An underwater acoustic target azimuth estimation method for a small array

Abstract

The present invention relates to the field of underwater acoustic detection technology, and provides an underwater acoustic target azimuth estimation method for a small array, including: forming an orthogonal structure by using four hydrophones with two pairs perpendicular to each other and the same distance from the intersection point (or reference center), subtracting (or differentiating) the received signals of each pair, then performing spectral estimation on the subtracted (differentiated) signals, and then multiplying their spectra by the conjugate of the reference center signal respectively. Through the imaginary part of the conjugate cross-spectrum, three azimuth estimation models and an averaging method based on the three azimuth estimation models are proposed to achieve azimuth angle estimation of signals from 0° to 360°. In view of the actual requirements of portable aviation-dropped, ship-dropped or suspended small sonar buoys or underwater submersible buoys, as well as underwater mine acoustic fuzes and other devices, the present invention proposes targeted signal detection and azimuth estimation algorithms to achieve robust and reliable signal detection and azimuth estimation.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic detection, and particularly relates to a method for estimating the azimuth of an underwater acoustic target for a small array. Background Art

[0002] The problems of "not seeing far and not distinguishing clearly" in the offshore underwater acoustic detection system are common problems faced by navies of all countries in the world. For sonar buoys or submerged buoys, due to volume limitations, generally a single omnidirectional sound pressure hydrophone, a vector hydrophone, or a circular array of micro-miniature sound pressure hydrophones is used. For a single omnidirectional scalar hydrophone, it can only detect whether there is a signal and cannot measure direction, and there is no array gain. Therefore, the detection distance is very limited and it is difficult to meet the detection of weak target signals. A single vector hydrophone estimates the azimuth of the target signal based on the conjugate correlation between the sound pressure channel P and the vibration velocities in the two horizontal directions x and y. However, its azimuth resolution performance is relatively weak, and the cost of a single vector hydrophone is relatively high compared to a sound pressure hydrophone. The size of a single vector hydrophone cannot change its detection performance, and the use effect is limited.

[0003] For a small circular array with a small aperture and a small number of array elements, existing methods all adopt the array processing method of beamforming. This method has two problems: on the one hand, because the number of array elements of the small array is small and the aperture (radius) is small, its array gain and azimuth resolution performance are very limited, which limits the performance of detecting weak signals and the azimuth estimation error is relatively large; on the other hand, the beamforming of an array of a certain scale stipulates its working frequency band. Otherwise, for the detection of broadband signals, problems such as beam broadening and grating lobes will occur. The fewer the number of array elements and the smaller the radius, the higher the corresponding working frequency band. According to the existing theoretical and experimental research in underwater acoustics, the energy of the radiation noise signal of a submarine is mainly distributed in the low frequency band. Therefore, using the conventional representation formation method on a small array is not conducive to the detection of submarine targets due to the limitation of the working frequency band. Summary of the Invention

[0004] The present invention mainly solves the technical problems in the prior art that due to the small number of array elements and small aperture (radius) of the small array, its array gain and azimuth resolution performance are very limited, and due to the limitation of the working frequency band, it is not conducive to the detection of submarine targets. The present invention proposes a method for estimating the azimuth of an underwater acoustic target for a small array to achieve the purpose of improving the sonar azimuth estimation performance and detection distance.

[0005] The present invention provides a method for estimating the azimuth of an underwater acoustic target for a small array, including:

[0006] Constructing an orthogonal cross circular array with uniformly distributed four-element orthogonal hydrophones;

[0007] Receive the four-channel signals of the four-element orthogonal hydrophone, calculate the difference signals of two orthogonal hydrophones in two orthogonal directions according to the four-channel signals, and sum and average the four-channel signals to obtain a center point reference signal;

[0008] Take N-point data of the difference signal and the center point reference signal to perform a fast Fourier transform to obtain a signal spectrum;

[0009] Obtain a conjugate signal through the signal spectrum, and obtain the azimuth angle and cross-spectrum energy of the frequency points in the signal spectrum according to the conjugate signal;

[0010] Judge whether there is a target and determine the target azimuth angle according to the azimuth angle and cross-spectrum energy of the frequency points by using the polar coordinate method or the energy statistics method.

