A method for extended aperture sonar imaging based on coefficient correction

Abstract

The application relates to a kind of underwater acoustic signal processing methods in the field of ocean, specifically to a kind of extended aperture sonar imaging method based on coefficient correction.The method of the application comprises the following steps: constructing the constraint of expected target signal intensity and beam pattern response sensitivity, establishing the constraint optimization problem about window function correction coefficient, and solving to obtain window function correction coefficient; using window function correction coefficient to correct and compensate the beam forming weighting vector in the extended aperture sonar imaging process, and obtaining extended aperture sonar image.The method of the application can realize the suppression of beam sidelobe in the extended aperture sonar imaging process, and realize high-resolution high-definition imaging effect.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of water acoustic signal processing methods in the field of ocean, specifically to a kind of extended aperture sonar high-definition imaging method based on coefficient correction. BACKGROUND

[0002] Extended aperture imaging sonar utilizes multi-transmit multi-receive waveform diversity technology, combined with phase center principle, transmit array and receiving array are distributed in a small range, form a large virtual array aperture, it is essentially to realize high resolution in image azimuth by using transmit-receive joint coherence processing, so extended aperture imaging sonar generally adopts compact deployment mode, i.e. transmitting and receiving array is basically concentrated in the same observation angle of target. Extended aperture imaging sonar utilizes virtual extension principle to improve azimuth resolution, and improves the quality of sonar image, but the virtual array may no longer be a truly uniform linear array, so the method of window function weighting commonly used in conventional imaging sonar to suppress azimuth sidelobes will lead to the failure of azimuth sidelobe suppression if directly used in extended aperture imaging sonar. SUMMARY

[0003] The present application aims to solve the problems existing in the prior art: extended aperture imaging sonar can form a virtual large aperture and improve resolution without changing the actual physical aperture, but the non-uniformity of the virtual extended array will lead to the failure of conventional window function weighting sidelobe suppression. To solve this problem, the present application first proposes an extended aperture sonar beam low sidelobe imaging method based on window function coefficient correction. This method solves the second-order cone programming constraint optimization problem about window function correction coefficient by introducing the constraints of expected target signal strength and beam pattern response sensitivity, and applies the obtained window function correction coefficient to the imaging process of extended aperture imaging sonar, to realize beam sidelobe suppression and achieve high-resolution high-definition imaging effect.

[0004] To achieve the above-mentioned purpose, the present application realizes by the following technical scheme.

[0005] The present application proposes an extended aperture sonar imaging method based on coefficient correction, which comprises:

[0006] The constraints of expected target signal strength and beam pattern response sensitivity are constructed, a constraint optimization problem about window function correction coefficient is established, and the window function correction coefficient is solved;

[0007] The window function correction coefficient is used to correct and compensate the beam forming weighting vector in the imaging process of extended aperture sonar, to obtain extended aperture sonar image.

[0008] As one of the improvements of the above technical scheme, the constraint of expected target signal strength is expressed as:

[0009]

[0010] wherein, denotes the window function weight correction coefficient, w eb is the Chebyshev window function weight for a given sidelobe height; a TR (θ d ) is the steering vector of the extended aperture imaging sonar with the beam pointing angle θ d ; the superscript H denotes the conjugate transpose;

[0011] The constraint on the beam pattern response sensitivity is expressed as:

[0012]

[0013] wherein, ξ is a constant set, and ||·|| is the 2-norm calculation symbol.

[0014] As one of the improvements of the above technical solutions, the constraint optimization problem on the window function correction coefficient is expressed as:

[0015]

[0016]

[0017]

[0018]

[0019] wherein, a TR (θ i ) is the steering vector of the extended aperture imaging sonar with the beam pointing angle θ i ; Θ SL denotes the sidelobe region other than the first zero point; is a real number set.

[0020] As one of the improvements of the above technical solutions, in the process of solving the second-order cone programming constraint optimization problem on the window function correction coefficient, the value of the second-order cone programming constraint optimization problem on the window function correction coefficient is not changed until is a real number, denotes the window function weight correction coefficient.

[0021] As one of the improvements of the above technical solutions, when is a real number, the constraint optimization problem on the window function correction coefficient is converted to:

[0022]

[0023] ​

[0024]

[0025]

[0026] As one of the improvements of the above technical solutions, the converted constraint optimization problem about the window function correction coefficient is a second-order cone programming problem, and the sedumi software is used for solving.

