Method and device for estimating direction of underwater target

Abstract

The invention discloses a method and a device for estimating the direction of an underwater target. The method comprises the following steps: receiving an array signal obtained by detecting the underwater target; determining the order of a fractional order of Fourier transform for performing fractional domain transform on the array signal, and performing fractional domain transform on the array signal; generating a fractional domain wave beam corresponding to the signal after the fractional domain transformation based on the signal after the fractional domain transformation; generating a fractional domain array directional diagram for the fractional domain beam, wherein the fractional domain array directional diagram refers to a spatial spectrum formed by the fractional domain beam; generating a fractional domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional domain beam; and taking the fractional domain deconvolution beam as the direction of arrival of the underwater target, namely the direction of the underwater target. According to the method, the spatial resolution of underwater signal direction-of-arrival estimation is improved on the basis of underwater sound signal direction-of-arrival estimation based on deconvolution beam forming.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and particularly to a method and device for estimating the direction of an underwater target. Background Art

[0002] In underwater acoustic array signal processing, due to the complexity of the ocean environment, the signals of underwater acoustic targets are often covered by strong interference or background noise, which increases the difficulty of underwater acoustic target recognition.

[0003] Therefore, a solution is needed that can identify underwater targets, especially determine the direction of an underwater target and estimate the direction of the underwater target. Summary of the Invention

[0004] In view of this, the present invention provides a method and device for estimating the direction of an underwater target, which can solve the technical problem of estimating the direction of an underwater target.

[0005] To solve the above technical problem, the present invention is implemented as follows.

[0006] A method for estimating the direction of an underwater target, the method comprising:

[0007] Step S1: Receive the array signal obtained by detecting the underwater target;

[0008] Step S2: Determine the order of the fractional order of the Fourier transform for performing fractional domain transformation on the array signal, and perform fractional domain transformation on the array signal;

[0009] Step S3: Generate a fractional domain beam corresponding to the signal after fractional domain transformation based on the signal after fractional domain transformation;

[0010] Step S4: Generate a fractional domain array steering diagram for the fractional domain beam, where the fractional domain array steering diagram refers to the spatial spectrum formed by the fractional domain beam;

[0011] Step S5: Generate a fractional domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional domain beam;

[0012] Step S6: Use the fractional domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

[0013] Preferably, step S2: Determine the order of the optimal Fourier transform fractional order for performing fractional domain transformation on the array signal, and perform fractional domain transformation on the array signal, includes:

[0014] Step S21: Perform a sliding window process on the array signal to cut it into several segmented signals,

[0015] S(t) = s(τ)g(τ - t)

[0016] Wherein, s(t) is a segmented signal, g(t) is a window function, and s(τ) is the array signal;

[0017] Step S22: Perform fractional-order transformation on each segmented signal. For each segmented signal:

[0018] Determine the order range and step size of the fractional-order p of the Fourier transform based on the output signal-to-noise ratio, and determine the order of the fractional-order of the Fourier transform for performing fractional-domain transformation on the array signal; perform fractional-order Fourier transform on the segmented signal S(t) to obtain the fractional-domain signal X p (u),

[0019]

[0020] Wherein, K p (u, t) is the kernel function, and x(t) is the input signal, that is:

[0021]

[0022] Wherein, α = pπ / 2, α is the rotation angle, u is the domain value of the fractional-order Fourier transform, and δ(t - u) is the unit impulse response.

[0023] Preferably, the step S3: Generate a fractional-domain beam corresponding to the signal after fractional-domain transformation, including:

[0024] Step S31: Perform wavelet decomposition on each fractional-domain signal X p (u). The wavelet decomposition formula is:

[0025]

[0026] Wherein, c 0,k = f k , f k is the discrete sampling data of the fractional-domain signal, N is the number of sampling points, h, g are the decomposition filter bank coefficients, j is the jth layer of decomposition, c j,k is the low-frequency decomposition coefficient of the fractional-domain signal, d j,k is the high-frequency decomposition coefficient of the fractional-domain signal, and n is the number of decomposition layers;

[0027] Step S32: Reconstruct each fractional-domain signal after wavelet decomposition to obtain the reconstructed signal X' p (u);

[0028] Step S33: Based on each reconstructed signal X' p(u)Generate a fractional-domain beam corresponding to the array signal.

[0029] Preferably, in step S4: generate a fractional-domain array directivity diagram for the fractional-domain beam, where the fractional-domain array directivity diagram refers to the spatial spectrum formed by the fractional-domain beam. The generation method of the spatial spectrum is as follows:

[0030]

[0031] Use the value corresponding to the peak of beamforming as the direction estimation result of fractional-domain beamforming.

