Multi-sensor broadband sound source localization method suitable for deep-sea reliable sound path environment

Abstract

The present application relates to a kind of multi-sensor wideband sound source positioning method suitable for deep-sea reliable sound path environment, utilize the same sound source D-SR time delay measurement value observed by deep-sea large depth multi-sensor to carry out three-dimensional positioning to sound source.In the first stage, based on the position of each sensor, depth, observed D-SR time delay and water body sound velocity profile information, a matrix and a vector are constructed, there is a linear relationship between the two and the position of sound source, the least square method is used to solve this linear relationship, obtain the estimation result of the two-dimensional position of sound source, based on two-dimensional position estimation result, the depth estimation result of sound source is obtained using depth solution formula;In the second stage, based on the three-dimensional position of sound source estimated in the first stage, the D-SR time delay value of the position of each sensor is predicted, then an auxiliary variable matrix is constructed, and new sound source two-dimensional horizontal position estimation result is obtained according to the rule of auxiliary variable estimator (IVE), and finally the final sound source depth estimation result is obtained according to depth solution formula.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of ocean engineering, underwater acoustic engineering, array signal processing and sonar technology, and relates to a multi-sensor wideband sound source positioning method suitable for deep-sea reliable acoustic path environment, which is suitable for passive estimation of three-dimensional position of a wideband sound source near the sea surface by a deep-sea multi-sensor. BACKGROUND

[0002] The accurate three-dimensional positioning of deep-sea underwater targets is the premise of navigation, communication, tracking, identification and attack, and is of great significance to underwater warfare and ocean engineering. Compared with a single sensor (single node, referring to a hydrophone or a hydrophone array), a multi-sensor (or distributed sensor) system has stronger detection capability and greater detection range, and networking and collaboration are the development trend of future underwater acoustic detection and underwater warfare. The target positioning method based on underwater multi-sensor has been widely concerned, and there are many research results at present, mainly including a target direction-based positioning method, a target signal propagation time difference-based positioning method and a target signal multi-path time delay-based positioning method. However, due to the complexity of deep-sea environment, such as waveguide fluctuation and sound ray bending, the existing multi-sensor positioning methods may have problems such as difficulty in implementation or large amount of calculation when applied. The characteristics of the existing several multi-sensor positioning methods are as follows:

[0003] (1) Multi-sensor positioning method based on target direction. Under the assumption of plane wave, a cost function is constructed according to the target direction measured by each sensor, and then a descending algorithm or an analytical solution is used to complete the solution of the target position. This method has a wide range of applications, but all sensors need to have the estimation capability of target azimuth and elevation angle, so each sensor must have a certain array aperture in the horizontal and vertical directions, which has high hardware cost and great practical deployment difficulty. In addition, in deep-sea environment, due to the refraction phenomenon in sound propagation process, the estimated direction of arrival of the sensor and the true geometric direction of the target often have deviation, which must be corrected by using the sound field model in practice, otherwise a large positioning deviation will be caused.

[0004] (2) Multi-sensor positioning method based on target signal propagation time difference. Under the assumption of spherical wave, the target positioning is realized by constructing a cost function through measuring the propagation time difference of target signal between sensors. This method has lower requirements for sensor platform, and in theory, each sensor only needs a single omnidirectional hydrophone to complete the target positioning, but it has high requirements for the clock synchronization accuracy between sensors, and in addition, each sensor needs to upload the original received signal to the processing center for time delay estimation, so it has high requirements for system communication capability. Finally, for the actual application in deep-sea environment, the propagation time error caused by refraction phenomenon and multi-path effect in sound ray propagation process often needs to be corrected based on the sound field model.

