensor signal processing. The MUSIC direction finding technology has small estimation error and high precision, and requires a covariance matrix of marine environmental noise received by an acoustic vector sensor as a unit matrix. In an ocean environment noise field, the power of ocean environment noise received by a sound pressure channel and a vibration velocity channel of an acoustic vector sensor is not equal, so that the MUSIC direction finding technology cannot obtain due high-precision estimation in underwater target detection. The invention finds that the inconsistency of the environmental noise power received by the sound pressure channel and the vibration velocity channel of the acoustic vector sensor causes a virtual source. To ensure orthogonality of the target steering vector and the noise subspace, the present invention attributes the steering vector of this virtual source to the signal subspace rather than the noise subspace. At lower signal-to-noise ratios, the present invention still has sharp spatial spectral peaks and small estimation errors. The method can be used for solving the problem of passive direction finding of the weak target in marine environmental noise.

Description

Single-vector sensor increased-rank MUSIC direction finding technology
Technical Field
The invention belongs to the technical field of sensor signal processing, and particularly relates to a single-vector sensor rank-increasing MUSIC direction-finding technology.
Background
The sound pressure channel and the vibration velocity channel of the sound vector sensor can simultaneously obtain the sound pressure and the vibration velocity information of a sound field at the same time, and a more favorable tool and more information are provided for the underwater target direction finding. The MUSIC direction finding technology is a super-resolution direction finding technology, and was originally proposed in radio direction finding applications by R.O.Schmidt (R.O.Schmidt.multiple event location and signal parameter estimation [ J ]. IEEE Transactions on Antennas and propagation.1986,34(3), pp: 276-. In recent years, the MUSIC direction finding technology is expanded to the direction finding application of a single vector sensor underwater target by a single DOA estimation method [ J ] of a single vector hydrophone (Zeng Xiongfeng, Su Gui, Li Yu, Huang Haining, etc. [ 2012,33(3):499 and 507 ]. When the acoustic vector sensor is applied underwater, the marine environmental noise is a main noise source, the power of the marine environmental noise in a sound pressure channel and a vibration velocity channel is not equal, and the power is subjected to detailed theoretical analysis and experimental verification by Sunpui et al (Sunpui, Yandson, Shinshou. spatial correlation coefficient [ J ] acoustics report 2003,28(6): 509) 513 based on the sound pressure and the particle vibration velocity of the vector hydrophone. When the existing MUSIC direction finding technology is applied to the direction finding of an acoustic vector sensor, the inconsistency of the power of marine environment noise received by a sound pressure channel and a vibration velocity channel of the acoustic vector sensor is not considered, so that the MUSIC direction finding technology cannot obtain the due super-resolution capability in underwater target detection. The invention discovers that the inconsistency of the power of the marine environment noise received by the sound pressure channel and the vibration velocity channel can cause a virtual source, and the orthogonality between the noise subspace of the received data covariance matrix and the target guide vector is destroyed, so that the MUSIC direction finding technology can not obtain due performance at low signal-to-noise ratio. The invention considers the influence of the virtual source and provides an increased-rank MUSIC direction finding technology which can still obtain a sharp spectral peak at a low signal-to-noise ratio and has smaller angle estimation error.
Disclosure of Invention
The invention aims to provide a single-vector sensor rank-increased MUSIC direction-finding technology which eliminates the influence of a virtual source, has small angle estimation error and solves the problems of high side lobe and thick main lobe.
The purpose of the invention is realized by the following technical scheme:
the acoustic vector sensor is formed by combining a sound pressure sensor and three vibration velocity sensors which are axially vertical in space at a common point. The sound vector sensor measures sound pressure and three vibration velocity components in x, y and z directions simultaneously at a spatial concurrent point.
A single vector sensor increased rank MUSIC direction finding technology comprises the following steps:
the method comprises the following steps: the acoustic vector sensor receives a far-field signal in an ocean environment noise field, and channel amplitude-phase errors do not exist between a sound pressure channel and a vibration speed channel of the calibrated acoustic vector sensor. In this case, the acoustic vector sensor outputs N pieces of snapshot data r (N), where r (N) is a single M × 1 vector, M is 4, and N is 1, …, N.