[0032] Preferably, wavelet decomposition is implemented by the Mallat fast algorithm.

[0033] An estimation device for the direction of an underwater target provided by the present invention, the device includes:

[0034] A signal acquisition module: configured to receive the array signal obtained by detecting the underwater target;

[0035] A first transformation module: configured to determine the order of the fractional order of the Fourier transform for performing fractional-domain transformation on the array signal, and perform fractional-domain transformation on the array signal;

[0036] A first beam module: configured to generate a fractional-domain beam corresponding to the signal after fractional-domain transformation based on the signal after fractional-domain transformation;

[0037] A spatial spectrum formation module: configured to generate a fractional-domain array directivity diagram for the fractional-domain beam, where the fractional-domain array directivity diagram refers to the spatial spectrum formed by the fractional-domain beam;

[0038] A second beam module: configured to generate a fractional-domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional-domain beam;

[0039] A direction determination module: configured to use the fractional-domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

[0040] A computer-readable storage medium provided by the present invention, where multiple instructions are stored in the storage medium; the multiple instructions are used to be loaded and executed by a processor to perform the method as described above.

[0041] An electronic device provided by the present invention, characterized in that the electronic device includes:

[0042] A processor for executing multiple instructions;

[0043] A memory for storing multiple instructions;

[0044] Among them, the multiple instructions are used to be stored by the memory and loaded and executed by the processor for the method as described above.

[0045] Beneficial technical effects brought by the present invention:

[0046] (1) Based on the deconvolution beamforming for the direction of arrival (DOA) estimation of underwater acoustic signals, the present invention improves the spatial resolution of the DOA estimation of underwater signals.

[0047] (2) The present invention realizes the high-resolution DOA estimation of broadband chirp signals under the conditions of small aperture and low signal-to-noise ratio.

[0048] (3) The present invention helps to realize the accurate detection and positioning of underwater targets. Description of the Drawings

[0049] Figure 1 It is a schematic flow chart of the method for estimating the direction where the underwater target is located according to the present invention;

[0050] Figure 2 It is a schematic diagram of the method for estimating the direction where the underwater target is located according to the present invention;

[0051] Figure 3 It is a comparison diagram of the deconvolution beam and the conventional beam according to the present invention;

[0052] Figure 4 It is a schematic structural diagram of the device for estimating the direction where the underwater target is located according to the present invention. Detailed Embodiments

[0053] The present invention will be described in detail below with reference to the drawings and embodiments.

[0054] As Figure 1 - Figure 2 shown, the present invention proposes a method for estimating the direction where an underwater target is located, and the method includes:

[0055] Step S1: Receive the array signal obtained by detecting the underwater target;

[0056] Step S2: Determine the order of the fractional order of the Fourier transform for performing the fractional domain transform on the array signal, and perform the fractional domain transform on the array signal;

[0057] Step S3: Generate a fractional domain beam corresponding to the signal after the fractional domain transform based on the signal after the fractional domain transform;

[0058] Step S4: Generate a fractional domain array steering diagram for the fractional domain beam, where the fractional domain array steering diagram refers to the spatial spectrum formed by the fractional domain beam;

[0059] Step S5: Generate a fractional domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional domain beam;

[0060] Step S6: Use the fractional-domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

[0061] Deconvolution is an effective solution to improve the spatial resolution of beamforming without increasing the array aperture. Deconvolution beamforming regards the spatial spectrum as the convolution of the spatial response of the receiving array to a unit-intensity point-source target (also known as the "directivity pattern") and the spatial distribution of the target energy. By using the deconvolution algorithm to weaken the influence of the array response and restore the real target spatial distribution, the high-resolution estimation of the direction of arrival can be achieved. The fractional Fourier transform of the present invention is a fractional-domain representation method formed by rotating the time-frequency domain coordinate axis counterclockwise around the origin by an arbitrary angle, and can analyze non-stationary signals. The fractional-domain beamforming method focuses the signal in the fractional domain through the fractional Fourier transform, and then estimates the direction of arrival through the narrowband beamforming method. As Figure 3 shown, it is an effective method for estimating the direction of arrival of signals.

