A method for shallow-water target depth resolution based on vertical beam spectrum spatial difference factor

Abstract

The present invention discloses a shallow sea target depth resolution method based on a vertical beam spectrum spatial difference factor. Conventional beam forming processing is performed on the sound signal received by the vertical array to obtain a data beam diagram; based on environmental parameters, a copy field beam diagram of the vertical array is obtained; two-dimensional correlation coefficients are calculated based on the data beam diagram and the copy field beam diagram; the average correlation coefficients of the corresponding surface sound source interval and underwater sound source interval are respectively calculated based on the two-dimensional correlation coefficients; the vertical beam spectrum spatial difference factor is calculated according to the average correlation coefficient; and a surface target or underwater target is judged according to the vertical beam spectrum spatial difference factor and a judgment threshold. The present invention distinguishes whether the signal originates from a surface target or an underwater target based on the positive or negative sign of the vertical beam spectrum spatial difference factor; the present invention is insensitive to the initial distance of the sound source, that is, the target depth interval can be judged without accurately knowing the initial distance information of the sound source, and it is robust to the mismatch between the base array tilt and the seabed parameters.

Description

Technical Field

[0001] The invention belongs to the technical field of underwater acoustic positioning and identification, and in particular relates to a shallow sea target depth resolution method based on a vertical beam spectrum spatial difference factor. Background Art

[0002] In recent years, with the US strategic focus shifting to the Indo-Pacific, the submarine forces of countries and regions surrounding my country have developed rapidly. After the United States, Japan, Australia, India and other military powers have successively equipped a large number of Kilo-class submarines, Vietnam's submarine force has also been significantly strengthened. As a result, the challenges faced by my country in underwater operations are becoming increasingly severe, among which the problem of underwater monitoring and warning is particularly urgent. my country is still in the initial stage of building rapid deployment regional underwater warning capabilities, and there is no available equipment. The United States, Europe and other naval powers, such as the United States, Russia, France, Ukraine and other countries are developing rapid deployment underwater warning systems with buoys as nodes, and the buoy detection nodes extract the target depth information contained in the received signals.

[0003] Bucker first proposed the concept of Matched Field Processing (MFP), which uses the measured acoustic information to estimate the distance and depth of the sound source. However, MFP is very sensitive to changes in environmental parameters and requires a larger array aperture. Since the modal functions of the normal wave change with depth, and the vertical array (Vertical Line Array, VLA) is used for the vertical aperture, sampling in the depth direction can be achieved. In view of this, some scholars proposed Matched Mode Processing (MMP) based on the vertical array to deal with the problem of distinguishing targets on the surface and underwater. MMP first uses the sound field simulation program to calculate the modal function corresponding to the depth of each array element according to the environmental parameters and construct a modal decomposition matrix. Then, the signal received by the vertical array and the modal decomposition matrix are used to perform modal filtering to calculate the modal intensity of each order excited by the sound source, and the target depth is distinguished by the distribution of modal intensity. It is worth noting that in the case of finite array aperture and finite array elements, the modal decomposition matrix is ​​not orthogonal and complete, which involves the problem of selecting the modal inverse matrix.

[0004] Domestic research on underwater target discrimination started relatively late, and most of them are still in the stage of concept and principle verification. Typical research works are as follows: Yu Yun, Hui Junying and others used the phase angle relationship between the complex sound intensity reactive component and the interactive negative sound intensity of the sound pressure and vertical velocity simple normal waves of dual receiving sensors to distinguish underwater targets on the water surface, which improved the working frequency. However, the method is limited by the depth of the two receiving sensors and requires that the propagable simple normal waves in the waveguide are of the second order. Fang Shiliang and others studied the single hydrophone distance and depth estimation method based on dispersion characteristics combined with time-frequency analysis. They used a multi-modal joint matching method to extract the required modes through the time-frequency filtering method of binary mask filtering, and established a cost function by calculating the error between the actual extracted modal energy and the predicted modal energy. The depth of the sound source was determined by modal energy matching, and the effectiveness of the method was verified by simulation in the shallow sea environment of the Pekeris waveguide model. Zhang Lu et al. used a vector vertical array to judge the positive and negative signs of the active components of the sound pressure and vibration velocity cross-spectral functions, and verified the method using numerical simulation and lake tests. Summary of the invention