Step two: according to NIndividual snapshot data estimation covariance matrix
Figure GDA0001979372750000021
Step three: eigenvalue decomposition of covariance matrix
Figure GDA0001979372750000022
Wherein gamma ismIs a characteristic value, arranged in descending order, vmIs a feature vector.
Step four: in the noise field of the marine environment, the inconsistency of the power of the marine environment noise received by the sound pressure channel and the vibration velocity channel causes virtual sources, and the number of the virtual sources is 1. At this time, v2Due to the signal subspace, while the noise subspace is formed by the set of vectors v3,…,vMAnd (5) expanding.
Step five: using { v3,…,vMConstructing a noise subspace projection matrix
Figure GDA0001979372750000023
Step six: by searching for the spectral peak positions of the following spatial spectrum, the angle estimate of the target is as follows:
Figure GDA0001979372750000024
wherein the content of the first and second substances,
Figure GDA0001979372750000025
and
Figure GDA0001979372750000026
an azimuth angle estimate and a pitch angle estimate of the target, S (theta, phi) u, respectivelyH(θ，φ)Pnu(θ，φ)-1Is a spatial spectrum, u (θ, Φ) ═ 1, cos (θ) cos (Φ), sin (Φ)]TIs the steering vector of the acoustic vector sensor at an angle (theta, phi), theta epsilon [ -pi, pi]Is the search azimuth, φ ∈ [ - π/2, π/2]Is the search pitch angle.
Spatial spectrum S (theta, phi) at target angle (theta)1,φ1) And (-180+ theta)1,-φ1) Two spectral peaks are present nearby, so
Figure GDA0001979372750000027
There is an angular ambiguity.
Step seven: using { v2,…,vM}, calculating
Figure GDA0001979372750000028
And
Figure GDA0001979372750000029
the coarse estimation of the target angle obtained by the MUSIC direction finding technology is as follows:
Figure GDA00019793727500000210
according to
Figure GDA00019793727500000211
Elimination
Figure GDA00019793727500000212
The angle of (c) is blurred.
The present invention may further comprise:
the fourth step also comprises:
under the condition of an isotropic noise field, the expected value of the covariance matrix of the data received by the acoustic vector sensor is as follows:
Figure GDA00019793727500000213
wherein u (θ)1，φ1)＝[1，cos(θ1)cos(φ1)，sin(θ1)cos(φ1)，sin(φ1)]TIs the guide vector of the target and is,
Figure GDA00019793727500000214
is the target power of the power to be supplied,
Figure GDA00019793727500000215
is the marine environmental noise power of the sound pressure sensor.
Figure GDA00019793727500000216
Figure GDA00019793727500000217
Power of marine environmental noise received by a vibration velocity sensor, IMIs a unit matrix of M × M, z1＝[1,0,0,0]TIs the steering vector of the virtual source. Under the condition of non-isotropic noise field, the number of virtual sources can still be 1.
When the acoustic vector sensor is formed by combining a sound pressure sensor and a two-dimensional vibration velocity sensor which is orthogonal to each other in a horizontal plane, M is 3, u (theta, phi) is [1, cos (theta) cos (phi), sin (theta) cos (phi)]T。
When the pitch angle of the target is known, the azimuth angle of the target is estimated by searching the spectral peak positions of the following spatial spectrum as follows:
Figure GDA0001979372750000031
at this time, the rough estimate of the target azimuth is as follows:
Figure GDA0001979372750000032
when the azimuth of the target is known, the pitch angle of the target is estimated as follows by searching the spectral peak positions of the following spatial spectrum:
Figure GDA0001979372750000033
at this time, the rough estimate of the target pitch angle is as follows:
Figure GDA0001979372750000034
the invention has the beneficial effects that:
the invention finds that the marine environmental noise power received by the sound pressure channel and the vibration velocity channel causes an imaginary source, and provides an increased rank MUSIC direction finding technology for eliminating the influence of the imaginary source. The rank increasing MUSIC direction finding technology increases the rank of a signal subspace by 1, so that an imaginary source is classified into the signal subspace, and the orthogonality of a noise subspace and a target guide vector is guaranteed. The increased rank MUSIC direction finding technology still has sharp spectral peaks and higher estimation precision under the condition of low signal-to-noise ratio. The problem that when the existing MUSIC direction finding technology is applied to an ocean environment noise field, the side lobe is high and the main lobe is fat is solved. The invention is mainly applied to passive detection of underwater weak targets.
