CN207663047U - Towing line array array shape estimation device based on single near field correction source - Google Patents
Towing line array array shape estimation device based on single near field correction source Download PDFInfo
- Publication number
- CN207663047U CN207663047U CN201721853931.1U CN201721853931U CN207663047U CN 207663047 U CN207663047 U CN 207663047U CN 201721853931 U CN201721853931 U CN 201721853931U CN 207663047 U CN207663047 U CN 207663047U
- Authority
- CN
- China
- Prior art keywords
- array
- signal
- correction source
- field correction
- source
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012937 correction Methods 0.000 title claims abstract description 67
- 238000012545 processing Methods 0.000 claims abstract description 20
- 230000008054 signal transmission Effects 0.000 claims abstract description 9
- 230000000644 propagated effect Effects 0.000 abstract description 4
- 238000012856 packing Methods 0.000 abstract 1
- 238000000034 method Methods 0.000 description 22
- 239000011159 matrix material Substances 0.000 description 20
- 230000015572 biosynthetic process Effects 0.000 description 18
- 238000005755 formation reaction Methods 0.000 description 18
- 239000013598 vector Substances 0.000 description 15
- 238000010586 diagram Methods 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 3
- 238000000354 decomposition reaction Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 208000001992 Autosomal Dominant Optic Atrophy Diseases 0.000 description 1
- 206010011906 Death Diseases 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
Landscapes
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
The utility model belongs to array signal processing field, to realize the refined orientation control of calibration source, to improve array shape estimation precision.For this purpose, the technical solution adopted in the utility model is, the towing line array array shape estimation device based on single near field correction source, by tow vessel, near field correction source, towing line array, array element, signal acquisition module, signal transmission module and signal processing module composition；Near field correction source is mounted on the head or tail portion of tow vessel, and the position coordinates of calibration source are determined by position sensor, array element receives the acoustical signal propagated by underwater acoustic channel, and it is translated into electric signal, electric signal is acquired by signal acquisition module, it converts analog signal to digital signal, each array element data is subjected to packing coded treatment in signal transmission module, and be transmitted to signal processing module.The utility model is mainly used in array signal processing occasion.
Description
Technical Field
The utility model belongs to array signal processing field especially relates to towing linear array formation estimation method and device based on single near field correction source.
Background
Towed linear array sonar is widely applied to the aspects of ocean monitoring, strategic early warning and the like, but a towed array is bent due to the disturbance of the change of the speed of a ship body, sudden steering, ocean current and the like, and most array Signal processing algorithms such as Multiple Signal Classification (hereinafter referred to as MUSIC), subspace fitting and the like realize positioning on the premise that the array is accurately known, so the array is firstly corrected before the azimuth angle of a sound source is estimated. The existing active lineup estimation methods all assume that an auxiliary correction information source is a far-field source, the aperture of a towed linear array sonar system is generally large, a correction source with an accurately known position needs to be placed at a position far away from a ship and other detection platforms, but the accurate position of a far-field correction source is difficult to ensure due to complex sea conditions at sea, so that the corrected lineup has a large error compared with the actual lineup, and the actual application is greatly limited. In order to overcome the problem of utilizing a far field correction source to face, the utility model provides a high-precision dragging array form estimation method and device utilizing a single near field source. By placing the near field correction source on the tow vessel, accurate azimuth control of the correction source can be achieved, thereby improving the accuracy of the lineup estimation.
Disclosure of Invention
In order to overcome the defects of the prior art, the utility model aims to provide a high-precision towed linear array formation estimation method and device by using a single near field correction source. By placing the near field correction source on the towing ship, the accurate azimuth control of the correction source is realized, thereby improving the accuracy of the lineup estimation. Therefore, the utility model adopts the technical scheme that the towed linear array shape estimation device based on the single near field correction source consists of a towed ship, a near field correction source, a towed linear array, an array element, a signal acquisition module, a signal transmission module and a signal processing module; the near-field correction source is arranged at the head or the tail of the towing ship, the position coordinate of the correction source is determined through the position sensor, the array elements receive acoustic signals transmitted through an underwater acoustic channel and convert the acoustic signals into electric signals, the electric signals are collected through the signal collection module, analog signals are converted into digital signals, and data of each array element are packaged and coded in the signal transmission module and transmitted to the signal processing module.
