Multi-dimensional high-precision direction finding method based on single vector hydrophone in shallow water channel model

Abstract

The invention discloses a multi-dimensional high-precision direction finding method of a single vector hydrophone based on a shallow sea channel model: extracting the sound pressure and three-dimensional vibration velocity channel information of the hydrophone and discretizing them; searching for a point source target signal as a cooperative sound source to obtain the sound pressure, horizontal and vertical vibration velocity; performing phase search compensation on the vibration velocity and calculating the correlation coefficient until all compensation angles are searched to obtain the best compensation phase angle of the vibration velocity; performing FFT transformation on four-channel discrete signals, performing phase offset compensation on the horizontal and vertical vibration velocities respectively, and extracting the instantaneous phase; performing variance calculation on the instantaneous phase difference and weighting it to the corresponding frequency units after mean filtering to obtain a frequency domain estimation value; performing three-channel sound pressure and vibration velocity conjugate cross-spectral processing on the sound pressure and three-dimensional vibration velocity frequency domain estimation values ​​and taking the real part to obtain a three-dimensional sound energy flow estimation value, and performing horizontal azimuth and pitch angle estimation on each frequency point; performing clustering division processing on the azimuth of each frequency point, and using the sound energy flow as a weight to calculate the angle estimation value to obtain the azimuth.

Description

Technical Field

[0001] The invention belongs to the technical field of signal processing, and relates to a target direction finding method under shallow sea boundary conditions, and specifically to a horizontal dimension and vertical dimension target direction finding method based on single vector hydrophone phase compensation. Background Art

[0002] Direction estimation has always been a research hotspot in the field of underwater acoustic signal processing. In recent years, vector hydrophone technology has received more and more attention as an important means of detection and direction estimation. Compared with traditional scalar hydrophones, vector hydrophones can synchronously pick up the three orthogonal components of sound pressure p and vibration velocity v in the sound field at the same point in space. x , v y , v z , the azimuth estimation of underwater targets can be completed by relying on a single vector hydrophone, which provides a spatial advantage for underwater small platforms equipped with acoustic sensors to detect targets. In the study of single vector hydrophone direction finding algorithm, Hui Junying et al. discussed the basic principle of joint processing of sound pressure and velocity, that is, the sound pressure and velocity responses of underwater far-field point source targets are completely coherent, while for isotropic background noise fields, their sound pressure and velocity responses are irrelevant, verifying that the relevant algorithm has a strong background noise suppression ability under the corresponding channel conditions. Based on this, Yao Zhixiang et al. proposed the complex sound intensity method and the improved bar chart method based on this. The above single vector hydrophone azimuth estimation algorithms are basically based on the deep sea free field model, while the sonar system in actual engineering often works in a shallow sea environment, and its acoustic channel is more complex than the deep sea free field. The traditional vector hydrophone azimuth estimation method based on the deep sea free field model generally has the problem of low direction finding accuracy and large variance under shallow sea conditions, and the comprehensive performance cannot fully meet the requirements of engineering applications. In view of this, the present invention studies and develops a vector field model under shallow sea channel conditions and a multi-dimensional high-precision direction finding method of a single vector hydrophone based on the model. Summary of the invention

[0003] The purpose of the present invention is to provide a single vector hydrophone multi-dimensional high-precision direction finding method based on collaborative sound source search and suitable for shallow sea channel environment. The present invention first performs collaborative sound source search, and then based on the collaborative sound source, the vector hydrophone sound pressure and velocity correlation coefficient is used as the objective function to calculate the velocity channel phase compensation angle and phase angle compensation, so as to achieve the maximum amplitude improvement of the sound pressure-velocity correlation of the target source, and then improve the signal-to-noise ratio of the line spectrum and narrowband signal through instantaneous phase difference weighted processing, and finally achieve high-precision azimuth estimation of the horizontal and vertical dimensions of the underwater target.

[0004] A single vector hydrophone multi-dimensional high-precision direction finding method based on a shallow sea channel model comprises the following steps:

[0005] Step 1: Extract the sound pressure channel and three-dimensional vibration velocity channel information of the single vector hydrophone, and then perform discretization processing.

