CN111505578B - ULA (ultra-low-resolution) target multi-source positioning method and device based on time reversal focusing - Google Patents
ULA (ultra-low-resolution) target multi-source positioning method and device based on time reversal focusing Download PDFInfo
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Abstract
The invention provides a time-reversal focusing-based ULA (ultra-low-power) target multi-source positioning method and device, wherein the method comprises the following steps: setting a real target position, acquiring the positions of a sea surface virtual source and a submarine virtual source, transmitting detection signals through a ULA under far field conditions, and acquiring azimuth vectors of the set real target, the sea surface virtual source and the submarine virtual source; estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm; and forming an overdetermined equation set by using the estimated sound source orientations, uniformly weighting a plurality of solutions of the overdetermined equation set, and estimating the real target position. The invention enhances the energy of each array element of the array to receive signals by utilizing a plurality of virtual sources formed by the multipath effect of the waveguide environment and the timely anti-adaptive airspace focusing characteristic, thereby achieving the purpose of accurate target azimuth estimation.
Description
Technical Field
The invention relates to the technical field of underwater acoustic signal processing, in particular to a time-reversal focusing-based ULA (ultra-low-power) target multi-source positioning method and device.
Background
Time Reversal (TR) has been developed in 1965 and has been widely used in various fields including ultrasonic target detection and localization, medical human pathology diagnosis, mathematical theory model, underwater sound target detection localization and wireless communication fields. The ultrasonic field M.Fink serves as a leader of the TR, not only unifies the definition of the TR, but also plays a great role in promoting the development of the TR both in experiments and in theory. In the medical field, the Benjamin T.Cox and Bradley E.Treeby apply TR to human photoacoustic imaging, so that whether a propagation medium is uniform or not due to the difference of internal structures of human bodies can be not considered, and the TR processing of cutting off received data can improve the quality of three-dimensional imaging. Fannjiang demonstrates the principle of TR mirrors in detail from the mathematical field, and introduces 5 different types of TR mirror models to analyze and discuss the relationship between boundary conditions, propagation waveforms and focal points in two-dimensional and three-dimensional contexts. Hydroacoustic workers have conducted extensive theoretical studies and extensive experiments on the hydroacoustic TR, representing the characters Darrell r.jackson, david r.dowling and w.a. kuperman. H.c.song et al studied a MIMO (Multi Input Multi Output, multiple input multiple output) system based on shallow channel TR communication, where multiple focalizations can be simultaneously obtained at different depths of reception in a linear system, indicating that MIMOTR communication can increase the communication rate between the signal source and the receiving array.
The target positioning is a key problem in the underwater acoustic signal processing, and a polar coordinate system is established by taking a detection system as an origin in a two-dimensional plane to position a target, so that the distance and the azimuth angle are required to be obtained, and the measurement of the target distance is also required during direction finding, and finally, the measurement can be summarized into joint estimation of the azimuth angle and the time delay. The azimuth estimation comprises a traditional beam forming method, a time delay estimation method and a high-resolution azimuth estimation method, and the time delay estimation comprises a generalized cross correlation method (GCC), a phase spectrum method, a parametric model method and an adaptive time delay estimation method. Many scholars propose some new delay estimation algorithms on the basis of the method, such as a high-order cumulant method and a wavelet transformation method; the new high-resolution azimuth estimation algorithm mainly comprises a subspace type method, a parameter model method, a deconvolution method, a maximum likelihood method and a second moment orientation method.
The new time delay estimation algorithm improves the estimation accuracy, but has the problems of high operation amount, high signal-to-noise ratio limit, model mismatch under the unknown noise background and the like. The direct paths in signal propagation are considered in the time reversal positioning of the uniform linear array, because the corresponding time delays of the direct paths can directly give the azimuth characteristics of the targets, and certain limitation exists on the application of the multipath effect of the shallow sea waveguide environment.
Disclosure of Invention
In order to avoid the defects of the prior art, the invention provides a time-reversal focusing-based ULA (Uniform Linear Array ) target multi-source positioning method and device, which solve the problem that effective target positioning cannot be performed in a waveguide shallow sea strong noise environment. The energy of the signals received by each array element of the array is enhanced by utilizing a plurality of virtual sources formed by the multipath effect of the waveguide environment and the timely anti-adaptive airspace focusing characteristic, so that the aim of accurately estimating the target azimuth is fulfilled.
