Line spectrum target depth attribute robust discrimination method for vertical array

Abstract

The invention belongs to the field of underwater target identification, and provides a line spectrum target depth attribute robust discrimination method for a vertical array, and the method comprises the steps: adding sampling points in the depth direction of a shallow sea waveguide, carrying out the filtering of an internal coupling mode of a receiving sound pressure amplitude of the vertical array through employing the modal orthogonality formed by the sampling of the vertical array, and carrying out the recognition of a target depth attribute. And extracting steady line spectrum sound pressure amplitude fluctuation characteristics of a sound source in a horizontal distance dimension. And fusing the vertical array element data to obtain a vertical array sound pressure amplitude. The modal orthogonality enables the vertical array sound pressure amplitude to eliminate the influence of a normal wave coherent item related to the sound source distance and the receiving depth on the fluctuation characteristics of the line spectrum amplitude. According to the method, a small amount of vertical array sound pressure amplitude data is utilized to construct the discriminating characteristic quantity sound pressure amplitude fluctuation index, efficient discrimination is realized, and the required calculation amount is small. Meanwhile, the sound source depth attribute discrimination performance is not reduced along with the change of the relative horizontal distance of the sound source, and robustness is achieved.

Description

Technical Field

[0001] The invention belongs to the field of underwater target recognition of water acoustics and water surfaces, and in particular relates to a robust discrimination method for depth attributes of line spectrum targets of a vertical array. Background Art

[0002] Depth attribute discrimination of sound sources in shallow water environments is one of the hot and difficult issues in the field of passive sonar detection. Accurately judging whether non-cooperative sound sources are located on the surface or underwater is of great practical significance for ensuring underwater environmental safety.

[0003] When a sound source moves in the ocean, its depth will fluctuate due to waves and seawater inhomogeneity. The fluctuation of the sound source depth causes the amplitude of the line spectrum noise radiated by the surface and underwater sound sources to fluctuate to varying degrees at the receiving point, among which the line spectrum fluctuation of the surface sound source is stronger than that of the underwater sound source. This difference in fluctuation characteristics can be used to distinguish between surface and underwater sound sources. Existing studies have shown that the essence of line spectrum fluctuation is the fluctuation of different-order simple normal waves excited by the sound source on the surface and underwater. Therefore, scholars have successively constructed the modal scintillation index (MSI), the improved (normalized) modal scintillation index (MMSI, Modified-MSI), and the fused modal scintillation index (FMSI, Fused-MSI), so as to distinguish the line spectrum targets on the surface and underwater by using the difference in the fluctuation of different-order modes on the surface and underwater. However, the premise of the above methods is to separate the modes of each order from the signal, which places high demands on the amount of calculation and is often difficult to meet.

[0004] In order to achieve more efficient source depth attribute discrimination, the sound pressure amplitude of the surface and underwater line spectrum sound sources at the receiving point is directly used to construct discrimination feature quantities. The prior art discloses a line spectrum target depth attribute discrimination method for a horizontal towed array ([RAWagstaff 1997] The AWSUM Filter: A 20-dB Gain Fluctuation-based Processor). This method constructs a normalized discrimination feature quantity using a small amount of data, which can achieve target depth attribute discrimination. However, when the horizontal distance of the sound source changes, the difference in the fluctuation characteristics of the surface and underwater sound pressure amplitudes obtained by the passive sonar system with a fixed working depth will weaken. This leads to a decrease in the discrimination accuracy of this method.

[0005] The invention patent with application number 2020102920511 and titled "Single hydrophone target identification method based on fused modal flicker index" and the invention patent with application number 2020106130377 and titled "Target depth identification method and system based on modal flicker index matching analysis" both utilize the undulating line spectrum and separate the mode from the signal to qualitatively identify the target as a surface target or underwater target. However, the calculation amount is large. The former requires a relatively long sound source motion time for judgment, and the latter uses a matching processing method, which makes the stability worse when the environment changes.