[0005] (3)Multi-sensor positioning method based on deep sea multi-path time delay. Under the condition of deep sea large depth reception, the propagation time delay between the direct path (D) and the sea surface reflection path (SR) of the target signal near the sea surface (D-SR time delay) is related to the three-dimensional position of the target. Based on this, the literature "Track of a sperm whale from delays between direct and surface-reflected clicks, Appl. Acoust., 2006, vol. 67, no. 11, pp. 1187-1201" proposes to construct a cost function using the D-SR time delay of the target signal observed by each sensor, and then use the grid scanning method for matching. The grid point that the measurement vector is most matched with the model calculation result is the target position estimation result. This method fully utilizes the characteristics of deep sea sound propagation, and can complete the three-dimensional positioning of the target without relying on the target azimuth information and the accurate clock synchronization of the multi-sensor. However, this method needs to perform three-dimensional grid scanning on the region of interest, and the calculation amount is large, which is not conducive to real-time processing. SUMMARY

[0006] TECHNICAL PROBLEM TO BE SOLVED

[0007] In order to avoid the shortcomings of the prior art, the present application proposes a multi-sensor wideband sound source positioning method suitable for deep sea reliable sound path environment, which solves the problems of insufficient array aperture, insufficient clock synchronization accuracy or slow calculation speed of the existing multi-sensor target positioning method in deep sea environment.

[0008] TECHNICAL SCHEME

[0009] A multi-sensor wideband sound source positioning method suitable for deep sea reliable sound path environment, characterized in that: a plurality of sensors below the critical depth are arranged to receive the wideband sound signals emitted by the sound source near the sea surface, the arrangement position of the nth sensor is p n =[x rn ,y rn ] T , the arrangement depth is z r , the sampling frequency is f s , and the received signal is x n (m), wherein n=1, 2, …, N, N is the number of sensors, and m is the time domain discrete sampling point; the multi-sensor wideband sound source positioning steps are as follows:

[0010] Step 1: For the received signal of each sensor, the D-SR time delay value of the sound source signal is obtained by autocorrelation, and the autocorrelation output of the nth sensor is:

[0011]

[0012] Autocorrelation output R n (q) there is a peak, and the peak position is q n-max The D-SR time delay value observed by the nth sensor (denoted as ) can be expressed as Where the superscript "~" indicates that there is a deviation between the observation value and its true value caused by random noise;

[0013] Step 2: According to the D-SR time delay observation values of the N sensors Construct the matrix And the vector b:

[0014]

[0015] b = [b2, …, b n , …, b N ] T

[0016] The

[0017]

[0018]

[0019] Where: x rn and y rn are the 1st and 2nd elements of p n , c ref is the average sound speed in the sea surface to the maximum sound source depth interval, Q1 and Q2 are parameters related to the sound speed profile, and κ = 0.72;

[0020] Step 3: According to the matrix And the vector b, use the least square method to solve the two-dimensional position of the sound source Get The first two elements of the vector are the two-dimensional coordinates of the sound source in the horizontal plane, denoted as

[0021]

[0022] Select the nearest sensor to the sound source horizontal distance, denoted as the ith sensor, and use the depth calculation formula to calculate the sound source depth:

[0023]

[0024] Where represents the horizontal distance between the above-mentioned ith sensor and the sound source, c(z) represents the sound speed value at depth z, and z r is the sensor deployment depth;

[0025] Step 4: with the sound source position: and Construct the auxiliary variable matrix G:

[0026]

[0027] The

[0028] The predicted value of the nth sensor D-SR time delay

[0029] Step 5: with the auxiliary variable matrix G, get the weighted auxiliary variable solution:

[0030]

[0031] The weighted matrix

[0032] Select the nearest sensor to the horizontal distance of the sound source, denoted as the jth sensor, and use the sound source depth solving formula to calculate the sound source depth:

[0033]

[0034] wherein represents the horizontal distance between the jth sensor and the sound source

[0035] Thus, the vector The first two elements of the vector are the two-dimensional position of the sound source in the horizontal plane, which is The sound source depth is

[0036] The parameter wherein c(z) is the sound speed of seawater at depth z, z r is the sensor deployment depth.

