A method for fast and high-precision estimation of distance and azimuth of deep sea shadow zone target

Abstract

The application relates to a deep-sea shadow zone target distance and azimuth fast high-precision estimation method. First, a large-aperture horizontal array is divided into two sub-arrays with a certain horizontal interval, and target azimuth estimation is performed on array receiving signals of the two sub-arrays; second, based on target azimuth estimation results of the two sub-arrays and geometric relation with the target, the sound line propagation distance of the target is estimated, and the sound line propagation distance is converted into the horizontal distance between the target and the receiving array through a virtual source model; finally, the horizontal distance obtained is utilized to correct the horizontal array system direction-finding error in combination with geometric knowledge. Compared with a traditional two-station direction-finding cross positioning method, the positioning precision of the method is higher. The basic principle and implementation scheme of the method are verified through computer numerical simulation, and the result shows that in a typical deep-sea environment, the method can effectively estimate the distance and azimuth of a near-sea surface target.

Description

Technical Field

[0001] This invention belongs to the fields of marine engineering, underwater acoustic engineering, array signal processing and sonar technology, and relates to a fast and high-precision method for estimating the distance and azimuth of targets in deep-sea shadow areas. It is applicable to the problem of azimuth estimation of near-sea surface targets by deep-sea large-aperture towed linear arrays. Background Technology

[0002] Sonar is the primary means of underwater target information perception. Passive sonar utilizes the target's radiated noise signals for passive detection, location, tracking, and identification, offering high concealment and making it an important tool for underwater target detection. Towed linear array sonar is a typical form of passive detection. It not only keeps the target far from the mother ship, significantly reducing the impact of towed platform noise, but its aperture is also not limited by the ship. Compared to flank array sonar, towed linear arrays can improve the signal-to-noise ratio by increasing the number of hydrophones, and can also reduce the sonar's operating frequency band by increasing the element spacing.

[0003] Due to the axisymmetry of horizontal arrays, it is impossible to distinguish between the horizontal azimuth and vertical elevation angles when estimating target orientation. Therefore, conventional target orientation estimation results are the combined effect of the signal azimuth angle in the horizontal plane and the elevation angle in the vertical plane, and these three factors satisfy certain constraints. For large-aperture horizontal arrays, they are divided into two subarrays with a certain interval, and the target distance can be estimated using the angular difference between the target and each subarray. However, due to the large direction-finding error in the target orientation results of horizontal arrays, the traditional two-station direction-finding cross-positioning method also suffers from significant errors, limiting its application in practical engineering. Based on the sound propagation characteristics and geometric knowledge of the shadow zone, this invention proposes a fast and high-precision estimation method for target distance and orientation in the shadow zone based on a horizontal array. This method improves the positioning accuracy by modifying the traditional two-station direction-finding cross-positioning method. This method is real-time, has a fast calculation speed, and is easy to implement in engineering. Summary of the Invention

[0004] Technical problems to be solved

[0005] To overcome the shortcomings of existing technologies, this invention proposes a fast and high-precision method for estimating the distance and bearing of targets in deep-sea shadow areas, thereby improving the accuracy of bearing estimation for targets in shadow areas.

[0006] Traditional two-station cross-location methods suffer from significant direction-finding errors, resulting in suboptimal positioning performance in shadowed environments. This new method first divides a large-aperture horizontal array into two subarrays with a certain horizontal spacing, estimating the target's azimuth for each subarray's received acoustic signal. Second, based on the target azimuth estimation results from the two subarrays and their geometric relationship with the target, the target's acoustic ray propagation distance is estimated. This distance is then converted into a horizontal distance between the target and the receiving array using a virtual source model. Finally, the obtained horizontal distance is used to correct the direction-finding error of the horizontal array system. Compared to traditional two-station cross-location methods, the proposed method achieves higher positioning accuracy.

[0007] Technical solution

[0008] A method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas, characterized by the following steps:

[0009] Step 1: Divide the N-element horizontal line array into subarrays, where the spacing between elements is d; when dividing the subarrays, the first N1 elements at the head are designated as the first subarray 1, and the last N2 elements are designated as the second subarray 2; θ1 and θ2 are the azimuth angles of the target in the horizontal plane relative to subarray 1 and subarray 2.

