CN115687901B - Water surface and underwater target distinguishing method and device based on shallow water sound field correlation - Google Patents

Water surface and underwater target distinguishing method and device based on shallow water sound field correlation Download PDF

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CN115687901B
CN115687901B CN202211273705.1A CN202211273705A CN115687901B CN 115687901 B CN115687901 B CN 115687901B CN 202211273705 A CN202211273705 A CN 202211273705A CN 115687901 B CN115687901 B CN 115687901B
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王燕
朱文博
邹男
王晋晋
邱龙皓
郝宇
张光普
齐滨
王逸林
付进
梁国龙
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Harbin Engineering University
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Abstract

A method and equipment for distinguishing underwater targets on water surface based on shallow water sound field correlation belong to the technical field of underwater target distinguishing on underwater sound surface. The method aims to solve the problems that the existing method for resolving the underwater target on the water surface based on the shallow sea waveguide theory has the problem that the resolving effect is affected due to the fact that the posture of a vertical array is difficult to maintain, and the problem that the energy attenuation of a higher-order Jian Zhengbo mode along with the distance is unfavorable for the use of a mode characteristic method. The invention respectively uses the front section and the rear section of the horizontal array to respectively beam-form the target, uses the two sections of beam-formed output signals to do cross spectrum, then uses the phase statistical characteristics which are relevant in depth and are not influenced by the fluctuation of frequency spectrum amplitude for depth resolution through the theoretical analysis of the phase change of the cross spectrum along with the frequency. The invention is used for distinguishing underwater targets on the water surface.

Description

Water surface and underwater target distinguishing method and device based on shallow water sound field correlation
Technical Field
The invention belongs to the technical field of underwater target resolution of underwater sound and water surfaces, and relates to a method and equipment for water surface underwater target resolution based on shallow water sound field correlation.
Background
The problem of depth resolution of passive sonar targets is always a difficult problem in the underwater acoustic field, and the main content is to judge whether the targets are on the water surface or under the water in noise and interference, so that the method has important practical significance for anti-diving operations. Currently, the resolution methods of underwater targets on water surface are divided into two main categories: one is a target depth resolution method based on a matching field; another class is depth resolution methods based on the normal wave mode features.
The matching field processing method is used for matching the sound field model with the received signal through the relationship between the underwater sound channel and the sound source position, further inverting the sound source position, and distinguishing the underwater targets on the water surface through the depth estimation result. Currently more efficient such methods are matched field technology (MFP) using modeled acoustic fields for matching and matched mode technology (MMP) based on shallow sea waveguide theory. Although the MFP method can realize estimation of the distance and depth of the underwater sound source, the lack of robustness and problems such as mismatching of environment or target movement can affect the estimation result. In order to improve the robustness of the MFP under adverse conditions, the subsequent scholars sequentially put forward improvements such as spatial filtering and self-adaptive methods, but in actual use, the MFP still cannot achieve ideal robustness. Until the modal filtering method is applied to the matching field and good effect is achieved, MMP technology has been developed. Students began to pay attention to the study of target depth resolution technology based on MMP methods.
The mode functions of each order of the simple wave in the shallow sea waveguide are affected by the depth, the shallow source is difficult to excite the low order Jian Zhengbo, and particularly in typical negative jump layer hydrologic conditions, the low-order mode energy ratio of the shallow source excitation is high, and the high-order mode energy ratio is high. V.E Premus and Conan according to the characteristic, simplifying the sound source localization problem of the matching field method into a two-classification problem, and providing a mode filtering method with different structures, and distinguishing underwater targets on the water surface by taking the energy ratio of a mode subspace as statistics. However, in an underwater acoustic environment, array aperture limitations result in overlap between modal subspaces. To address this problem, premus introduced a Scharf-Friedlander matched subspace detector, however this approach is not ideal for horizontal arrays. Y.C Yang proposes a moving sound source positioning method based on synthetic aperture mode beam forming, environmental information is not needed, the problem of environmental adaptation is avoided, single array elements can be used for estimation, but a certain horizontal relative movement distance between a target and a receiving array is needed to avoid interference between modes.