Drawings
FIG. 1 is a flow chart of an increased rank MUSIC direction finding technique;
FIG. 2 is a two-dimensional spatial spectrum of an increased rank MUSIC direction finding technique;
FIG. 3 is a two-dimensional spatial spectrum of the MUSIC direction finding technique;
fig. 4 shows the results of the anechoic pool experiment.
Detailed Description
The following further describes embodiments of the present invention with reference to the accompanying drawings:
the first embodiment is as follows:
with reference to fig. 1, the process flow of the present invention comprises the following steps:
the acoustic vector sensor is formed by combining a sound pressure sensor and three vibration velocity sensors which are axially vertical in space at a common point. The sound vector sensor measures sound pressure and three vibration velocity components in x, y and z directions simultaneously at a spatial concurrent point.
The method comprises the following steps: the acoustic vector sensor receives a far-field signal in an ocean environment noise field, and channel amplitude-phase errors do not exist between a sound pressure channel and a vibration speed channel of the calibrated acoustic vector sensor. The acoustic vector sensor output is N pieces of snapshot data r (N), where r (N) is an M × 1 vector, M is 4, N is 1, …, N.
Step two: estimating covariance matrix from N snapshot data
Figure GDA0001979372750000041
Step three: eigenvalue decomposition of covariance matrix
Figure GDA0001979372750000042
Wherein gamma ismIs a characteristic value, arranged in descending order, vmIs a feature vector.
Step four: in the noise field of the marine environment, the inconsistency of the power of the marine environment noise received by the sound pressure channel and the vibration velocity channel causes virtual sources, and the number of the virtual sources is 1. At this time, v2Due to the signal subspace, while the noise subspace is formed by the set of vectors v3,…,vMAnd (5) expanding.
Step five: using { v3,…,vM}, constructing a noise subspace
Figure GDA0001979372750000043
Step six: by searching the spectral peak positions of the following spatial spectrum, the angle of the target is estimated as follows:
Figure GDA0001979372750000044
wherein the content of the first and second substances,
Figure GDA0001979372750000045
and
Figure GDA0001979372750000046
an estimate of the azimuth and the elevation of the source, S (theta, phi) u, respectivelyH(θ，φ)Pnu(θ，φ)-1Is a spatial spectrum, u (θ, Φ) ═ 1, cos (θ) cos (Φ), sin (Φ)]TIs the guide vector of the acoustic vector sensor at the angle (theta, phi), theta is ∈ [ -pi, pi]Is the search azimuth, φ ∈ [ - π/2, π/2]And searching for a pitch angle.
Spatial spectrum S (theta, phi) at target angle (theta)1,φ1) And (-180+ theta)1,-φ1) Two spectral peaks are present nearby, so
Figure GDA0001979372750000047
There is an angular ambiguity.
Step seven: and (5) utilizing the MUSIC direction finding technology to remove the angle ambiguity in the step six. Specifically, using { v2,…,vM}, calculating
Figure GDA0001979372750000048
And
Figure GDA0001979372750000049
and roughly estimate the angle of the target as follows:
Figure GDA00019793727500000410
according to
Figure GDA00019793727500000411
Elimination
Figure GDA00019793727500000412
The angle of (c) is blurred.