The utility model discloses a characteristics and beneficial effect are:
the utility model can effectively overcome the defects that the prior array shape estimation method depends on poor practicability of a far field correction source and has large calculation amount, and can solve the phase difference from different array elements to a reference array element by the characteristic that the subspaces formed by the signal subspace and the column vector of the array flow pattern matrix are the same, the calculation method is simple, and the calculation amount is reduced; the single near-field correction source is adopted for array shape estimation, and on the premise that the array element spacing of the towed linear array is known, the near-field correction source is placed on the towed ship, so that the direction of the correction source can be accurately controlled, the actual application condition is met, and the estimation precision is improved; just the utility model discloses only adopt a near-field source, reduce the error that the position measurement of correction source is inaccurate to arouse, can further reduce the calculated amount.
Description of the drawings:
other objects and aspects of the invention will become apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which:
fig. 1 shows a block diagram of the general scheme of the towed linear array formation estimation system of the present invention.
Fig. 2 shows a schematic diagram of the array estimation model based on single near-field calibration source of the present invention.
Fig. 3 shows a block diagram of the array shape estimation method based on the single near field calibration source of the present invention.
FIG. 4 shows the mean root mean square error of the position coordinates of the array elements under different SNR of the present inventionAnd CRLB values.
Fig. 5 shows the estimation results of 5 different formations using the method of the present invention.
Fig. 6 shows a DOA estimation result graph of the MUSIC algorithm before and after the matrix is corrected by using the method provided by the present invention.
In fig. 1: 1 is a towing ship; 2 is a near field correction source; 3, transmitting an underwater acoustic signal for correcting the formation by a correction source; 4 is a towed linear array; 5 is a rectangular coordinate system established by taking the reference array element as an origin; 6 is an array element; 7 is a signal acquisition module; 8 is a signal transmission module; 9 is a signal processing module; and 10 is sea level.
In fig. 2: 11 is a uniform linear array; 12 is a single near field correction source; 13 is an array element; 14 is a reference array element; and 15 is a rectangular coordinate system established by taking the reference array element as an origin.
In fig. 3: 16 is the number M of array elements; 17, collecting acoustic signals for each array element and transmitting the acoustic signals to a control center for processing; 18 is to solve the covariance matrix R of the received data; 19, performing eigenvalue decomposition on the covariance matrix R; 20, solving the phase difference of different array elements by the eigenvector phase; 21, a phase difference module for solving the problem that different array elements receive acoustic signals; 22, acquiring the position information of the near field correction source and the reference array element by a position sensor such as a GPS; 23, solving the distance difference between adjacent array elements; 24 isSolving the distance from the correction source to the reference array element; 25, iteratively solving the distance from each array element to a reference array element; 26, establishing a polar coordinate system by taking the near field correction source as an origin; 27 for solving the polar angle of each array element28, solving the position coordinates (x, y) of each array element; and 29, a lineup estimation module based on a single near-field correction source.
Detailed Description
The utility model aims at overcoming the defect that the prior array shape estimation method depends on the poor practicability of a far field correction source, providing a method for estimating the towed linear array shape by using a single near field correction source, and under the premise that the spacing of towed linear array elements is known, by placing the near field correction source on a towed ship, the position of the correction source can be accurately controlled, the practical application condition is met, and the estimation precision is improved; just the utility model discloses the method only adopts a near field correction source, and the change parameter reduces, has reduced the calculated amount.
The first step is to determine the overall scheme of the towed linear array formation estimation system.
The overall scheme block diagram of the towed linear array formation estimation system is shown in fig. 1, and the towed linear array formation estimation system mainly comprises a towed ship 1, a near-field correction source 2, a towed linear array 4, an array element 6, a signal acquisition module 7, a signal transmission module 8 and a signal processing module 9.