The method for distinguishing the underwater targets on the water surface based on the shallow sea waveguide theory still needs to rely on a vertical array or an array with effective vertical apertures (a horizontal array with targets in the end-fire direction of the array) to obtain the ideal effect. However, the pose of the vertical array is difficult to maintain, and the energy decay of the higher order Jian Zhengbo mode with distance is detrimental to the use of the mode characterization approach. Therefore, the method for distinguishing the underwater targets on the water surface also needs more research on a method for extracting modal characteristics by using a horizontal array.
Disclosure of Invention
The method aims to solve the problems that the existing method for resolving the underwater target on the water surface based on the shallow sea waveguide theory has the problem that the resolving effect is affected due to the fact that the posture of a vertical array is difficult to maintain, and the problem that the energy attenuation of a higher-order Jian Zhengbo mode along with the distance is unfavorable for the use of a mode characteristic method.
A method for distinguishing underwater targets on water surface based on shallow water sound field correlation comprises the following steps:
in shallow water waveguides, the distance r and depth z are as follows r The sound field at the location is expressed as a seriesSuperposition of simple normal waves
Figure BDA0003895652670000021
wherein ,zs For the sound source depth, X (f) is the spectrum of the sound source radiated noise, j is the imaginary number, ρ is the water density,
Figure BDA0003895652670000022
is a depth dependent modal function, k m and βm The horizontal wave number and the attenuation coefficient of the M-th order Jian Zhengbo are respectively, and M is the order of the simple wave;
for an N-element horizontal array near the water bottom, the front N/2 array elements of the horizontal array are used for carrying out wave beam formation on the target to obtain a complex sound pressure signal p 1 The target is beamformed by N/2 array elements to obtain a complex sound pressure signal p 2 ；
Based on complex sound pressure p 1 and p2 Obtaining
Figure BDA0003895652670000023
Representing complex sound pressure p 2 Conjugation of (C) to obtain
Figure BDA0003895652670000024
wherein ,
Figure BDA0003895652670000025
r a 、r b a, b represent array element serial numbers for the horizontal distance between the array element and the target; z r 、z s For depth->
Figure BDA0003895652670000026
Is a modal function with respect to depth; k is the wave number, k m and kn The horizontal wave numbers of m-th and n-th steps Jian Zhengbo, respectively; beta m and βn Attenuation coefficients of m-th and n-th steps Jian Zhengbo, respectively; d is array element spacing, θ is the clip of the target and the horizontal directionA corner;
when the horizontal distance r between the reference array element and the target is more than ten times of the array aperture, there is
Figure BDA0003895652670000027
wherein ,
Figure BDA0003895652670000028
G mn for the real part containing the addition of the array element ordinal terms,
Figure BDA0003895652670000031
when m is not equal to n, smoothing distance and depth is performed to obtain
Figure BDA0003895652670000032
wherein ,
Figure BDA0003895652670000033
depth of up-down inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure BDA0003895652670000034
wherein ,SRm Is the horizontal distance the intrinsic sound ray passes in a loop region;
Figure BDA0003895652670000035
c (z) is the sound velocity at depth z, +.>
Figure BDA0003895652670000036
Omega is angular frequency, f is frequency, E is constant;
approximating the accumulation of equation (9) as an integral
Figure BDA0003895652670000037
wherein ,α0 To grazing angle expressed in integral object, the integral lower limit alpha 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 Wave number at the minimum depth of sound velocity;
finally obtain p 1 and p2 Is of the correlation coefficient of (2)
Figure BDA0003895652670000038
wherein ,W(α0 ) Is angular energy density;
wideband signal with L frequency domain sampling points, the horizontal correlation coefficient is expressed as
Figure BDA0003895652670000039
Γ(f l ) A first term of wideband signal cross spectrum Γ; w (W) l (α 0 ) Energy density as a function of glancing angle as a function of frequency;
and further determine the phase of Γ
φ(z s ,ω)＝angle(Γ) (17)
Finally based on the phase phi (z s ω), the identification of shallow sources or deep sources is realized by adopting a binary signal detection model.