[0027] As one of the improvements of the above technical solutions, the using window function correction coefficient corrects and compensates the beam forming weighting vector in the extended aperture sonar imaging process, and obtains the extended aperture sonar imaging, including:

[0028] According to the angle resolution requirement, combining the phase center theorem and the constraint of the carrier platform size, the extended aperture sonar array is designed, and the element position of the virtual array of the extended aperture sonar is determined;

[0029] Through N R receive elements, N R channel echo signals are received;

[0030] The received N R channel echo signals are subjected to window function weighting matched filtering processing and waveform separation processing, and N R M T groups of echo data are obtained, M T is the number of transmitting elements;

[0031] The window function correction coefficient is used to correct and compensate the beam forming weighting vector, and the transmit-receive joint beam forming weighting vector of the extended imaging sonar is obtained;

[0032] According to the transmit-receive joint beam forming weighting vector, N R M T groups of echo data are received to form multiple beams, and the extended aperture sonar image is obtained.

[0033] As one of the improvements of the above technical solutions, the steering vector of the virtual array is represented as:

[0034]

[0035] Among them, represents the Kron product, a T is the steering vector of the sonar transmitting array of the extended aperture sonar, and a R is the steering vector of the receiving array.

[0036] As one of the improvements of the above technical solutions, the beam pattern of the virtual array is represented as:

[0037]

[0038] Where, d T d is the spacing between adjacent transmitting elements, λ is the wavelength corresponding to the center frequency of the transmitted signal, and d is the wavelength of the transmitted signal. R The distance between adjacent receiving array elements, variable Y p =sinθ - sinθ p θ p Let be the direction angle of the p-th target.

[0039] As one improvement to the above technical solution, the transmit-receive joint beamforming weighting vector W of the extended imaging sonar... TR (θ d The expression for ) is:

[0040]

[0041] The advantages of this invention compared to the prior art are:

[0042] 1) The method of the present invention has no special requirements on the array shape of the extended aperture sonar;

[0043] 2) The window function correction coefficient obtained by the method of the present invention is a real number, which will not change with the beam pointing angle and is independent of the guide vector of different beam pointing angles. At the same time, in the near-field focusing region, it is not affected by the different phase differences at different distances. Therefore, it is not necessary to store multiple distance points or beam pointing angle weight coefficients in advance, but only a set of correction coefficients needs to be calculated in advance. The method of the present invention is easy to implement in engineering.

[0044] 3) The method of the present invention can obtain an extended aperture sonar image with a beam sidelobe of about 40dB. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method of the present invention;

[0046] Figures 2(a)-2(d) Figure 2(a) shows a comparison of two-dimensional sonar images obtained using the MIMO imaging sonar method and azimuth slices at an 11m target. Figure 2(b) shows a sonar image obtained using the Chebyshev window weighting method, Figure 2(c) shows a sonar image obtained using the correction coefficient weighting method of this invention, and Figure 2(d) shows a comparison of azimuth slices at an 11m target using the above three methods. Detailed Implementation

[0047] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0048] Example 1

[0049] like Figure 1As shown, a flow chart of the method of the present application.

[0050] The constraints of the desired target signal intensity and beam pattern response sensitivity are constructed, a constraint optimization problem about the window function correction coefficient is established, and the window function correction coefficient is solved;

[0051] The window function correction coefficient is used to correct and compensate the beam forming weighting vector in the extended aperture sonar imaging process, and the extended aperture sonar image is obtained.

[0052] Specifically, the following steps are included:

[0053] Firstly, according to the angle resolution requirement, combining the phase center theorem and the constraint of the carrier platform size, a suitable extended aperture array is designed, considering that the actual receiving array and the transmitting array are both uniform linear arrays, the element position of the virtual array of the extended aperture is equal to the element position of the receiving array convolved with the element position of the transmitting array, and the steering vector of the virtual array can be expressed as,

[0054]

[0055] Wherein, represents the Kron product, a T is the steering vector of the sonar transmitting array of the extended aperture sonar, a R is the steering vector of the receiving array.

[0056] The beam pattern of the virtual array can be expressed as

[0057]

[0058] Wherein, d T is the interval of adjacent transmitting elements, λ is the wavelength corresponding to the center frequency of the transmitting signal, d R is the interval of adjacent receiving elements, N R is the number of receiving elements, M T is the number of transmitting elements, Y p =sinθ-sinθ p , θ p is the direction angle of the pth target.

