CN115687901A - Water surface and underwater target distinguishing method and equipment based on shallow water sound field correlation - Google Patents

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

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CN115687901A
CN115687901A CN202211273705.1A CN202211273705A CN115687901A CN 115687901 A CN115687901 A CN 115687901A CN 202211273705 A CN202211273705 A CN 202211273705A CN 115687901 A CN115687901 A CN 115687901A
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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 a device for distinguishing underwater and water surface targets based on shallow water sound field correlation belong to the technical field of underwater and water surface target distinguishing. The method aims to solve the problems that the resolution effect is influenced due to the fact that the posture of a vertical array is difficult to maintain in the existing method for resolving the underwater targets on the water surface based on the shallow sea waveguide theory, and the energy attenuation of a high-order normal wave mode along with the distance is not beneficial to the use of a mode characteristic method. The invention respectively uses the front section and the rear section of the horizontal array to respectively form beams for a target, makes the output signals formed by the two sections of beams into a cross spectrum, then carries out theoretical analysis on the change of the cross spectrum phase along with the frequency, and finally utilizes the phase statistical characteristics which are related in depth and are not influenced by the fluctuation of the frequency spectrum amplitude for depth resolution. The invention is used for distinguishing the underwater target on the water surface.

Description

Water surface and underwater target distinguishing method and equipment based on shallow water sound field correlation
Technical Field
The invention belongs to the technical field of underwater sound surface and underwater target resolution, and relates to a surface and underwater target resolution method and device based on shallow water sound field correlation.
Background
The passive sonar target depth resolution problem is a difficult problem of an underwater acoustic boundary all the time, the main content of the passive sonar target depth resolution problem is to judge whether a target is on the water surface or underwater in noise and interference, and the passive sonar target depth resolution problem has important practical significance for anti-submarine battles. At present, the methods for distinguishing underwater targets on water surface are divided into two categories: one is a matching field based target depth resolution method; another is a depth-resolved method based on normal wave modal characteristics.
The matching field processing method matches the sound field model with the received signals through the relation between the underwater sound channel and the sound source position, further inverts the position of the sound source, and distinguishes underwater targets on the water surface through the depth estimation result. Such methods, which are currently more effective, are matched field techniques (MFPs) using a modeled acoustic field for matching and matched mode techniques (MMPs) based on the shallow sea waveguide theory. Although the MFP method can realize the estimation of the underwater sound source distance and depth, the estimation result is affected by the problems of lack of robustness, environmental mismatch, target motion and the like. In order to improve the robustness of the MFP under adverse conditions, subsequent scholars propose improvements such as spatial filtering and 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 a good effect is obtained, the MMP technique is developed accordingly. The researchers began to devote attention to the study of a target depth-resolved technique based on the MMP method.
The normal wave in the shallow sea waveguide has the influence of depth on each order of modal function, and a shallow source is difficult to excite the low-order normal wave, and particularly under the typical negative jump layer hydrological condition, the low-order modal energy occupation ratio of the shallow source excitation is low, and the high-order modal energy occupation ratio is high. According to the characteristic, V.E Premus and Conan simplify the sound source positioning problem of the matching field method into two classification problems, provide modal filtering methods with different structures, and distinguish underwater targets on the water surface by taking the energy ratio of modal subspace as statistic. However, in an underwater acoustic environment, array aperture limitations result in overlap between modal subspaces. For this problem, premus introduced Scharf-Friedlander matched subspace Detector, however, this method was not ideal in horizontal matrix effect. Y.C Yang provides a method for positioning a moving sound source based on the formation of synthetic aperture modal beams, does not need environmental information to avoid the problem of environmental adaptation, can use a single array element for estimation, but needs a certain horizontal relative movement distance between a target and a receiving array to avoid the interference between the modalities.
The method for resolving the targets on the water surface and under the water 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 array end-fire direction) to obtain the ideal effect. However, the attitude of the vertical array is difficult to maintain, and the attenuation of the energy of the higher-order normal wave mode with distance is not favorable for the use of the mode characteristic method. Therefore, the method for distinguishing the underwater targets on the water surface needs more researches on a method for extracting modal characteristics by using a horizontal array.