Further, based on the phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), frequency domain variance of the phase
Figure BDA0003895652670000041
This is taken as statistics of sound source depth discrimination and denoted as R var ；
When R is var Greater than or equal to the frequency domain variance threshold eta var When the target is a shallow source; otherwise, the target is a deep source.
or ,
based on the phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), the frequency domain first order difference diff (phi (z) s ω), which is used as a statistic for sound source depth discrimination, is denoted as R diff ；
When R is diff Greater than or equal to the frequency domain first order difference threshold eta diff When the target is a shallow source; otherwise, the target is a deep source.
or ,
based on the phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), the variance var of the first order difference in the phase-frequency domain (diff (phi (zs, ω))), is taken as the statistic of sound source depth discrimination, and is denoted as R vdiff ；
When R is vdiff A variance threshold eta greater than or equal to the first order difference of the phase frequency domain vdiff When the target is a shallow source; otherwise, the target is a deep source.
Further, the angular energy density W (α 0 ) The following are provided:
Figure BDA0003895652670000042
wherein SR (alpha) 0 ) Is an angle alpha 0 Corresponding to the horizontal distance traversed by the intrinsic sound ray in one of the recirculation zones,
Figure BDA0003895652670000043
and />
Figure BDA0003895652670000044
Depth z respectively s and zr Glancing angle at, real +.>
Figure BDA0003895652670000045
β(α 0 ) For SR (alpha) 0 ) Corresponding energy loss.
Further, the complex sound pressure p 1 and p2 The following are provided:
Figure BDA0003895652670000051
Figure BDA0003895652670000052
where k is the wave number.
Further, based on complex sound pressure p 1 and p2 Obtaining
Figure BDA0003895652670000053
Based on complex sound pressure p 1 and p2 Is determined by the correlation coefficient of the complex sound pressure p 1 and p2 The correlation coefficient of (2) is as follows:
Figure BDA0003895652670000054
where |·| represents taking the absolute value,
Figure BDA0003895652670000055
representing a smoothed average over distance.
Further, the horizontal distance between the array element and the target is as follows:
r i ＝r+(i-1)dcosθ
wherein ,ri Representing the horizontal distance of the ith element from the target.
Further, the wave number
Figure BDA0003895652670000056
ω=2pi f is angular frequency, f is frequency, c is underwater sound velocity.
A shallow water sound field correlation-based water surface and underwater target resolution device, the device comprising a processor and a memory, wherein at least one instruction is stored in the memory, and the at least one instruction is loaded and executed by the processor to realize the shallow water sound field correlation-based water surface and underwater target resolution method.
The beneficial effects are that:
the invention respectively uses the front section and the rear section of the horizontal array to respectively form wave beams for the target, and the two wave beam forming output signals are subjected to cross spectrum; by theoretical analysis of the phase change of the cross spectrum along with the frequency, depth resolution is performed by utilizing a plurality of phase statistical features which are depth-related and hardly affected by the fluctuation of the frequency spectrum amplitude, the target resolution accuracy can be improved, the depth resolution depends on the phase change of the cross power spectrum, and no mode space information or earth sound parameters are needed. Therefore, the method can also well solve the problem that the energy attenuation of the higher-order Jian Zhengbo mode along with the distance is unfavorable for the use of a mode characteristic method, and can also well solve the problem that the resolution effect is influenced due to the fact that the gesture of the vertical array is difficult to maintain in a water surface and underwater target resolution method based on the shallow sea waveguide theory.
Drawings
Fig. 1 is a sound velocity cross-sectional view.
Fig. 2 is a graph of horizontal correlation of different sound source depths.
Fig. 3 (a) to 3 (d) are graphs of phase versus frequency for different depths (3 m, 15m, 49m and 139 m).