[0037] The parameter wherein c α and c β respectively represent the average sound speed in the depth z sw to the sound channel axis depth z DSC and z DSC to the deployment depth z r interval of the surface waveguide near the sea surface, and c ref is the average sound speed in the interval from the sea surface to the maximum sound source depth.

[0038] The step is applied to a typical deep-sea reliable sound path environment, with a water depth greater than 4000m.

[0039] The sound source is located at the sea surface, with a depth not less than 10m and not greater than 500m; the sound source signal is a broadband signal with a bandwidth not less than 100Hz.

[0040] The receiving sensors are not collinear in a horizontal plane, and each sensor is arranged at the same depth, the number of sensors is not less than 5, the distance between any two sensors is not less than 2km, and the horizontal distance between the sound source and any sensor is not more than 25km.

[0041] The proposed positioning method is suitable for single hydrophone received signals or sensor array beam output signals.

[0042] Beneficial effects

[0043] The present application proposes a multi-sensor wideband sound source positioning method suitable for deep sea reliable sound path environment, which uses the same sound source D-SR time delay measurement value observed by deep sea large depth multi-sensor to perform three-dimensional positioning of the sound source. The method includes two stages: in the first stage, based on the position, depth, observed D-SR time delay of each sensor and the water sound speed profile information, a matrix and a vector are constructed, which have a linear relationship with the sound source position, the least square method is used to solve this linear relationship, and the estimated result of the two-dimensional position of the sound source (in the horizontal plane) is obtained, based on the two-dimensional position estimation result, the depth solving formula is used to obtain the depth estimation result of the sound source; in the second stage, based on the three-dimensional position of the sound source estimated in the first stage, the D-SR time delay value of each sensor is predicted, then an auxiliary variable matrix is constructed, and a new two-dimensional horizontal position estimation result of the sound source is obtained according to the rule of the auxiliary variable estimator (IVE), and finally the final depth estimation result of the sound source is obtained according to the depth solving formula.

[0044] The beneficial effects of the present application are that: in view of the problems of insufficient array aperture, insufficient clock synchronization accuracy and slow solving speed of the existing multi-sensor sound source positioning method in deep sea practical application, the present application proposes a deep sea multi-sensor wideband sound source three-dimensional positioning fast method based on the direct and sea surface reflection path propagation time delay of the same sound source observed by the multi-sensor in the deep sea reliable sound path environment. Compared with the existing method, the method proposed by the present application does not need to synchronize the clocks of the multi-sensor accurately, and does not need a large-aperture three-dimensional array, and has the advantages of low hardware cost and small actual deployment difficulty. At the same time, the method proposed by the present application solves the three-dimensional coordinates of the sound source through several formulas, and the calculation speed is fast, which can be applied to real-time systems. The basic principle and implementation scheme of the present application have been verified by computer numerical simulation, and the results show that the passive positioning method of the multi-sensor sound source proposed by the present application can realize the fast three-dimensional positioning of the wideband sound source near the deep sea surface. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is the change of sound speed with sea depth in the simulation scene

[0046] Figure 2is the multi-sensor distribution and the position of the sound source in the simulation scene (top view)

[0047] Figure 3 is the time-domain waveform of the received signal of each sensor simulated using the Bellhop sound field model

[0048] Figure 4 is a flow chart of a multi-sensor wideband sound source positioning method suitable for deep-sea reliable sound path environment

[0049] Figure 5 is the autocorrelation output of the received signal of each sensor

[0050] Figure 6 is the positioning result of 100 independent repeated tests. Subgraph (a) is the sound source position estimation result in the horizontal plane, and subgraph (b) is the sound source depth estimation result DETAILED DESCRIPTION

[0051] The present application will be further described in conjunction with embodiments and drawings:

[0052] Compared with existing multi-sensor positioning methods, the method proposed in the present application does not depend on accurate clock synchronization or sound field modeling between sensors, nor does it need a hydrophone array with a large aperture. In theory, each sensor only needs an omnidirectional sound pressure hydrophone to realize three-dimensional positioning of the sound source, which is low in cost in actual application. In addition, the method proposed in the present application uses several formulas to solve the sound source position, does not need to perform optimization algorithm or grid scanning, and has a fast calculation speed, which can be applied to real-time systems.