Disclosure of Invention
The invention aims to solve the problems that the resolution effect is influenced due to the fact that the posture of a vertical array is difficult to maintain in the existing method for resolving the underwater targets on the water surface based on the shallow sea waveguide theory, and the energy attenuation of a high-order normal wave mode is not beneficial to the use of a mode characteristic method along with the distance.
A method for distinguishing water surface and underwater targets based on shallow water sound field correlation comprises the following steps:
in a shallow water waveguide, the distance r, depth z will be r Where the sound field is represented as a superposition of a series of simple normal waves
Figure BDA0003895652670000021
wherein ,zs X (f) is the frequency spectrum of the sound source radiation noise, j represents an imaginary number, ρ is the water density,
Figure BDA0003895652670000022
is a depth-dependent modal function, k m and βm Respectively the horizontal wave number and the attenuation coefficient of the mth order normal wave, wherein M is the order of the normal wave;
aiming at an N-element horizontal array near the water bottom, the first N/2 array elements of the horizontal array are used for carrying out beam forming on a target to obtain a complex sound pressure signal p 1 Then N/2 array elements carry out beam forming on the target to obtain a complex sound pressure signal p 2 ；
Based on complex sound pressure p 1 and p2 To obtain
Figure BDA0003895652670000023
Representing complex sound pressure p 2 Is further conjugated to obtain
Figure BDA0003895652670000024
wherein ,
Figure BDA0003895652670000025
r a 、r b a and b represent array element serial numbers which are horizontal distances between the array elements and the target; z is a radical of formula r 、z s In order to be the depth of the film,
Figure BDA0003895652670000026
is a modal function with respect to depth; k is the wave number, k m and kn Respectively of m and n ordersHorizontal wave number of normal wave; beta is a beta m and βn Attenuation coefficients of the mth order and nth order normal waves respectively; d is the array element spacing, and theta 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 larger than the aperture of the array, the reference array element and the target have the same horizontal distance
Figure BDA0003895652670000027
wherein ,
Figure BDA0003895652670000028
G mn the real part containing the sum of array element ordinal terms,
Figure BDA0003895652670000031
when m is not equal to n, the distance and the depth are smoothed to obtain
Figure BDA0003895652670000032
wherein ,
Figure BDA0003895652670000033
depth of inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure BDA0003895652670000034
wherein ,SRm The horizontal distance traveled by the intrinsic sound ray in a circulation region;
Figure BDA0003895652670000035
c (z) is the speed of sound at depth z,
Figure BDA0003895652670000036
omega isAngular frequency, f frequency, E constant;
approximating the accumulation of equation (9) as an integral
Figure BDA0003895652670000037
wherein ,α0 For grazing angles expressed as integral objects, the lower limit of integration α 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 The wave number at the depth where the sound velocity is minimum;
finally obtain p 1 and p2 Correlation coefficient of
Figure BDA0003895652670000038
wherein ,W(α0 ) Is the angular energy density;
a wideband signal having L frequency domain samples, the horizontal correlation coefficient being expressed as
Figure BDA0003895652670000039
Γ(f l ) The l term of the broadband signal cross spectrum Γ; w is a group of l (α 0 ) Energy density with respect to frequency-dependent grazing angle;
to determine the phase of gamma
φ(z s ,ω)＝angle(Γ) (17)
Finally based on the phase phi (z) s Omega), the binary signal detection model is adopted to realize the identification of shallow source or deep source.
Further, based on the phase phi (z) s Omega) the process of identifying shallow or deep sources using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω) is made as the frequency domain variance of the phase
Figure BDA0003895652670000041
Make it intoStatistics for sound source depth discrimination, 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 Omega) the process of identifying shallow or deep sources by using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω), make the frequency domain first order difference diff (φ (z) of the phase s ω)) as a statistic for sound source depth discrimination, and is denoted as R diff ；
When R is diff Greater than or equal to 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 Omega) the process of identifying shallow or deep sources using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω), the variance var (diff (Φ (zs, ω))) of the first order difference of the phase frequency domain is taken as the statistic of sound source depth judgment and is recorded as R vdiff ；
When R is vdiff Variance threshold eta greater than or equal to first-order difference of 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 were used:
Figure BDA0003895652670000042
wherein, SR (alpha) 0 ) Is an angle alpha 0 Corresponding to the horizontal distance traveled by the intrinsic ray in one of the loop regions,
Figure BDA0003895652670000043
and
Figure BDA0003895652670000044
respectively a depth z s and zr Grazing angle of (d), real
Figure BDA0003895652670000045
β(α 0 ) Is SR (alpha) 0 ) Corresponding energy loss.