Detailed Description
The first embodiment is as follows:
the embodiment is a method for distinguishing underwater targets on a water surface based on shallow water sound field correlation, which comprises the following steps:
in shallow water waveguides, the distance r and depth z are as follows r The sound field at this point being represented by the superposition of a series of simple positive waves
Figure BDA0003895652670000061
wherein ,zs For the sound source depth, X (f) is the spectrum of the sound source radiated noise, j is the imaginary number, ρ is the water density,
Figure BDA0003895652670000062
is a depth dependent modal function, k m and βm The horizontal wave number and attenuation coefficient of the mth order Jian Zhengbo are respectively, and M is the order of the simple wave.
Consider an N-element horizontal array near the water bottom, wherein the array element distance is d, and the included angle between the target and the horizontal direction is theta. The horizontal distance between the i-th array element and the target is expressed as
r i ＝r+(i-1)dcosθ (2)
Beam forming is carried out on the target by using the first N/2 array elements of the horizontal array to obtain a complex sound pressure signal p 1 The target is beamformed by N/2 array elements to obtain a complex sound pressure signal p 2 Has the following components
Figure BDA0003895652670000063
wherein ,
Figure BDA0003895652670000064
for wave number, ω=2pi f is angular frequency, f is frequency, and c is underwater sound velocity. a. b represents the array element sequence number;
Figure BDA0003895652670000065
is a modal function with respect to depth; k (k) n and βn The horizontal wavenumber and attenuation coefficient of nth order Jian Zhengbo, respectively;
recording device
Figure BDA0003895652670000066
Complex sound pressure p 1 and p2 Is of the correlation coefficient of
Figure BDA0003895652670000067
wherein ,
Figure BDA0003895652670000068
representing complex sound pressure p 2 Is the absolute value, |·| represents the conjugate of +.>
Figure BDA0003895652670000069
Representing a smoothed average over distance.
Recording device
Figure BDA0003895652670000071
And substituting formula (3) into the mixture to obtain
Figure BDA0003895652670000072
wherein ,
Figure BDA0003895652670000073
when the horizontal distance r between the target and the array is far greater than the array aperture (the horizontal distance between the target and the array is more than ten times the array aperture), the following approximation can be made
Figure BDA0003895652670000074
Figure BDA0003895652670000075
Substituting the formula (6) and the formula (7) into the formula (5), and finishing the products
Figure BDA0003895652670000076
wherein ,
Figure BDA0003895652670000077
G mn for the real part containing the sum of array element ordinal terms
Figure BDA0003895652670000078
When m=n, the first term in brackets of formula (8) is a slowly varying function of distance and depth; when m.noteq.n, the second term in brackets of formula (8) varies drastically with distance and depth due to weak correlation between different modalities, and disappears after smoothing of distance and depth
Figure BDA0003895652670000079
wherein ,
Figure BDA00038956526700000710
depth of up-down inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure BDA00038956526700000711
In the above, SR m Is the horizontal distance the intrinsic sound ray passes in a loop region;
Figure BDA0003895652670000081
c (z) is the speed of sound at depth z; />
Figure BDA0003895652670000082
Constant e=0.875.
When the sound source frequency is higher, multi-order simple positive waves exist in shallow water, and glancing angles are nearly continuous. The accumulation of equation (9) can be approximated as an integral
k m ＝k(z)cosα z (11)
Figure BDA0003895652670000083
wherein ,αz is the glancing angle at depth z. Substituting the formulas (10) and (11), (12) into the formula (9), and finishing to obtain
Figure BDA0003895652670000084
wherein ,α0 To grazing angle expressed in integral object, the integral lower limit alpha 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 Is the wave number at the minimum depth of sound velocity.
Thus far p can be obtained 1 and p2 Is of the correlation coefficient of (2)
Figure BDA0003895652670000085
Wherein the angular energy density
Figure BDA0003895652670000086
SR(α 0 ) Is an angle alpha 0 Corresponding to the horizontal distance alpha travelled by the intrinsic sound ray in a cyclic zone zs and αzr Depth z respectively s and zr Glancing angle, real number at
Figure BDA0003895652670000087
β(α 0 ) For each cycle distance SR (alpha 0 ) Energy loss of (2).