[0011] Further, the orthogonal cross-circle array composed of the uniformly distributed four-element orthogonal hydrophones has a radius of d. Assume that the far-field signal arrives at the reference point, that is, the signal at the center O of the circle is s(t). Taking the extension line of the center O and the first array element as the reference direction, the incident angle of the target signal is θ, and the ambient noise at the i-th receiving point is n i (t) (i = 1, …, 4).

[0012] Further, the receiving the four-channel signals of the four-element orthogonal hydrophone, calculating the difference signals of two orthogonal hydrophones in two orthogonal directions according to the four-channel signals, and summing and averaging the four-channel signals to obtain a center point reference signal includes:

[0013] The received signals at the array elements i = 1, …, 4 can be expressed as:

[0014]

[0015] Among them,

[0016]

[0017] The signal arriving at the reference center O point is:

[0018]

[0019] Among them, is the ambient noise at the reference center point;

[0020] The Fourier transform of s(t) obtained from equation (2) is S(ω), which contains the noise component N(ω);

[0021] According to equation (1), calculate the difference signals of two hydrophones in two orthogonal directions:

[0022] x 13\(y(t)=x1(t)-x3(t)\) (3-1)

[0023] x 24 \((t)=x2(t)-x4(t)\) (3-2).

[0024] Further, taking N-point data of the difference signal and the center point reference signal for fast Fourier transform to obtain a signal spectrum, including:

[0025] Performing Fourier transform on equations (3-1) and (3-2) respectively to obtain the spectrum of the difference signal:

[0026]

[0027]

[0028] where \(\omega = 2\pi f\), \(f\) is the frequency of the signal being analyzed; \(N\) 13 and \(N\) 24 are the Fourier transforms of \(n1(t)-n3(t)\) and \(n2(t)-n4(t)\) respectively.

[0029] Further, obtaining a conjugate signal from the signal spectrum, and obtaining the azimuth angle and cross-spectrum energy of the frequency points in the signal spectrum, including:

[0030] Performing Fourier transform on \(s(t)\) obtained from equation (2) to obtain \(S(\omega)\), taking its conjugate, and performing conjugate multiplication with the Fourier transforms of the difference signals in equations (4-1) and (4-2) respectively, and taking the imaginary part to obtain:

[0031]

[0032]

[0033] Assuming that the conjugate signal is uncorrelated with the noise, the latter term of the above two equations is approximately 0;

[0034] Using equation (5), calculating an incident azimuth angle for each frequency point after fast Fourier transform. For the \(k\)-th frequency point, the signal incident azimuth angle is calculated by the following equation:

[0035]

[0036]

[0037] where:

[0038]

[0039] In the formula, \(Z(k)\) is the magnitude of the cross-spectrum energy corresponding to the \(k\)-th frequency point;

[0040] The incident azimuth angle of the frequency point can also be obtained through Equation (8):

[0041]

[0042] Furthermore, according to the signal incident azimuth angle and the incident azimuth angle of the frequency point, the target azimuth angle of the frequency point estimation is calculated through Equation (9), including:

[0043]

[0044] Furthermore, the method for judging whether there is a target by the polar coordinate method includes:

[0045] For each frequency point k, (θ(k), Z(k)) can be obtained, and the polar coordinates are defined thereby;

[0046] The (θ(k), Z(k)) obtained from different frequency points will be distributed at different azimuths and distances centered on the origin;

[0047] If the (θ(k), Z(k)) obtained from different frequency points are irregularly distributed in azimuth and the magnitudes of their cross-spectral energies Z(k) are very close, it indicates that there is only environmental background noise in the received signal and no target signal;

[0048] If there is a Z(k) that is significantly higher than the background cross-spectral energy at some frequency points, a target is judged to exist at the corresponding azimuth θ(k);

[0049] If this situation occurs in multiple directions, it is judged that there are multiple targets.

[0050] Furthermore, the method for judging whether there is a target by the polar coordinate method or the energy statistics method and determining the target azimuth angle includes:

[0051] For each frequency point f k an azimuth θ(k) and its energy value Z(k) can be obtained;

[0052] Within the range of 0° - 360°, Z within this azimuth angle region is accumulated at a certain azimuth angle interval Δθ k to obtain the energy distribution of the azimuth θ(k) and its energy value Z(k) of all frequency points within the range of 0° - 360°. The azimuth angle corresponding to the energy exceeding the threshold energy is the detected target azimuth angle.