[0006] Step 2: Use methods such as histograms to search for a point source target signal as a collaborative sound source and obtain the sound pressure p and horizontal vibration velocity v. x And the vertical vibration velocity v z .

[0007] Step 3: In the range of [-90°, 90°], the horizontal and vertical vibration speeds are adjusted with a step size of and Phase search compensation is performed, and the correlation coefficient c between the compensated vibration velocity and sound pressure is calculated i and c ii .

[0008] Step 4: Repeat step 3 until all compensation angles are searched, and then use the correlation coefficient as the objective function to obtain the optimal compensation phase angle of horizontal vibration velocity. and vertical vibration speed optimal compensation phase angle

[0009] Step 5: Perform FFT transformation on the four-channel discrete signals of the vector hydrophone, and calculate the values ​​of the horizontal two-dimensional vibration velocity and the vertical vibration velocity. The phase offset is compensated, and then the instantaneous phase of each frequency unit of the four channels is extracted.

[0010] Step 6: Calculate the variance of the instantaneous phase difference of the four channels, perform mean filtering, and weight them to the corresponding frequency units to obtain the final frequency domain estimation value.

[0011] Step 7: Perform three-channel sound pressure and velocity conjugate cross-spectrum processing on the sound pressure and three-dimensional velocity frequency domain estimation values ​​after the weighted processing, and take the real part to obtain the three-dimensional acoustic energy flow estimation value, and use the acoustic energy flow estimation value to estimate the horizontal azimuth and pitch angle of each frequency point.

[0012] Step 8: Cluster the azimuth angles of each frequency point, use the acoustic energy flow as the weight to calculate the angle estimation value, and finally obtain the precise azimuth.

[0013] The method of the present invention is applicable to shallow sea channel environments, and is generally applicable to target azimuth estimation with a sound source frequency of more than 200 Hz.

[0014] Preferably, the method of the present invention analyzes the shallow water channel based on the multipath ray model, and the normalized vector output model expression at the shallow water multipath receiving point is:

[0015]

[0016] A comprehensive analysis of the virtual source point position, pitch angle, and attenuation coefficient under the model shows that the shallow sea channel conditions have multiple influences on the joint processing of sound pressure and vibration velocity, with a larger impact on the near field and a relatively smaller impact on the far field; the impact on the horizontal vibration velocity component is relatively smaller than the vertical vibration velocity.

[0017] Preferably, the offset angle search algorithm of the present invention introduces a cooperative sound source. Any target with a certain correlation between sound pressure and vibration velocity can be used as a cooperative sound source. In the absence of an obvious target, anisotropic noise can also be used as a cooperative sound source target. Taking the correlation (correlation coefficient) of the cooperative sound source target as the compensation target, all compensation angles are searched within [-90°, 90°], and their Pearson correlation coefficients are calculated. The calculation method is as follows:

[0018]

[0019] The optimal compensation phase angle of horizontal vibration velocity is obtained And the vertical vibration speed optimal compensation angle

[0020] Preferably, the horizontal velocity and vertical velocity of the vector hydrophone are analytically compensated by the searched horizontal and vertical velocity compensation phase angles, and the analyzed complex signal is obtained by Hilbert transform:

[0021]

[0022] Perform phase offset compensation on horizontal and vertical vibration velocities:

[0023]

[0024] The four-channel signal obtained after compensation is more in line with the shallow sea channel environment conditions, and DOA estimation using this signal will have higher accuracy.

[0025] Preferably, in step 6, the signal-to-noise ratio of the line spectrum and the narrowband channel is improved by instantaneous phase difference weighted processing, and the processing method is as follows:

[0026]

[0027] The present invention has the following beneficial effects:

[0028] 1. Aiming at the problems existing in the existing shallow water channel direction finding methods, the present invention adds the correlation compensation of the target sound source on the basis of the instantaneous phase difference weighted method. Through the cooperative sound source, the compensation phase angle is calculated and searched to achieve the maximum amplitude compensation of the correlation between the sound pressure and the velocity of the target sound source, which solves the serious problem of the lack of correlation between the sound pressure and the velocity of the existing method under shallow water conditions. Compared with the existing method, the invented method can achieve higher azimuth estimation accuracy and smaller estimation variance in shallow water direction finding.