[0010] Step 2: Estimate the target azimuth for the received acoustic signals of the two subarrays respectively. First, calculate the beam output power spectrum P(θ) of the two subarrays, and obtain the estimated azimuth angles corresponding to the peak values ​​of the beam output power spectrum P(θ) of the target relative to subarray 1 and subarray 2 respectively. and

[0011]

[0012] Step 3: Based on the triangular relationship between the two subarrays and the target's mirror image with respect to the seabed interface, obtain the propagation path length of the sound rays emitted from the target after reflection from the seabed to subarrays 1 and 2. and They are respectively:

[0013]

[0014] In the formula, L is the interval between the two subarrays, defined as the horizontal distance between the centers of the two subarrays;

[0015] Step 4: Based on the virtual source model, convert the distance of the sound ray propagation path within the shadow area into the horizontal distance between the target and each subarray;

[0016] Length of sound propagation path and Substitute them into the following formulas respectively:

[0017]

[0018] The obtained target is located at horizontal distances R1 and R2 relative to the two subarrays;

[0019] Where: H represents sea depth;

[0020] Step 5: Calculate the target's position coordinates (x, y) in the horizontal plane. s ,y s )for:

[0021]

[0022] Where: (x1, y1) are the position coordinates of the center of the first subarray, (x2, y2) are the position coordinates of the center of the second subarray; a and b are intermediate variables;

[0023] Step 6: Based on the target position coordinates obtained in Step 5, the estimated azimuth of the target relative to each subarray is as follows:

[0024]

[0025] The horizontal line array is a large-aperture uniform horizontal line array.

[0026] The azimuth angles do not take into account the ambiguity of the port and starboard sides, and the starboard direction is defined as 0 to 180°, and the port direction is defined as 0 to -180°.

[0027] The target azimuth estimation method for the array-received acoustic signals of the two subarrays is as follows:

[0028] Calculate the beam output power spectrum

[0029] Where θ is the beam pointing angle, representing θ1 or θ2; P(θ) represents the output power of the beamformer; L is the number of frequency points; and w(f l ,θ) is the frequency point f l The beam weighting vector at the corresponding angle θ, where the superscript H denotes the conjugate transpose; R(f l ) is the frequency point f l The covariance matrix of the received acoustic signal.

[0030] The frequency point f l The beam weighting vector w(f) at the corresponding angle θ l The calculation method for θ is as follows:

[0031]

[0032] Where k = 2πf / c, f is the frequency point f l The corresponding frequency value, where c is the reference speed of sound, indicated by the superscript (·). T This indicates transpose.

[0033] The frequency point fl The covariance matrix R(f) of the received acoustic signal l The calculation method for ) is as follows:

[0034] R(f l )=E[x H (f l )x(f l )]

[0035] Where x(f) l ) represents the array receiving signal at frequency point f l The spectral vector at point , and E[.] represents the expectation.

[0036] The intermediate variables a and b are:

[0037]

[0038] The target depth range is 0–500m, and the signal is single-frequency or broadband.

[0039] The receiving array is located near the sea surface. For a typical deep-sea munk environment, the receiving distance ranges from 6 to 40 km, and the receiving depth ranges from 0 to 500 m.

[0040] An application of a fast and high-precision method for estimating the distance and azimuth of a target in a deep-sea shadow area is characterized by its applicability to conventional beamforming methods and uniform linear arrays, as well as other azimuth estimation methods and non-uniform linear arrays.

[0041] Beneficial effects

[0042] This invention proposes a fast and high-precision method for estimating the distance and bearing of targets in deep-sea shadow areas. It directly provides closed-form solutions for the distance and bearing of targets in shadow areas, with concise calculation formulas and clear physical meanings of the parameters. The proposed method does not rely on complex marine environmental parameters and does not require acoustic field modeling, which greatly saves computational load and is easy to implement quickly in engineering applications.

[0043] The proposed method fully considers and utilizes the acoustic field characteristics of the deep-sea shadow area. First, the large-aperture horizontal array is divided into two subarrays with a certain horizontal spacing, and the target azimuth is estimated for the array received signals of each subarray. Second, based on the target azimuth estimation results of the two subarrays and their geometric relationship with the target, the target acoustic ray propagation distance is estimated, and the acoustic ray propagation distance is converted into a horizontal distance between the target and the receiving array using a virtual source model. Finally, the obtained horizontal distance is used in conjunction with geometric knowledge to correct the direction-finding error of the horizontal array system. Compared with the traditional two-station cross-location method, the proposed method has higher positioning accuracy. The basic principle and implementation scheme of the proposed method have been verified by computer numerical simulation. The results show that in typical deep-sea environments, the proposed method can effectively estimate the distance and azimuth of near-surface targets. In the given typical implementation case, the proposed method (compared to the traditional method) can reduce the distance estimation error from 46.32% to 6.82%, and the azimuth estimation error from 71.67% to 4.97%. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the sound velocity profile in a simulated scene.