Further, the complex sound pressure p 1 and p2 The following were used:
Figure BDA0003895652670000051
Figure BDA0003895652670000052
wherein k is the wave number.
Further, based on complex sound pressure p 1 and p2 To obtain
Figure BDA0003895652670000053
Based on complex sound pressure p 1 and p2 Determined by the correlation coefficient of (2), complex sound pressure p 1 and p2 The correlation coefficient of (a) is as follows:
Figure BDA0003895652670000054
wherein, | - | represents taking an absolute value,
Figure BDA0003895652670000055
representing a smooth 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 Indicating the horizontal distance of the ith array element from the target.
Further, the wave number
Figure BDA0003895652670000056
ω =2 π f is the angular frequency, f is the frequency, c is the speed of sound in water.
A device for resolving targets on water surface and underwater based on shallow water sound field correlation comprises 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 method for resolving the targets on water surface and underwater based on the shallow water sound field correlation.
Has the advantages that:
the invention respectively uses the front section and the rear section of the horizontal array to respectively form beams for a target, and makes the output signals of the two sections of beam forming into a cross spectrum; through the theoretical analysis of the change of the cross-spectrum phase along with the frequency, the depth resolution is carried out by utilizing a plurality of phase statistical characteristics which are related in depth and hardly influenced by the fluctuation of the frequency spectrum amplitude, the accuracy of the target resolution can be improved, and the depth resolution depends on the phase change of the cross-power spectrum without mode space information or earth-sound parameters. Therefore, the method can well solve the problem that the energy attenuation of the high-order normal wave mode along with the distance is not beneficial to the use of the mode characteristic method, and can well solve the problem that the resolving effect is influenced due to the fact that the posture of the vertical array is difficult to maintain in the water surface underwater target resolving method based on the shallow sea waveguide theory.
Drawings
Fig. 1 is a sound velocity cross-sectional view.
Fig. 2 is a horizontal correlation diagram for different sound source depths.
Fig. 3 (a) to 3 (d) are graphs of phase with frequency for different depths (3 m, 15m, 49m, and 139 m).
Detailed Description
The first specific implementation way is as follows:
the embodiment is a method for distinguishing underwater targets on water surface based on shallow water sound field correlation, which comprises the following steps:
in a shallow water waveguide, the distance r, depth z will be r Where the sound field is represented as a superposition of a series of simple normal waves
Figure BDA0003895652670000061
wherein ,zs X (f) is the frequency spectrum of the sound source radiation noise, j represents an imaginary number, ρ is the water density,
Figure BDA0003895652670000062
is a depth-dependent modal function, k m and βm The horizontal wave number and the attenuation coefficient of the mth order normal wave are respectively, and M is the order of the normal wave.
Consider an N-element horizontal array close to the water bottom, with the array element spacing d and the target angle theta to the horizontal. Let the horizontal distance between the reference array element and the target be r, the horizontal distance between the ith array element and the target can be expressed as
r i ＝r+(i-1)dcosθ (2)
Using the first N/2 array elements of the horizontal array to perform wave beam forming on the target to obtain a complex sound pressure signal p 1 Then N/2 array elements form wave beams to the target to obtain a complex sound pressure signal p 2 Is provided with
Figure BDA0003895652670000063
wherein ,
Figure BDA0003895652670000064
in wave number, ω =2 π f is the angular frequency, f is the frequency, and c is the speed of sound in water. a. b represents array element serial number;
Figure BDA0003895652670000065
is a modal function with respect to depth; k is a radical of formula n and βn Respectively the horizontal wave number and the attenuation coefficient of the nth order normal wave;
note the book
Figure BDA0003895652670000066
Complex sound pressure p 1 and p2 Has a correlation coefficient of
Figure BDA0003895652670000067
wherein ,
Figure BDA0003895652670000068
representing complex sound pressure p 2 The conjugate, | - |, represents the absolute value,
Figure BDA0003895652670000069
representing a smooth average over distance.