The acoustic vector sensor increased rank MUSIC direction finding technology further comprises the following steps:
when the acoustic vector sensor is formed by combining a sound pressure sensor and a two-dimensional vibration velocity sensor which is orthogonal to each other in a horizontal plane, M is 3, u (theta, phi) is [1, cos (theta) cos (phi), sin (theta) cos (phi)]T。
When the pitch angle of the target is known, the azimuth angle of the target is estimated by searching the spectral peak positions of the following spatial spectrum as follows:
Figure GDA0001979372750000051
at this time, the rough estimate of the target azimuth is as follows:
Figure GDA0001979372750000052
when the azimuth of the target is known, the pitch angle of the target is estimated as follows by searching the spectral peak positions of the following spatial spectrum:
Figure GDA0001979372750000053
at this time, the rough estimate of the target pitch angle is as follows:
Figure GDA0001979372750000054
the following further describes the present invention in terms of simulation examples and test examples.
Simulation example:
the acoustic vector sensor is formed by combining a sound pressure sensor and three vibration velocity sensors which are axially vertical in space at a common point. The sound vector sensor measures sound pressure and three vibration velocity components in x, y and z directions simultaneously at a spatial concurrent point. The marine environmental noise is isotropic noise, where etax＝ηy＝ηz1/3, one target is driven by (θ)1,φ1) Incident on the acoustic vector sensor at (40 °,10 °), the signal-to-noise ratio is-3 dB. Fig. 2 is a spatial spectrum of the increased rank MUSIC direction finding technique, and fig. 3 is a spatial spectrum of the conventional MUSIC direction finding technique. As can be seen from FIG. 2, the increased rank MUSIC direction finding technique is at (-180 ° + θ)1，-φ1) There is an angular ambiguity around. From fig. 3, MUSIC direction finding technique gives a peak at (42.8 °, 10.6 °), from which we can judge that in fig. 2, (40.1 °, 9.9 °) are angle estimates of the target, and (-140.8 °, -11.6 °) are angle ambiguities. Comparing fig. 2 and fig. 3, it can be known that the side lobe of the MUSIC direction finding technology is higher, and the main lobe is very wide, while the side lobe of the increased rank MUSIC direction finding technology of the present invention is very low, and the main lobe is very narrow. In addition, as can be seen from fig. 2 and 3, the increased rank MUSIC direction finding technology of the present invention is lowerThe estimation error of (2).
Anechoic pool test example:
and carrying out an acoustic vector target azimuth angle estimation experiment in a silencing pool of Harbin engineering university. The acoustic vector sensor consists of a sound pressure sensor and two vibration velocity sensors which are orthogonal to each other in a horizontal plane. In the experiment, a target sound source emits a single-frequency signal, the signal frequency is 2kHz, the distance between the sound source and the acoustic vector sensor is 15m, the sound source and the acoustic vector sensor are positioned at the same depth, and the pitch angle phi is formed at the moment 10 deg.. Since this acoustic vector sensor does not contain a velocity sensor perpendicular to the horizontal plane, we only give the azimuthal spatial spectrum, as shown in fig. 4. Comparing the MUSIC direction finding technique with the increased rank MUSIC direction finding technique, it can be seen that the side lobe of the increased rank MUSIC direction finding technique at 135.8 degrees corresponds to the true target azimuth, while the peak at-66.2 degrees is the angle estimation ambiguity. In addition, the side lobe of the MUSIC direction finding technology is higher and the main lobe is wider, which is a virtual source caused by the inconsistency of the power of the ocean environment noise received by the sound pressure channel and the vibration velocity channel of the acoustic vector sensor, which is not considered in the MUSIC direction finding technology. The increased rank MUSIC direction finding technology enables the virtual source to be classified into a signal subspace, so that the orthogonality of a target guide vector and a noise subspace is guaranteed, and a lower side lobe and a narrower main lobe are obtained.