In a first aspect of the present invention, a method for positioning ULA targets in multiple sources based on time reversal focusing is provided, the method comprising the steps of:
s1, setting a real target position, acquiring positions of a sea surface virtual source and a seabed virtual source, and acquiring azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source through each array element of the ULA under far field conditions;
s2, estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
s3, forming an overdetermined equation set by using the estimated sound source directions, and uniformly weighting a plurality of solutions of the overdetermined equation set to obtain the real target position.
Preferably, the step S1 specifically includes:
the ULA is known to consist of J omni-directional array elements, the array element distance is d, the sea depth is H, and the actual target depth and the distance are respectively H T And l, the depth and the distance of the corresponding sea surface virtual source are respectively-h T And the depth and the distance of the submarine virtual source are H+h respectively T And l; taking the array element closest to the sea surface as the 1 st array element, numbering each array element in sequence, wherein the depth of each array element of the ULA is h 1 ,h 2 ,…,h J And the azimuth vectors of the real target, the sea surface virtual source and the sea bottom virtual source are respectively as follows:
wherein ,
the azimuth vectors corresponding to the real target, the sea surface virtual source and the seabed virtual source relative to all array elements of the ULA respectively, namely theta, alpha and beta respectively represent the azimuth of the real target, the sea surface virtual source and the seabed virtual source under far field conditions, i is an imaginary unit, and lambda represents the wavelength of sound waves.
Preferably, the step S2 specifically includes:
estimating the azimuth theta, alpha and beta of each sound source by adopting the following ULA target directional gain algorithm:
wherein GΘ (θ) orientation results corresponding to real target, G A (alpha) corresponds to the orientation result of the sea surface virtual source, G B (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Represents an array decay TR matrix,
Representing the array manifold matrix after virtual TR processing.
Preferably, the step S3 specifically includes:
s31, using the estimated sound source orientations theta, alpha, beta and h T 、H、h 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
wherein l represents a target horizontal distance;
s32 (h) of the above overdetermined equation set T L) has a plurality of solutions, weighted average of the plurality of solutions of the system of overdetermined equations, deriving a specific position (h) of the real target T ,l)。
In a second aspect of the present invention, there is provided a ULA target multi-source positioning device based on time reversal focusing, the device comprising:
azimuth vector acquisition module: the method comprises the steps of setting a real target position, obtaining the positions of a sea surface virtual source and a seabed virtual source, and obtaining azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source through each array element of the ULA under far field conditions;
a multi-source azimuth estimation module: the method is used for estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
a real target positioning module: and the method is used for forming an overdetermined equation set by using the estimated sound source positions, and uniformly weighting a plurality of solutions of the overdetermined equation set to obtain the real target position.
Preferably, in the azimuth vector obtaining module, the azimuth vectors of the set real target, the sea surface virtual source and the sea bottom virtual source obtained by each array element of the ULA in the far field condition are respectively:
wherein ,
the azimuth vectors corresponding to the real target, the sea surface virtual source and the seabed virtual source relative to all array elements of the ULA respectively, namely theta, alpha and beta respectively represent the azimuth of the real target, the sea surface virtual source and the seabed virtual source under far field conditions, and lambda represents the wavelength of sound waves.
Preferably, in the multi-source azimuth estimation module, the ULA target directional gain algorithm is:
wherein GΘ (θ) orientation results corresponding to real target, G A (alpha) corresponds to the orientation result of the sea surface virtual source, G B (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Represents an array decay TR matrix,
Representing the array manifold matrix after virtual TR processing.
Preferably, the real target positioning module specifically includes:
an equation set establishing unit: for using the estimated sound source orientations theta, alpha, beta and the true target depth h T Sea depth H, 1 st array element depth H 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
where l represents the horizontal distance of the real target;
a weighted positioning unit: for obtaining a plurality of solutions of the above-mentioned overdetermined equation set, weighting and averaging the plurality of solutions of the overdetermined equation set to obtain a specific position (h T ,l)。
1) Compared with the ULA conventional array signal processing, the method overcomes the influence of multipath effect of the waveguide environment, and expands the application under the weak target background by improving the strength of the received signal through the time-reversal self-adaptive airspace focusing characteristic.
