A deep-sea shadow target positioning estimation method suitable for underwater mobile platform observation

Abstract

The present invention provides a method for positioning and estimating a target in a deep-sea shadow area suitable for underwater mobile platform observation, which belongs to the field of deep-sea positioning and measurement technology. The method comprises first using an M-element horizontal array to receive a narrowband signal of a near-sea surface sound source in a deep-sea shadow area, and obtaining an initial target wave arrival angle estimate through conventional beam forming. The horizontal array is then rotated clockwise T times, the heading angle difference of each rotation is recorded and a signal is received, and beam forming is performed on the received signal after rotation to obtain a target wave arrival angle estimate. Based on the wave arrival angle estimate and the heading angle difference before and after the rotation, a cost function is constructed and an optimal solution is found to obtain a horizontal azimuth angle and a vertical pitch angle estimate. Finally, the vertical pitch angle estimate is substituted into a sound source distance estimation formula to calculate a sound source distance estimate, thereby achieving three-dimensional positioning. The method solves the problem that the sound source azimuth and distance estimation of an underwater mobile platform in a deep-sea environment in the prior art requires a large-aperture horizontal array or large-bandwidth information, which is difficult to apply in practice.

Description

Technical Field

[0001] The present invention belongs to deep sea positioning technology, and in particular, relates to a deep sea shadow area target positioning estimation method suitable for underwater mobile platform observation. Background Art

[0002] In deep-sea environments, target position and distance are key information for underwater target situational awareness. Accurate, robust, and fast estimation of target position and distance is a research hotspot in deep-sea acoustic detection. At present, underwater mobile platforms such as autonomous underwater vehicles, underwater gliders, and other underwater equipment have ushered in unprecedented development opportunities. Underwater early warning detection can be achieved by combining the signals received by the horizontal array carried on the underwater mobile platform with signal processing methods. Traditional deep-sea sound source positioning methods are matching field positioning processing, or methods based on angle or time delay characteristics. Such methods require large-aperture horizontal arrays or large signal bandwidth conditions. However, in deep-sea shadow areas, due to the low signal-to-noise ratio environment, it is difficult to observe the continuous broadband spectrum of the target and the installation space of the underwater mobile platform observation equipment is limited. The positioning performance of traditional methods is seriously reduced or even fails.

[0003] The invention patent with publication number CN118259233A proposes a deep-sea shadow target positioning method that takes into account the horizontal array direction finding error. The horizontal array is divided into two sub-arrays, and the target azimuth information estimated by the sub-arrays is used to estimate the distance of the sound source. This method requires a horizontal array with a larger aperture so that different target azimuth information can be observed in the dual sub-arrays, but the underwater observation platform has a small array space, which limits the performance of this method.

[0004] The paper "Target Azimuth Estimation and Correction Method Based on Interference Fringe" proposed a method for estimating the azimuth and distance of a horizontal array, but this method requires large target broadband continuous spectrum information in order to accurately estimate the multipath time delay. However, due to the low signal-to-noise ratio in the deep sea shadow area, the target broadband information is often submerged by noise, and the performance of this method is limited.

[0005] That is to say, the existing technology for estimating the direction and distance of the sound source of an underwater mobile platform in a deep-sea environment requires a large-aperture horizontal array or wide-bandwidth information, which is difficult to apply under actual conditions. Summary of the invention

[0006] In view of this, the present invention provides a deep-sea shadow area target positioning estimation method suitable for underwater mobile platform observation, which solves the technical problem that the prior art requires a large-aperture horizontal array or wide-bandwidth information and is difficult to apply under actual conditions.