[0062] The said step S2: Determine the order of the best Fourier transform for the fractional-domain transformation of the array signal, and perform the fractional-domain transformation on the array signal, including:

[0063] Step S21: Perform a sliding window process on the array signal and cut it into several segmented signals,

[0064] S(t) = s(τ)g(τ - t)

[0065] where s(t) is the segmented signal, g(t) is the window function, and s(τ) is the array signal;

[0066] Step S22: Perform fractional-order transformation on each segmented signal. For each segmented signal:

[0067] Based on the output signal-to-noise ratio, determine the order range and step size of the fractional order p of the Fourier transform, and determine the order of the fractional order of the Fourier transform for the fractional-domain transformation of the array signal; perform the fractional Fourier transform on the segmented signal S(t) to obtain the fractional-domain signal X p (u),

[0068]

[0069] where K p (u, t) is the kernel function, and x(t) is the input signal, that is:

[0070]

[0071] where, α = pπ / 2, where α is the rotation angle, u is the domain value of the fractional Fourier transform, and δ(t - u) is the unit impulse response.

[0072] The step S3: generating a fractional domain beam corresponding to the signal after fractional domain transformation based on the signal after fractional domain transformation, includes:

[0073] Step S31: performing wavelet decomposition on each fractional domain signal X p (u), and the wavelet decomposition formula is:

[0074]

[0075] where c 0,k = f k , f k is the discrete sampling data of the fractional domain signal, N is the number of sampling points, h and g are the coefficients of the decomposition filter bank, j is the j-th layer of decomposition, c j,k is the low-frequency decomposition coefficient of the fractional domain signal, d j,k is the high-frequency decomposition coefficient of the fractional domain signal, and n is the number of decomposition layers.

[0076] In this embodiment, the wavelet decomposition is implemented by the Mallat fast algorithm.

[0077] Step S32: reconstructing each fractional domain signal after wavelet decomposition to obtain the reconstructed signal X' p (u).

[0078] Step S33: generating a fractional domain beam corresponding to the array signal based on each reconstructed signal X' p (u).

[0079] The step S4: generating a fractional domain array steering diagram for the fractional domain beam, where the fractional domain array steering diagram refers to the spatial spectrum formed by the fractional domain beam, and the generation method of the spatial spectrum is:

[0080]

[0081] Taking the value corresponding to the peak of beamforming as the direction estimation result of fractional domain beamforming.

[0082] The step S5: generating a fractional domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional domain beam, includes:

[0083] In this embodiment, the output of fractional domain beamforming of the target signal can be expressed as the integral of the product of the complex directivity pattern of the array to the signal and the spatial distribution of the target signal over all target angles θ, that is:

[0084]

[0085] If the above formula is made into a function of the cosine value of the angle, it can be rewritten in the form of convolution:

[0086]

[0087] The R-L algorithm is an iterative algorithm based on Bayesian, which is applied to the deblurring problem and can be used as a deconvolution algorithm, given by the following formula:

[0088]

[0089] In the above formula, l represents the number of iterations. As the number of iterations increases, the deconvolution result s(n) approaches the sound source direction more closely.

[0090] The step S6: Take the fractional-domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

[0091] As Figure 4 shown, the present invention provides an estimation device for the direction where an underwater target is located. The device includes:

[0092] A signal acquisition module: configured to receive the array signal obtained by detecting the underwater target;

[0093] A first transformation module: configured to determine the order of the fractional order of the Fourier transform for performing the fractional-domain transformation on the array signal, and perform the fractional-domain transformation on the array signal;

[0094] A first beam module: configured to generate a fractional-domain beam corresponding to the signal after the fractional-domain transformation based on the signal after the fractional-domain transformation;

[0095] A spatial spectrum formation module: configured to generate a fractional-domain array pointing diagram for the fractional-domain beam, where the fractional-domain array pointing diagram refers to the spatial spectrum formed by the fractional-domain beam;

[0096] A second beam module: configured to generate a fractional-domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional-domain beam;

[0097] A direction determination module: configured to take the fractional-domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

[0098] A computer-readable storage medium provided by the present invention, wherein multiple instructions are stored in the storage medium; the multiple instructions are used to be loaded and executed by a processor for the method described above.

[0099] An electronic device provided by the present invention, characterized in that the electronic device includes:

[0100] A processor, configured to execute multiple instructions;

[0101] A memory for storing a plurality of instructions;

[0102] Wherein, the plurality of instructions are used to be stored by the memory and loaded and executed by the processor for the method as described above.

[0103] The above specific embodiments only describe the design principle of the present invention. The shapes and names of the components in this description can be different and are not restricted. Therefore, those skilled in the art of the present invention can modify or make equivalent replacements to the technical solutions recorded in the foregoing embodiments; and these modifications and replacements do not depart from the spirit and technical solutions of the present invention, and should all fall within the protection scope of the present invention.