[0053] Furthermore, the specific steps for determining the target azimuth angle are:

[0054] Set the statistical azimuth angle interval range to be Δθ;

[0055] Statistically calculate i azimuth angle intervals θ i -θi+1 (θ i+1 = θ i + Δθ) energy distribution:

[0056]

[0057] where θ i < θ(k) ≤ θ i+1 ;

[0058] Taking the statistical interval θ i as the abscissa and P(θ i ) as the ordinate, we get:

[0059] The energy distribution histogram of (θ(k), Z(k)) within a certain angular range Δθ from 0° to 360°;

[0060] Taking the direction with the maximum energy exceeding the set threshold as the target azimuth angle;

[0061] The said threshold is determined according to the equipment and experimental data.

[0062] In view of the actual requirements of small sonar buoys or underwater submersible buoys that are easy to deploy lightly by air dropping, ship dropping or hanging, as well as underwater mine acoustic fuzes and other devices, the present invention proposes a target detection and azimuth estimation method based on a microarray. Using only 4 pressure hydrophones, through the orthogonal design of the hydrophones, targeted signal detection and azimuth estimation algorithms are proposed to achieve robust and reliable signal detection and azimuth estimation. The method proposed by the present invention is effective for broadband signals and can achieve more robust and reliable results for signals with strong line spectra.

[0063] The advantages of the present invention include:

[0064] 1. The orthogonal micro - four - element array and its azimuth estimation method proposed by the present invention have advantages such as strong azimuth estimation performance and long detection range compared with a single omnidirectional or single vector hydrophone. Moreover, it has a simple structure, small computational amount, simple algorithm, and is easy to implement in engineering, and is suitable for autonomous calculation of low - energy - consumption and embedded chip devices underwater;

[0065] 2. The target azimuth estimation method proposed by the present invention is different from the conventional representation formation method, is not restricted by the working frequency band, can achieve azimuth estimation of low - SNR signals with a small circular array, and does not have grating lobes (false target azimuths), and is suitable for detecting the energy range of submarine radiated noise signals;

[0066] 3. The method proposed by the present invention has better flexibility. In the simulation case of the orthogonal four - element array, appropriately expanding the radius of the microarray (while still maintaining the characteristics of the microarray), such as Figure 4 (radius 0.1 m) and Figure 12It can be seen from (a radius of 0.2 m) that when the signal-to-noise ratio drops from -10 dB to -15 dB, the signal margin remains basically the same. It can be seen that the performance of target detection and azimuth estimation can be significantly improved. This is an advantage that a single vector hydrophone and the conventional beamforming method do not have. Description of the Drawings

[0067] Figure 1 is the implementation flowchart of the underwater acoustic target azimuth estimation method for a microarray provided by the present invention;

[0068] Figure 2 is the schematic structural diagram of the array design of the four-element orthogonal hydrophone of the present invention;

[0069] Figure 3 is the implementation logic flowchart of the present invention;

[0070] Figure 4 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -5 dB;

[0071] Figure 5 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -10 dB;

[0072] Figure 6 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a simulated target signal, recorded ocean ambient noise, and a signal-to-noise ratio of 0 dB;

[0073] Figure 7 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a simulated target signal, recorded ocean ambient noise, and a signal-to-noise ratio of -3 dB;

[0074] Figure 8 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a recorded ship signal at sea, Gaussian white noise, and a signal-to-noise ratio of 0 dB;

[0075] Figure 9 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a recorded ship signal at sea, recorded ocean ambient noise, and a signal-to-noise ratio of 5 dB;

[0076] Figure 10 is the schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.1 m, a recorded ship signal at sea, recorded ocean ambient noise, and a signal-to-noise ratio of 0 dB;

[0077] Figure 11It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -5 dB;

[0078] Figure 12 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -12 dB;

[0079] Figure 13 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -15 dB;

[0080] Figure 14 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, recorded marine environmental noise, and a signal-to-noise ratio of 0 dB;

[0081] Figure 15 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, recorded marine environmental noise, and a signal-to-noise ratio of -3 dB;