[0029] 2. The method of the present invention can estimate the horizontal azimuth and elevation angle in the horizontal dimension and the vertical dimension respectively, and can achieve a high direction finding accuracy, thus realizing multi-dimensional direction finding.

[0030] 3. After the method of the present invention searches for the best compensation through the cooperative sound source, the target signal can be processed for direction finding without repeatedly obtaining the compensation angle. The method of the present invention runs relatively fast. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a shallow water multipath acoustic signal propagation model.

[0032] Figure 2 It is a schematic diagram of Cartesian vector coordinates.

[0033] Figure 3 This is the offset compensation angle search flow chart.

[0034] Figure 4 It is a flow chart of the phase compensation direction finding algorithm.

[0035] Figure 5 It is a schematic diagram of the experimental system deployment.

[0036] FIG6(a) and FIG6(b) are comparison diagrams of the correlation between the original signal and the vertical vibration velocity, and the correlation between the sound pressure and the horizontal vibration velocity of the compensated signal, respectively.

[0037] Figure 7(a) and Figure 7(b) are the vertical time-azimuth history diagrams of the conventional method and the phase search compensation method under shallow sea conditions, respectively, and Figure 7(c) is the horizontal time-azimuth history diagram based on the phase search compensation method.

[0038] Figure 8 It is a comparison chart of the root mean square error of the conventional complex sound intensity method, the instantaneous phase difference weighted method and the phase search compensation method. DETAILED DESCRIPTION

[0039] The present invention will be described in further detail below with reference to the accompanying drawings.

[0040] The present invention relates to a high-precision multi-dimensional direction finding method for a single vector hydrophone in a shallow sea channel. Traditional single vector direction finding methods represented by a bar graph direction finding method are basically based on a deep sea free field model, so that the direction finding accuracy is often low in a shallow sea channel. The present invention analyzes the problem of the lack of correlation between the sound pressure and vibration velocity of a vector hydrophone in a shallow sea channel by establishing a shallow sea multipath model, and proposes a single vector hydrophone multi-dimensional high-precision direction finding method based on a cooperative sound source and suitable for a shallow sea channel environment.

[0041] 1. Analysis of joint processing of sound pressure and vibration velocity under shallow sea channel conditions

[0042] The shallow sea channel model mainly considers the boundary effect between the sea surface and the seabed, that is, the multipath effect caused by the boundary. The sound field at the receiving point is not a single direct sound line, but a convergence of multiple sound lines. Figure 1 Each reflected sound ray can be regarded as a direct sound ray emitted by a virtual source. Based on this theory, a ray model is established. Assume that the sound source in a shallow sea multipath environment is located at point O, the receiving point is located at point R, the horizontal azimuth angle from the sound source to the receiving point is θ, and the propagation path length of the i-th sound ray is r i , the corresponding pitch angle is φ i , i = 1, 2, ..., in three-dimensional space, the description of the vibration velocity signal follows the Cartesian coordinate definition, such as Figure 2 As shown, according to acoustic theory, the normalized vector output model at the receiving point can be expressed as:

[0043]

[0044] Where p is the sound pressure signal picked up by the vector hydrophone, v x is the velocity signal in the X-axis direction picked up by the vector hydrophone, v y is the Y-axis velocity signal picked up by the vector hydrophone, v z is the vibration velocity signal in the Z-axis direction picked up by the vector hydrophone. In the formula, wave number k = ω / c, ω is the angular velocity of the signal, a i It is the normalized attenuation factor, including the superposition of attenuation of the sea surface and the seabed, and the attenuation of the sea surface and the seabed is related to multiple factors. Among them, the acoustic impedance ratio Z = ρc is a proportional constant of the ratio of sound pressure to vibration velocity mode, which is only related to the properties of the medium itself.