Claims

1. A method for estimating the direction of an underwater target, characterized in that, Including: Step S1: Receive the array signal obtained by detecting the underwater target; Step S2: Determine the order of the fractional - order of the Fourier transform for performing fractional - domain transformation on the array signal, and perform fractional - domain transformation on the array signal; Step S3: Generate a fractional - domain beam corresponding to the signal after fractional - domain transformation based on the signal after fractional - domain transformation; Step S4: Generate a fractional - domain array steering diagram for the fractional - domain beam, where the fractional - domain array steering diagram refers to the spatial spectrum formed by the fractional - domain beam; Step S5: Generate a fractional - domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional - domain beam; Step S6: Take the fractional - domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

2. The method according to claim 1, characterized in that, The said Step S2: Determine the optimal order of the fractional - order of the Fourier transform for performing fractional - domain transformation on the array signal, and perform fractional - domain transformation on the array signal, including: Step S21: Perform sliding - window processing on the array signal and cut it into several segmented signals, S(t) = s(τ)g(τ - t) where s(t) is the segmented signal, g(t) is the window function, and s(τ) is the array signal; Step S22: Perform fractional - order transformation on each segmented signal. For each segmented signal: Determine the order range and step size of the fractional order p of the Fourier transform based on the output signal-to-noise ratio, and determine the order of the fractional order of the Fourier transform for performing fractional domain transformation on the array signal; perform fractional Fourier transform on the segmented signal S(t) to obtain the fractional domain signal X p (u), Among them, K p (u, t) is the kernel function, and x(t) is the input signal, that is: Among them, α = pπ / 2, where α is the rotation angle, u is the domain value of the fractional Fourier transform, and δ(t - u) is the unit impulse response.

3. The method according to claim 2, wherein The said Step S3: Generate a fractional - domain beam corresponding to the signal after fractional - domain transformation based on the signal after fractional - domain transformation, including: Step S31: Perform wavelet decomposition on each fractional-domain signal X p (u), and the wavelet decomposition formula is: where c 0,k = f k , f k is the discrete sampling data of the fractional-domain signal, N is the number of sampling points, h and g are the coefficients of the decomposition filter bank, j is the j-th layer of decomposition, c j,k is the low-frequency decomposition coefficient of the fractional-domain signal, d j,k is the high-frequency decomposition coefficient of the fractional-domain signal, and n is the number of decomposition layers; Step S32: Reconstruct each fractional-domain signal after wavelet decomposition to obtain the reconstructed signal X' p (u); Step S33: Generate a fractional-domain beam corresponding to the array signal based on each reconstructed signal X' p (u).

4. The method according to claim 3, wherein The said Step S4: Generate a fractional - domain array steering diagram for the fractional - domain beam, where the fractional - domain array steering diagram refers to the spatial spectrum formed by the fractional - domain beam. Among them, the generation method of the spatial spectrum is: P FrFB P(θ) = |Y(θ)| 2 Take the value corresponding to the peak of beamforming as the direction - estimation result of fractional - domain beamforming.

5. The method according to any one of claims 3-4, characterized in that, Wavelet decomposition is implemented by the Mallat fast algorithm.

6. An estimation device for the direction of an underwater target, characterized in that, Including: Signal acquisition module: Configured to receive the array signal obtained by detecting the underwater target; First transformation module: Configured to determine the order of the fractional - order of the Fourier transform for performing fractional - domain transformation on the array signal, and perform fractional - domain transformation on the array signal; First beam module: Configured to generate a fractional - domain beam corresponding to the signal after fractional - domain transformation based on the signal after fractional - domain transformation; Spatial spectrum formation module: Configured to generate a fractional - domain array steering diagram for the fractional - domain beam, where the fractional - domain array steering diagram refers to the spatial spectrum formed by the fractional - domain beam; Second beam module: Configured to generate a fractional - domain deconvolution beam corresponding to the array signal based on the spatial spectrum formed by the fractional - domain beam; Direction determination module: Configured to take the fractional - domain deconvolution beam as the direction of arrival of the underwater target, that is, the direction of the underwater target.

7. A computer - readable storage medium, in which multiple instructions are stored; the multiple instructions are used to be loaded and executed by a processor to perform the method according to any one of claims 1 - 5.

8. An electronic device, characterized in that, The said electronic device includes: A processor for executing multiple instructions; A memory for storing multiple instructions; Among them, the multiple instructions are used to be stored by the memory and loaded and executed by the processor to perform the method according to any one of claims 1 - 5.

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