2) Compared with a method for positioning by utilizing direct path signals by using ULA, the method fully utilizes the real target and virtual source azimuth in the multipath effect of the waveguide environment, gives a multi-source positioning hyperstatic equation set model of the waveguide environment on the relation between the virtual source and the real target, reduces positioning errors by average weighting of all sound source azimuth, and realizes effective estimation of the real target azimuth.
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In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the technical description of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 (a) is a typical time-reversal adaptive spatial focusing effect, and fig. 1 (b) is an energy distribution of signals received by each array element after ULA time-reversal processing;
FIG. 2 is a schematic flow chart of a time-reversal focusing-based ULA target multi-source positioning method provided by the invention;
FIG. 3 is a background of the multi-source positioning method in a shallow sea waveguide environment provided by the present invention;
FIG. 4 is a schematic diagram of a weighted average flow scheme provided by the present invention;
FIG. 5 is a schematic illustration of the acoustic ray trace of a target signal propagating to ULA 1 st element;
fig. 6 (a) is an azimuth estimation of a real target, fig. 6 (b) is an azimuth estimation of a sea surface virtual source, fig. 6 (c) is an azimuth estimation of a sea bottom virtual source, and fig. 6 (d) is an estimation result of a real target positioning;
fig. 7 (a) is the azimuth estimation of the real target under the input signal-to-noise ratio of-10 dB, fig. 7 (b) is the azimuth estimation of the sea surface virtual source under the input signal-to-noise ratio of-10 dB, fig. 7 (c) is the azimuth estimation of the sea surface virtual source under the input signal-to-noise ratio of-10 dB, fig. 7 (d) is the azimuth estimation of the sea surface reflection corresponding to the virtual source under the input signal-to-noise ratio of-10 dB, fig. 7 (e) is the azimuth estimation of the sea surface reflection corresponding to the virtual source under the input signal-to-noise ratio of-10 dB, and fig. 7 (f) is the estimation result of the real target positioning under the input signal-to-noise ratio of-10 dB.
Detailed Description
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The idea of the invention is that: compared with the traditional signal detection method, the time reversal can carry out in-phase superposition of multipath signals on the basis of propagation channel matching, and the energy of a received signal is enhanced, so that the time reversal has the strong advantage of signal detection in a strong noise environment. Although time reversal can be used to approximate the target's bearing information from the focusing results, the focusing effect is related not only to the physical structure of the array, but also to the noise intensity. Therefore, the method only has strong signal detection advantages in the environment where strong noise exists, and has no target positioning advantages. Besides the signal detection, the accurate target positioning technology also needs a further signal processing process to extract the azimuth information of the target.
The uniform linear array is adopted to conveniently carry out self-adaptive wave beam formation so as to achieve the purpose of accurate positioning of the target. Referring to fig. 1, fig. 1 (a) shows the time-reversal adaptive spatial focusing effect, and fig. 1 (b) shows the energy distribution of the received signal of each array element after ULA time reversal processing. Because each path of the target signal propagating to reach the array is accompanied by different time delays due to the shallow sea multipath effect, if the direct path of the signal propagating to reach the array is simply considered, the positioning accuracy is likely to be reduced under the condition that additive noise exists, so that how to accurately perform target positioning under the background of complex shallow sea multipath channels and accompanying strong noise is needed to be further studied.
Therefore, a new method is required to be provided for effectively positioning the target in the waveguide shallow sea strong noise environment, so that not only can the energy of the array received signal be enhanced by utilizing the multipath effect, but also the effect of strong noise can be overcome to accurately realize the effective positioning of the target.
Taking a typical shallow sea waveguide environment as an example, embodiments of the present invention are given:
under far field conditions, the ULA, propagation medium, signal and noise are assumed to satisfy the following conditions:
(1) The ULA is located in the far field of the target and in one plane with the target, and the received narrowband signal can be considered approximately a plane wave;
(2) No mutual coupling exists among array elements, each array element is isotropic, and the space gain is 1;
(3) The propagation medium is uniform and isotropic;
(4) The mean value of the additive noise is 0, and the variance is sigma 2 And the noise between each array element is uncorrelated in both time and space domains.