Wideband signal with L frequency domain sampling points, the horizontal correlation coefficient can be expressed as
Figure BDA0003895652670000088
Γ(f l ) Is the first term of wideband signal cross spectrum Γ. W (W) l (α 0 ) Is the energy density with respect to glancing angle relative to frequency (expressed in broadband as W l (·))；
The phase of gamma is
φ(z s ,ω)＝angle(Γ) (17)
φ(z s Law of variation of ω) and correlation γ (z) s ,z r F) are concerned.
Under the condition that the negative sonic velocity gradient (thermocline) and the receiving depth are close to the water bottom, the shallow source (surface source) is difficult to excite the low-order mode, compared with the deep source (submerged source), the high-order mode of the shallow source occupies higher proportion, the horizontal correlation is low (the correlation coefficient is small), and the phase phi (z) s Omega) with frequency hopping strongly; through long-distance propagation, the loss of a high-order mode is large due to boundary reflection and the like, the low-order mode is dominant in the modes excited by a deep source, the horizontal correlation is higher (the correlation coefficient is large), and the phase phi (z) s ω) varies relatively smoothly with frequency.
To illustrate this feature, simulations were performed in an environment with the sonic gradient shown in fig. 1. The sound source frequency is 200Hz to 400Hz, and the sound source signal is incident from 0 deg.. Even horizontal array with array element spacing of 5m, array element number N of 80, horizontal distance r between sound source and reference array element of 10km, and receiving depth z r 160m. Fig. 2 is a graph of horizontal correlation coefficients for different sound source depths at a receiving location. The phase variation with frequency is calculated using equation (17) for different sound source depths as shown in fig. 3 (a) to 3 (d).
FIGS. 3 (a) to 3 (d) show phi (z) at sound source depths of 3m, 15m, 49m and 139m s ω) as a function of frequency. As can be seen from comparison, the phase of the shallow source (3 m, 15 m) varies drastically with frequency, at [ -pi, pi]Rapid jump between the two; the deep sources (49 m and 139 m) have gentle phase changes along with the frequency, almost all the phases change slowly, and only jump occurs at certain frequencies. The phase change rules of the shallow source and the deep source are matched with the horizontal correlation of the receiving depth. To more intuitively describe this law of variation:
a is the frequency domain variance of the phase
Figure BDA0003895652670000091
Describing the dispersion degree of the phase in the frequency band, wherein the variance of the phase which changes rapidly along with the frequency is large, and the variance of the slow change is small;
b is the phase frequency domain first order difference diff (phi (z s ω), the speed of change of the phase within the frequency band is described. With the phase of rapid frequency change, more spikes representing speed jump appear in the first-order difference, less spikes of slow change are compared with flat spikes, the underwater target on the water surface can be judged by counting the number of the spikes of jump, diff (phi (z) s ,ω)) l ＝φ(z s ,ω l+1 )-φ(z s ,ω l ) L=1, 2, …, L-1 is the first term of diff (Φ (zs, ω));
c is the variance var of the first difference in the phase frequency domain (diff (z s ω)) describes the degree of dispersion of the first-order difference of the phase, and the phase which changes rapidly with frequency has more spikes of the first-order difference, large dispersion, less spikes which change slowly with large variance, small dispersion and small variance.
And judging whether the sound source is on the water surface or underwater by using a binary signal detection model in the detection theory and through the noisy signals received by the horizontal array. The problem can be described as follows
Figure BDA0003895652670000101
wherein ,zlim To distinguish depth, it is generally set to 15m to 30m under water, with the positive direction of the depth axis z pointing in the direction of increasing water depth. Sound source depth z s Less than z lim The target being a water surface source (shallow source), i.e. assume H 0 The method comprises the steps of carrying out a first treatment on the surface of the Sound source depth z s Greater than z lim The target being an underwater source (deep source), i.e. assuming H 1 。
The three characteristic quantities are used to describe the phase change, and are respectively used as statistics of sound source depth discrimination and respectively marked as R var ，R diff and Rvdiff According to the description of the phase law in the upper section, there are
Figure BDA0003895652670000102
R mod For one of the above statistics, when R mod When the threshold eta is larger than or equal to the threshold eta, the target is a shallow source (a water surface target); when the statistic is smaller than the threshold η, the target is a deep source (underwater target).