[0045] Figure 2 This is a schematic diagram of the cross-positioning of two subarrays.

[0046] (a) Three-dimensional schematic diagram;

[0047] (b) Top view of the scene.

[0048] Figure 3 It is the characteristic sound ray propagation trajectory of the deep-sea shadow area obtained using the ray model.

[0049] Figure 4 This is the output result of the two subarray beams.

[0050] Figure 5 It is the result of the two subarrays being positioned at an intersection in the horizontal plane.

[0051] Figure 6 These are the range estimation results at different target distances (relative to subarray 1, target azimuth 30°, depth 200m, reception depth 200m).

[0052] (a) Comparison of estimated distance and actual distance;

[0053] (b) Distance estimation error.

[0054] Figure 7 These are the azimuth estimation results at different target distances (relative to subarray 1, target azimuth 30°, depth 200m, reception depth 200m).

[0055] (a) Comparison of estimated and actual orientation;

[0056] (b) Azimuth estimation error. Detailed Implementation

[0057] The present invention will now be further described in conjunction with the embodiments and accompanying drawings:

[0058] Traditional two-station cross-location methods suffer from significant direction-finding errors, resulting in suboptimal positioning performance in shadowed environments. This new method first divides a large-aperture horizontal array into two subarrays with a certain horizontal spacing, estimating the target's azimuth for each subarray's received acoustic signal. Second, based on the target azimuth estimation results from the two subarrays and their geometric relationship with the target, the target's acoustic ray propagation distance is estimated. This distance is then converted into a horizontal distance between the target and the receiving array using a virtual source model. Finally, the obtained horizontal distance is used to correct the direction-finding error of the horizontal array system. Compared to traditional two-station cross-location methods, the proposed method achieves higher positioning accuracy.

[0059] The technical solution adopted by the present invention to solve its technical problem is as follows: the receiving array is located near the sea surface, and for a typical deep-sea munk environment, the receiving distance ranges from 6 to 40 km and the receiving depth ranges from 0 to 500 m.

[0060] The target depth range is 0–500 m, and it can be either single-frequency or broadband.

[0061] A fast and high-precision method for estimating the distance and orientation of targets in deep-sea shadow areas is characterized by the following steps:

[0062] Step 1: For an N-element large-aperture uniform horizontal array with an element spacing of d, the array is first divided into subarrays. The first N1 elements at the bow are taken as subarray 1, and the last N2 elements are taken as subarray 2. θ1 and θ2 are defined as the azimuth angles of the target in the horizontal plane relative to subarray 1 and subarray 2, respectively. Ignoring port and starboard ambiguity, the starboard direction is defined as 0–180°, and the port direction as 0–-180°.

[0063] Step 2: Estimate the target's azimuth relative to subarray 1 and subarray 2 by performing target azimuth estimation on the received acoustic signals of the two subarrays respectively. and The target location estimation method is as follows:

[0064]

[0065] Where θ is the beam pointing angle, P(θ) represents the output power of the beamformer, L is the number of frequency points, and w(f l ,θ) is the frequency point f l The beam weighting vector at the corresponding angle θ, where the superscript H denotes the conjugate transpose. Taking subarray 1 as an example, w(fl ,θ) can be represented as,

[0066]

[0067] Where k = 2πf / c, f is the frequency point f l The corresponding frequency value, where c is the reference speed of sound, indicated by the superscript (·). T Indicates transpose. R(f) l ) is the frequency point f l The covariance matrix of the received acoustic signal can be calculated using the following formula:

[0068] R(f l )=E[x H (f l )x(f l (3)

[0069] Where x(f) l ) represents the array receiving signal at frequency point f l The spectral vector at point , and E[.] represents the expectation.