Note the book
Figure BDA0003895652670000071
And substituting the formula (3) into
Figure BDA0003895652670000072
wherein ,
Figure BDA0003895652670000073
when the horizontal distance r between the target and the array is much larger than the aperture of the array (the horizontal distance between the target and the array is more than ten times the aperture of the array), the following approximation can be made
Figure BDA0003895652670000074
Figure BDA0003895652670000075
Substituting the formula (6) and the formula (7) into the formula (5), and finishing to obtain
Figure BDA0003895652670000076
wherein ,
Figure BDA0003895652670000077
G mn for real part containing array element ordinal number term after addition
Figure BDA0003895652670000078
When m = n, the first term in parentheses of equation (8) is a slow varying function of distance and depth; when m ≠ n, the second term in the parenthesis of equation (8) varies strongly 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 inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure BDA00038956526700000711
In the above formula, SR m The horizontal distance traveled by the intrinsic sound ray in a circulation region;
Figure BDA0003895652670000081
c (z) is the speed of sound at depth z;
Figure BDA0003895652670000082
constant E =0.875.
When the frequency of the sound source is higher, multi-order normal waves exist in shallow water, and the grazing angle approaches to be 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), (11) and (12) into the formula (9), and finishing to obtain
Figure BDA0003895652670000084
wherein ,α0 For grazing angles expressed as integration objects, lower integration limit α 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 The wave number at the depth where the speed of sound is the minimum.
Thus, p can be obtained 1 and p2 Correlation coefficient of
Figure BDA0003895652670000085
Wherein the angular energy density
Figure BDA0003895652670000086
SR(α 0 ) Is an angle alpha 0 Corresponding to the horizontal distance, alpha, traveled by the intrinsic ray in a region of the cycle zs and αzr Respectively a depth z s and zr Grazing angle of (d), real
Figure BDA0003895652670000087
β(α 0 ) For a distance SR (alpha) per cycle 0 ) Energy loss of (2).
For wideband signals having L frequency domain samples, the horizontal correlation coefficient can be expressed as
Figure BDA0003895652670000088
Γ(f l ) Is the l-th term of the wideband signal cross-spectrum Γ. W is a group of l (α 0 ) For the energy density at frequency-dependent grazing angles (the expression over a wide band is denoted as W l (·))；
Recording the phase of gamma as
φ(z s ,ω)＝angle(Γ) (17)
φ(z s ω) and the correlation γ (z) s ,z r And f) related.
Under the conditions of negative sound velocity gradient (thermocline) and receiving depth close to the water bottom, because a shallow source (surface source) is difficult to excite a low-order mode and a deeper source (submerged source), the high-order mode of the shallow source has higher proportion, the horizontal correlation is low (the correlation coefficient is small), and the phase phi (z) of the cross spectrum is small s ω) sharp jump with frequency; after long-distance transmission, due to boundary reflection and other reasons, the loss of the high-order mode is large, in the deep source excited modes, the low-order mode occupies the dominant position, the horizontal correlation is higher (the correlation coefficient is large), and the phase phi (z) is large s ω) varies relatively smoothly with frequency.
To illustrate this characteristic, simulations were performed in an environment having a sound velocity gradient as shown in fig. 1. The sound source frequency is 200Hz to 400Hz, and the sound source signal is incident from 0 degrees. A uniform 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 Is 160m. Fig. 2 is a horizontal correlation coefficient at a receiving position for different sound source depths. The phase variation with frequency at different sound source depths is calculated using equation (17) 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 the comparison, the shallow source (3 m, 15 m) has a phase which varies strongly with frequency, at [ - π, π]Jumping rapidly; the phase of the deep sources (49 m and 139 m) is flat with frequency, the phase changes almost slowly, and jumps occur only at certain frequencies. The law of the phase change of the shallow source and the deep source is in accordance with the horizontal correlation of the receiving depth. To describe this change rule more intuitively:
frequency domain variance of A-phase
Figure BDA0003895652670000091
Describing the discrete 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 which changes slowly is small;
b is the frequency domain first order difference diff (phi (z) of the phase s ω)), the change speed of the phase within the band is described. Along with the phase of the rapid change of the frequency, more spikes representing the speed jump appear in the first-order difference, the slowly-changed spikes are fewer and are relatively flat, and the underwater target on the water surface can be judged by counting the number of the jumping spikes, diff (phi (z) s ,ω)) l ＝φ(z s ,ω l+1 )-φ(z s ,ω l ) L =1,2, \8230, L-1 is the L-th term of diff (Φ (zs, ω));
c is the variance var (diff (phi (z) of the first order difference of the phase frequency domain s Omega)) of the phase, and the dispersion degree of the first-order difference of the phase is described, along with the phase which changes rapidly with frequency, the first-order difference has more spikes and large dispersion, and the spikes which change slowly with large variance are fewer, the dispersion is small, and the variance is small.