[0005] One of the purposes of the present invention is to provide a shallow sea target depth resolution method based on a vertical beam spectrum spatial difference factor, so as to solve the problem that the existing target depth resolution method in the background technology is limited by the deployment depth and waveguide requirements.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor comprises the following steps:

[0008] Perform conventional beamforming processing on the acoustic signals received by the vertical array to obtain a data beam diagram;

[0009] Based on the environmental parameters and the vertical array configuration, a copy field beam pattern of the vertical array is obtained;

[0010] Calculating a two-dimensional correlation coefficient based on the data beam pattern and the copy field beam pattern;

[0011] Based on the two-dimensional correlation coefficient, the average correlation coefficients of the corresponding water surface sound source interval and the underwater sound source interval are calculated respectively;

[0012] Calculate the vertical beam spectrum spatial difference factor according to the average correlation coefficient;

[0013] According to the vertical beam spectrum spatial difference factor and the decision threshold, a decision is made on the surface target or underwater target.

[0014] Preferably, the formula for performing conventional beamforming processing to obtain a data beam pattern is: data (θ, r, zs )=|∑ j exp(-ikz j sinθ)p data (z j , r, z s )| 2 , where θ is the beam forming angle, r is the distance variable, and z s is the actual sound source depth, i is the imaginary unit, k is the wave number, p data (z j , r, z s ) is the measured complex sound pressure field, z j is the depth of the jth array element.

[0015] Preferably, the obtaining of the copy field beam pattern of the vertical array comprises the following steps:

[0016] Based on the environmental parameters and vertical array information, the copy field vertical array data p is generated through the sound field model. rplc (r, z; z j ), r is the distance variable, z is the depth variable, z j is the depth of the jth array element;

[0017] Perform conventional beamforming processing on the copy field vertical array data to obtain the copy field beam diagram A rplc (θ, r, z);

[0018] The formula for performing conventional beamforming processing to obtain the copy field beam pattern is:

[0019] A rplc (θ, r, z) = |∑ j exp(-ikz j sinθ)p rplc (r, z; z j )| 2 , where θ is the beam forming angle, r is the distance variable, z is the depth variable, i is the imaginary unit, k is the wave number, and z j is the depth of the jth array element.

[0020] Preferably, the sound field model is a normal wave model.

[0021] Preferably, the calculation formula of the two-dimensional correlation coefficient is:

[0022]

[0023] Among them, θ0 is the vertical array inclination angle, z is the depth variable, Respectively and The average of the sum of the matrix elements of . Indicates A data The element in the mth row and nth column of Indicates A rplc The element in the mth row and nth column of .

[0024] Preferably, the calculation formula of the average correlation coefficient of the water surface sound source interval is: z1 is the critical depth of the set surface target;

[0025] The calculation formula of the average correlation system of the underwater sound source interval is: z2 is the upper critical depth of the underwater target, and z3 is the lower critical depth of the underwater target.

[0026] Preferably, the calculation formula of the vertical beam spectrum spatial difference factor is R d =R d1 -R d2 .

[0027] Preferably, the decision on the surface target or underwater target is made according to the vertical beam spectrum spatial difference factor and the decision threshold as R d (z s )>0, it is a surface target; R d (z s )<0, it is an underwater target.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention defines a vertical beam spectrum spatial difference factor that implies target depth information from the perspective of energy correlation after beamforming, and distinguishes whether the signal originates from a surface target or an underwater target based on the positive or negative sign of the vertical beam spectrum spatial difference factor; the present invention is insensitive to the initial distance of the sound source, that is, it is not necessary to accurately know the initial distance information of the sound source, and can also distinguish the target depth interval, and is robust to the mismatch between the base array tilt and the seabed parameters. The present invention can be applied to anti-submarine warning detection based on buoy nodes in shallow water environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is an algorithm flow chart of the shallow water target depth resolution method based on the vertical beam spectrum spatial difference factor.