[0053] The technical solution adopted by the present application to solve the technical problems: a multi-sensor wideband sound source fast positioning method suitable for deep-sea reliable sound path environment, characterized by comprising the following steps:

[0054] Step 1: In a typical deep-sea environment, several sensors below the critical depth are laid to receive the wideband signals emitted by the sound source near the sea surface. The position of the nth sensor is denoted as p n = [x rn ,y rn ] T , the depth is z r , the sampling frequency is f s , and the received signal is x n (m), where n = 1, 2, …, N, N is the number of sensors. For the received signal of each sensor, the D-SR time delay value of the target signal is obtained using autocorrelation, and the autocorrelation output of the nth sensor can be expressed as:

[0055]

[0056] The autocorrelation output R n The peak position of (q) is q n-max The D-SR time delay value observed by the nth sensor is denoted as It can be expressed as Where the superscript "~" indicates that there is a deviation between the observation value and its true value caused by random noise.

[0057] The sound speed profile information of the current sea area is measured, and the sound speed of seawater at depth z is denoted as c(z). A typical deep sea sound speed profile can be divided into three sections: the first section is the surface waveguide near the sea surface, denoted as depth z sw ; the second section is from the surface waveguide to the sound channel axis depth, denoted as sound channel axis depth z DSC ; the third section is from the sound channel axis to the receiving sensor depth. The average sound speed in the intervals z DSC to z r and z sw to z DSC is calculated respectively, denoted as c β and c α .

[0058] Step two: based on the D-SR time delay value observation value of N sensors According to the requirements, the matrix and the vector b are constructed, and the specific method is as follows:

[0059]

[0060] Where

[0061]

[0062] Where x rn and y rn are the 1st and 2nd elements of p n , c ref is the average sound speed in the interval from the sea surface to the maximum sound source depth, κ = 0.72, Q1 and Q2 are parameters related to the sound speed profile, which are calculated by the following formula:

[0063]

[0064] Where c α and c β represent the average sound speed in the intervals z sw to z DSC and z DSC to z r .

[0065] Step three: based on the matrix and the vector b constructed in step two, the two-dimensional position of the sound source is solved using the least square method:

[0066]

[0067] Obtain The first two elements of the vector are the two-dimensional coordinates of the sound source in the horizontal plane, denoted as

[0068] Then, select the nearest sensor to the sound source in the horizontal distance, denoted as the ith sensor, and calculate the sound source depth using the depth solving formula. The sound source depth solving formula is:

[0069]

[0070] wherein represents the horizontal distance between the ith sensor and the sound source.

[0071] Step four: based on the sound source position estimated in step three: and Construct an auxiliary variable matrix G, and the specific construction method is as follows:

[0072]

[0073] wherein

[0074]

[0075] wherein is the predicted value of the nth sensor D-SR delay, calculated by the following formula:

[0076]

[0077] Step five: using the constructed auxiliary variable matrix G, the weighted auxiliary variable solution is obtained according to the following formula:

[0078]

[0079] wherein the weighted matrix can be constructed according to the sound source position obtained in step three, according to the following formula:

[0080]

[0081] Obtain the vector The first two elements of the vector are the two-dimensional position of the sound source in the horizontal plane, denoted as

[0082] Then, select the nearest sensor to the sound source in the horizontal distance, denoted as the jth sensor, and calculate the sound source depth using the sound source depth solving formula. The sound source depth solving formula is:

[0083]

[0084] in This represents the horizontal distance between the j-th sensor and the sound source.