[0006] In summary, the depth attribute discrimination method of the undulating line spectrum target in the prior art cannot achieve both high discrimination efficiency and good discrimination performance. Therefore, it is urgent to use a new discrimination method that can achieve robust target depth attribute discrimination. Summary of the invention

[0007] In order to overcome the shortcomings of the existing target depth attribute discrimination method based on the fluctuation line spectrum amplitude that it is difficult to have both discrimination efficiency and discrimination performance, the present invention proposes a robust discrimination method for shallow sea line spectrum target depth attributes for vertical arrays. This method adds sampling points in the depth direction of the shallow sea waveguide, and uses the modal orthogonality formed by vertical array sampling to filter the intrinsic coupling mode of the vertical array received sound pressure amplitude, and extracts the line spectrum sound pressure amplitude fluctuation characteristics that are robust in the horizontal distance dimension of the sound source. The vertical array array metadata is fused to obtain the vertical array sound pressure amplitude. Modal orthogonality enables the vertical array sound pressure amplitude to eliminate the influence of the simple normal wave coherence terms related to the sound source distance and receiving depth on the line spectrum amplitude fluctuation characteristics. The present invention uses a small amount of vertical array sound pressure amplitude data to construct a discriminant feature quantity sound pressure amplitude fluctuation index to achieve efficient discrimination. At the same time, the sound source depth attribute discrimination performance does not decrease with the change of the relative horizontal distance of the sound source, and is robust.

[0008] The technical solution of the present invention is: a robust discrimination method for line spectrum target depth attributes of a vertical array, comprising the following steps:

[0009] Step 1: Extract the line spectrum sound pressure amplitude from the time domain signal received by the vertical array elements;

[0010] Step 2: Use modal orthogonality to filter out the simple normal wave coherence terms related to horizontal distance and obtain the vertical array sound pressure amplitude;

[0011] Step 3: Calculate the normalized depth attribute discrimination feature quantity related to the vertical array sound pressure amplitude fluctuation degree;

[0012] Step 4: Preset the discrimination threshold value according to the waveguide environment information, and compare the discrimination feature quantity with the discrimination threshold value.

[0013] Furthermore, the step 1 includes the following sub-steps:

[0014] Step 1.1: In a shallow sea environment with a water depth of D, an N-element vertical array is used to receive the target radiation line spectrum signal. The line spectrum frequency domain sound pressure field received by the nth array element is expressed as

[0015]

[0016] z n 、z s are the receiving depth of the nth array element in the vertical array and the sound source depth, r is the relative horizontal distance between the sound source and the vertical array, With k rm They represent the modal function and horizontal wave number of the mth mode excited by the sound source, Q represents the sound pressure amplitude related term, the target moves away from the vertical array, and the fluctuation of the movement depth is Δz s , M is the M-order simple normal wave excited by the sound source, and N is greater than M;

[0017] Step 1.2: Define the receiving depth of the nth array element as z n The nth group of time domain signals collected by the vertical array within time t is recorded as x n (t). Divide the nth group of time domain signals within time t into L frame time domain sub-bands, and divide the time domain signals received by the vertical array into N×L frame time domain sub-bands x n (t l ), perform Fourier transform on each frame of time domain signal to frequency domain; determine the target line spectrum frequency, and extract the N×L dimensional sound pressure matrix of the target frequency point, denoted as Y:

[0018] Y=[p 1 ,p 2 ,,p L ]

[0019] Among them, p l Represents the column vector composed of the frequency domain sound pressure on all array elements of the vertical array in the lth frame;

[0020] Without considering the change of the horizontal distance of the sound source, the amplitude of the frequency domain line spectrum sound pressure of the first frame received by the vertical array can be expressed in vector form by combining equation (1):

[0021] p l =[p(r,z 0 ,z s ),p(r,z 1 ,z s ),,p(r,z N-1 ,z s )] T

[0022] =a T ψ

[0023] Among them, the superscript T represents the matrix transpose, a represents the modal matrix corresponding to the vertical array, ψ represents the sound source position matrix, and the expressions are as follows:

[0024]

[0025]