[0070] The azimuth corresponding to the peak value of the beam output power spectrum P(θ) is the estimated azimuth angle of the target:

[0071]

[0072] Step 3: Based on the triangular relationship between the two subarrays and the target's mirror image with respect to the seabed interface, the propagation path length of the sound rays emitted from the target, after reflection from the seabed, to subarrays 1 and 2 can be estimated. and They are respectively:

[0073]

[0074] In the formula, L is the interval between the two subarrays, defined as the horizontal distance between the centers of the two subarrays.

[0075] Step 4: Based on the virtual source model, convert the distance of the sound ray propagation path within the shadow area into the horizontal distance between the target and each subarray. For near-sea targets and receiving horizontal arrays, the influence of depth can be ignored, and the sound ray propagation path length is... and Substituting into the following formulas respectively, the calculated results are the horizontal distances R1 and R2 of the target relative to the two subarrays obtained by the method proposed in this invention:

[0076]

[0077] Where H represents ocean depth.

[0078] Step 5: Assume the center coordinates of the two subarrays are (x1, y1) and (x2, y2) respectively. Then, based on the geometric relationship between the target and the two subarrays, the target's position coordinates in the horizontal plane can be obtained (x1, y1) and (x2, y2). s ,y s )for:

[0079]

[0080] Intermediate variables are defined here:

[0081]

[0082] Step Six: Based on the target position coordinates obtained in Step Five, the estimated azimuth of the target relative to each subarray is as follows:

[0083]

[0084] The specific implementation method is as follows:

[0085] 1. Deep-sea environment configuration

[0086] To verify the effectiveness of the method of this invention, a computer simulation experiment was conducted. This embodiment considers a typical deep-sea environment, a Munk sound velocity profile, and a sea depth of 5000m, as shown in the attached figure. Figure 1 As shown. The sound speed at the sea surface is 1548.5 m / s, the sound channel axis depth is 1100 m, the sound speed at the sound channel axis is 1500 m / s, the critical depth is 4050 m, and the sound speed on the seabed is 1567 m / s. The seabed is modeled as a uniform infinite half-space, with a sound speed of 1600 m / s and a density of 1.6 g / cm³. 3 The attenuation coefficient is 0.2dB / λ.

[0087] 2. A method for estimating the distance and orientation of targets in deep-sea shadow areas.

[0088] The specific implementation process of the deep-sea shadow area target distance and orientation estimation method proposed in this invention is as follows:

[0089] Step 1: The large-aperture horizontal array has 225 elements, the element spacing is d = 4m, and the receiving depth is z. r =200m. Take 100 elements from the head and tail of each subarray as subarray 1 and subarray 2 respectively. The horizontal distance between the centers of the two subarrays, i.e., the subarray spacing L = 500m. Assume the target radiates a broadband signal with a frequency of 100-200Hz and a depth z. s =200m.

[0090] With the first element of the horizontal array as the origin and the array axis as the X-axis, establish the XOY and XOY' coordinate systems respectively, as shown in the attached figure. Figure 2As shown, point O represents the position of subarray 1 with coordinates (x1, y1) as (0, 0), point A represents the position of subarray 2 with coordinates (x2, y2) as (L, 0), and point B is the target with coordinates (x1, y1) as (0, 0). s ,y s Point C is the mirror image of the target with respect to the seabed interface; θ1 and θ2 are the azimuth angles of the target in the horizontal plane, i.e., the XOY plane, relative to subarray 1 and subarray 2, respectively; R1 and R2 are the horizontal distances between the target and subarray 1 and subarray 2, respectively. and These are the solid angles of the target relative to subarray 1 and subarray 2 in the XOY' plane, respectively, i.e., the estimated target azimuth angles of the two subarrays. and These are the straight-line distances between the mirror target and subarrays 1 and 2, respectively, which represent the path length of the sound rays emitted from point B after refraction through water and reflection from the seabed and sea surface to the receiving point.

[0091] Ignoring port and starboard ambiguity, we define the starboard direction as 0–180° and the port direction as 0–-180°. Assume that at time t, the horizontal distances between the target and subarrays 1 and 2 are R1 = 10 km and R2 = 10.44 km respectively, and the true azimuth angles relative to subarrays 1 and 2 are θ1 = 30° and θ2 = 28.63° respectively. At this time, the target's true position coordinates (x...) s ,y s The distance is (-8.66, 5) km, and it is located on the starboard side of the array. The array received signals of the two subarrays are obtained. The propagation trajectories of four primary seabed reflection characteristic acoustic rays received by the first element of subarray 1 under this transceiver configuration are obtained by simulation using the Bellhop ray model, as shown in the attached figure. Figure 3 As shown, the sound field in the sound shadow zone is mainly contributed by primary seabed reflected waves. Secondary and subsequent seabed reflected waves have significant energy attenuation due to the numerous reflections at the interface, and therefore their impact on the sound field is negligible. In this case, sound rays can be approximated as straight-line propagation after reflection from the sea surface and seabed.