[0007] The present invention is implemented in this way. The present invention provides a deep-sea shadow area target positioning estimation method suitable for underwater mobile platform observation, comprising the following steps:

[0008] S10, using an M-element horizontal array near the sea surface to receive narrowband signals emitted by the near-sea surface sound source in the deep-sea shadow area;

[0009] S20, performing conventional beamforming on the received signals of the M-element horizontal array to obtain a target angle of arrival estimate, which is recorded as the target angle of arrival estimate before the horizontal array is rotated;

[0010] S30, rotating the M-element horizontal array in a clockwise direction T times, recording the heading angle difference after each rotation relative to the horizontal array before rotation, and establishing a rotating heading angle difference array; and simultaneously receiving a narrowband signal emitted by a near-sea surface sound source in a deep-sea shadow area;

[0011] S40, performing conventional beamforming on the M-element horizontal array receiving signal after each rotation to obtain a target angle of arrival estimation value, and establishing an array of rotating target angle of arrival estimation values;

[0012] S50, according to the obtained target arrival angle estimation value before the horizontal array rotation, the heading angle difference array during rotation and the target arrival angle estimation value array during rotation, the cost function is brought into search for the horizontal azimuth angle estimation value and the vertical pitch angle estimation value which minimize the constructed cost function, and the target azimuth estimation value is obtained.

[0013] S60, using the estimated value of the vertical pitch angle, substituting it into a sound source distance estimation formula to obtain an estimated value of the sound source distance.

[0014] Among them, step S10, using the offshore platform The horizontal array receives narrowband signals from sound sources near the sea surface in the acoustic shadow area. The horizontal distance of the sound source is , the true position is The sound source radiates a narrowband signal, and the available frequency is [ f 1 , f 2 , … , f F ] , is the frequency point number used. The horizontal array receiving signal is x a ( f i ) = [ x a 1 ( f i ) , x a 2 ( f i ) , … , x a M ( f i ) ] H ,in, The frequency received by the mth array element before horizontal array rotation is signal.

[0015] In step S20, conventional beamforming is performed on the horizontal array received signal before rotation to obtain the target arrival angle estimation value before horizontal array rotation. The specific operation process is as follows:

[0016] Divide the space [0,180]° into N grids, denoted as i = [ i 1 ,..., i N ] , where 0° and 180° are the end-fire directions of the array, and 90° is the transverse direction. The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival before rotation is:

[0017] ;

[0018] in,

[0019] ;

[0020] is the estimated spectrum of the angle of arrival before rotation, where R a ( f i ) = E [ x a ( f i ) x a H ( f i ) ] The frequency of the received signal before the array rotation is The covariance matrix of a ( f i , i n ) = [ 1 , e − j 2 π f i d cos i n , … , e − j ( M − 1 ) 2 π f i d cos i n ] H , represents the horizontal array element spacing, [ · ] H represents transpose, E [ · ] Expressing expectation.

[0021] In step S30, the M-element horizontal array is rotated clockwise T times, and the heading angle difference after each rotation relative to the horizontal array before rotation is recorded. , establish the heading angle difference array in rotation i t = [ i turn ， 1 , i turn ， 2 , … , i turn ， T ] ; At the same time, the narrowband signal emitted by the near-sea surface sound source in the deep-sea shadow area is received. The received signal after the horizontal array rotates for the tth time is recorded as x b, t ( f i ) = [ x t 1 ( f i ) , x t 2 ( f i ) , … , x t M ( f i ) ] H ,in, The frequency received by the mth array element after the tth rotation is signal.

[0022] In step S40, conventional beamforming is performed on the M-element horizontal array receiving signal after each rotation to obtain the target angle of arrival estimation value and establish the rotating target angle of arrival estimation value array. The specific operation process is as follows:

[0023] The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival after the tth rotation is:

[0024] ;

[0025] in;

[0026] ;

[0027] is the estimated spectrum of the angle of arrival after the tth rotation, where R b , t ( f i ) = E [ x b , t ( f i ) x b , t H ( f i ) ] The received signal frequency after the array is rotated for the tth time is The covariance matrix of .