[0026] Furthermore, the step 2 includes the following sub-steps:

[0027] Step 2.1: Calculate the sum of the frequency domain acoustic powers received by the N vertical array elements in the lth frame

[0028]

[0029] Step 2.2: Combined with step 2.1, further obtain the vertical array sound pressure amplitude of the first frame received by the vertical array:

[0030]

[0031] Among them, the vector composed of the vertical array sound pressure amplitude of L frames is recorded as

[0032]

[0033] Among them, diag means taking diagonal elements;

[0034] 4. The robust discrimination method for depth attribute of line spectrum target for vertical array according to claim 1, characterized in that in said step 3, the L-frame vertical array received sound pressure amplitude obtained in step 2 is used to calculate the discrimination feature quantity. The discrimination feature quantity is named as the sound pressure amplitude fluctuation index (Amplitude Fluctuation Index, AFI), which is specifically written as

[0035]

[0036] Among them, |p l | represents the vertical array sound pressure amplitude in the lth frame, and the denominator is the harmonic mean of the vertical array receiving sound pressure amplitudes in L frames.

[0037] Furthermore, the step 4 includes the following sub-steps:

[0038] Step 4.1: At different sound source depths, use the acoustic toolbox to calculate the result of equation (13) corresponding to the line spectrum frequency to be determined, and draw the depth distribution curve of the sound pressure amplitude fluctuation index;

[0039] Step 4.2: Determine the critical depth for distinguishing between surface and underwater targets, and preset the discrimination threshold value AFIh according to the sound pressure amplitude fluctuation index curve;

[0040] Step 4.3: Compare the sound pressure amplitude fluctuation index AFI calculated in step 3 with the discrimination threshold value AFIh to judge whether the target is on the water surface or underwater. If AFI<AFIh, the target is an underwater target; otherwise, the target is a surface target.

[0041] Effects of the Invention

[0042] The technical effect of the present invention is that the basic principle and implementation scheme of the present invention have been verified by computer numerical simulation, and the results show that the present invention directly uses the line spectrum sound pressure amplitude received by the vertical array to construct the discrimination feature quantity, and the required calculation amount is extremely small. At the same time, the method proposed by the present invention makes full use of the modal orthogonality formed by the vertical array, and filters the horizontal distance item of the sound source that affects the difference in the fluctuation characteristics of the line spectrum amplitude on the water surface and underwater, thereby having better sound source depth attribute discrimination performance than the method of a single receiving depth. The present invention has both the advantages of discrimination efficiency and discrimination performance, and can achieve robust line spectrum target depth attribute discrimination. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A coordinate schematic diagram of the discrimination method proposed by the present invention;

[0044] Figure 2 Flowchart of the present invention

[0045] Figure 3 A process for processing vertical array acquisition signals to determine target depth attributes;

[0046] Figure 4 (a) vertical array sound pressure amplitude corresponding to 5m and 70m sound sources, Figure 4 (b) discrimination result of depth attributes of 5m and 70m sound sources;

[0047] Figure 5 The sound pressure amplitude fluctuation index at different sound source distances;

[0048] Figure 6 Discrimination-false alarm probability curves of the existing discrimination method (single receiving depth) and the method proposed in the present invention. DETAILED DESCRIPTION

[0049] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0050] See also Figure 1-Figure 6 , the present invention proposes a method for robustly discriminating the depth attributes of shallow-water line spectrum targets for vertical arrays. The method adds sampling points in the depth direction of the shallow-water waveguide, and utilizes the modal orthogonality formed by vertical array sampling to filter the intrinsic coupling modes of the vertical array received sound pressure amplitude, and extracts the line spectrum sound pressure amplitude fluctuation characteristics that are robust to the horizontal distance dimension of the sound source. The vertical array sound pressure amplitude is obtained by fusing the vertical array array metadata. Modal orthogonality enables the vertical array sound pressure amplitude to eliminate the influence of the simple normal wave coherence terms related to the sound source distance and receiving depth on the line spectrum amplitude fluctuation characteristics. The present invention uses a small amount of vertical array sound pressure amplitude data to construct a discriminant feature quantity sound pressure amplitude fluctuation index to achieve efficient discrimination. In addition, the sound source depth attribute discrimination performance does not decrease with the change of the relative horizontal distance of the sound source, and is robust.