[0082] Figure 16 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a simulated target signal, recorded marine environmental noise, and a signal-to-noise ratio of -5 dB;

[0083] Figure 17 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a ship signal recorded at sea, recorded marine environmental noise, and a signal-to-noise ratio of 0 dB;

[0084] Figure 18 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.2 m, a ship signal recorded at sea, recorded marine environmental noise, and a signal-to-noise ratio of -3 dB;

[0085] Figure 19 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.5 m, a simulated target signal, Gaussian white noise, and a signal-to-noise ratio of -15 dB;

[0086] Figure 20 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.5 m, a simulated target signal, recorded marine environmental noise, and a signal-to-noise ratio of -5 dB;

[0087] Figure 21 It is a schematic diagram of the azimuth estimation result in the simulation test of the present invention under the conditions of a radius of 0.5 m, a ship signal recorded at sea, Gaussian white noise, and a signal-to-noise ratio of -13 dB;

[0088] Figure 22 It is a schematic diagram of the azimuth estimation result under the conditions of a radius of 0.5 m, real recorded ship signals, real recorded ocean ambient noise, and a signal-to-noise ratio of -5 dB in the simulation test of the present invention. Specific Embodiments

[0089] To make the technical problems solved by the present invention, the technical solutions adopted, and the achieved technical effects clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Additionally, it should be noted that for the sake of description, only parts related to the present invention are shown in the drawings rather than all the content.

[0090] As Figure 1 shown, the underwater acoustic target azimuth estimation method for a microarray provided by an embodiment of the present invention includes:

[0091] 101. Form an orthogonal cross circular array with uniformly distributed four-element orthogonal hydrophones;

[0092] Specifically, the forming of an orthogonal cross circular array with uniformly distributed four-element orthogonal hydrophones includes:

[0093] The distances from each hydrophone in the four-element orthogonal hydrophones to the center of the circle are the same, the lines connecting them in pairs are perpendicular, and they must be symmetric about the intersection point;

[0094] For the orthogonal cross circular array formed by the uniformly distributed four-element orthogonal hydrophones with a radius of d, assuming that the signal reaching the reference point, i.e., the center O of the circle, in the far field is s(t), using the extension line of the center O and the first array element as the reference direction, the incident angle of the target signal is θ, and the ambient noise at the i-th receiving point is n i (t) (i = 1,..., 4). Its structure is as Figure 2 shown.

[0095] 102. Receive the four-channel signals of the four-element orthogonal hydrophones, calculate the difference signals of two orthogonal hydrophones in two orthogonal directions according to the four-channel signals, and sum and average the four-channel signals to obtain the center point reference signal;

[0096] Specifically, the received signals at the array elements i = 1,..., 4 can be expressed as:

[0097]

[0098] Among them,

[0099]

[0100] The signal reaching the reference center O is:

[0101]

[0102] Among them, is the environmental noise at the reference center point;

[0103] The Fourier transform of s(t) obtained from equation (2) is S(ω), which contains the noise component N(ω);

[0104] According to equation (1), calculate the difference signals of two hydrophones in two orthogonal directions:

[0105] x 13 (t) = x1(t) - x3(t) (3 - 1)

[0106] x 24 (t) = x2(t) - x4(t) (3 - 2).

[0107] 103. Take N - point data of the difference signal and the center - point reference signal to perform a fast Fourier transform to obtain the signal spectrum;

[0108] Specifically, perform Fourier transforms on equations (3 - 1) and (3 - 2) respectively to obtain the spectra of the difference signals:

[0109]

[0110]

[0111] where ω = 2πf, f is the signal frequency for analysis; N 13 and N 24 are the Fourier transforms of n1(t) - n3(t) and n2(t) - n4(t) respectively.