[0031] Figure 2 This is a graph showing the variation of the vertical beam spectrum spatial difference factor with distance and sound source depth.

[0032] Figure 3 This is a graph showing how the beam output changes with beam angle and distance when the vertical array receives the 145Hz line spectrum data of shallow sound sources and the 148Hz line spectrum data of deep sound sources under conventional beamforming.

[0033] Figure 4 for Figure 2 The vertical beam spectrum spatial difference factor extraction results of the corresponding data. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0035] A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor specifically includes the following 6 sub-steps.

[0036] Step 1: Perform conventional beamforming processing on the data recorded by the vertical receiving array to obtain data beam pattern A data (θ, r, z s ):

[0037] A data (θ, r, z s )=|∑ j exp(-ikz j sinθ)p data (z j , r, z s )| 2 (1)

[0038] Where θ is the beam forming angle, r is the distance variable, and z s is the actual sound source depth, i is the imaginary unit, k is the wave number, p data (z j , r, z s ) is the measured complex sound pressure field, z j is the depth of the jth array element.

[0039] In step 1 of the present invention, the data beam diagram is the relationship between the beam energy and the vertical array steering angle and time.

[0040] Step 2: Based on the environmental parameters and vertical array information, the copy field vertical array data p is generated using the sound field model (simple normal wave model) rplc (r, z; z j ), perform conventional beamforming processing on the copy field vertical array data to obtain the copy field beam pattern A rplc (θ, r, z):

[0041] A rplc (θ, r, z) = |∑ j exp(-ikzj sinθ)p rplc (r, z; z j )| 2 (2)

[0042] Where θ is the beam forming angle, r is the distance variable, z is the depth variable, i is an imaginary number, k is the wave number, and z j is the depth of the jth array element.

[0043] Step 3, calculate the two-dimensional correlation coefficient based on the data beam pattern and the copy field beam pattern:

[0044]

[0045] Among them, θ0 is the base array inclination angle, z is the depth variable, Respectively and The average value of the sum of the matrix elements of , Indicates A data The element in the mth row and nth column of Indicates A rplc The element in the mth row and nth column of .

[0046] Step 4, calculate the average correlation coefficients of the corresponding surface sound source interval and underwater sound source interval respectively:

[0047] z1 is the critical depth of the set surface target;

[0048] z2 is the upper critical depth of the underwater target, and z3 is the lower critical depth of the underwater target.

[0049] For the

[0050] Step 5: Calculate the vertical beam spectrum spatial difference factor R according to the average correlation coefficient of the corresponding surface sound source interval and underwater sound source interval. d =R d1 -R d2 .

[0051] Step 6: Distinguish the target type according to the following decision criteria: d (z s )>0, it is a surface target; R d (z s )<0, it is an underwater target.

[0052] Figure 2The vertical beam spectrum spatial difference factor is given with the distance and sound source depth (the distance range of the simulation beam is fixed at 3500m to 4000m). It can be seen that the value of the characteristic quantity corresponding to the sea surface sound source is significantly greater than the value of the characteristic quantity corresponding to the underwater sound source, and the resolution quantity corresponding to the shallow sound source is positive, and the resolution quantity corresponding to the deep sound source is negative. Even if the value of the characteristic quantity is related to the distance, the distribution of the positive and negative signs of the characteristic quantity is approximately independent of the distance, so the discrimination of surface and underwater targets can be achieved based on the positive and negative signs of the characteristic quantity.