The first array element of the array element 6 is set as a reference array element, the position of the reference array element is measured by a position sensor such as a GPS and the like, and a rectangular coordinate system 5 is established by taking the reference array element as an origin. The near Field correction source 2 is installed at the head or tail of the towing ship 1 to ensure the accurate control of the position of the correction source, and the position coordinate of the correction source is determined by a position sensor to transmit the designed underwater acoustic signal 3 for correcting the Array shape, on the premise that the distance between the linear Array elements is known, the Array elements 6 receive the acoustic signal propagated through the underwater acoustic channel and convert the acoustic signal into an electric signal, the electric signal is acquired by a signal acquisition module 7, an analog signal is converted into a digital signal, the data of each Array element is packaged and coded in a signal transmission module 8 and transmitted to a signal processing module 9, and the position coordinate of each Array element is obtained through the processing of an Array shape estimation algorithm, the modules can depend on a digital signal processing system (DSP for short, hereinafter referred to as FPGA), a Field Programmable Gate Array (Field-Gate Array for short), a Field Programmable Gate Array (FPGA), RISC microprocessor (Acorn RISC Machine, hereinafter referred to as ARM) and the like.
And the second step is to design a phase difference solving method for receiving data by different array elements.
As shown in fig. 2, the uniform linear array 11 bends due to the influence of ocean currents or ship speed changes, and assuming that the reflection of the calibration acoustic signals and the change of the array elements in the depth direction are negligible, a single near-field calibration source 12 transmits acoustic signals to be received by M hydrophones 13 (array elements), the array received data vector can be expressed as,
X(t)＝AS(t)+N(t) (1)
where X (t) is the M × 1 dimensional snapshot data vector of the array, A is the M × 1 dimensional array flow pattern matrix, S (t) is the spatial signal vector, and N (t) is the M × 1 dimensional noise data vector of the array. A rectangular coordinate system 15 is established by taking the reference array element 14 as an origin point, (x)i,yi) And (i ═ 2, 3., M) is the position coordinate of the ith array element, and θ is the DOA of the correction source. Fig. 3 is a block diagram of a method for estimating a lineup based on a single near-field correction source. For the phase difference part 21 for solving the received data of different array elements, firstly, the number M16 of the array elements is set, all the array elements collect the acoustic signals emitted by the correction source and transmit the acoustic signals to the control center for processing 17, the part can be realized by depending on hardware platforms such as DSP, FPGA, ARM and the like, then, a covariance matrix R18 for receiving data vectors is solved, characteristic value decomposition 19 is carried out on R, and according to an array signal processing theory, a signal subspace is the same as a subspace spanned by column vectors of an array flow matrix A, so that the phase difference 20 of different array elements can be solved according to the phases of the characteristic vectors for further estimating the position coordinates of the array elements.
And designing a formation estimation model based on a single near-field correction source.
As shown in FIG. 2, assuming that there is a straight line between adjacent array elements and the distance is d, the near field calibration source S1(xa,ya) At a distance r from the reference array element 141DOA is θ. (x)i,yi) Is the position coordinate of the ith array element, riFor correcting the source S1The array shape estimation module 29 based on single near field source shown in fig. 3 firstly obtains the positions 22 of the near field correction source and the reference array element through the position sensors such as GPS, and establishes a rectangular coordinate system with the reference array element as the origin, and then according to the phase difference △ phi between different array elements solved in the second stepiThe difference 23 between the distances of two adjacent array elements to the reference array element can be obtained, as follows,
ri＝ri-1-△φi·λ/(2·π),i＝2,3,...,M (2)
according to the initially calculated distance r between the near field correction source and the reference array element1The distance 25 from each array element to the reference array element can be solved iteratively 24. Because the acoustic signal emitted by the near-field correction source is spherical wave, the near-field correction source S is used1Establishing a polar coordinate system 26 for the origin, the polar angle of the ith array elementCan be expressed as a number of times,
as can be seen from FIG. 2, the rectangular coordinate (x) of the ith array elementi,yi)28 can be calculated by the following formula,
and fourthly, deducing a Cramer-Rao low bound (CRLB) of the proposed method for estimating the array based on the single near field correction source, and comparing Root-Mean-Square Error (RMSE) of position coordinates of the array elements under different Signal-to-Noise ratios (SNR) with the CRLB value to obtain a conclusion that the RMSE is reduced along with the increase of the SNR and is not greatly different from the CRLB value, thereby verifying the correctness of the method.