[0085] Through the above steps, the final sound source location estimation result is as follows: and Specific implementation examples:

[0087] 1. Deep-sea waveguide environment, broadband sound source location, and sensor receiving location

[0088] To verify the effectiveness of the method of this invention, a computer simulation experiment was conducted. This embodiment considers a typical deep-sea environment at a depth of 6000m, with the seawater sound velocity profile being a Munk sound velocity profile with a channel axis depth of 1100m and a surface waveguide thickness of 90m, as shown in the attached figure. Figure 1 As shown, the density of seawater is 1.0 g / cm³. 3 The speed of sound in the seabed half-space is 1600 m / s, and the density is 1.5 g / cm³. 3 The seabed compression wave attenuation coefficient is 0.14 dB / λ. The sound source is located at p. s =[7,12] T At a distance of km, the sound source depth is z s =100m. Six sensors are deployed at p1 = [10, 16.5]. T km, p2 = [16.18, 12.00] T km, p3 = [13.82, 4.74] T km, p4 = [6.18, 4.74] T km, p5 = [3.81, 12.00] T km and p6 = [10, 10] T At a distance of km, the sensor deployment depth is z. r =4700m. The sensor distribution and sound source location in the simulation scenario are shown in the attached figure. Figure 2 As shown.

[0089] 2. Sensor receives signals

[0090] In this embodiment, the sound source signal is modeled as a linear frequency modulated signal with a pulse width of 0.5s and a frequency of 100Hz to 1500Hz. The Bellhop sound field model is used to simulate the received signals from six sensors: assuming the amplitude of the sound source signal is 1, each sensor begins acquiring data simultaneously with the emission of the sound source signal, the receiver's power-on time is 30s, and the sampling frequency is f. s =10kHz.

[0091] The simulation method of the received signal is as follows: firstly, for the receiving sensors at different positions, the Bellhop sound field model is used to calculate the arrival time and amplitude of each sound line between the sound source position and the receiving sensor position. Then the channel impulse response is constructed using these sound line arrivals, and the sound source signal is convolved with the channel impulse response in the time domain, so that the sensor received signal can be obtained. Finally, according to the signal-to-noise ratio, noise is added to the simulated received signal. Assuming that the signal-to-noise ratio of each sensor within T R is SNR=-5dB, the above signal simulation operation is sequentially performed on the six sensors, and the received time domain signals of each sensor are as shown in the accompanying Figure 3 .

[0092] 3. A multi-sensor wideband sound source fast positioning method suitable for deep sea reliable sound path environment

[0093] As shown in the accompanying Figure 4 , the specific implementation process of the multi-sensor wideband sound source fast positioning method suitable for deep sea reliable sound path environment is as follows:

[0094] Step one: in a typical deep sea reliable sound path environment, six sensors with a depth of z r =4700m are laid to receive the wideband signals emitted by the sound source near the sea surface. The six sensors are laid at p1=[10, 16.5] T km, p2=[16.18, 12.00] T km, p3=[13.82, 4.74] T km, p4=[6.18, 4.74] T km, p5=[3.81, 12.00] T km and p6=[10, 10] T km. The sampling frequency of the sensor is f s =10kHz. The received signal of the nth sensor is x n (m), and the length is 3×10 5 , where n=1, 2, …, 6. In this embodiment, this process has been simulated by the Bellhop sound field model.