[0045] Will Figure 1 As shown, the xΟy plane is set as the sea surface and is a flat free interface. According to ray acoustics, the sound source sound line will be received by the receiving point after being reflected from the seabed in the picture. The actual sound field is the superposition of each virtual source sound line. The model is as follows Figure 1 shown. Figure 1 D in the figure is the direct sound line of the sound source, 0i (i=1,2...) is the virtual source formed by the sound source O after the i-1th reflection on the sea surface and then the i-1th reflection on the seabed; 1i (i=1,2...) is the virtual source formed by the sound source O after the i-1th seabed reflection and the i-1th sea surface reflection. i It refers to the sound rays that are reflected from the sea surface for the first time after being transmitted and reflected from the seabed before reaching the receiving end. i It refers to the sound line that experiences the first reflection from the sea surface after being transmitted and then reflects from the sea surface before reaching the receiving end. Therefore, the sound line can be classified as BS i ,BB i , SS i , S.B. i(i=1,2...) four types, which are convenient for subsequent parameter calculation.

[0046] Depend on Figure 1 It can be seen that, except for the direct sound line, each sound line corresponds to a virtual source. i With virtual source 1(2i-1) Correspondence: BS i With virtual source 1(2i) Corresponding. According to the law of mirror reflection, the general expression of each virtual source coordinate can be obtained as follows:

[0047]

[0048]

[0049] Among them, H is the shallow sea depth, h is the vector hydrophone depth, and n is the number of sound line groups, which is generally 10.

[0050] Each sound line corresponds to a pitch angle, so the corresponding pitch angle can be obtained after determining the virtual source position. The general expression for the pitch angles of the four types of sound lines obtained from the virtual source position is:

[0051]

[0052] Among them, z is the depth of the hydrophone, and x is the horizontal distance between the hydrophone and the target source. Finally, the sound propagation reflection coefficient is determined. The number of reflections of each type of sound line on the sea surface and the seabed is different, so the corresponding reflection coefficient of the sound line is also different. It is a multiple superposition of the sea surface and the seabed. The reflection coefficient of each type of sound line can be calculated and summarized as follows:

[0053]

[0054] Where a is the seawater absorption coefficient, r s 、r b are the sea surface reflection coefficient and the seabed reflection coefficient respectively.

[0055] The sound pressure and velocity can be jointly analyzed through the shallow sea sound propagation model. It can be seen from equations (4) and (5) that when the environment is a far field with a large horizontal distance x, the sound line with a large i value contributes less to the combined sound field due to multiple superposition and attenuation of the sea surface and the seabed. The sound line with a small i value has a small corresponding pitch angle due to the large x. Combined with equation (1), it can be seen that in this case, the impact on the joint processing of sound pressure and velocity is small. In summary, under far-field conditions, the lack of coherence between sound pressure and velocity is small, and when x is large enough, it can be approximated to be completely coherent. Therefore, the impact of shallow sea multipath conditions on the joint processing of sound pressure and velocity is multifaceted: according to analysis, the shallow sea channel has a larger impact on the near field and a smaller impact on the far field; the impact on the horizontal velocity component is relatively smaller than the impact on the vertical velocity. In response to the problem of missing correlation, the present invention adopts a method of compensating for phase angles and proposes a high-precision direction finding method under shallow sea channels.

[0056] 2. Vector hydrophone direction finding based on cooperative sound source search and phase compensation

[0057] From the analysis of the sound pressure velocity model under the shallow sea multipath model, it can be seen that there is a serious lack of correlation between the velocity (especially the vertical velocity) and the sound pressure in the shallow sea environment. Therefore, in order to achieve high-precision direction finding, it is necessary to first search for the compensation angle of the velocity channel. The compensation angle search method of the present invention introduces a cooperative sound source to assist in searching for the maximum compensation phase angle. The specific steps of the preferred embodiment of the present invention are as follows:

[0058] Step 1: The three-dimensional vector hydrophone receives the sound pressure and vibration velocity signals of the target source. The received signal is first filtered and amplified. The frequency band of the bandpass filter is 200-400 Hz. Then it is sampled through the A / D circuit with a sampling rate of f s , and obtain the discrete signal p(n'T s ),v x (n'T s ),v y (n'T s ),v z (n'T s ), where T s =1 / f s , n'=1,2,…,N', N' is the data length.