[0028] Based on this, an array of estimated values ​​of the target arrival angle in rotation is established. i ^ b = [ i ^ b , 1 , i ^ b , 2 , … , i ^ b , T ] ;

[0029] In step S50, the target arrival angle estimation value before the horizontal array rotation is obtained , the heading angle difference array in rotation i t = [ i turn ， 1 , i turn ， 2 , … , i turn ， T ] and an array of target angle of arrival estimates in rotation i ^ b = [ i ^ b , 1 , i ^ b , 2 , … , i ^ b , T ] Substitute the cost function into the target position estimation value and the vertical pitch angle estimation value to minimize the cost function. The specific operation process is as follows:

[0030] The horizontal azimuth angle space [0,180]° to be estimated is divided into P discrete grids, denoted as α p = [ α 1 ,..., α P ] , the vertical pitch angle space [0,180]° to be estimated is divided into Q discrete grids, denoted as β q = [ β 1 ,..., β Q ] , construct the following cost function:

[0031] ;

[0032] Find the horizontal azimuth estimate that minimizes the constructed cost function and the vertical pitch angle estimate :

[0033] [ α ^ p , β ^ q ] = argmin α p ∈ α p , β q ∈ β q E ( α p , β q ) ;

[0034] This gives the estimated target position:

[0035] .

[0036] In step S60, the vertical pitch angle estimation value is , substitute into the sound source distance estimation formula to get the estimated value of the sound source distance. The specific operation process is as follows:

[0037] The vertical pitch angle estimate , into the sound source distance estimation formula:

[0038] ;

[0039] That is, the target distance estimate is obtained ,in, For the depth of the sea.

[0040] The present invention effectively solves the technical limitation of the prior art that a large aperture horizontal array or a large bandwidth signal is required. The method only requires a small aperture horizontal array and a narrowband signal to realize the azimuth and distance estimation of the target, which significantly improves the feasibility under practical application conditions. Specifically, the present invention obtains the target wave arrival angle information at different rotation angles by performing multiple rotation observations on the horizontal array, and constructs an optimization cost function in combination with the heading angle difference to realize the joint estimation of the horizontal azimuth angle and the vertical pitch angle. This method cleverly utilizes the spatial diversity gain brought by the platform rotation, overcomes the performance limitation of the traditional matching field positioning method under small aperture conditions, and avoids the dependence of the delay feature-based method on broadband signals. At the same time, the method fully considers the characteristics of the low signal-to-noise ratio environment in the deep sea shadow area, and improves the robustness of the algorithm by processing only narrowband signals. Through the vertical pitch angle estimation and simple geometric relationship, the method can also obtain the estimated value of the target distance, thereby realizing the full-dimensional positioning of the target. This innovative technical solution not only reduces the hardware requirements for the observation equipment, improves the practicality on the underwater mobile platform, but also maintains good positioning performance in complex deep-sea environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The main steps of the present invention are as follows;

[0042] Figure 2 Set up the environment for the Kraken sound field model simulation parameters;

[0043] Figure 3 This is a schematic diagram of the horizontal array maneuvering of the present invention;

[0044] Figure 4 is the estimated spectrum of the angle of arrival before the horizontal array is rotated;

[0045] Figure 5 is the estimated spectrum of the angle of arrival after the first rotation of the horizontal array;

[0046] Figure 6 It is the estimated spectrum of the angle of arrival after the second rotation of the horizontal array. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0048] In order to verify the effectiveness of the method of the present invention, a computer simulation experiment was performed. This simulation experiment considers a typical deep sea environment with a sea depth of 5000m and a seawater sound velocity profile as shown in the attached figure. Figure 2 As shown, the density of seawater is ; The speed of sound in the seabed half space is , the density is , the attenuation coefficient of the seafloor compression wave is The number of horizontal array elements is M=60, the array element spacing is d=1m, the sound source depth is 50m, and the receiving array depth is 100m. The number of frequency points used , the frequencies are 500, 550 and 580 Hz, and the horizontal distance of the sound source is in the deep sea shadow area at R = 20 km. The true direction of the sound source is =40°, the horizontal array clockwise maneuver times T=2, the heading angle difference is ,like Figure 3 Kraken sound field software is used to calculate the received signal of each element in the horizontal array.