[0095] For the received signal of each sensor, the D-SR time delay value of the target signal is obtained using autocorrelation, and the autocorrelation output of the nth sensor can be expressed as:

[0096]

[0097] Let the peak position of the autocorrelation output R n (q) be q n-max , then the D-SR time delay value observed by the nth sensor is denoted as It can be represented as The autocorrelation outputs of each sensor are shown in the attached figure. Figure 5 As shown, the D-SR delay estimation results are as follows:

[0098] The current sound velocity profile in the ocean area is a typical Munk sound velocity profile, which can be divided into three segments. The first segment is the surface waveguide near the sea surface, denoted by depth z. sw =90m; the second segment is the depth from the surface waveguide to the channel axis, denoted as z. DSC =1100m; the third segment is the depth from the sound channel axis to the placement depth of the receiving sensor. Calculate z separately. DSC To z r and z sw To z DSC The average speed of sound within the interval is denoted as c. β and c α Calculate c ref This represents the average sound speed over the depth range from the sea surface to the maximum sound source. The relevant parameters for the sound speed profile are calculated as follows:

[0099] z sw To z DSC Average speed of sound within the interval: c α =1518.5m / s;

[0100] z DSC To z r Average speed of sound within the interval: c β =1530.7m / s;

[0101] The average sound speed within the range from the sea surface to the maximum sound source depth (300m): c ref =1534.1m / s.

[0102] Step 2: D-SR delay values ​​observed by 6 sensors Constructing a matrix The specific construction method for vector b is as follows:

[0103]

[0104] in

[0105]

[0106] Where x rn and y rn p n The first and second elements, κ = 0.72, and Q1 and Q2 are environmental parameters related to the sound speed profile, calculated by the following formula.

[0107]

[0108] For the Munk sound speed profile considered in this embodiment, Q1 = 4586.1, Q2 = -17.1. The constructed matrix has a dimension of 5 x 4, and the length of vector b is 5.

[0109]

[0110] Step three: based on the matrix and vector b constructed in step two, the two-dimensional position of the sound source is solved using the least square method:

[0111]

[0112] The first two elements of the obtained vector are the two-dimensional coordinates of the sound source in the horizontal plane, denoted as

[0113] Then, the nearest sensor to the sound source in the horizontal direction is selected, which is the i = 5th sensor, and the depth of the sound source is calculated using the depth solving formula of the sound source, which is:

[0114]

[0115] wherein is the horizontal distance between the 5th sensor and the sound source.

[0116] The sound source depth solving result is

[0117] Step four: based on the target position estimation result estimated in step three: and an auxiliary variable matrix G is constructed, and the specific construction method is as follows:

[0118]

[0119] wherein

[0120]

[0121] wherein is the predicted value of the D-SR delay of the nth sensor, which is calculated by the following formula:

[0122]

[0123] For this embodiment, the prediction result of the D-SR delay is: The constructed auxiliary variable matrix has a dimension of 5 x 4.

[0124]

[0125] Step five: using the constructed auxiliary variable matrix G, the weighted auxiliary variable solution is obtained according to the following formula:

[0126]

[0127] The weighted matrix can be constructed according to the target position obtained in step three, according to the following formula:

[0128]

[0129] The first two elements of the vector obtained are the two-dimensional position estimation results of the sound source in the horizontal plane, denoted as

[0130] Then, the nearest sensor to the horizontal distance of the sound source is selected, denoted as the j=5th sensor, and the sound source depth is calculated using the depth solving formula, which is:

[0131]

[0132] Wherein represents the horizontal distance between the 5th sensor and the sound source.

[0133] The sound source depth solving result obtained is:

[0134] Through the above steps, the final sound source position estimation result is: and It can be seen that the method of the present application realizes the three-dimensional positioning of the wideband sound source near the surface of the deep sea better. In a typical deep sea environment, the positioning error in the horizontal plane is 6.17 m, and the depth estimation error is 0.18 m.