The technical proposal of the utility model is that the first array element of the towing linear array is set as the reference array element, the position is measured by the position sensors such as the GPS and the like, a rectangular coordinate system is established by taking the reference array element as an origin, the near-field correction source for experiment is arranged at the head or the tail of the towing ship, the position coordinate of the correction source is determined by the position sensor, for transmitting a designed underwater acoustic signal for correcting the array form, the array elements receive acoustic signals propagated through the underwater acoustic channel, and converts the signals into electric signals, and transmits the electric signals to a control center through a signal acquisition module and a transmission module, the part can be realized by depending on hardware platforms such as a DSP (digital signal processor), an FPGA (field programmable gate array), an ARM (advanced RISC machines) and the like, and the control center establishes an array shape estimation model based on a single near-field correction source and solves the position coordinates of each array element by solving the phase difference between different array elements and a reference array element and the geometric relation between the correction source and the array element.
The present invention will be described in further detail with reference to the accompanying drawings and embodiments of the invention.
The first step is to place the near field calibration source and set the relevant parameters of the transmitted acoustic signal.
Near field Source distance Condition from array 0.62 (D)3/λ)1/2<r≤2D2λ, where D is the array aperture and λ is the central wavelength of the signal source; r is the distance from the signal source to the reference array element, the near field correction source is fixed at a proper position at the tail of the towing ship, and the rectangular coordinate of the near field correction source is obtained by measurement and conversion of a position sensor such as a GPS (0,150), so that the distance from the near field correction source to the reference array element is 150m, and the arrival azimuth DOA is 0; the acoustic signal is selected from a sinusoidal signal having a center frequency of125 Hz; in the experiment, a uniform linear array is selected, the number M of array elements is 25, and the spacing d of the array elements is 3M; the sampling frequency of the signal acquisition module is 1 kHz; the repeated test times are set to be 100 times, so that the accidental test results are avoided.
The second step is to solve the phase difference of the received acoustic signals of different array elements.
The array element receives the acoustic signal propagated through the underwater acoustic channel, converts the acoustic signal into an electric signal, transmits the electric signal to the control center for processing through the signal acquisition module and the transmission module, the uniform linear array 11 bends under the influence of ocean current or ship speed change, the acoustic signal emitted by the near-field correction source 12 is received by 25 hydrophones 13 (array elements) under the assumption that the reflection action of the corrected acoustic signal and the change of the array element in the depth direction can be ignored, the array shape related information is contained in the 25 x 1 dimensional array flow pattern matrix A, which can be expressed as,
wherein phikThe phase from the source to the kth array element is corrected for the near field, k being 1,2, 25. As indicated by the general representation of the,
where r is the distance from the near field calibration source to the reference array element 14 and is 150m, and λ is the center wavelength of the calibration source and is 12m, (x)k,yk) And (k is 1, 2.. multidot.m) is the position coordinate of the kth array element, and theta is the DOA of the correction source to the reference array element and is 0. Further, the covariance R18 of the received data vector is solved and the eigenvalue decomposition 19 is performed on R, as shown below,
whereinsIs characteristic value ξkDiagonal matrix of ekFor the corresponding eigenvectors, according to the theory of array signal processing, the subspace of the signals is the same as the subspace spanned by the column vectors of the array flow pattern matrix A, and the phase difference 20 of different array elements is solved according to the phase of the eigenvectors, further expressed as the phase phik＝Arg(ek) Then the phase difference from the ith array element to the kth array element is,
φk-φi＝Arg(ek)-Arg(ei)i＝2,3,...,M；k＝1,2,...,M (8)
therefore, the phase difference between different array elements can be obtained and used for estimating the position coordinates of the array elements.