Referring to fig. 2, a flowchart of a ULA object multi-source positioning method based on time reversal focusing according to the present invention includes the following steps:
s1, setting a real target position, acquiring positions of a sea surface virtual source and a seabed virtual source, transmitting detection signals through a ULA under far field conditions, and acquiring azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source;
referring to fig. 3, fig. 3 is a background schematic diagram of a multi-source positioning method in a shallow sea waveguide environment, assuming that the ULA is composed of J omni-directional array elements and the array element spacing is d, the sea depth is H, and the real target depth and distance are H respectively T And l, the depth and the distance of the corresponding sea surface virtual source are respectively-h T And the depth and the distance of the submarine virtual source are H+h respectively T And l; taking the array element closest to the sea surface as the 1 st array element, numbering each array element in sequence, wherein the depth of each array element of the ULA is h 1 ,h 2 ,…,h J Under the assumption that 1 far-field target exists in the shallow sea environment, the 1 st array element is used as a reference array element, and rectangular windowing CW signals are transmitted to perform target detection, the azimuth vectors of the real target, the sea surface virtual source and the sea bottom virtual source are respectively as follows:
wherein ,
the azimuth vectors corresponding to the real target, the sea surface virtual source and the seabed virtual source relative to all array elements of the ULA respectively, namely theta, alpha and beta respectively represent the azimuth of the real target, the sea surface virtual source and the seabed virtual source under far field conditions, i is an imaginary unit, and lambda represents the wavelength of sound waves.
S2, estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
specifically, the snapshot data received by the ULA is expressed as:
wherein s (t) is a target signal, Y (t) = [ Y ] 1 (t),y 2 (t),…,y J (t)] T Representing an array received signal vector, Q (t) = [ Q ] 1 (t),q 2 (t),…,q J (t)] T Representing an array noise vector;
representing an array attenuation matrix, ">
a j,1 、a j,2 A j,3 The attenuation coefficients of direct waves, sea surface reflected waves and submarine reflected waves from the target to the jth array element are represented; array attenuation TR matrix->
wherein 
i is an imaginary unit, j=1, 2, … J, τ A 、τ B Respectively representing the time delay difference of sea surface reflected waves reaching the reference array element and submarine reflected waves relative to the direct waves, wherein lambda is the wavelength of sound waves;
the array manifold matrix after the virtual TR processing is:
estimating the azimuth theta, alpha and beta of each sound source by adopting the following ULA target directional gain algorithm:
wherein GΘ (θ) orientation results corresponding to real target, G A (alpha) corresponds to the orientation result of the sea surface virtual source, G B (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Represents an array decay TR matrix,
Representing the array manifold matrix after virtual TR processing.
S3, forming an overdetermined equation set by using the estimated sound source directions, and uniformly weighting a plurality of solutions of the overdetermined equation set to obtain the real target position.
S31, using the estimated sound source orientations theta, alpha, beta and h T 、H、h 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
wherein l represents a target horizontal distance;
s32 (h) of the above overdetermined equation set T L) hasA plurality of solutions, weighted-averaging the plurality of solutions of the system of overdetermined equations, deriving a specific position (h T L). Specifically, referring to fig. 3, a weighted average flow chart is shown, (h T ,l) 1 Represents coordinates derived from θ and α, (h) T ,l) 2 Represents coordinates derived from θ and β, (h) T ,l) 3 Represents coordinates derived from α and β, (h) T L) represents the coordinates of the real object. The weighted average can be given different weighting factors according to the propagation attenuation degree of the multipath signals, and the nonlinear component contained in the analytical expression of the overdetermined equation set has a certain influence on the positioning error, so that the error can be reduced in a uniformly weighted manner.
The invention also provides a time-reversal focusing-based ULA target multi-source positioning device, which comprises:
azimuth vector acquisition module: the method comprises the steps of setting a real target position, obtaining the positions of a sea surface virtual source and a seabed virtual source, and obtaining azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source through each array element of the ULA under far field conditions;
a multi-source azimuth estimation module: the method is used for estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
a real target positioning module: and the method is used for forming an overdetermined equation set by using the estimated sound source positions, and uniformly weighting a plurality of solutions of the overdetermined equation set to obtain the real target position.
Further, in the azimuth vector obtaining module, azimuth vectors of the set real target, the sea surface virtual source and the sea bottom virtual source are obtained through each array element of the ULA in the far field condition respectively:
wherein ,
respectively corresponding to a real target, a sea surface virtual source and the sea bottomThe azimuth vectors of the virtual source relative to all array elements of the ULA, namely theta, alpha and beta under far field conditions respectively represent the azimuth of a real target, a sea surface virtual source and a submarine virtual source, i is an imaginary unit, and lambda represents the wavelength of sound waves.