[0051] The main contents of the present invention are:

[0052] 1. In the shallow sea environment, a vertical linear array is used to receive the target radiation line spectrum noise signal. The vertical array covers the entire water depth and is arranged at equal intervals. The number of vertical array elements is greater than the order of the simple normal wave excited by the sound source in the shallow sea. The vertical array elements are increased in the depth direction of the sound source to fully sample the modes excited by the sound source. The modal orthogonality is used to filter the intrinsic coupling modes of the sound pressure amplitude received by the vertical array to extract the robust line spectrum fluctuation characteristics of the horizontal distance dimension of the sound source.

[0053] 2. Extract the sound pressure amplitude fluctuation characteristic from the vertical array acquisition signal. Divide the time domain signal of the N array element channels into N×L time domain subbands, and perform Fourier transform on them to extract the N×L dimensional sound pressure matrix of the line spectrum target frequency point. Multiply the conjugate transpose of the frequency domain sound pressure matrix with itself, extract all diagonal elements from the resulting L×L dimensional square matrix, and obtain the L×1 dimensional vertical array element sound power and vector after modal filtering. Take the square root of the sound power and vector to obtain the L-frame vertical array sound pressure amplitude with stable fluctuation characteristics, which is defined as the vertical array sound pressure amplitude. Calculate the harmonic mean and arithmetic mean of the L-frame vertical array sound pressure amplitude to obtain the normalized characteristic quantity that characterizes the sound pressure amplitude fluctuation, which is defined as the sound pressure amplitude fluctuation index.

[0054] 3. Draw a sound pressure amplitude fluctuation index curve based on environmental information to preset the discrimination threshold. Compare the sound pressure amplitude fluctuation index with the discrimination threshold value to obtain the depth attribute discrimination result of the sound source.

[0055] 4. The feasibility of the discrimination method proposed in the present invention is given through computer numerical simulation, and the accuracy of sound source depth attribute discrimination between the horizontal array method with a fixed receiving depth and the method proposed in the present invention is compared, thereby proving that the method proposed in the present invention can obtain more robust sound source depth attribute discrimination performance.

[0056] like Figure 2 As shown in the flow chart, the technical solution adopted by the present invention to solve the existing problems can be divided into the following four steps:

[0057] 1) In a shallow sea environment, an N-element vertical array (N is greater than the order of the simple normal wave excited by the sound source) is used to receive the target radiation line spectrum noise signal. The time domain signal in which the sound source movement distance is much smaller than the horizontal distance of the sound source within the time period is intercepted, and the time domain signal is divided into L-frame time domain subbands. Each frame of the time domain signal is Fourier transformed into the frequency domain, and the N×L-dimensional sound pressure matrix of the line spectrum target frequency point is extracted.

[0058] 2) Calculate the product of the conjugate transposed matrix of the N×L dimensional sound pressure matrix in 1) and itself to obtain an L×L dimensional square matrix, extract all diagonal elements in the L×L dimensional square matrix, and obtain an L×1 dimensional vector composed of the sum of the vertical array element sound powers. Due to the modal orthogonality formed by the vertical array, the vector elements filter out the simple normal wave coherence terms related to the horizontal distance of the sound source. Calculate the square root of the vector elements to obtain the L-frame vertical array sound pressure amplitude. The vertical array sound pressure amplitude has a robust fluctuation characteristic in the horizontal distance dimension of the sound source.

[0059] 3) Calculate the harmonic mean and arithmetic mean of the vertical array sound pressure amplitude of L frames in 2) to obtain the normalized sound pressure amplitude fluctuation characteristic quantity, that is, the sound pressure amplitude fluctuation index.