And thirdly, solving the position coordinates of the array elements according to an array shape estimation model based on the single near-field source.
The phase difference between different array elements, solved according to the second step, results in a distance difference 23 between two adjacent array elements, which is expressed as follows,
△di＝△φi·λ/(2·π) (9)
according to the initially calculated distance r between the near field correction source and the reference array element124 and the distance difference between the adjacent array element and the reference array element, the distance 25 from each array element to the reference array element can be solved iteratively, as shown below,
r1＝150m (10)
ri＝ri-1-△φi·λ/(2·π) (11)
because the acoustic signal emitted by the near-field correction source is spherical wave, the near-field correction source S is used1Establishing a polar coordinate system 26 for the origin, the polar angle of the ith array elementCan be expressed as a number of times,
as can be seen from FIG. 2, the rectangular coordinate (x) of the ith array elementi,yi)28 may be represented as, for example,
the fourth step is to derive and analyze the error and CRLB about the array element coordinate in the method of the utility model
Defining the phase vector of all array elements relative to the reference array element to be phi ═ phi [ [ phi ] ]2,φ3,...,φM]Then the CRLB for phi can be represented by the inverse of the Fisher information matrix J,
CRLB(Φ)＝J-1(14)
where ρ (X | Φ) is a probability density matrix of the received data matrix X with respect to the phase vector Φ, and since the received data matrix X follows a complex gaussian distribution of 0 mean and the data sampling points are relatively independent, the Fisher information matrix J and the covariance matrix R of the received data are represented as,
wherein N is the number of sampling points, A (phi) is an array flow pattern matrix,the signal power of the source is corrected for the near field,is the noise signal power. The phase phi of the covariance matrix R with respect to the ith array elementiThe first derivative of (a) and the inverse of R are expressed as,
wherein M is the number of array elements, ViIs an (M-1) x (M-1) dimensional matrix with diagonal positions of 1 and the rest of 0, and I is an (M-1) x (M-1) dimensional matrix with all elements of 1, and the SNR can be expressed asSo CRLB (Φ) is expressed as follows,
where 1 is a (M-1) × 1-dimensional vector in which all elements are 1, η ═ M +1/SNR)/(MN · SNR),
the x coordinate vector defining the array element is x ═ x2(Φ),x3(Φ),...,xM(Φ)]TCRLB (x) can be obtained by transforming the vector parameter of CRLB (phi), and the relationship is expressed as follows,
so the CRLB (x) of the ith array element coordinatei) And CRLB (y)i) As indicated by the general representation of the,
according toDerivation of CRLB (x)i,yi) In order to realize the purpose,
wherein,
mean root mean square error value of all array elements of towed linear arrayThe solution is shown below, where M is the number of array elements and P is the number of Monte Carlo experiments. CRLB AND/OR by aligning coordinates of elementsThe performance of the proposed formation estimation method can be further analyzed.
FIG. 4 shows the mean root mean square error of the position coordinates of the array elements under different SNRAnd CRLB values, as can be seen from fig. 4, mean root mean square error of array element coordinatesThe SNR is reduced along with the increase of the SNR, and the difference is not great with the CRLB, and the correctness of the method of the utility model is verified.
Fig. 5 is adopting the utility model discloses the estimation result of 5 kinds of different formation of method can be seen through the utility model discloses the formation is rectified to the method, and the fitting degree of estimating formation and actual formation is higher, can realize the formation accurately and estimate.
Fig. 6 is a DOA estimation result diagram of the MUSIC algorithm before and after the method provided by the utility model corrects the formation, and three far-field source azimuth DOAs to be estimated are selected to be-30, 30 and 80. It can be seen from the figure that the DOA estimation appears fuzzy before the formation correction, the DOA estimation result after the correction is-29.99, 29.95,79.98, and the difference with the actual azimuth is not big, thereby effectively improving the DOA estimation performance of the MUSIC algorithm and proving the effectiveness of the method of the utility model.