Example two:
a single vector sensor increased rank MUSIC direction finding technology comprises the following steps:
(1) the acoustic vector sensor receives a far-field signal in an ocean environment noise field, the acoustic vector sensor is calibrated to enable a channel amplitude-phase error to be avoided between a sound pressure channel and a vibration velocity channel, the output of the acoustic vector sensor is N pieces of snapshot data r (N), r (N) is a M multiplied by 1 vector, M is 4, N is 1, …, N is a positive integer;
(2) estimating covariance matrix from N snapshot data
Figure GDA0001979372750000061
(3) Performing eigenvalue decomposition on the obtained covariance matrix
Figure GDA0001979372750000062
Wherein gamma ismIs a characteristic value, v, arranged in descending ordermIs a feature vector;
(4) in a noise field of marine environment, the inconsistency of the power of the marine environment noise received by a sound pressure channel and a vibration velocity channel causes virtual sources, the number of the virtual sources is 1, and v is calculated2Subspaced into signal subspace, noise subspace is formed by vector group { v3,…,vMIs formed by expansion;
(5) using { v3,…,vMConstructing a noise subspace projection matrix
Figure GDA0001979372750000063
(6) By searching for the spectral peak positions of the spatial spectrum, the angle estimate of the target is as follows:
Figure GDA0001979372750000064
wherein the content of the first and second substances,
Figure GDA0001979372750000065
and
Figure GDA0001979372750000066
an azimuth angle estimate and a pitch angle estimate of the target, S (theta, phi) u, respectivelyH(θ，φ)Pnu(θ，φ)-1Is a spatial spectrum, u (θ, Φ) ═ 1, cos (θ) cos (Φ), sin (Φ)]TIs the steering vector of the acoustic vector sensor at an angle (theta, phi), theta epsilon [ -pi, pi]Is the search azimuth, φ ∈ [ - π/2, π/2]Is the search pitch angle;
(7) using { v2,…,vM}, calculating
Figure GDA0001979372750000067
And
Figure GDA0001979372750000068
the coarse estimation of the target angle obtained by the MUSIC direction finding technology is as follows:
Figure GDA0001979372750000069
according to
Figure GDA00019793727500000610
Elimination
Figure GDA00019793727500000611
The angle of (c) is blurred.
The step (4) specifically comprises the following steps:
(4.1) under the condition of an isotropic noise field, the expected value of the covariance matrix of the data received by the acoustic vector sensor is as follows:
Figure GDA00019793727500000612
wherein u (θ)1，φ1)＝[1，cos(θ1)cos(φ1)，sin(θ1)cos(φ1)，sin(φ1)]TIs the guide vector of the target and is,
Figure GDA00019793727500000613
is the target power of the power to be supplied,
Figure GDA00019793727500000614
is the power of the marine environmental noise of the acoustic pressure sensor,
Figure GDA00019793727500000615
Figure GDA00019793727500000616
power of marine environmental noise received by a vibration velocity sensor, IMIs a unit matrix of M × M, z1＝[1,0,0,0]TThe method is characterized in that the method is a guide vector of virtual sources, and the number of the virtual sources is 1 under the condition of a non-isotropic noise field;
(4.2) when the acoustic vector sensor is composed of a sound pressure sensor and a level sensorWhen two-dimensional vibration velocity sensors orthogonal to each other in plane are combined in space at a common point, M is 3, u (theta, phi) is [1, cos (theta) cos (phi), sin (theta) cos (phi)]T，
(4.3) when the pitch angle of the target is known, set to φ1By searching the spectral peak positions of the following spatial spectrum, the azimuth angle of the target is estimated as follows:
Figure GDA0001979372750000071
at this time, the rough estimate of the target azimuth is as follows:
Figure GDA0001979372750000072
(4.4) when the azimuth of the target is known, set to θ1By searching the spectral peak positions of the following spatial spectrum, the pitch angle of the target is estimated as follows:
Figure GDA0001979372750000073
at this time, the rough estimate of the target pitch angle is as follows:
Figure GDA0001979372750000074
the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (2)