The second embodiment is as follows:
the embodiment is a device for resolving underwater targets on water surface based on shallow water sound field correlation, the device comprises a processor and a memory, and it should be understood that the device comprising any device comprising the processor and the memory described in the invention can also comprise other units and modules for displaying, interacting, processing, controlling and other functions through signals or instructions;
it should also be appreciated that the memory may include a non-transitory machine-readable medium having stored thereon instructions, which may be used to program a computer system, or other electronic device. The storage medium may include, but is not limited to, magnetic storage media, optical storage media; the magneto-optical storage medium includes: read only memory ROM, random access memory RAM, erasable programmable memory (e.g., EPROM and EEPROM), and flash memory layers; or other type of medium suitable for storing electronic instructions.
The memory stores at least one instruction which is loaded and executed by the processor to realize the method for distinguishing the underwater target on the water surface based on the correlation of the shallow water sound field.
The above examples of the present invention are only for describing the calculation model and calculation flow of the present invention in detail, and are not limiting of the embodiments of the present invention. Other variations and modifications of the above description will be apparent to those of ordinary skill in the art, and it is not intended to be exhaustive of all embodiments, all of which are within the scope of the invention.

Claims (10)

1. A method for distinguishing underwater targets on water surface based on shallow water sound field correlation is characterized by comprising the following steps:
in shallow water waveguides, the distance r and depth z are as follows r The sound field at this point being represented by the superposition of a series of simple positive waves
Figure FDA0003895652660000011
wherein ,zs For the sound source depth, X (f) is the spectrum of the sound source radiated noise, j is the imaginary number, ρ is the water density,
Figure FDA0003895652660000012
is a depth dependent modal function, k m and βm The horizontal wave number and the attenuation coefficient of the M-th order Jian Zhengbo are respectively, and M is the order of the simple wave;
for an N-element horizontal array near the water bottom, the front N/2 array elements of the horizontal array are used for carrying out wave beam formation on the target to obtain a complex sound pressure signal p 1 The target is beamformed by N/2 array elements to obtain a complex sound pressure signal p 2 ；
Based on complex sound pressure p 1 and p2 Obtaining
Figure FDA0003895652660000013
Figure FDA0003895652660000014
Representing complex sound pressure p 2 Conjugation of (C) to obtain
Figure FDA0003895652660000015
wherein ,
Figure FDA0003895652660000016
r a 、r b a, b represent array element serial numbers for the horizontal distance between the array element and the target; z r 、z s For depth->
Figure FDA0003895652660000017
Is the switchA modal function at depth; k is the wave number, k m and kn The horizontal wave numbers of m-th and n-th steps Jian Zhengbo, respectively; beta m and βn Attenuation coefficients of m-th and n-th steps Jian Zhengbo, respectively; d is the array element spacing, and θ is the included angle between the target and the horizontal direction;
when the horizontal distance r between the reference array element and the target is more than ten times of the array aperture, there is
Figure FDA0003895652660000018
wherein ,
Figure FDA0003895652660000019
G mn for the real part containing the addition of the array element ordinal terms,
Figure FDA00038956526600000110
when m is not equal to n, smoothing distance and depth is performed to obtain
Figure FDA00038956526600000111
wherein ,
Figure FDA0003895652660000021
depth of up-down inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure FDA0003895652660000022
wherein ,SRm Is the horizontal distance the intrinsic sound ray passes in a loop region;
Figure FDA0003895652660000023
c (z) is the sound velocity at depth z, +.>
Figure FDA0003895652660000024
Omega is angular frequency, f is frequency, E is constant;
approximating the accumulation of equation (9) as an integral
Figure FDA0003895652660000025
wherein ,α0 To grazing angle expressed in integral object, the integral lower limit alpha 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 Wave number at the minimum depth of sound velocity;
finally obtain p 1 and p2 Is of the correlation coefficient of (2)
Figure FDA0003895652660000026
wherein ,W(α0 ) Is angular energy density;
wideband signal with L frequency domain sampling points, the horizontal correlation coefficient is expressed as
Figure FDA0003895652660000027
Γ(f l ) A first term of wideband signal cross spectrum Γ; w (W) l (α 0 ) Energy density as a function of glancing angle as a function of frequency;
and further determine the phase of Γ
Figure FDA0003895652660000028
Finally based on the phase phi (z s ω), the identification of shallow sources or deep sources is realized by adopting a binary signal detection model.