Preferably, in the multi-source azimuth estimation module, the ULA target directional gain algorithm is:
wherein GΘ (θ) orientation results corresponding to real target, G A (alpha) corresponds to the orientation result of the sea surface virtual source, G B (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Represents an array decay TR matrix,
Representing the array manifold matrix after virtual TR processing.
Further, the real target positioning module specifically includes:
an equation set establishing unit: for using the estimated sound source orientations theta, alpha, beta and the true target depth h T Sea depth H, 1 st array element depth H 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
where l represents the horizontal distance of the real target;
weighted positioning sheetThe element: for obtaining a plurality of solutions of the above-mentioned overdetermined equation set, weighting and averaging the plurality of solutions of the overdetermined equation set to obtain a specific position (h T ,l)。
Experiments are carried out by adopting the ULA target multi-source positioning method based on time reversal focusing, and the shallow sea channel medium with the depth of 500m is assumed to be uniform, and the sound velocity c=1500m/s. A horizontal distance between the target and ULA of 8000m, wherein the target depth is 300m; the ULA comprises 21 array elements, and the depth range of the ULA is 300-305 m; the reference array element is nearest to the sea surface, and a rectangular windowing CW signal is transmitted to perform target detection, wherein the center frequency is 3000Hz, and the pulse width is 5ms. Only the acoustic line propagation model of the sea surface or the sea bottom, which is reflected at most once, is considered, and the array elements are numbered sequentially, namely the 1 st array element closest to the sea surface and the 21 st array element closest to the sea bottom.
The schematic diagram of the sound ray track of the target signal transmitted to the 1 st array element of the ULA is shown in fig. 5, and the target reflection signal reaches the 1 st array element through a direct path, sea surface reflection, submarine reflection, sea surface and submarine reflection firstly and then, sea surface and sea surface reflection firstly.
Experiments are carried out by adopting the ULA target multi-source positioning method based on time-reversal focusing, the experimental results are shown in fig. 6 and 7, fig. 6 is a target positioning result only when a direct path, sea surface reflection and submarine reflection signals reach each array element, wherein fig. 6 (a) shows the azimuth estimation of a real target, fig. 6 (b) shows the azimuth estimation of a sea surface virtual source, and fig. 6 (c) shows the azimuth estimation of a submarine virtual source. The sea surface virtual source and the seabed virtual source are respectively positioned at two ends of the normal line of the ULA reference array element, and the normal line deflects towards the seabed direction to be positive, so that the azimuth of the sea surface virtual source is negative, and the azimuth of the seabed virtual source is positive. Position confirmation of a real target is performed in combination with an overdetermined equation set, the result of which is shown as "×" in fig. 6 (d), for a plurality of (h T The weighted average result of l) the positions is shown as "Δ" in fig. 6 (d). FIG. 6 shows that the method of determining the position of the target object by applying the method to a plurality (h T The weighted average of l) the positions can significantly reduce the error of the target positioning estimation.
Adding environmental noise in original simulation environment to enable SNR in = -10dB, and introducing multiple virtual sources in fig. 5, i.e. target reflected signals via direct pathsDiameter, sea surface reflection, submarine reflection, sea surface reflection, and arrival at each array element, the target orientation is performed under the max-SNR criterion, the result of which is shown in fig. 7. Wherein fig. 7 (a) shows the azimuth estimation of a real target, fig. 7 (b) shows the azimuth estimation of a sea surface virtual source, fig. 7 (c) shows the azimuth estimation of a sea bottom virtual source, fig. 7 (d) shows the azimuth estimation of a virtual source corresponding to sea surface-before-sea bottom reflection, and fig. 7 (e) shows the azimuth estimation of a virtual source corresponding to sea bottom-before-sea surface reflection. The target positioning result is shown in fig. 7 (f), and the target positioning result is shown in (h T The weighted average result of l) is shown as "Δ" in fig. 7 (f), and the depth error Δh thereof T As can be seen from comparison of fig. 6, the accuracy of target positioning is affected by low signal-to-noise ratio, as shown by the horizontal distance error Δl=60 m=2m.