1. A single vector sensor increased rank MUSIC direction finding technology is characterized by comprising the following steps:
(1) the acoustic vector sensor receives a far-field signal in an ocean environment noise field, the acoustic vector sensor is calibrated to enable a channel amplitude-phase error to be avoided between a sound pressure channel and a vibration velocity channel, the output of the acoustic vector sensor is N pieces of snapshot data r (N), r (N) is a M multiplied by 1 vector, M is 4, N is 1, …, N is a positive integer;
(2) estimating covariance matrix from N snapshot data
Figure FDA0003434633080000011
(3) Performing eigenvalue decomposition on the obtained covariance matrix
Figure FDA0003434633080000012
Wherein gamma ismIs a characteristic value, v, arranged in descending ordermIs a feature vector;
(4) in a noise field of marine environment, the inconsistency of the power of the marine environment noise received by a sound pressure channel and a vibration velocity channel causes virtual sources, the number of the virtual sources is 1, and v is calculated2Subspaced into signal subspace, noise subspace is formed by vector group { v3,…,vMIs formed by expansion;
(5) using { v3,…,vMConstructing a noise subspace projection matrix
Figure FDA0003434633080000013
(6) By searching for the spectral peak positions of the spatial spectrum, the angle estimate of the target is as follows:
Figure FDA0003434633080000014
wherein the content of the first and second substances,
Figure FDA0003434633080000015
and
Figure FDA0003434633080000016
an azimuth angle estimate and a pitch angle estimate of the target, S (theta, phi) u, respectivelyH(θ，φ)Pnu(θ，φ)-1Is a spatial spectrum, u (θ, Φ) ═ 1, cos (θ) cos (Φ), sin (Φ)]TIs the steering vector of the acoustic vector sensor at an angle (theta, phi), theta epsilon [ -pi, pi]Is the search azimuth, φ ∈ [ - π/2, π/2]Is the search pitch angle;
(7) using { v2,…,vM}, calculating
Figure FDA0003434633080000017
And
Figure FDA0003434633080000018
the coarse estimation of the target angle obtained by the MUSIC direction finding technology is as follows:
Figure FDA0003434633080000019
according to
Figure FDA00034346330800000110
Elimination
Figure FDA00034346330800000111
The angle of (c) is blurred.
2. The single-vector-sensor increased-rank MUSIC direction-finding technique according to claim 1, wherein the step (4) specifically comprises:
(4.1) under the condition of an isotropic noise field, the expected value of the covariance matrix of the data received by the acoustic vector sensor is as follows:
Figure FDA00034346330800000112
wherein u (θ)1，φ1)＝[1，cos(θ1)cos(φ1)，sin(θ1)cos(φ1)，sin(φ1)]TIs a guide vector of the target，
Figure FDA00034346330800000113
Is the target power of the power to be supplied,
Figure FDA00034346330800000114
is the power of the marine environmental noise of the acoustic pressure sensor,
Figure FDA00034346330800000115
Figure FDA00034346330800000116
power of marine environmental noise received by a vibration velocity sensor, IMIs a unit matrix of M × M, z1＝[1,0,0,0]TThe method is characterized in that the method is a guide vector of virtual sources, and the number of the virtual sources is 1 under the condition of a non-isotropic noise field;
(4.2) when the acoustic vector sensor is formed by combining the sound pressure sensor and the two-dimensional vibration velocity sensor space common point which is orthogonal to each other in the horizontal plane, M is 3, u (theta, phi) is [1, cos (theta) cos (phi), sin (theta) cos (phi)]T，
(4.3) when the pitch angle of the target is known, set to φ1By searching the spectral peak positions of the following spatial spectrum, the azimuth angle of the target is estimated as follows:
Figure FDA0003434633080000021
at this time, the rough estimate of the target azimuth is as follows:
Figure FDA0003434633080000022
(4.4) when the azimuth of the target is known, set to θ1By searching the spectral peak positions of the following spatial spectrum, the pitch angle of the target is estimated as follows:
Figure FDA0003434633080000023
at this time, the rough estimate of the target pitch angle is as follows:
Figure FDA0003434633080000024
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