2. A method for resolving a water surface and underwater target based on correlation of a shallow water sound field according to claim 1, wherein the method is based on a phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), frequency domain variance of the phase
Figure FDA0003895652660000031
This is taken as statistics of sound source depth discrimination and denoted as R var ；
When R is var Greater than or equal to the frequency domain variance threshold eta var When the target is a shallow source; otherwise, the target is a deep source.
3. A method for resolving a water surface and underwater target based on correlation of a shallow water sound field according to claim 1, wherein the method is based on a phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), the frequency domain first order difference diff (phi (z) s ω), which is used as a statistic for sound source depth discrimination, is denoted as R diff ；
When R is diff Greater than or equal to the frequency domain first order difference threshold eta diff When the target is a shallow source; otherwise, the target is a deep source.
4. A method for resolving a water surface and underwater target based on correlation of a shallow water sound field according to claim 1, wherein the method is based on a phase phi (z s ω) the process of identifying shallow or deep sources using a binary signal detection model comprises the steps of:
based on the phase phi (z s ω), variance var (diff (z s ω)) as statistics of sound source depth discrimination, denoted as R vdiff ；
When R is vdiff A step greater than or equal to the phase frequency domainVariance threshold eta of the score vdiff When the target is a shallow source; otherwise, the target is a deep source.
5. A method of resolving a target under water on the basis of shallow water acoustic field correlation according to one of claims 1 to 4, characterized in that the angular energy density W (α 0 ) The following are provided:
Figure FDA0003895652660000032
wherein SR (alpha) 0 ) Is an angle alpha 0 Corresponding to the horizontal distance traversed by the intrinsic sound ray in one of the recirculation zones,
Figure FDA0003895652660000033
and />
Figure FDA0003895652660000034
Depth z respectively s and zr Glancing angle at, real +.>
Figure FDA0003895652660000035
β(α 0 ) For SR (alpha) 0 ) Corresponding energy loss.
6. The method for distinguishing underwater and water targets based on shallow water sound field correlation according to claim 5, wherein the complex sound pressure p 1 and p2 The following are provided:
Figure FDA0003895652660000041
Figure FDA0003895652660000042
where k is the wave number.
7. The method for distinguishing underwater and water targets based on shallow water sound field correlation as recited in claim 6, wherein the method is based on complex sound pressure p 1 and p2 Obtaining
Figure FDA0003895652660000043
Based on complex sound pressure p 1 and p2 Is determined by the correlation coefficient of the complex sound pressure p 1 and p2 The correlation coefficient of (2) is as follows:
Figure FDA0003895652660000044
where |·| represents taking the absolute value,
Figure FDA0003895652660000045
representing a smoothed average over distance.
8. The method for distinguishing underwater targets on water surface based on correlation of shallow water sound field as recited in claim 7, wherein horizontal distance between array elements and targets is as follows:
r i ＝r+(i-1)d cosθ
wherein ,ri Representing the horizontal distance of the ith element from the target.
9. The method for distinguishing underwater and water targets based on shallow water sound field correlation as claimed in claim 8, wherein the wave number is the same as the wave number
Figure FDA0003895652660000046
ω=2pi f is angular frequency, f is frequency, c is underwater sound velocity.
10. A shallow water sound field correlation-based surface underwater target resolution apparatus, characterized in that the apparatus comprises a processor and a memory, the memory having stored therein at least one instruction which is loaded and executed by the processor to implement a shallow water sound field correlation-based surface underwater target resolution method as claimed in one of claims 1 to 7.
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