[0059] Then, the waveform separation processing is performed on the echo signals actually received by N R channels, and N R M T groups of echo data are obtained.

[0060] Then, the base value of the beam domain output power expectation value will depend on the sensitivity function T se and the variance of the disturbance, and the effect is to limit the depth of the beam pattern zero point. When designing the optimal array, a sensitivity constraint should be applied.

[0061] T se ||w 2 ||≤T o (3)

[0062] where w is the beamforming weight vector, T o is a design constant, which makes the performance of the array more robust to perturbation and lower null depth.

[0063] The beam sidelobe after weighting the window function coefficients is limited, and the expected target signal strength and the sidelobe level expectation sensitivity are constrained, and then the constraint optimization problem of the correction coefficient is obtained, and then the modified window function nonlinear coefficient is obtained by solving the second-order cone programming optimization, and the equal ripple low sidelobe level beam response is obtained by weighting the virtual array amplitude through the nonlinear coefficient. The window function weight correction coefficient can be obtained by the following constraint estimation:

[0064]

[0065]

[0066]

[0067]

[0068] In the formula, w eb is the Chebyshev window function weight of the given sidelobe height, and the commonly used sidelobe height is-40dB. a TR (θ d ) is the extended aperture imaging sonar steering vector with beam pointing angle θ d ; a TR (θ i ) is the extended aperture imaging sonar steering vector with beam pointing angle θ i ; Θ SL represents the sidelobe region other than the first zero point; ||·|| is the 2-norm calculation symbol; ξ is a constant, the value of which is related to the robustness of the algorithm and the expected sidelobe height, and when the value is less than or equal to 0.01, the beam pattern sidelobe height has a-40dB null; is a real number set.

[0069] In formula (4), when the optimal solution of w is found, the value of its cost function will not change until (w·w eb ·a TR (θ d )) H a TR (θ d) is a real number. Therefore, without loss of generality, it can be assumed that (w·w eb ·a TR (θ d )) H a TR (θ d ) is a real number, the above formula can be expressed as:

[0070]

[0071]

[0072]

[0073]

[0074] The constraint problem of the window function correction weight coefficient in formula (5) is a second-order cone programming problem, which can be solved by using the sedumi software, and the convergence speed is fast and time-saving.

[0075] Finally, the beam pointing angle is θ d , and the transmit-receive joint beamforming weight vector of the extended imaging sonar is obtained as:

[0076]

[0077] According to formula (6), a plurality of pre-formed beams are received, and a high-resolution high-definition image with a sidelobe level of about -40dB of the extended sonar is obtained.

[0078] The extended aperture imaging sonar includes a receiving array and a transmitting array. According to the angle resolution index design requirement, the number of elements of the linear uniform receiving array is 192, the linear transmitting array includes two transmitting sub-arrays, which are located at both ends of the receiving array and respectively transmit positive and negative slope linear frequency modulation signals. In the simulation condition, it is assumed that there are 12 point target echoes which are not correlated with each other, and the 12 point targets form an “L” shape. First, the echo signal is processed by window function weighting and matched filtering to separate and suppress the distance sidelobes, and then the transmit-receive joint beamforming is used to obtain the sonar image.

[0079] As shown in Figures 2(a)-2(d) , it is a two-dimensional sonar image of the MIMO imaging sonar and a comparison effect diagram of the azimuth direction slice at the 11m target, wherein, Fig. 2(a) is a sonar image obtained by using the uniform weighting method, Fig. 2(b) is a sonar image obtained by using the Chebyshev window weighting method, Fig. 2(c) is a sonar image obtained by using the modified coefficient weighting method of the present application, and Fig. 2(d) is a comparison effect diagram of the azimuth direction slice at the 11m target of the above three methods.