[0049] Step 1) Use the 60-element horizontal array on the offshore platform to receive the narrowband signal from the sound source near the offshore surface in the acoustic shadow area. The horizontal distance of the sound source is 20 km, and the true azimuth is 40°. The sound source radiates a narrowband signal, and the available frequency points are [ 500 , 550 , 580 ] Hz, the number of frequencies used The horizontal array receiving signal is recorded as x a ( f i ) = [ x a 1 ( f i ) , x a 2 ( f i ) , … , x a M ( f i ) ] H ,in, The frequency received by the mth array element before horizontal array rotation is In this embodiment, this step has been completed by simulating the Kraken sound field model.

[0050] Step 2) Perform conventional beamforming on the horizontal array received signal before rotation to obtain the target arrival angle estimation value before horizontal array rotation. The specific operation process is as follows:

[0051] The space [0,180]° is divided into 1801 grids, denoted as i = [ i 1 ,..., i 1801 ] , where 0° and 180° are the end-fire directions of the array, and 90° is the transverse direction. The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival before rotation is:

[0052] .

[0053] in,

[0054] .

[0055] is the estimated spectrum of the angle of arrival before rotation, such as Figure 3 As shown. Among them, R a ( f i ) = E [ x a ( f i ) x a H ( f i ) ] The frequency of the received signal before the array rotation is The covariance matrix of a ( f i , i n ) = [ 1 , e − j 2 π f i d cos i n , … , e − j ( M − 1 ) 2 π f i d cos i n ] H , represents the horizontal array element spacing, [ · ] H represents transpose, E [ · ] Expressing expectation.

[0056] Step 3) Rotate the 60-element horizontal array clockwise twice, and record the heading angle difference after each rotation relative to the horizontal array before rotation. , establish the heading angle difference array in rotation i t = [ 20 o , 40 o ] ; At the same time, the narrowband signal emitted by the near-sea surface sound source in the deep-sea shadow area is received. The received signal after the horizontal array rotates for the tth time is recorded as x b, t ( f i ) = [ x t 1 ( f i ) , x t 2 ( f i ) , … , x t M ( f i ) ] H ,in, The frequency received by the mth array element after the tth rotation is signal.

[0057] Step 4) Perform conventional beamforming on the received signals of the 60-element horizontal array after each rotation to obtain the target arrival angle estimation value and establish the target arrival angle estimation value array in rotation. The specific operation process is as follows:

[0058] The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival after the tth rotation is:

[0059] .

[0060] in

[0061] .

[0062] is the estimated spectrum of the angle of arrival after the tth rotation, where R b , t ( f i ) = E [ x b , t ( f i ) x b , t H ( f i ) ] The received signal frequency after the array is rotated for the tth time is The covariance matrix of . Figure 5 is the estimated spectrum of the angle of arrival after the first rotation, Figure 6 is the estimated spectrum of the angle of arrival after the second rotation.

[0063] Based on this, an array of estimated values ​​of the target arrival angle in rotation is established. i ^ b = [ 63 . 6 o , 81 . 2 o ] .

[0064] Step 5) Based on the estimated target arrival angle before horizontal array rotation , the heading angle difference array in rotation i t = [ 20 o , 40 o ] and an array of target angle of arrival estimates in rotation i ^ b = [ 63 . 6 o , 81 . 2 o ] Substitute the cost function into the target position estimation value and the vertical pitch angle estimation value to minimize the cost function. The specific operation process is as follows:

[0065] The horizontal azimuth angle space [0,180]° to be estimated is divided into 1801 discrete grids, denoted as α p = [ α 1 ,..., α P ] , the vertical pitch angle space [0,180]° to be estimated is divided into Q discrete grids, denoted as β q = [ β 1 ,..., β Q ] , construct the following cost function:

[0066] ;

[0067] Find the horizontal azimuth estimate that minimizes the constructed cost function and the vertical pitch angle estimate :

[0068] [ α ^ p = 40 . 1 o , β ^ q = 27 . 1 o ] = argmin α p ∈ α p , β q ∈ β q E ( α p , β q ) .