[0059] Step 2: Search for cooperative sound sources and obtain their sound pressure, horizontal velocity, and vertical velocity channel signals. All non-primary targets with a certain correlation between sound pressure and velocity can be used as cooperative sound sources. In the marine environment, isotropic noise is uncorrelated with sound pressure and velocity, while anisotropic noise is correlated. Therefore, in the absence of an obvious target, anisotropic noise can also be used as a cooperative target.

[0060] Step 3: Perform correlation calculation on these channel signals to obtain their Pearson correlation coefficients. The calculation method is as follows:

[0061]

[0062] In the formula, p and v' are the combined field strength of each reflected sound line, and v' is the vibration velocity signal after phase compensation. and is the mean of the corresponding sequence. The phase compensation angle is searched in the range of [-90°, 90°], and the phase offset compensation is performed on the horizontal and vertical vibration velocities. x 、v y The correlation is almost perfect, and the phase compensation angle is approximately equal. The Hilbert transform can be used to obtain the complex signal after the original real signal is analyzed:

[0063]

[0064] The complex signal carries the instantaneous phase information, which is convenient for processing and performing phase offset on the horizontal and vertical vibration velocities:

[0065]

[0066] in, and is the phase compensation angle of the horizontal and vertical dimensions, v' x (n) and v' z (n) is the signal sequence after compensation. After phase shift, the out-of-phase wave of the original waveform is obtained, and its correlation coefficient is calculated.

[0067] Step 4: Repeat step 3. After searching all compensation angles, use equation (6) as the objective function to obtain a horizontal vibration phase compensation angle: and vertical vibration phase compensation angle The corresponding compensation is to achieve the maximum amplitude of the sound pressure-velocity correlation of the target source. The process of step 2 to step 4 is shown in Figure (3).

[0068] Step 5: Perform FFT transformation on the four channels, convert the time domain to the frequency domain, and obtain the frequency domain signal of each channel as P(f m )、Vx(f m )、Vy(f m ) and Vz(f m ), m = 1, 2, ..., M, where M is the number of all frequency units, and the instantaneous phase of all frequency units is Extraction, taking the sound pressure channel as an example, the extraction method is as follows:

[0069]

[0070] Where n = n'T s , sampling period T s =1 / fs , f s is the sampling rate, n'=1,2,…,N', N' is the data length.

[0071] Step 6: After extracting the instantaneous phase difference, calculate the variance of the difference, average the variance of the four channels, and get the weighted value after mean filtering. The signal spectrum is weighted by phase difference, and the final spectrum expression is:

[0072]

[0073] What you get and is the final spectrum.

[0074] Step 7: Conjugate the processed three-channel vibration velocity spectrum with the sound pressure spectrum to obtain the cross-spectrum results:

[0075]

[0076] in, and V x (f) V y (f) and V z (f) Conjugate spectrum.

[0077] According to the basic characteristics of Fourier transform, the energy of two signals with the same phase is mainly concentrated in the real part. In the shallow sea channel, the horizontal vibration velocity v x and v y The correlation loss with the sound pressure is small and is approximately in phase, and the vertical vibration velocity and sound pressure also basically conform to this characteristic after correlation compensation. Therefore, the sound energy flow I of each frequency energy is obtained by taking the real part of each cross spectrum result. x (f) I y (f) and I z (f) Use the acoustic energy flow to estimate the horizontal azimuth and elevation angle at this frequency:

[0078]

[0079] What you get and φ(f) are the estimated values ​​of the horizontal azimuth and elevation angle, respectively.