[0060] 4) Obtain water depth, sound velocity profile and bottom quality data, and use the acoustic toolbox to draw the depth distribution curve of the sound pressure amplitude fluctuation index of the line spectrum in 1). Determine the critical depth for distinguishing surface and underwater targets, and preset the discrimination threshold value on the sound pressure amplitude fluctuation index curve. In a given shallow sea environment, the threshold value is independent of the horizontal distance from the sound source and is stable. Compare the size of the sound pressure amplitude fluctuation index in 3) and the discrimination threshold value. If the discrimination feature value is less than the threshold value, the target is underwater; otherwise, the target is on the surface.

[0061] Each step of the present invention is described in detail below:

[0062] The specific contents involved in step 1) are as follows:

[0063] like Figure 1 As shown in the figure, in a shallow sea environment with a water depth of D, an N-element vertical array is used to receive the target radiation line spectrum signal. The receiving depth of the nth array element is z n The nth group of time domain signals collected by the vertical array within time t is recorded as x n (t). The sound source excites an M-order normal wave. Where N is greater than M. According to the normal wave propagation theory, the line spectrum frequency domain sound pressure field received by the nth array element can be expressed as

[0064]

[0065] Among them, zn 、z s are the receiving depth of the nth array element in the vertical array and the sound source depth, r is the relative horizontal distance between the sound source and the vertical array, With k rm They represent the modal function and horizontal wave number of the mth mode excited by the sound source, and Q represents the sound pressure amplitude related term. The target moves away from the vertical array, and the fluctuation of the movement depth is Δz s .

[0066] like Figure 3 As shown in the process, the time domain signal is divided into N×L frame time domain subbands x n (t l ). In a set of signals, the sound source depth changes once per frame. Perform Fourier transform on each frame of the time domain signal to the frequency domain. Determine the target line spectrum frequency and extract the N×L dimensional sound pressure matrix Y of the target frequency point. The sound pressure matrix Y consists of L frequency domain sound pressure column vectors, denoted as

[0067] Y=[p 1 ,p 2 ,,p L ] (2)

[0068] Among them, p l Represents the column vector composed of the frequency domain sound pressure on all array elements of the vertical array in the lth frame.

[0069] Line spectrum fluctuation is a fast-changing feature. The moving distance of the sound source in L frames is much smaller than the relative distance between the sound source and the receiver. The change of the horizontal distance of the sound source is not considered here. Combining formula (1), the frequency domain sound pressure vector of the lth frame received by the vertical array is expressed as

[0070]

[0071] The superscript T represents the matrix transpose. The modal matrix and the sound source position matrix corresponding to the vertical array are expressed as

[0072]

[0073] The specific contents involved in step 2) are as follows:

[0074] Calculate the sum of the N frequency domain sound powers in each frame, and then square the result to get the sound pressure amplitude received by the vertical array. Define the modal correlation matrix R = aa H , then the sum of the N frequency domain sound powers in the lth frame is It can be expressed as

[0075]

[0076] The superscript H represents the conjugate transpose.

[0077] The vertical array covering the entire water depth can fully sample the information of each mode. At this time, the modal functions satisfy the orthogonal relationship, that is,

[0078]

[0079] Among them, ρ(z) represents the water density at different depths, δ mn is the Dirac function. From equation (7), we can see that when the water density is uniform, the modal correlation matrix obtained by vertical array sampling with a finite number of array elements is approximately a diagonal matrix with equal diagonal elements, while the non-diagonal elements are approximately 0. Let the water density be 1. At this time, the mean sound power of equation (6) is approximately

[0080]

[0081] The vertical array sound pressure amplitude of the first frame received by the vertical array is further obtained as

[0082]

[0083] The vector composed of the vertical array sound pressure amplitude of L frames is recorded as It is composed of the square root of the diagonal elements of the matrix after multiplying the sound pressure matrix of formula (2) with its conjugate transposed matrix. It can be written as

[0084]

[0085] Among them, diag means taking diagonal elements.