[0092] Step 2: Estimate the target's azimuth relative to subarray 1 and subarray 2 by performing target azimuth estimation on the received acoustic signals of the two subarrays respectively. and The target location estimation method is as follows:

[0093]

[0094] Where θ is the beam pointing angle, P(θ) represents the output power of the beamformer, L is the number of frequency points, and w(f l ,θ) is the frequency point f l The beam weighting vector at the corresponding angle θ, where the superscript H denotes the conjugate transpose. Taking subarray 1 as an example, the weighting vector w(f) l,θ) can be represented as,

[0095]

[0096] Where k = 2πf / c, f is the frequency point f l The corresponding frequency value, where c is the reference speed of sound, indicated by the superscript (·). T This indicates transpose.

[0097] R(f l ) is the frequency point f l The covariance matrix of the received acoustic signal can be calculated using the following formula.

[0098] R(f l )=E[x H (f l )x(f l (12)

[0099] Where x(f) l ) represents the array receiving signal at frequency point f l The spectral vector at point , and E[.] represents the expectation.

[0100] The azimuth corresponding to the peak value of the beam output power spectrum P(θ) is the estimated azimuth angle of the target.

[0101]

[0102] The output results of the two subarray beams calculated using the above method are shown in the appendix. Figure 4 As shown, the peak azimuth of the beam output can be obtained as follows: and At this point, the target's true location is assumed to be at 51.5° in subarray 1 and at 50° in subarray 2.

[0103] Step 3: Based on the triangular relationship between the two subarrays and the target's mirror image with respect to the seabed interface, the path length of the sound rays emitted from the target, after reflection from the seabed, to each subarray can be estimated, i.e., the lengths of line segments OC and AC. and They are respectively,

[0104]

[0105] In the formula, L is the spacing between the two subarrays, which is 500m in this implementation. The target azimuth estimation angles obtained from each subarray are then... and Substituting the subarray spacing L into equation (12) yields...

[0106] Step 4: Based on the virtual source model, convert the distance of the sound ray propagation path within the shadow area into the horizontal distance between the target and each subarray. For near-sea surface targets and receiving horizontal arrays, the influence of depth can be ignored, and the sound ray propagation path length can be converted into... and Substituting these values ​​into the following formulas, the calculated results are the horizontal distances R1 and R2 of the target relative to the two subarrays obtained by the method proposed in this invention.

[0107]

[0108] In the formula, H represents the ocean depth. and Substituting into equation (13), we can obtain the estimated horizontal distances of the target relative to subarray 1 and subarray 2 as R1 = 10.68 km and R2 = 11.11 km, respectively.

[0109] Step 5: Assume the center coordinates of the two subarrays are (x1, y1) and (x2, y2) respectively. Then, based on the geometric relationship between the target and the two subarrays, the target's position coordinates in the horizontal plane can be obtained (x1, y1) and (x2, y2). s ,y s )for,

[0110]

[0111] Among them, intermediate variables are defined.

[0112]

[0113] In this implementation, the target is located on the starboard side of the horizontal array. Therefore, by substituting the parameters (x1,y1) and (x2,y2) and the horizontal distances R1 and R2 of the target relative to the two subarrays obtained in step four into equations (14) and (15), we can obtain x. s = -9.11km, y s = 5.58km. That is, the target coordinates estimated by this invention are (-9.11, 5.58)km, and the positioning results are attached. Figure 5 As shown.

[0114] Step Six: Based on the target position coordinates obtained in Step Five, the estimated azimuth of the target relative to each subarray is as follows:

[0115]

[0116] The horizontal azimuth angles of the target relative to each subarray can be calculated using the above formula as θ1 = 31.49° and θ2 = 30.14°, with azimuth estimation errors of 4.97% and 5.28%, respectively. The estimation result for conventional beamforming before correction is... and The errors were 71.67% and 74.66% respectively, which shows that the present invention effectively improves the accuracy of target orientation estimation.