[0112] 104. Obtain the conjugate signal from the signal spectrum, and obtain the azimuth angle and cross - spectral energy of the frequency points in the signal spectrum according to the conjugate signal;

[0113] Specifically, perform a Fourier transform on s(t) obtained from equation (2) to get S(ω), take its conjugate, and perform conjugate multiplication with the Fourier transforms of the difference signals in equations (4 - 1) and (4 - 2) respectively, and take the imaginary part to obtain:

[0114]

[0115]

[0116] Assume that the conjugate signal is uncorrelated with the noise, and the latter term of the above two equations is approximately 0;

[0117] Using equation (5), calculate an incident azimuth angle for each frequency point after the fast Fourier transform. For the k - th frequency point, calculate the signal incident azimuth angle from the following formula:

[0118]

[0119]

[0120] Wherein:

[0121]

[0122] In the formula, Z(k) is the magnitude of the cross-spectrum energy corresponding to the k-th frequency point. The azimuth angle of the frequency point k can also be obtained through Equation (8):

[0123]

[0124] In order to improve the anti-noise performance, the azimuth angles of the signals at the k-th frequency point calculated by Equations (6-1), (6-2), and (8) can be averaged as the target azimuth angle estimated for this frequency point:

[0125]

[0126] 105. According to the azimuth angle and cross-spectrum energy of the frequency points, it is judged whether there is a target by the polar coordinate method or the energy statistics method, and the target azimuth angle is determined.

[0127] Specifically, judging whether there is a target by the polar coordinate method includes:

[0128] (1) For each frequency point k, (θ(k), Z(k)) can be obtained, and the polar coordinates are defined thereby.

[0129] (2) The (θ(k), Z(k)) obtained from different frequency points will be distributed at different azimuths and distances centered on the origin.

[0130] (3) If the (θ(k), Z(k)) obtained from different frequency points are irregularly distributed in azimuth and their cross-spectrum energy Z(k) magnitudes are very close, it means that only environmental background noise is received in the signal and there is no target signal.

[0131] (4) If there is a Z(k) that is significantly higher than the background cross-spectrum energy at some frequency points, then a target is judged to exist at the corresponding azimuth θ(k).

[0132] (5) If this situation occurs in multiple directions, it is judged that there are multiple targets.

[0133] Judging the target azimuth angle by the energy statistics method includes:

[0134] For each frequency point f kAn azimuth θ(k) and its energy value Z(k) can be obtained; within the range of 0° - 360°, the Z within this azimuth angle region is accumulated at a certain azimuth angle interval Δθ k to obtain the energy distribution of the azimuth θ(k) and its energy value Z(k) of all frequency points within the range of 0° - 360°. The azimuth angle corresponding to the energy exceeding the threshold energy is the detected target azimuth angle.

[0135] The specific steps are as follows:

[0136] (1) Set the statistical azimuth angle interval range to be Δθ;

[0137] (2) Statistically calculate the energy distribution of i azimuth angle intervals θ i -θ i+1 (θ i+1 =θ i +Δθ):

[0138]

[0139] where θ i <θ(k)≤θ i+1 ;

[0140] (3) Using the statistical interval θ i as the abscissa and P(θ i ) as the ordinate, obtain:

[0141] (θ(k), Z(k)) within a certain angular range Δθ of 0° - 360° energy distribution histogram;

[0142] (4) Take the direction with the maximum energy exceeding the set threshold as the target azimuth angle.

[0143] The implementation logic flowchart of the above embodiment is as Figure 3 shown

[0144] Simulation test results:

[0145] (1) Simulation parameters

[0146] The sampling frequency of the simulation example is 25 kHz, the sound speed is 1507 m / s, and the radius of the circular array is considered in three cases: 0.1 m, 0.2 m, and 0.5 m. The simulation considers a single target with a target azimuth angle of 45°. Two types of target signals are considered: one is a simulation signal composed of five frequency components of 301 Hz, 501 Hz, 801 Hz, 1001 Hz, and 1501 Hz; the other is the ship radiated noise signal recorded at sea. The background noise uses Gaussian white noise and the recorded sea environment noise respectively. The time for one FFT is 1 second, the time length for outputting the signal processing result every 5 times is 5 seconds, and the frequency band range of signal processing is 100 Hz - 2000 Hz.

[0147] (2) Simulation Results

[0148] For different simulation conditions, the simulation results are as Figures 4 to 22 shown. Each simulation result graph includes: the left graph (polar coordinate distribution graph) and the right graph (energy distribution histogram of the signal within each 1° azimuth range).