[0069] This gives the estimated target position:

[0070] .

[0071] Step 6) Convert the vertical pitch angle estimate , substitute into the sound source distance estimation formula to get the estimated value of the sound source distance. The specific operation process is as follows:

[0072] The vertical pitch angle estimate , into the sound source distance estimation formula:

[0073] .

[0074] The target distance estimate can be obtained .in, For the depth of the sea.

[0075] After completing the above steps, the final estimated value of the sound source direction is , the error is , the distance estimation result is 19.5km, with an error of 0.5km.

[0076] In order to better understand and implement the present invention, an embodiment of a specific application scenario of the present invention is provided below: a certain unit conducts underwater target detection tests in the deep water area of ​​the western Pacific Ocean. The average water depth of the test sea area is about 4,000 meters, and the sound velocity profile shows typical deep-sea characteristics. The experimental platform is a certain type of scientific research ship, on which a 16-element uniform linear array system is installed to receive narrowband signals emitted by the target. The experiment aims to verify the effectiveness and practicality of the joint estimation method of passive azimuth and distance of deep-sea shadow zone targets proposed in the present invention.

[0077] Experimental conditions and parameter settings

[0078] Experimental environment parameters:

[0079] Test area: a deep water area in the western Pacific Ocean.

[0080] Average water depth: 4000 meters.

[0081] Sea condition: Level 3, the sea is relatively calm.

[0082] Water temperature: 25°C on the surface, thermocline at a depth of about 100 meters.

[0083] Environmental noise level: Background noise is about 45dB.

[0084] Receiving system parameters:

[0085] Linear array parameters:

[0086] Number of array elements (M): 16.

[0087] Array element spacing (d): 1.5 meters.

[0088] Working frequency band: 300Hz to 500Hz.

[0089] Sampling rate: 12kHz.

[0090] Array element sensitivity: -180dB.

[0091] Signal characteristics:

[0092] Target radiation signal: narrowband signal.

[0093] Available frequency points (F): 5.

[0094] Frequency distribution: [300Hz, 350Hz, 400Hz, 450Hz, 500Hz].

[0095] Signal-to-noise ratio: about 3dB.

[0096] Experimental control parameters:

[0097] Number of horizontal array rotations (T): 6 times.

[0098] Each rotation angle: fixed 10 degrees.

[0099] Signal acquisition time: 20 seconds per location.

[0100] Specific implementation steps

[0101] Step 1: Signal Reception

[0102] The experimental platform first deploys a 16-element horizontal array at the initial position. The receiving system uses a digital receiving unit to condition and sample the received acoustic signal. The system collects data at 5 preset frequency points, and the received signal at each frequency point is recorded as:

[0103] ;

[0104] The value of i ranges from 1 to 5, corresponding to the above five frequency points. After preliminary signal processing, the complex data sequence of each array element at each frequency point is obtained.

[0105] Step 2: Initial Angle of Arrival Estimation

[0106] Before beamforming, the search space [0,180] degrees is divided into 1801 grid points with a grid interval of 0.1 degrees. The conventional beamforming algorithm is used to process the data of each frequency point separately. The specific steps are as follows:

[0107] Calculate the covariance matrix of the received signal at each frequency point:

[0108] Get the covariance matrix of 5 frequency points .

[0109] To perform beamforming:

[0110] Construct a direction vector.

[0111] The beam output is calculated for each of the 1801 direction points.

[0112] The average is performed at 5 frequency points.

[0113] After processing, the initial angle of arrival estimate is obtained Spend.

[0114] Step 3: Array rotation and data acquisition

[0115] According to the preset plan, the horizontal array is rotated clockwise 6 times, each time by 10 degrees. The specific rotation process is recorded as shown in Table 1 below:

[0116] Table 1 Rotation process record

[0117]

[0118] At each rotation position, 20 seconds of data are collected, and the collection process is the same as the initial position. The received signal obtained at each position is recorded as:

[0119] ;

[0120] Where t represents the number of rotations (1 to 6), and i represents the frequency point number (1 to 5).