[0086] Equation (9) shows that by superimposing the sound power received by all array elements, the horizontal distance factor of the sound source coupled with the modal in the simple normal wave coherence term is filtered out. The sound pressure amplitude is only a simple superposition of the modal functions of each order. By taking the derivative of equation (9) in the direction of the sound source depth, the fluctuation of the sound pressure amplitude in adjacent frames can be obtained, that is,

[0087]

[0088] At the water surface depth, the modal function and its derivative are always positive. Equation (11) satisfies the inequality at the water surface depth

[0089]

[0090] At a depth far from the water surface, according to the Cauchy-Schwarz inequality, equation (11) satisfies the inequality

[0091]

[0092] The right-hand side of equations (12) and (13) has the characteristic that the water surface is higher than that underwater. It can be further seen that the vertical array sound pressure amplitude obtained by equation (9) has a stable fluctuation characteristic difference between the water surface and underwater.

[0093] The specific contents involved in step 3) are as follows:

[0094] The discriminant feature quantity is calculated using the L-frame vertical array received sound pressure amplitude obtained in step 2). The discriminant feature quantity is named as the sound pressure amplitude fluctuation index (AFI, Amplitude Fluctuation Index), specifically:

[0095]

[0096] Among them, |p l | represents the vertical array sound pressure amplitude in the lth frame. The denominator of formula (13) is the harmonic mean of the vertical array received sound pressure amplitude in L frames. Formula (13) reflects the degree of deviation of the vertical array sound pressure amplitude relative to the average value, that is, the degree of fluctuation of the sound pressure amplitude in L frames described in formula (11). In addition, the sound pressure amplitude fluctuation index is independent of the horizontal distance of the sound source, the sound source level, and the number of array elements.

[0097] The specific contents involved in step 4) are as follows:

[0098] Get rough water depth, sound velocity profile and bottom data. From step 2), it can be seen that the modal orthogonality formed by the vertical array makes the vertical array sound pressure amplitude only a simple superposition of each order mode function. Therefore, the line spectrum fluctuation characteristics are not sensitive to changes in the sound velocity profile and bottom. At different sound source depths, the acoustic toolbox is used to calculate the result of formula (13) corresponding to the line spectrum frequency to be judged, and the depth distribution curve of the sound pressure amplitude fluctuation index is plotted. Determine the critical depth for distinguishing between surface and underwater targets, and preset the discrimination threshold value AFI based on the sound pressure amplitude fluctuation index curve. h Since the sound pressure amplitude fluctuation index depth distribution curve is stable in the horizontal distance dimension of the sound source, the threshold value is also reliable. Compare the discriminant feature quantity AFI calculated in step 3) with the discriminant threshold value AFI h , thereby determining whether the target is on the water surface or underwater. Specifically, if AFI<AFI h , the target is an underwater target; otherwise, the target is a surface target.

[0099] Taking the line spectrum target depth attribute discrimination in a shallow sea environment as an example, an implementation example of the present invention is given.

[0100] Basic simulation parameters:

[0101] In a shallow sea environment with constant sound velocity, the sea depth is 200m, the seawater sound velocity is 1500m / s, and the seawater density is 1.0g / cm 3 , the speed of sound on the seabed is 1800m / s, and the density of seawater is 1.5g / cm 3 , seabed absorption coefficient is 0.2dB.km / Hz.

[0102] Simulation 1: The frequency of the line spectrum sound source is 30Hz, and the 5th order simple normal wave is excited in the simulation environment. An 8-element receiving vertical array is set to cover the water layer of 1-200m. Consider the sound source at two depths, surface and underwater, with depths of 5m and 70m respectively. The sound source is 5km away from the vertical array. The critical depth for judging the target depth attribute is set to 15m. The sound source depth fluctuation follows a standard normal distribution with a mean of 0 and a variance of 1.