[0149] It can be seen from the simulation results that the method proposed in this invention patent can estimate the azimuth of the target signal at low signal-to-noise ratio for a 4-element micro-scale array with a radius of 0.1 m to 0.2 m. If the radius is increased to 0.5 m, the azimuth of the target signal from -5 dB to -15 dB can be estimated.

[0150] The core point of the present invention is:

[0151] Using four hydrophones with two pairs perpendicular to each other and the same distance from the intersection point (or reference center) to form an orthogonal structure, subtracting (or differentiating) the received signals of each pair, then performing spectral estimation on the subtracted (differentiated) signals, and then multiplying their spectra by the conjugate of the reference center signal respectively. Through the imaginary part of the conjugate cross-spectrum, three azimuth estimation models and an averaging method based on the three azimuth estimation models are proposed to achieve the azimuth angle estimation of the signal from 0° to 360°; the reference center signal can be the actual hydrophone sampling signal. In the case of no center point sampling (i.e., only four hydrophones), the center point signal can be obtained by summing and averaging the signals of the four mutually perpendicular hydrophones; the spectral estimation of each path of signal can use FFT or other high-resolution spectral estimation methods; any spectral estimation can use multi-segment time accumulation averaging to improve the signal-to-noise ratio and stability of the signal spectrum; an azimuth angle and its corresponding energy are obtained for each analysis frequency, the energy within the azimuth angle interval is summed, and a certain threshold is set to achieve the detection and azimuth estimation of the target signal; the detection and azimuth estimation obtained by the above method can be further improved by continuous multiple time integrations (averages);

[0152] The present invention has a more obvious effect on single-frequency or multi-frequency signals with strong line spectra. Before performing signal detection and azimuth estimation by the above method, line spectrum enhancement techniques such as adaptive line spectrum enhancement and deep learning line spectrum enhancement can be adopted, which helps to further improve the detection and azimuth estimation effects of the target signal.

[0153] The present invention is applicable to underwater acoustic target detection of micro-arrays such as airborne dropped sonar buoys, ship-hung or dropped buoys, underwater moored buoys, underwater acoustic reconnaissance equipment, UUVs, and underwater mine acoustic fuzes.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: modifying the technical solutions recorded in the foregoing embodiments, or equivalently replacing some or all of the technical features therein, does not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An underwater acoustic target azimuth estimation method for a small array, characterized in that, The underwater acoustic target azimuth estimation method for the small array includes: Forming an orthogonal cross circular array with uniformly distributed four-element orthogonal hydrophones; Receiving the four-channel signals of the four-element orthogonal hydrophones, calculating the difference signals of two orthogonal hydrophones in two orthogonal directions according to the four-channel signals, and summing and averaging the four-channel signals to obtain a center point reference signal; Performing a fast Fourier transform on N-point data of the difference signal and the center point reference signal to obtain a signal spectrum; Obtaining a conjugate signal through the signal spectrum, and obtaining the azimuth angle and cross-spectrum energy of the frequency points in the signal spectrum according to the conjugate signal; According to the azimuth angle and cross-spectrum energy of the frequency points, judging whether there is a target by the polar coordinate method or the energy statistics method, and determining the target azimuth angle.

2. The method for underwater acoustic target azimuth estimation for a microarray according to claim 1, characterized in that, The forming of an orthogonal cross circular array with uniformly distributed four-element orthogonal hydrophones includes: The distances from each hydrophone in the four-element orthogonal hydrophones to the center of the circle are the same, the two-by-two connections are perpendicular, and they must be symmetric about the intersection point; The orthogonal cross circular array composed of the evenly distributed four-element orthogonal hydrophones has a radius of d. Let the signal arriving at the reference point, i.e., the center O of the circle, in the far field be s(t). Taking the extension line of the center O and the first array element as the reference direction, the incident angle of the target signal is θ, and the ambient noise at the i-th receiving point is n i (t), where i = 1, …, 4.

3. The method for underwater acoustic target azimuth estimation for a small array according to claim 2, wherein The receiving of the four-channel signals of the four-element orthogonal hydrophones, calculating the difference signals of two orthogonal hydrophones in two orthogonal directions according to the four-channel signals, and summing and averaging the four-channel signals to obtain a center point reference signal includes: The received signals at array elements i = 1, …, 4 can be expressed as: Where, The signal arriving at the reference center O point is: Among them, is the environmental noise at the reference center point; The Fourier transform of s(t) obtained from equation (2) is S(ω), which contains the noise component N(ω); According to equation (1), calculate the difference signals of two hydrophones in two orthogonal directions: x 13 y(t) = x1(t) - x3(t) (3-1) x 24 (t) = x2(t) - x4(t)(3 - 2).