[0080] From the simulation results, for the extended aperture imaging sonar array, the conventional uniform linear weighting method generates higher side lobes near the target, causing the target point to separate and blur; the Chebyshev window function weighting method reduces the side lobes in the angle region far from the target, but due to the non-uniformity of the virtual extended array, the Chebyshev window weighting causes high side lobes near the main lobe of the extended aperture imaging sonar image target, and multiple false targets near the true target. However, the modified coefficient weighting method proposed in the present application, for the extended aperture imaging sonar array, after compensation processing by the window function correction coefficient, the obtained beam side lobes are lower than-40dB, reducing the influence of high side lobes near the target, achieving the purpose of suppressing the side lobes of the extended aperture imaging sonar in the azimuth direction, and without raising the beam side lobes, improving the clarity of the extended aperture imaging sonar image.

[0081] As can be seen from the above, by introducing the constraints of the expected target signal strength and the beam pattern response sensitivity, the second-order cone programming constraint optimization problem about the window function correction coefficient is solved, the obtained window function correction coefficient is applied to the imaging process of the extended aperture imaging sonar, the suppression of the beam side lobes is realized, and the high-resolution high-definition imaging effect is realized.

[0082] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the examples, those skilled in the art should understand that modifications or equivalent replacements of the technical solutions of the present application do not deviate from the spirit and scope of the present application, and they should be covered in the scope of the claims of the present application.

Claims

1. A method for extended aperture sonar imaging based on coefficient correction, the method comprising: constructing a constraint of expected target signal strength and beam pattern response sensitivity, establishing a constraint optimization problem about window function correction coefficient, and solving to obtain the window function correction coefficient; using the window function correction coefficient to correct and compensate the beamforming weighting vector in the extended aperture sonar imaging process, and obtaining the extended aperture sonar image; the constraint of the expected target signal strength is expressed as: wherein, denotes a window function weight correction coefficient, w eb is a Chebyshev window function weight for a given sidelobe height; a TR (θ d ) is a steering vector of the extended aperture imaging sonar with a beam pointing angle of θ d , and the superscript H denotes a conjugate transpose. the constraint of the beam pattern response sensitivity is expressed as: wherein ξ is a constant set, and ||·|| is a 2-norm calculation symbol.

2. The method of claim 1, wherein, the constraint optimization problem about the window function correction coefficient is expressed as: wherein a TR (θ i ) is the extended aperture imaging sonar steering vector with beam pointing angle i Θ SL represents the side lobe region other than the first zero point; is a real number set.

3. The method of claim 2, wherein, In solving the second order cone programming constraint optimization problem about the window function correction coefficient, the following is obtained Without changing the value of the second order cone programming constraint optimization problem about the window function correction coefficient until is a real number, represents the window function weight correction coefficient.

4. The method of claim 3, wherein, When is a real number, the constraint optimization problem expression for the window function correction coefficient is converted to:

5. The coefficient correction based extended aperture sonar imaging method of claim 4, wherein, the converted constraint optimization problem about the window function correction coefficient is a second-order cone programming problem, and is solved by using sedumi software.

6. The method of claim 4, wherein, the using of the window function correction coefficient to correct and compensate the beamforming weighting vector in the extended aperture sonar imaging process, and obtaining the extended aperture sonar imaging, comprises: according to the angle resolution requirement, combining the phase center theorem and the constraint of the carrier platform size, designing the extended aperture sonar array, and determining the element position of the virtual array of the extended aperture sonar; The echo signals of N R channels are received by N R receive elements, respectively. The received echo signals of N R channels are subjected to window function weighting matched filter processing and waveform separation processing to obtain N R M T groups of echo data, M T is the number of transmitting elements. using the window function correction coefficient to correct and compensate the beamforming weighting vector, and obtaining the transmit-receive joint beamforming weighting vector of the extended imaging sonar; According to the transmit-receive joint beamforming weight vector pair N R M T The received echo data is preformed into multiple beams to obtain an extended aperture sonar image.

7. The method of claim 6, wherein, the steering vector of the virtual array is expressed as: wherein, denotes the Frobenius norm, a T is the steering vector of the sonar transmitting array of the extended aperture sonar, a R is the steering vector of the receiving array.

8. The method of claim 7, wherein, the beam pattern of the virtual array is expressed as: where d T is the distance between adjacent transmitting elements, λ is the wavelength corresponding to the center frequency of the transmitted signal, d R is the distance between adjacent receiving elements, and the variable Y p = sin θ - sin θ p , θ p is the direction angle of the pth target.

9. The coefficient correction based extended aperture sonar imaging method of claim 6, wherein, The transmit-receive joint beamforming weight vector W of the extended imaging sonar TR (θ d ) is given by

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