[0103] According to step 1) and step 2), the acoustic toolbox is used to calculate the frequency domain sound pressure of the sound source depth change 5 times (5 frames). In step 2), the normalized comparison result of the vertical array sound pressure amplitude corresponding to the surface and underwater sound sources is given in Figure 4(a). According to step 3), the sound pressure amplitude fluctuation index AFI of the two surface and underwater sound sources is calculated. According to step 4), after inputting the line spectrum target frequency, water depth, sound velocity profile, and bottom data into the acoustic toolbox, the depth distribution curve of the sound pressure amplitude fluctuation index is drawn. The discrimination threshold value is preset by the critical depth. The discrimination result is given in Figure 4(b).

[0104] In Figure 4(a), there is a difference in the fluctuation of the sound pressure amplitudes of the water surface and underwater vertical arrays received by the vertical array, among which the fluctuation of the water surface sound pressure amplitude represented by the 5m sound source is significantly stronger than that of the underwater sound pressure amplitude represented by the 70m sound source. Based on this characteristic difference, the sound pressure reproduction fluctuation index AFI of the two groups of vertical array sound pressure amplitudes is calculated. In Figure 4(b), the sound pressure amplitude fluctuation index corresponding to the 5m sound source is higher than the discrimination threshold corresponding to the 15m depth, while the 70m sound source is lower than the discrimination threshold. In addition, the discrimination threshold completely distinguishes targets with depth attributes above and below 15m. If the sound source is at other depths, the depth attribute can also be determined by the discrimination criterion of the present invention. This shows that the present invention can clearly discriminate the depth attribute of the line spectrum target.

[0105] Simulation 2: The frequency of the line spectrum sound source is 30Hz, and the relative distance between the sound source and the vertical array is set to 2-15km. Other parameters are the same as in simulation 1. The frequency domain sound pressure of the sound source depth is taken 5 times (5 frames), and the sound pressure amplitude fluctuation index of the sound source moving at a water depth of 1-200m is calculated by steps 2) and 3). The effect of the horizontal distance of the sound source on the depth attribute discrimination feature quantity is given by Figure 5 Given.

[0106] Figure 5 In the figure, the red dotted line represents the contour line of the -30dB discrimination threshold corresponding to the critical depth of 15m. The sound pressure amplitude fluctuation index on both sides of the contour line is significantly different. This shows that when the same sound source is located at different horizontal distances, the characteristic quantity of the present invention can characterize the stable surface and underwater sound pressure amplitude fluctuation differences, and the discrimination method is robust. In addition, when the sound source is located at different horizontal distances, the discrimination threshold value preset according to the environmental information is stable.

[0107] Simulation 3: The simulation parameters are the same as those of Simulation 2. The sound source is located at a distance of 5km and 6km from the receiving end respectively. The signal-to-noise ratio in the line spectrum band on the vertical array element is set to 15dB. Set 200 sound sources of 1-200m, and calculate the probability of accurate discrimination of each sound source depth and the probability of false alarm (the target is on the water surface but is judged to be underwater) based on the results of step 4), and draw the ROC curve. In addition, the ROC curve of the sound source depth attribute discrimination of the two receiving depth hydrophones of 1m and 50m is plotted. 100 Monte Carlo experiments are carried out for each case. Statistical proof of the robustness of the sound source depth attribute discrimination of the present invention compared with the prior art (single receiving depth). The results are shown in the figure. Figure 6 Given.

[0108] Figure 6 In the study, for sound sources at the same horizontal distance, the performance of hydrophones at different receiving depths in distinguishing the depth attributes of the sound sources showed great differences. The discrimination accuracy of the present invention reached 0.99 when the false alarm probability was 0.1, and the discrimination accuracy was better than that of the existing horizontal array (single receiving depth) method. When the horizontal distance of the sound source changes, the discrimination performance of the present invention remains unchanged, while the accuracy of the sound source depth attribute discrimination of the single receiving depth decreases. The statistical results show that the present invention is more robust than the depth attribute discrimination method of the single receiving depth.