[0053] Figure 3 The left figure shows the change of beam output of the conventional beamforming with beam angle and distance when the vertical array receives the 145Hz line spectrum data of the shallow sound source. Figure 3 The right figure in the figure shows the change of beam output of conventional beamforming with beam angle and distance when the vertical array receives the 148Hz line spectrum data of deep sound source; Figure 3 It can be seen that the energy arrival angle range of the beam pattern corresponding to the underwater sound source approximately covers ±20°, while the energy of the beam pattern corresponding to the surface sound source is very weak at small grazing angles, and the beam patterns corresponding to deep and shallow sound sources show obvious differences.

[0054] Figure 4 Given Figure 2 The results of the extraction of spatial difference factors of the vertical beam spectrum of the corresponding data, where the solid line represents the 7m surface sound source and the dotted line represents the 54m underwater sound source. It can be seen that the resolution corresponding to 145Hz is all positive in the distance range of 1 to 7km; the resolution corresponding to 148Hz is all negative in the distance range of 1 to 7km. Therefore, based on the sign of the statistical test resolution, the discrimination of surface and underwater targets is achieved.

Claims

1. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor, characterized in that: The following steps are involved: Perform conventional beamforming processing on the acoustic signals received by the vertical array to obtain a data beam diagram; Based on the environmental parameters and the vertical array configuration, a copy field beam pattern of the vertical array is obtained; Calculating a two-dimensional correlation coefficient based on the data beam pattern and the copy field beam pattern; Based on the two-dimensional correlation coefficient, the average correlation coefficients of the corresponding water surface sound source interval and the underwater sound source interval are calculated respectively; Calculate the vertical beam spectrum spatial difference factor according to the average correlation coefficient; According to the vertical beam spectrum spatial difference factor and the decision threshold, a decision is made on the surface target or underwater target.

2. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 1, characterized in that: The formula for performing conventional beamforming processing to obtain a data beam pattern is: A data (θ, r, z s )=|∑ j exp(-ikz j sinθ)p data (z j , r, z s )| 2 , where θ is the beam forming angle, r is the distance variable, and z s is the actual sound source depth, i is the imaginary unit, k is the wave number, p data (z j , r, z s ) is the measured complex sound pressure field, z j is the depth of the jth array element.

3. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 1 or 2, characterized in that: The obtaining of the copy field beam pattern of the vertical array comprises the following steps: Based on the environmental parameters and vertical array information, the copy field vertical array data p is generated through the sound field model. rplc (r, z; z j ), r is the distance variable, z is the depth variable, z j is the depth of the jth array element; Perform conventional beamforming processing on the copy field vertical array data to obtain the copy field beam diagram A rplc (θ, r, z); The formula for performing conventional beamforming processing to obtain the copy field beam pattern is A rplc (θ, r, z) = |∑ j exp(-ikz j sinθ)p rplc (r, z; z j )| 2 , where θ is the beam forming angle, r is the distance variable, z is the depth variable, i is the imaginary unit, k is the wave number, and z j is the depth of the jth array element.

4. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 3, characterized in that: The sound field model is a simple normal wave model.

5. The shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor according to claim 1, characterized in that: The calculation formula of the two-dimensional correlation coefficient is: Among them, θ0 is the vertical array inclination angle, z is the depth variable, Respectively and The average value of the sum of the matrix elements of , Indicates A data The element in the mth row and nth column of Indicates A rplc The element in the mth row and nth column of .

6. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 5, characterized in that: The calculation formula of the average correlation coefficient of the water surface sound source interval is: z1 is the critical depth of the set surface target; The calculation formula of the average correlation system of the underwater sound source interval is: z2 is the upper critical depth of the underwater target, and z3 is the lower critical depth of the underwater target.

7. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 6, characterized in that: The calculation formula of the vertical beam spectrum spatial difference factor is R d =R d1 -R d2 .

8. A shallow sea target depth resolution method based on vertical beam spectrum spatial difference factor as claimed in claim 7, characterized in that: The above-mentioned decision on the surface target or underwater target according to the vertical beam spectrum spatial difference factor and the decision threshold is R d (z s )>0, it is a surface target; R d (z s )<0, it is an underwater target.

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