4. The underwater acoustic target azimuth estimation method for a small array according to claim 3, characterized in that, The performing of a fast Fourier transform on N-point data of the difference signal and the center point reference signal to obtain a signal spectrum includes: Performing Fourier transforms on equations (3-1) and (3-2) respectively to obtain the spectrum of the difference signal: where ω = 2πf and f is the signal frequency to be analyzed; N 13 and N 24 are the Fourier transforms of n1(t) - n3(t) and n2(t) - n4(t), respectively.

5. The method for underwater acoustic target azimuth estimation for a small array according to claim 4, characterized in that, The obtaining of a conjugate signal through the signal spectrum, and obtaining the azimuth angle and cross-spectrum energy of the frequency points in the signal spectrum according to the conjugate signal includes: Performing a Fourier transform on s(t) obtained from equation (2) to obtain S(ω), taking its conjugate, and performing conjugate multiplication with the Fourier transforms of the difference signals in equations (4-1) and (4-2) respectively, and taking the imaginary part to obtain: Assuming that the conjugate signal is uncorrelated with the noise, the latter term of the above two equations is approximately 0; Using equation (5), calculate an incident azimuth angle for each frequency point after the fast Fourier transform. For the k-th frequency point, calculate the signal incident azimuth angle from the following equation: Where: In the equation, Z(k) is the magnitude of the cross-spectrum energy corresponding to the k-th frequency point; The incident azimuth angle of the frequency point can also be obtained through equation (8):

6. The method for underwater acoustic target azimuth estimation for a microarray according to claim 5, characterized in that According to the signal incident azimuth angle and the incident azimuth angle of the frequency point, calculate the target azimuth angle estimated by the frequency point through equation (9), including:

7. The method for estimating the azimuth of an underwater acoustic target for a small array according to claim 6, characterized in that The judging whether there is a target by the polar coordinate method includes: For each frequency point k, (θ(k), Z(k)) can be obtained, and the polar coordinates are defined thereby; The (θ(k), Z(k)) obtained from different frequency points will be distributed at different azimuths and distances centered on the origin; If the (θ(k), Z(k)) obtained at different frequency points are irregularly distributed in azimuth and their cross-spectrum energy Z(k) magnitudes are very close, it indicates that only environmental background noise is present in the received signal and there is no target signal; If there is a Z(k) that is significantly higher than the background cross-spectrum energy at certain frequency points, then a target is judged to exist at the corresponding azimuth θ(k); If this situation occurs in multiple directions, it is judged that there are multiple targets.

8. The method for underwater acoustic target azimuth estimation for a small array according to claim 7, characterized in that The determination of whether there is a target and the determination of the target azimuth angle by the polar coordinate method or the energy statistics method include: For each frequency point f k an azimuth θ(k) and its energy value Z(k) can be obtained; Within the range of 0° - 360°, Z included in this azimuth region is accumulated at a certain azimuth angle interval Δθ k to obtain the energy distribution of the azimuth θ(k) and its energy value Z(k) of all frequency points within the range of 0° - 360°. The azimuth angle corresponding to the energy exceeding the threshold energy is the detected target azimuth angle.

9. The method for underwater acoustic target azimuth estimation for a small array according to claim 8, characterized in that, The specific steps for determining the target azimuth angle are: Set the statistical azimuth angle interval range as Δθ; Statistically analyze the energy distribution in i azimuth angle intervals θ i -θ i+1 (θ i+1 = θ i + Δθ): where, θ i <θ(k) ≤ θ i+1 ; With a statistical interval θ i as the abscissa and P(θ i ) as the ordinate, we obtain: The energy distribution histogram of (θ(k), Z(k)) within a certain angular range Δθ of 0° - 360°; Take the direction with the maximum energy exceeding the set threshold as the target azimuth angle; The said threshold is determined according to the equipment and experimental data.

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