The device embodiments and the method embodiments are in one-to-one correspondence, and the device embodiments are omitted, and reference is made to the method embodiments.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
While the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that the foregoing embodiments are merely illustrative of the invention and not limiting thereof: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. A time-reversal focusing-based ULA target multi-source positioning method, which is characterized by comprising the following steps:
s1, setting a real target position, acquiring positions of a sea surface virtual source and a seabed virtual source, transmitting detection signals through a ULA in a shallow sea environment, and acquiring azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source; the method specifically comprises the following steps:
let ULA consist of J omni-directional array elements with spacing d, sea depth H, and real target depth and distance H respectively T And l, the depth and the distance of the corresponding sea surface virtual source are respectively-h T And the depth and the distance of the submarine virtual source are H+h respectively T And l; taking the array element closest to the sea surface as the 1 st array element, numbering each array element in sequence, wherein the depth of each array element of the ULA is h 1 ,h 2 ,…,h J Taking the 1 st array element as a reference array element, the azimuth vectors of the real target, the sea surface virtual source and the sea bottom virtual source are respectively as follows:
wherein ,
azimuth vectors corresponding to all array elements of the real target, the sea surface virtual source and the submarine virtual source relative to the ULA respectively, namely, θ, α and β under far field conditions respectively represent the azimuth of the real target, the sea surface virtual source and the submarine virtual source, i is an imaginary unit, and λ represents the wavelength of sound waves;
s2, estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
s3, forming an overdetermined equation set by using the estimated sound source orientations, uniformly weighting a plurality of solutions of the overdetermined equation set, and estimating a real target position; the method specifically comprises the following steps:
s31, using the estimated sound source orientations theta, alpha, beta and h T 、H、h 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
wherein l represents a target horizontal distance;
s32 (h) of the above overdetermined equation set T L) have multiple solutionsA weighted average of the solutions of the system of overdetermined equations is performed to derive a specific position (h T ,l)。
2. The method for time-reversal focusing-based ULA object multi-source localization according to claim 1, wherein the step S2 is specifically:
estimating the azimuth theta, alpha and beta of each sound source by adopting the following ULA target directional gain algorithm:
wherein GΘ (θ) orientation results corresponding to real target, G Α (alpha) corresponds to the orientation result of the sea surface virtual source, G Β (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Representing an array decay TR matrix, ">
Representing the array manifold matrix after virtual TR processing.
3. A time-reversal focusing-based ULA object multi-source positioning device, the device comprising:
azimuth vector acquisition module: the method comprises the steps of setting a real target position, obtaining the positions of a sea surface virtual source and a seabed virtual source, and obtaining azimuth vectors of the set real target, the sea surface virtual source and the seabed virtual source through each array element of the ULA under far field conditions; in the azimuth vector acquisition module, azimuth vectors of a set real target, a sea surface virtual source and a sea bottom virtual source are acquired through each array element of the ULA under the far field condition and are respectively as follows:
wherein ,
azimuth vectors corresponding to all array elements of the real target, the sea surface virtual source and the submarine virtual source relative to the ULA respectively, namely, θ, α and β under far field conditions respectively represent the azimuth of the real target, the sea surface virtual source and the submarine virtual source, i is an imaginary unit, and λ represents the wavelength of sound waves;
a multi-source azimuth estimation module: the method is used for estimating the orientations of a real target, a sea surface virtual source and a sea bottom virtual source by adopting a ULA target directional gain algorithm;
a real target positioning module: the method comprises the steps of forming an overdetermined equation set by using estimated sound source orientations, and uniformly weighting a plurality of solutions of the overdetermined equation set to obtain a real target position; the real target positioning module specifically comprises:
an equation set establishing unit: for using the estimated sound source orientations theta, alpha, beta and the true target depth h T Sea depth H, 1 st array element depth H 1 The relation of (2) constitutes an overdetermined equation set, θ, α, β and h T 、H、h 1 The following relationship is satisfied:
where l represents the horizontal distance of the real target;
a weighted positioning unit: for obtaining a plurality of solutions of the above-mentioned overdetermined equation set, weighting and averaging the plurality of solutions of the overdetermined equation set to obtain a specific position (h T ,l)。
4. A ULA target multi-source positioning device based on time-reversal focusing according to claim 3, wherein in the multi-source position estimation module, the ULA target directional gain algorithm is:
wherein GΘ (θ) orientation results corresponding to real target, G A (alpha) corresponds to the orientation result of the sea surface virtual source, G B (beta) corresponds to the orientation result of the submarine virtual source,
is->
Respectively representing the corresponding weight vectors; />
Representing an array decay TR matrix, ">
Representing the array manifold matrix after virtual TR processing. />
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