[0135] 4. Independent repeated test

[0136] Finally, a multi-sensor wideband sound source fast positioning method suitable for reliable sound path environment in deep sea is used to perform 100 independent repeated simulation tests. The simulation environment and transmission configuration are the same as those in the above embodiment. In each independent repeated test, the D-SR time delay value observed by each sensor is artificially added with Gaussian white noise with a standard deviation of 1 ms, and the 100 independent repeated test results are shown in the attached Figure 6 It can be seen that in the case of D-SR time delay observation noise standard deviation of 1 ms, the positioning method proposed in the present application has an estimation deviation of the two-dimensional sound source position not greater than 250 m, and a depth estimation deviation not greater than 3 m.​

Claims

1. A multi-sensor broadband acoustic source localization method suitable for reliable acoustic path environments in deep sea, characterized in that: Several sensors are deployed below a critical depth to receive broadband acoustic signals emitted by sound sources near the sea surface. The deployment position of the nth sensor is p. n =[x rn ,y rn ] T Deployment depth is z r The sampling frequency is f s The received signal is x n (m), where n = 1, 2, ..., N, N is the number of sensors, and m is the discrete sampling point in the time domain; the multi-sensor broadband sound source localization steps are as follows: Step 1: For the received signal from each sensor, obtain the D-SR delay value of the sound source signal using autocorrelation. The autocorrelation output of the nth sensor is: Autocorrelation output R n (q) has a peak value, and the peak value is located at q. n-max The D-SR delay value observed by the nth sensor is denoted as . Represented as The superscript "~" indicates that there is a deviation between the observed value and its true value caused by random noise. Step 2: Based on the D-SR time delay observations from N sensors Constructing a matrix And vector b: b=[b2,…,b n ,…,b N ] T The Where: x rn and y rn p n The first and second elements, c ref The average sound speed is the distance from the sea surface to the maximum sound source depth. Q1 and Q2 are parameters related to the sound speed profile, and κ = 0.

72. Step 3: Based on the matrix Given vector b, use the least squares method to solve for the two-dimensional location of the sound source. get The first two elements of the vector are the two-dimensional coordinates of the sound source in the horizontal plane, denoted as... Select the sensor that is horizontally closest to the sound source, denoted as the i-th sensor, and calculate the sound source depth using the depth calculation formula: in c(z) represents the horizontal distance between the i-th sensor and the sound source, and c(z) represents the sound speed at depth z. r For sensor deployment depth; Step 4: Based on the location of the sound source: and Construct the auxiliary variable matrix G: The Predicted value of the D-SR delay of the nth sensor Step 5: Using the auxiliary variable matrix G, obtain the weighted auxiliary variable solution: Weighted matrix Select the sensor that is horizontally closest to the sound source, denoted as the j-th sensor, and calculate the sound source depth using the sound source depth calculation formula: in This represents the horizontal distance between the j-th sensor and the sound source. This yields the vector. The first two elements represent the two-dimensional position of the sound source in the horizontal plane. The depth of the sound source is 2. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The parameters Where c(z) is the speed of sound in the seawater at depth z, z r This refers to the sensor deployment depth.

3. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The parameters Where c α and c β The depth z of the surface waveguide near the sea surface are respectively represented by the following: sw To the channel axis depth z DSC and z DSC To deployment depth z r The average speed of sound within the interval, c ref It represents the average sound speed within the range from the sea surface to the depth of the maximum sound source.

4. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The application scenario described is a typical deep-sea reliable acoustic path environment with a sea depth greater than 4000m.

5. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The sound source is located on the sea surface at a depth of not less than 10m and not more than 500m; the sound source signal is a broadband signal with a bandwidth of not less than 100Hz.

6. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The receiving sensors are distributed non-collinearly in the horizontal plane, and each sensor is placed at the same depth. The number of sensors is not less than 5, the distance between any two sensors is not less than 2km, and the horizontal distance between the sound source and any sensor does not exceed 25km.

7. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1 or 6, characterized in that: The acoustic receiving unit of the sensor is an omnidirectional hysterophone or an array containing omnidirectional hysterophones.

8. The multi-sensor broadband acoustic source localization method for reliable acoustic path environments in deep seas according to claim 1, characterized in that: The proposed positioning method is applicable to signals received by a single hydrophone or beam output signals from a sensor array.

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