[0117] When estimating target distance using the traditional two-station cross-location method, it is assumed that the target orientation estimation result is error-free, and the distance estimation results are as follows: The distance estimation errors relative to each subarray were 46.32% and 43.24%, respectively. However, after correcting the distance estimation results to R1 = 10.68 km and R2 = 11.11 km based on the sound propagation characteristics of the shadow area, the distance estimation errors decreased to 6.82% and 6.47%.

[0118] Figure 6 The distance estimation results and errors (relative to subarray 1) of the proposed cross-positioning method are presented for different target distances, with a target azimuth of 30°, a target depth of 200m, and a receiving depth of 200m. Figure 7 The figure shows the azimuth estimation results and errors at different target distances, and compares them with the positioning results of traditional methods. The average distance estimation error of the proposed method at different target distances is 6.05%, and the average azimuth estimation error is 3.14%. Furthermore, as can be seen from the figure, the distance and azimuth estimation accuracy of the proposed method is significantly improved compared to traditional methods, especially at close range in the shadow area, which verifies the effectiveness of the proposed method.

Claims

1. A method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas, characterized in that... The steps are as follows: Step 1: For N The horizontal array is divided into subarrays, where the spacing between array elements is... d When dividing the subarray, the head part is in front. N One array element serves as the first subarray 1, at the tail. N Two array elements form the second subarray 2; θ 1 and θ 2 represents the azimuth angle of the target relative to subarray 1 and subarray 2 in the horizontal plane; Step 2: Estimate the target azimuth of the received acoustic signals from the two subarrays separately. First, calculate the beam output power spectrum of the two subarrays. P ( θ The beam output power spectrum of the target relative to subarray 1 and subarray 2 is obtained. P ( θ The estimated azimuth angles corresponding to the peak values ​​are respectively and : ； Step 3: Based on the triangular relationship between the two subarrays and the target's mirror image with respect to the seabed interface, obtain the propagation path length of the sound rays emitted from the target after reflection from the seabed to subarrays 1 and 2. and They are respectively: In the formula, L The interval between the two subarrays is defined as the horizontal distance between the centers of the two subarrays. Step 4: Based on the virtual source model, convert the distance of the sound ray propagation path within the shadow area into the horizontal distance between the target and each subarray; Length of sound propagation path and Substitute them into the following formulas respectively: The obtained target horizontal distance relative to the two subarrays R 1 and R 2; in: H Indicates sea depth; Step 5: Calculate the target's position coordinates in the horizontal plane. x s , y s )for: in:( x 1, y 1) represents the coordinates of the center of the first subarray. x 2, y 2) These are the coordinates of the center of the second subarray; and As an intermediate variable; Step 6: Based on the target position coordinates obtained in Step 5, the estimated azimuth of the target relative to each subarray is as follows: 。 2. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The horizontal line array is a large-aperture uniform horizontal line array.

3. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The azimuth angles do not take into account the ambiguity of the port and starboard sides, and the starboard direction is defined as 0~180°, and the port direction is defined as 0~-180°.

4. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The target azimuth estimation method for the array-received acoustic signals of the two subarrays is as follows: Calculate the beam output power spectrum in, θ Beam pointing angle; P ( θ The ) represents the output power of the beamformer. M For frequency points, w ( f m , θ (Frequency point) f m Corresponding angle θ The beam weighting vector, where the superscript H denotes the conjugate transpose; R ( f m (Frequency point) f m The covariance matrix of the received acoustic signal.

5. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 4, characterized in that: The frequency point f m Corresponding angle θ Beam weighting vector w ( f m , θ The calculation method for ) is as follows: in, , f For frequency point f m The corresponding frequency value, c For reference to the speed of sound, use the superscript (·). T Indicates transpose. d The distance between array elements.

6. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 4, characterized in that: The frequency point f m The covariance matrix of the received acoustic signal R ( f m The calculation method for ) is as follows: in, x ( f m () represents the frequency point of the array received signal. f m The spectral vector at point , and E[.] represents the expectation.

7. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The intermediate variable and for: 。 8. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The target depth range is 0~500m, and the signal is single-frequency or broadband.

9. The method for rapid and high-precision estimation of target distance and orientation in deep-sea shadow areas according to claim 1, characterized in that: The receiving array is located near the sea surface. For a typical deep-sea munk environment, the receiving distance ranges from 6 to 40 km, and the receiving depth ranges from 0 to 500 m.

Images