And judging whether the sound source is on the water surface or under the water by using a binary signal detection model in a detection theory and a noisy signal received by a horizontal array. The problem can be described as follows
Figure BDA0003895652670000101
wherein ,zlim To resolve the depth, typically set to 15m to 30m below the water, the positive direction of the depth axis z points in the direction of increasing water depth. Depth z of sound source s Less than z lim With the target being a surface source (shallow source), say H 0 (ii) a Depth z of sound source s Greater than z lim With the target being an underwater source (deep source), i.e. assuming H 1 。
The phase change is described using three kinds of feature quantities, and each of them is regarded as a statistic for sound source depth discrimination and is denoted as R var ，R diff and Rvdiff According to the description of the phase law in the previous section, there are
Figure BDA0003895652670000102
R mod For one of the above statistics, when R mod When the target is greater than or equal to the threshold eta, the target is a shallow source (a water surface target); when the statistic is less than the threshold eta, the target is a deep source (underwater target).
The second embodiment is as follows:
the embodiment is a surface and underwater target distinguishing device based on shallow water sound field correlation, the device comprises a processor and a memory, and it should be understood that the device comprises any device described in the present invention, including the processor and the memory, and the device may also comprise other units and modules which perform display, interaction, processing, control 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. Storage media may include, but is not limited to, magnetic storage media, optical storage media; a magneto-optical storage medium comprising: read-only memory ROM, random access memory RAM, erasable programmable memory (e.g., EPROM and EEPROM), and flash memory layers; or other type of media suitable for storing electronic instructions.
The memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to realize the method for resolving the underwater and water surface targets based on the shallow water sound field correlation.
The above-described calculation examples of the present invention are merely to describe the calculation model and the calculation flow of the present invention in detail, and are not intended to limit the embodiments of the present invention. It will be apparent to those skilled in the art that other variations and modifications can be made on the basis of the foregoing description, and it is not intended to exhaust all of the embodiments, and all obvious variations and modifications which fall within the scope of the invention are intended to be included within the scope of the invention.

Claims (10)

1. A method for distinguishing water surface and underwater targets based on shallow water sound field correlation is characterized by comprising the following steps:
in a shallow water waveguide, the distance r, depth z will be r Where the sound field is represented as a superposition of a series of normal waves
Figure FDA0003895652660000011
wherein ,zs X (f) is the frequency spectrum of the sound source radiation noise, j represents an imaginary number, rho is the water density,
Figure FDA0003895652660000012
is a depth-dependent modal function, k m and βm Respectively the horizontal wave number and the attenuation coefficient of the mth order normal wave, wherein M is the order of the normal wave;
aiming at an N-element horizontal array near the water bottom, the first N/2 array elements of the horizontal array are used for carrying out beam forming on a target to obtain a complex sound pressure signal p 1 Then N/2 array elements form wave beams to the target to obtain a complex sound pressure signal p 2 ；
Based on complex sound pressure p 1 and p2 To obtain
Figure FDA0003895652660000013
Figure FDA0003895652660000014
Representing complex sound pressure p 2 Is further conjugated to obtain
Figure FDA0003895652660000015
wherein ,
Figure FDA0003895652660000016
r a 、r b a and b represent array element serial numbers which are horizontal distances between the array elements and the target; z is a radical of r 、z s In order to be the depth of the film,
Figure FDA0003895652660000017
is a modal function with respect to depth; k is the wave number, k m and kn The horizontal wave numbers of the mth order normal wave and the nth order normal wave respectively; beta is a m and βn Attenuation coefficients of the mth order and nth order normal waves respectively; d is the array element spacing, and theta 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 larger than the aperture of the array, the reference array element and the target have the same structure
Figure FDA0003895652660000018
wherein ,
Figure FDA0003895652660000019
G mn the real number part is the real number part which contains the array element ordinal number term after being added,
Figure FDA00038956526600000110