[0080] Step 8. The azimuth and elevation angles corresponding to each frequency point are counted. When the frequency range of the target radiation noise is unknown, the target azimuth cannot be directly obtained. Therefore, it is necessary to use the histogram statistics method to count the azimuths corresponding to each frequency point. When there is a broadband target signal, the azimuths corresponding to each frequency point of the signal are within a certain range, while the azimuths corresponding to each frequency point in the noise band are randomly distributed. Divide [0°, 360°] into several intervals Δθ, and divide [-90°, 90°] into several intervals Δφ, then the total number of intervals allowed for the spatial angle is:

[0081]

[0082] Scan the entire frequency band to obtain the corresponding angle. Assume that the number of estimated azimuths of each frequency point in the horizontal dimension that fall into each statistical angle interval is The number of vertical dimensions is Then calculate the following statistic R(θ):

[0083]

[0084] The distribution of acoustic energy flow in each statistical interval is obtained; where R θ (f) and R φ (f) is the modulus of the acoustic energy flow that conforms to the angle range of the statistical interval, and the specific calculation formula is as follows:

[0085]

[0086] These modulus values ​​are used as weights of the corresponding azimuth counts, and the estimated values ​​of each frequency point are counted. The final result is the accurate horizontal azimuth and pitch angle. The accurate azimuth estimation process of step 5 to step 8 is shown in Figure (4).

[0087] 3. Performance Analysis

[0088] In order to verify the principle of joint analysis of sound pressure and vibration velocity in shallow sea channels, a phase angle search and compensation experiment based on cooperative sound sources was first carried out. The sea surface in the simulation was an ideal mirror, i.e., r s =1, the seafloor reflection coefficient is r b=0.7, the sound speed is c=1500m / s, the seabed depth H is 35m, the sound source depth h=12m, the receiving point hydrophone depth z=15m, the target sound source and the hydrophone horizontal distance x=100m, the target signal is a Gaussian white noise superimposed with a line spectrum signal of 200-400Hz (step length is 1Hz), to simulate the sound source signal and the ocean background noise, the sampling frequency is 1024Hz, the signal-to-noise ratio is -5-30dB randomly distributed, and the number of each type of sound line n is 10. A comparison chart of the sound pressure and vertical vibration velocity correlation coefficient of the original signal and the compensated signal is given, as shown in Figure 6(a). In this frequency band, the method of the present invention can increase the correlation coefficient by an average of 0.1307, which is an average increase of 180.69% compared with the original signal; a comparison chart of the sound pressure and horizontal vibration velocity correlation coefficient of the original signal and the compensated signal is given, as shown in Figure 6(b). In this frequency band, the correlation coefficient of the signal compensated by the method of the present invention is increased by an average of 29% compared with the original signal.

[0089] The time-azimuth history diagrams of the traditional method and the correlation compensation direction-finding method are plotted to obtain the direction-finding stability results of the method, as shown in Figure 7(a) and Figure 7(b), respectively. By comparing Figure 7(a) and Figure 7(b), it can be seen that the traditional complex sound intensity method has a large correlation loss between the vertical velocity and the sound pressure in the shallow sea environment, the angle estimation accuracy is low and the variance is large, and the time-azimuth history diagram is relatively fuzzy. In contrast, the direction-finding method under phase search compensation has better correlation and a clearer history diagram, which reflects that it has higher stability than the traditional method. At the same time, the method of the present invention also achieves a higher direction-finding accuracy in the azimuth estimation of the horizontal dimension. The time-azimuth history diagram of the method of the present invention is shown in Figure 7(c).

[0090] Monte Carlo comparison experiments were conducted on the method of the present invention, the traditional complex sound intensity method, and the instantaneous phase difference weighted direction finding method within the signal-to-noise ratio range of -20 to 30 dB, and 40,000 independent direction finding experiments were conducted for each spectral level ratio. The sampling length was T = 10s, and the sampling frequency was f s is 1024Hz. The sampling target line spectrum frequency of each experiment is uniformly distributed within 200Hz~400Hz, the horizontal azimuth angle is uniformly distributed within 0°~360°, the sound source depth h, the hydrophone depth and the horizontal distance x between the two are randomly distributed. Under this condition, the pitch angle is uniformly distributed within -90°~90°, so that the target signal is in the ocean environment noise simulated by Gaussian white noise. The simulation results are shown in Figure 8 As shown in the figure, the relationship between the root mean square error (RMSE) and the signal-to-noise ratio of the three is obtained. Under different signal-to-noise ratios, the method of the present invention has a lower root mean square error. In the signal-to-noise ratio range of -20 to 30 dB, the root mean square error of the method of the present invention is reduced by 33.55% compared with the traditional complex sound intensity method. Experiments show that the method of the present invention has higher direction finding accuracy in shallow sea environments.