[0121] Step 4: Estimation of the angle of arrival after rotation

[0122] For the data of each rotation position, the same processing method as the initial position is used to estimate the angle of arrival. The specific results are shown in Table 2 below:

[0123] Table 2 Rotation data table

[0124]

[0125] Step 5: Position estimation

[0126] When making the final azimuth estimation, the horizontal azimuth angle space [0,180] degrees to be estimated is divided into 1801 grid points (with an interval of 0.1 degrees), and the vertical pitch angle space [0,180] degrees is also divided into 1801 grid points. Then the cost function is constructed and optimized. The specific steps are as follows:

[0127] Construct the grid search space:

[0128] Horizontal azimuth grid points: Spend.

[0129] Vertical pitch angle grid points: Spend.

[0130] Calculate the cost function:

[0131] Substitute the initial angle of arrival estimate, the angle of arrival estimate of the six rotation positions, and the corresponding heading angle difference into the cost function.

[0132] All possible combinations of horizontal azimuth angle and vertical pitch angle are traversed and calculated.

[0133] Find the optimal solution:

[0134] A grid search is performed to find the parameter combination that minimizes the cost function.

[0135] Get the final horizontal azimuth estimate: Spend.

[0136] Get the vertical pitch angle estimate: Spend.

[0137] Step 6: Distance Estimation

[0138] Substitute the obtained vertical pitch angle estimate into the distance estimation formula:

[0139] ;

[0140] Where H is the sea depth of 4000 meters, Spend.

[0141] The estimated target distance is calculated as follows: km.

[0142] Experimental results analysis

[0143] Estimation accuracy analysis:

[0144] Azimuth estimation error: By comparing with the true value, the horizontal azimuth estimation error is less than 0.5 degrees.

[0145] Distance estimation error: The relative error is about 7%, which has good engineering value in practical applications.

[0146] Algorithm performance analysis:

[0147] Implementation effect: This example fully verifies the feasibility and effectiveness of this method in the actual marine environment, which is mainly reflected in the following aspects: the horizontal azimuth estimation accuracy is better than 0.5 degrees; the relative error of target distance estimation is less than 10%; and it meets the actual engineering application needs.

[0148] Conclusion: This embodiment demonstrates the specific application of a method for joint estimation of passive azimuth and distance of deep-sea shadow targets based on horizontal array rotation. Through experimental verification in the actual waters of the South China Sea, this method has shown good performance and practical value. The experimental results show that this method can effectively solve the problem of deep-sea shadow target positioning and provide a new technical approach for underwater target detection. This method has the characteristics of low equipment requirements, simple implementation, and high accuracy, and is suitable for promotion and application in actual engineering.

[0149] Additional Notes

[0150] Data processing instructions:

[0151] All data processing uses double-precision floating-point operations.

[0152] The signal is processed using Hanning window.

[0153] Environmental conditions description:

[0154] The weather was fine during the experiment.

[0155] Wind speed 3 to 4.

[0156] Seawater temperature and sound speed profiles remain relatively stable.

[0157] Note:

[0158] The array must remain stable during rotation.

[0159] Avoid large shaking of the hull during data collection.

[0160] The system clocks need to be synchronized.

[0161] Perform system calibration regularly.