Claims

1. A robust method for distinguishing line spectrum target depth attributes for vertical arrays, characterized in that: The following steps are involved: Step 1: Extract the line spectrum sound pressure amplitude from the time domain signal received by the vertical array elements; Step 2: Use modal orthogonality to filter out the simple normal wave coherence terms related to horizontal distance and obtain the vertical array sound pressure amplitude; Step 3: Calculate the normalized depth attribute discrimination feature quantity related to the vertical array sound pressure amplitude fluctuation degree; Step 4: Preset the discrimination threshold value according to the waveguide environment information, and compare the discrimination feature quantity with the discrimination threshold value.

2. The robust method for distinguishing line spectrum target depth attributes for a vertical array according to claim 1, characterized in that: The step 1 includes the following sub-steps: Step 1.1: In a shallow sea environment with a water depth of D, an N-element vertical array is used to receive the target radiation line spectrum signal. The line spectrum frequency domain sound pressure field received by the nth array element is expressed as z n 、z s are the receiving depth of the nth array element in the vertical array and the sound source depth, r is the relative horizontal distance between the sound source and the vertical array, With k rm They represent the modal function and horizontal wave number of the mth-order mode excited by the sound source, Q represents the sound pressure amplitude related term, the target moves away from the vertical array, and the fluctuation of the movement depth is Δz s , M is the M-order simple normal wave excited by the sound source, and N is greater than M; Step 1.2: Define the receiving depth of the nth array element as z n The nth group of time domain signals collected by the vertical array within time t is recorded as x n (t). Divide the nth group of time domain signals within time t into L frame time domain sub-bands, and divide the time domain signals received by the vertical array into N×L frame time domain sub-bands x n (t l ), perform Fourier transform on each frame of time domain signal to frequency domain; determine the target line spectrum frequency, and extract the N×L dimensional sound pressure matrix of the target frequency point, denoted as Y: Y=[p1,p2,…,p L ] Among them, p l Represents the column vector composed of the frequency domain sound pressure on all array elements of the vertical array in the lth frame; Without considering the change of the horizontal distance of the sound source, the frequency domain line spectrum sound pressure amplitude of the first frame received by the vertical array can be expressed in vector form by combining formula (1): p l =[p(r,z0,z s ),p(r,z1,z s ),…,p(r,z N-1 ,With s )] T =a T ψ Among them, the superscript T represents the matrix transpose, a represents the modal matrix corresponding to the vertical array, ψ represents the sound source position matrix, and the expressions are as follows:

3. The robust method for distinguishing line spectrum target depth attributes for a vertical array according to claim 1, characterized in that: The step 2 includes the following sub-steps: Step 2.1: Calculate the sum of the frequency domain acoustic powers received by the N vertical array elements in the lth frame Step 2.2: Combined with step 2.1, further obtain the vertical array sound pressure amplitude of the first frame received by the vertical array: Among them, the vector composed of the vertical array sound pressure amplitude of L frames is recorded as Among them, diag means taking diagonal elements.

4. The robust method for distinguishing line spectrum target depth attributes for a vertical array according to claim 1, characterized in that: In step 3, the discriminant feature quantity is calculated using the sound pressure amplitude of the L-frame vertical array received by step 2. The discriminant feature quantity is named as the sound pressure amplitude fluctuation index, which is specifically written as: Among them, |p l | represents the vertical array sound pressure amplitude in the lth frame, and the denominator is the harmonic mean of the vertical array receiving sound pressure amplitudes in L frames.

5. The robust method for distinguishing line spectrum target depth attributes for a vertical array according to claim 1, characterized in that: The step 4 includes the following sub-steps: Step 4.1: At different sound source depths, use the acoustic toolbox to calculate the result of equation (13) corresponding to the line spectrum frequency to be determined, and draw the depth distribution curve of the sound pressure amplitude fluctuation index; Step 4.2: Determine the critical depth for distinguishing between surface and underwater targets, and preset the discrimination threshold value AFIh according to the sound pressure amplitude fluctuation index curve; Step 4.3: Compare the sound pressure amplitude fluctuation index AFI calculated in step 3 with the discrimination threshold value AFIh, so as to judge whether the target is on the water surface or underwater. If AFI<AFIh, the target is an underwater target; Otherwise, the target is a surface target.

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