when m is not equal to n, the distance and the depth are smoothed to obtain
Figure FDA00038956526600000111
wherein ,
Figure FDA0003895652660000021
depth of inversion [ eta ] in mth order mode m ,ξ m ]The square average of the internal mode function is
Figure FDA0003895652660000022
wherein ,SRm Water passing through a circulation zone for intrinsic sound raysA flat distance;
Figure FDA0003895652660000023
c (z) is the speed of sound 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 For grazing angles expressed as integral objects, the lower limit of integration α 0I ＝arccos(max(k(z s ),k(z r ))/k 0 )，k 0 Is the wave number at the depth where the sound velocity is the minimum;
finally obtain p 1 and p2 Correlation coefficient of (2)
Figure FDA0003895652660000026
wherein ,W(α0 ) Is the angular energy density;
a wideband signal having L frequency domain samples, the horizontal correlation coefficient being expressed as
Figure FDA0003895652660000027
Γ(f l ) The l-th term of the broadband signal cross spectrum Γ; w l (α 0 ) Energy density with respect to frequency-dependent grazing angle;
to determine the phase of gamma
Figure FDA0003895652660000028
Last radicalIn phase phi (z) s ω), a binary signal detection model is adopted to realize the identification of shallow sources or deep sources.
2. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 1, characterized by being based on the phase phi (z) s Omega) the process of identifying shallow or deep sources using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω) as a frequency domain variance of the phase
Figure FDA0003895652660000031
This is taken as the statistic for sound source depth discrimination and is 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. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 1, wherein the method is based on phase phi (z) s Omega) the process of identifying shallow or deep sources using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω), make the frequency domain first order difference diff (φ (z) of the phase s ω)) as a statistic for sound source depth discrimination, and is denoted as R diff ；
When R is diff Greater than or equal to frequency domain first-order difference threshold eta diff When, the target is a shallow source; otherwise, the target is a deep source.
4. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 1, characterized by being based on the phase phi (z) s Omega) the process of identifying shallow or deep sources using a binary signal detection model comprises the following steps:
based on the phase phi (z) s ω), variance var (diff (φ (z)) of the first order difference of the phase frequency domain s ω))) as the sound source depth criterionOther statistics, denoted as R vdiff ；
When R is vdiff Variance threshold eta greater than or equal to first-order difference of phase frequency domain vdiff When the target is a shallow source; otherwise, the target is a deep source.
5. Method for resolving underwater and surface targets based on shallow water sound field correlation according to one of claims 1 to 4, wherein the angular energy density W (α) 0 ) The following were used:
Figure FDA0003895652660000032
wherein, SR (alpha) 0 ) Is an angle alpha 0 Corresponding to the horizontal distance traveled by the intrinsic ray in one of the loop regions,
Figure FDA0003895652660000033
and
Figure FDA0003895652660000034
respectively depth z s and zr Grazing angle of (d), real
Figure FDA0003895652660000035
β(α 0 ) Is SR (alpha) 0 ) Corresponding energy loss.
6. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 5, wherein the complex sound pressure p is 1 and p2 The following:
Figure FDA0003895652660000041
Figure FDA0003895652660000042
wherein k is the wave number.
7. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 6, wherein the method is based on complex sound pressure p 1 and p2 To obtain
Figure FDA0003895652660000043
Based on complex sound pressure p 1 and p2 Determined by the correlation coefficient of (2), complex sound pressure p 1 and p2 The correlation coefficient of (a) is as follows:
Figure FDA0003895652660000044
wherein, | - | represents taking an absolute value,
Figure FDA0003895652660000045
representing a smooth average over distance.
8. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 7, wherein the horizontal distance between the array element and the target is as follows:
r i ＝r+(i-1)d cosθ
wherein ,ri Indicating the horizontal distance of the ith array element from the target.
9. The method for resolving the underwater and water surface targets based on the shallow water sound field correlation as claimed in claim 8, wherein the wave number is
Figure FDA0003895652660000046
ω =2 π f is the angular frequency, f is the frequency, c is the speed of sound in water.
10. A shallow water acoustic field correlation based water surface and underwater target resolution device, which comprises a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement a shallow water acoustic field correlation based water surface and underwater target resolution method according to any one of claims 1 to 7.
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