[0162] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for estimating the location of a target in a deep-sea shadow area suitable for underwater mobile platform observation, characterized in that: The following steps are involved: S10, using an M-element horizontal array near the sea surface to receive narrowband signals emitted by the near-sea surface sound source in the deep-sea shadow area; S20, performing conventional beamforming on the received signals of the M-element horizontal array to obtain a target angle of arrival estimate, which is recorded as the target angle of arrival estimate before the horizontal array is rotated; S30, rotating the M-element horizontal array in a clockwise direction T times, recording the heading angle difference after each rotation relative to the horizontal array before rotation, and establishing a rotating heading angle difference array; and simultaneously receiving a narrowband signal emitted by a near-sea surface sound source in a deep-sea shadow area; S40, performing conventional beamforming on the M-element horizontal array receiving signal after each rotation to obtain a target angle of arrival estimation value, and establishing an array of rotating target angle of arrival estimation values; S50, according to the obtained target arrival angle estimation value before the horizontal array rotation, the heading angle difference array during rotation, and the target arrival angle estimation value array during rotation, the cost function is brought into search for the horizontal azimuth angle estimation value and the vertical pitch angle estimation value which minimize the constructed cost function, and the target azimuth estimation value is obtained; S60, using the estimated value of the vertical pitch angle, substituting it into a sound source distance estimation formula to obtain an estimated value of the sound source distance; Wherein, in step S10, the horizontal distance of the sound source is , the true position is ; The sound source radiates a narrowband signal, and the frequency point used is , is the frequency point number used; the horizontal array receiving signal is ,in, The frequency received by the mth array element before horizontal array rotation is signal; The specific operation process of step S20 is as follows: Divide the space [0,180]° into N grids, denoted as , where 0° and 180° are the end-fire directions of the array, and 90° is the transverse direction. The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival before rotation is: ； in, ； is the estimated spectrum of the angle of arrival before rotation, where The frequency of the received signal before the array rotation is The covariance matrix of , represents the horizontal array element spacing, represents transpose, Expressing expectation.

2. The method for positioning and estimating a target in a deep-sea shadow area suitable for underwater mobile platform observation according to claim 1, characterized in that: The specific operation process of step S30 is as follows: Rotate the M-element horizontal array clockwise T times, and record the heading angle difference after each rotation relative to the horizontal array before rotation. , establish the heading angle difference array in rotation ; At the same time, the narrowband signal emitted by the near-sea surface sound source in the deep-sea shadow area is received. The received signal after the horizontal array rotates for the tth time is recorded as ,in, The frequency received by the mth array element after the tth rotation is signal.

3. The method for positioning and estimating a target in a deep sea shadow area suitable for underwater mobile platform observation according to claim 2, characterized in that: The specific operation process of step S40 is as follows: The conventional beamforming algorithm is used to estimate the angle of arrival, and the estimated angle of arrival after the tth rotation is: ； in, ； is the estimated spectrum of the angle of arrival after the tth rotation, where The received signal frequency after the array is rotated for the tth time is Covariance matrix of the target; create an array of estimated values ​​of the rotating target angle of arrival .

4. The method for estimating the location of a target in a deep sea shadow area suitable for underwater mobile platform observation according to claim 3, characterized in that: The step S50 specifically comprises: obtaining the target arrival angle estimation value before the horizontal array rotation , the heading angle difference array in rotation and an array of target angle of arrival estimates in rotation Substitute the cost function into the target position estimation value and the vertical pitch angle estimation value to minimize the constructed cost function. The specific operation process of this step is as follows: The horizontal azimuth angle space to be estimated [0,180]° is divided into P discrete grids, denoted as , divide the vertical pitch angle space [0,180]° to be estimated into Q discrete grids, denoted as , construct the following cost function: Find the horizontal azimuth estimate that minimizes the constructed cost function and the vertical pitch angle estimate : ； This gives the estimated target position: 。 5. The method for estimating the location of a target in a deep sea shadow area suitable for underwater mobile platform observation according to claim 4, characterized in that: The step S60 is specifically: The vertical pitch angle estimate , into the sound source distance estimation formula: ； That is, the target distance estimate is obtained ,in, For the depth of the sea.

6. The method for positioning and estimating a target in a deep sea shadow area suitable for underwater mobile platform observation according to any one of claims 1 to 5, characterized in that: The number of horizontal array elements is M=60.

7. The method for estimating the location of a target in a deep sea shadow area suitable for underwater mobile platform observation according to claim 6, characterized in that: The spacing between horizontal array elements is d=1m.

8. The method for estimating the location of a target in a deep sea shadow area suitable for underwater mobile platform observation according to claim 7, characterized in that: The number of clockwise maneuvers of the horizontal array is T=2.

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