[0091] In summary, the present invention discloses a single vector hydrophone multi-dimensional high-precision direction finding method based on a shallow sea channel model. The traditional vector hydrophone direction finding method is basically based on a deep sea free field model, which is characterized by the sound pressure and vibration velocity of underwater point source targets being completely correlated. However, the related methods generally have the problem of low direction finding accuracy and large variance in a shallow sea multi-path environment, and the same problem exists in the pitch angle estimation in the vertical dimension. Based on this, the present invention firstly gives a shallow sea channel model of a vector hydrophone according to the Cartesian coordinate system, analyzes the problem of the lack of correlation between the sound pressure and velocity of the vector hydrophone under shallow sea channel conditions based on the shallow sea channel model, and proposes a multi-dimensional high-precision direction finding method of a single vector hydrophone based on a cooperative sound source and suitable for a shallow sea channel environment. The present invention first searches for a cooperative sound source, and then based on the cooperative sound source, calculates the phase compensation angle of the velocity channel and compensates the phase angle with the correlation coefficient between the sound pressure and velocity of the vector hydrophone as the objective function, so as to achieve the maximum amplitude improvement of the sound pressure-velocity correlation of the target source, and then improves the signal-to-noise ratio of the line spectrum and narrowband signal through instantaneous phase difference weighted processing, and finally achieves high-precision azimuth estimation of the horizontal and vertical dimensions of the underwater target. The simulation analysis results prove the effectiveness and good engineering practicality of the processing method of the invention.

[0092] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the scope of the present application should be based on the protection scope of the claims.

Claims

1. A single vector hydrophone multi-dimensional high-precision direction finding method based on a shallow sea channel model is characterized by: The following steps are involved: Step 1, extracting the sound pressure channel and three-dimensional vibration velocity channel information of the single vector hydrophone and performing discretization processing; Step 2: Search for a point source target signal as a collaborative sound source and obtain the sound pressure p and horizontal vibration velocity v x And the vertical vibration velocity v z ; Step 3: In the range of [-90°, 90°], the horizontal and vertical vibration speeds are adjusted with a step size of and Phase search compensation is performed, and the correlation coefficient c between the compensated vibration velocity and sound pressure is calculated i and c ii ; Step 4: Repeat step 3 until all compensation angles are searched, and then use the correlation coefficient as the objective function to obtain the optimal compensation phase angle of horizontal vibration velocity. and vertical vibration speed optimal compensation phase angle Step 5: Perform FFT transformation on the four-channel discrete signals of the vector hydrophone, and calculate the values ​​of the horizontal two-dimensional vibration velocity and the vertical vibration velocity. Phase offset compensation is performed to extract the instantaneous phase of each frequency unit of the four channels; Step 6: Calculate the variance of the instantaneous phase difference of the four channels, perform mean filtering, and weight them to the corresponding frequency units to obtain the final frequency domain estimation value; Step 7: Perform three-channel sound pressure and vibration velocity conjugate cross-spectral processing on the weighted sound pressure and three-dimensional vibration velocity frequency domain estimation values, and then take the real part to obtain a three-dimensional acoustic energy flow estimation value, and use the acoustic energy flow estimation value to estimate the horizontal azimuth and pitch angle of each frequency point; Step 8: Cluster the azimuth angles of each frequency point, use the acoustic energy flow as a weight to calculate the angle estimate, and obtain the precise azimuth.

2. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 1, characterized in that: The normalized vector output model expression at the shallow sea multipath receiving point is: Among them, the horizontal azimuth angle from the sound source to the receiving point is θ, and the propagation path length of the i-th sound line is r i , the corresponding pitch angle is φ i , the corresponding attenuation factor is a i , i = 1, 2, ···, j is the imaginary unit, e is the base of the natural logarithm, p is the sound pressure signal picked up by the vector hydrophone, v x is the velocity signal in the X-axis direction picked up by the vector hydrophone, v y is the vibration velocity signal in the Y-axis direction picked up by the vector hydrophone, v z is the vibration velocity signal in the Z-axis direction picked up by the vector hydrophone, the wave number k = ω / c, ω is the angular velocity of the signal, and the acoustic impedance ratio Z = ρc is a constant of the ratio of sound pressure to the vibration velocity mode.

3. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 1 or 2, characterized in that: In step 1, the single vector hydrophone receives the sound pressure and vibration velocity signals of the target source. The received signal is first filtered and amplified, with a bandpass filter of 200 to 400 Hz, and then sampled by an A / D circuit with a sampling rate of f s , and get the discrete signals p(n), v x (n), v y (n), v z (n).

4. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 3, characterized in that: In step 3, the correlation of the cooperative sound source target is used as the compensation target, all compensation angles are searched within [-90°, 90°], and the Pearson correlation coefficient is calculated as follows: In the formula, p and v' are the combined field strength of each reflected sound line, and v' is the vibration velocity signal after phase compensation. and is the mean of the corresponding series.

5. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 4, characterized in that: In step 3, the horizontal and vertical vibration velocities of the vector hydrophone are analytically compensated by the searched horizontal and vertical vibration compensation phase angles, and the analyzed complex signal is obtained by Hilbert transform: Perform phase offset compensation on horizontal and vertical vibration velocities: in, and is the phase compensation angle of the horizontal and vertical dimensions, v' x (n) and v' z (n) is the signal sequence after compensation.

6. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 5, characterized in that: In step 5, the four-channel discrete signals are transformed by FFT, and the time domain is converted to the frequency domain, and the frequency domain signal of each channel is obtained as P(f m )、Vx(f m )、Vy(f m ) and Vz(f m ), m = 1, 2, ···, M, where M is the number of all frequency units, and the instantaneous phase of all frequency units is Extraction, the formula is as follows: Where n = n'T s , sampling period T s =1 / f s , f s is the sampling rate, n'=1,2,···,N', N' is the data length.

7. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 6 is characterized by: In step 6, the instantaneous phase difference is weighted as follows: in, is the weighted value obtained after the four-channel average fitting and mean filtering. and is the final spectrum.

8. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 7, characterized in that: In step 7, the processed three-channel sound pressure velocity spectrum is conjugated with the sound pressure spectrum to obtain the cross-spectrum result: in, and V x (f) V y (f) and V z (f) The conjugate spectrum; After averaging the cross-spectrum results over time and taking the real part, the acoustic energy flow I of each frequency energy is obtained. x (f) I y (f) and I z (f) Use the acoustic energy flow to estimate the horizontal azimuth and elevation angle at the frequency point: What you get and are the estimated values ​​of the horizontal azimuth and elevation angle respectively.

9. The single vector hydrophone multi-dimensional high-precision direction finding method based on the shallow sea channel model as claimed in claim 8, characterized in that: In step 8, [0°, 360°] is divided into several intervals Δθ, and [-90°, 90°] is divided into several intervals Δφ. The total number of intervals allowed for the spatial angle is: Scan the entire frequency band to obtain the corresponding angle. Assume that the number of estimated azimuths of each frequency point in the horizontal dimension that fall into each statistical angle interval is m1, m2, m3, ..., The number of vertical dimensions are m1, m2, m3, ..., Then calculate the following statistic R(θ): The distribution of acoustic energy flow in each statistical interval is obtained; where R θ (f) and R φ (f) is the modulus of the acoustic energy flow that conforms to the statistical interval angle range, and the specific calculation formula is as follows: The modulus value is used as the weight of the corresponding azimuth count, and the estimated values ​​of each frequency point are counted. The final result is the accurate horizontal azimuth and pitch angle.

Images