Claims (1)
1. A towed linear array form estimation device based on a single near-field correction source is characterized by comprising a towed ship, a near-field correction source, a towed linear array, an array element, a signal acquisition module, a signal transmission module and a signal processing module; the near-field correction source is arranged at the head or the tail of the towing ship, the position coordinate of the correction source is determined through the position sensor, the array elements receive acoustic signals transmitted through an underwater acoustic channel and convert the acoustic signals into electric signals, the electric signals are collected through the signal collection module, analog signals are converted into digital signals, and data of each array element are packaged and coded in the signal transmission module and transmitted to the signal processing module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721853931.1U CN207663047U (en) | 2017-12-26 | 2017-12-26 | Towing line array array shape estimation device based on single near field correction source |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721853931.1U CN207663047U (en) | 2017-12-26 | 2017-12-26 | Towing line array array shape estimation device based on single near field correction source |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN207663047U true CN207663047U (en) | 2018-07-27 |
Family
ID=62943649
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201721853931.1U Active CN207663047U (en) | 2017-12-26 | 2017-12-26 | Towing line array array shape estimation device based on single near field correction source |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN207663047U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115656994A (en) * | 2022-10-08 | 2023-01-31 | 哈尔滨工程大学 | Real-time calibration method for double-base active detection towed array formation |
-
2017
- 2017-12-26 CN CN201721853931.1U patent/CN207663047U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115656994A (en) * | 2022-10-08 | 2023-01-31 | 哈尔滨工程大学 | Real-time calibration method for double-base active detection towed array formation |
| CN115656994B (en) * | 2022-10-08 | 2023-08-15 | 哈尔滨工程大学 | Real-time calibration method for bistatic active detection towing array shape |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108169731A (en) | Towing line array array shape estimation method and apparatus based on single near field correction source | |
| CN110764053B (en) | Multi-target passive positioning method based on underwater sensor network | |
| CN111537982B (en) | Distortion drag array line spectrum feature enhancement method and system | |
| CN107179535A (en) | A kind of fidelity based on distortion towed array strengthens the method for Wave beam forming | |
| CN111580048B (en) | Broadband sound source depth estimation method using single-vector hydrophone | |
| CN108089155B (en) | Passive positioning method for single hydrophone sound source in deep sea environment | |
| CN111025273B (en) | Distortion drag array line spectrum feature enhancement method and system | |
| CN109799495B (en) | Broadband time delay estimation method for high fidelity array processing | |
| CN103513250B (en) | A kind of mould base localization method based on robust adaptive beamforming principle and system | |
| CN112630784B (en) | Plane array amplitude-phase error correction method based on convex optimization and neural network | |
| CN111239829A (en) | Towed controllable source electromagnetic and underwater sound composite underwater target detection system and method | |
| CN113011006B (en) | Target depth estimation method based on cross-correlation function pulse waveform matching | |
| CN103076590A (en) | Method for positioning underwater sound pulse signal on basis of frequency estimation | |
| CN114280541B (en) | Target passive positioning method based on deep-sea distributed vertical linear array | |
| CN102721966B (en) | Below high precision depth-sounding method and system by coherent depth-sounding sonar | |
| CN116879901B (en) | Vector hydrophone vertical array deep sea broadband sound source depth estimation method | |
| CN104977565A (en) | Underwater target three-dimensional positioning method realized based on distributed arrays | |
| CN104714235A (en) | Ranging method and system for double low-frequency vector hydrophone arrays | |
| CN207663047U (en) | Towing line array array shape estimation device based on single near field correction source | |
| CN109407048B (en) | Underwater DOA estimation method and device based on non-circular signal and included angle adjustable array | |
| CN113325401B (en) | Distortion towing linear array signal reconstruction method based on line spectrum phase difference deblurring | |
| CN115902849A (en) | Deep sea sound source depth estimation method based on beam output intensity resampling | |
| CN113126029B (en) | Multi-sensor pulse sound source positioning method suitable for deep sea reliable acoustic path environment | |
| CN213813947U (en) | Offshore wind power foundation submarine cable access end detection system | |
| CN109407102B (en) | Two-dimensional underwater environment detection method based on transducer receiving phase |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |