CN116359893B - Matching field underwater sound source positioning method suitable for unsynchronized arrays - Google Patents
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Abstract
The invention discloses a matching field underwater sound source positioning method suitable for an unsynchronized array, which aims at solving the problem that the existing matching field positioning algorithm cannot be applied to the unsynchronized array, successfully eliminates the frequency spectrum of an unknown sound source and the phase deviation generated by unsynchronized reception by normalizing and taking amplitude values of unsynchronized reception signals, and simultaneously improves positioning resolution by utilizing a compressed sensing algorithm to obtain a high-resolution low-sidelobe positioning result. The invention does not require strict synchronization of the array receiving signals, has higher positioning precision and resolution, is suitable for asynchronous array positioning scenes under high signal-to-noise ratio, and has simple steps and good reliability.
Description
Technical Field
The invention relates to a sonar signal processing algorithm, in particular to a matching field underwater sound source positioning method suitable for an asynchronous array, and belongs to the field of sonar signal processing.
Background
In general, array processing methods such as matched field positioning or DOA estimation require a synchronous array to determine the arrival delay difference of signals between different array elements. However, a large-size synchronous array requires accurate time alignment, is expensive to construct, and cannot be used in array processing when one or more of the array elements of the synchronous array are clocked out. In practical sea test, a user can often encounter that a received signal is acquired through an unsynchronized array formed by a plurality of self-contained hydrophones, and the conventional synchronous array signal processing method is not applicable. Therefore, the research of the underwater sound source localization method of the matching field suitable for the asynchronous array has important engineering significance and practical value.
Disclosure of Invention
The invention aims to provide a matching field underwater sound source positioning method suitable for an unsynchronized array, which can realize underwater sound source positioning in a passive mode under the condition that the array receiving signals are not strictly synchronized.
In order to solve the technical problems, the invention comprises the following steps:
step 1: the data received from the hydrophone group is extracted and formed into an array received signal, so that the received signals are approximately located in the same time window, and strict synchronization of the array received signals is not required at this time. And meanwhile, preprocessing array received data, and obtaining frequency information of a sound source signal through technologies such as time-frequency analysis and the like.
Step 2: and selecting a proper sound propagation model according to information such as sea depth, sound source frequency and the like, determining grid division and sound source searching range, inputting array parameters, array receiving data and environment parameter information (sea depth, sound velocity profile, substrate parameters and the like).
Step 3: and normalizing the received data of the asynchronous array and the copy field data calculated by the acoustic propagation model and taking amplitude value for processing.
Step 4: and (3) improving the positioning resolution ratio by using a compressed sensing algorithm, initializing parameters and carrying out iterative solution by using a sparse Bayesian learning update formula.
Step 5: and outputting the sound source estimation position according to the iteration result.
Further:
the normalized amplitude value processing described in step 3 can be described as:
when noise is not considered, the first frequency domain snapshot y of the N-ary asynchronous vertical receiving array at frequency ω l May be represented by the sound source spectrum and the spectrum of the channel transfer function. At this time, the non-synchronous array receiving signals and the channel transfer function are normalized and subjected to amplitude value extraction processing, and vector 2 norm normalization is adopted in the processing.
Where S (ω) represents the sound source spectrum,indicating that the sound source is located +.>A channel transfer function spectrum at>Representing sound source position information, & lt + & gt>The phase offset generated in each array element due to asynchronous reception is represented as an unknown, and the superscript T represents the vector transposition.For normalizing the coefficient, +.>And->And respectively normalizing the asynchronous receiving signal and the channel transfer function after amplitude value acquisition. The frequency spectrum of the unknown sound source and the phase deviation generated by asynchronous receiving are successfully eliminated through normalization amplitude-taking processing.
The sparse bayesian learning update formula described in step 4 can be described as:
in the method, in the process of the invention,the superscript + represents the mole-penrose generalized inverse of the matrix for a matrix of K non-zero value-corresponding copy field dictionary vectors in γ. />For normalized sampling covariance matrix after taking amplitude, wherein +.>In the iteration process, when the noise variance is smaller than a certain threshold or the iteration reaches the maximum number of times, the iteration is terminated, and the noise threshold is generally 0.001, and the maximum number of iterations is 100.
The beneficial effects of the invention are as follows:
the invention provides a method for realizing underwater sound source positioning by utilizing a passive mode under the condition that array receiving signals are not strictly synchronous. According to the method, the frequency spectrum of an unknown sound source and the phase deviation generated by asynchronous receiving are successfully eliminated by normalizing and taking the amplitude of an asynchronous receiving signal, and meanwhile, the positioning resolution is improved by utilizing a compressed sensing algorithm, so that a high-resolution low-sidelobe positioning result is obtained. The invention does not require strict synchronization of the array receiving signals, and has higher positioning precision and resolution.
The method provided by the invention is suitable for the asynchronous array positioning scene under the high signal-to-noise ratio, and has simple steps and good reliability.
Drawings
FIG. 1 is a flow chart of a matched field underwater positioning method applicable to an asynchronous array of the present invention;
FIG. 2 is an environmental schematic of a demonstration test of an embodiment
FIG. 3 (a) is an example simulated synchronous array receive signal;
FIG. 3 (b) is a diagram of an example simulated asynchronous array received signal
FIG. 4 (a) is a diagram of the positioning result of a conventional Bartlett method for processing asynchronous signals;
fig. 4 (b) is a diagram of the positioning result of the algorithm proposed by the present invention for processing the asynchronous signal.
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
Aiming at the problem that the prior matching field positioning algorithm requires synchronous array receiving signals and cannot process asynchronous signals, the invention provides a method for realizing underwater sound source positioning by utilizing a passive mode under the condition that the array receiving signals are not strictly synchronous.
As shown in fig. 1, a flow chart of a matching field underwater positioning method suitable for an unsynchronized array is shown. The asynchronous array receives signals, which essentially cannot accurately determine the arrival time of the signals, i.e. cannot determine the delay difference between the arrival of the signals at different array elements. Thus, compared to a synchronous array, the signal received by each element of an unsynchronized array is time shifted in the time domain, which is equivalent to a phase shift in the frequency domain, and those beamforming algorithms that rely on the difference in the arrival time delay of the received signal fail at this point. The invention provides the method for normalizing the received signals, only matching the amplitude values to realize the matching field positioning of the asynchronous array, and simultaneously improving the positioning resolution by using a compressed sensing algorithm to obtain a high-resolution low-sidelobe positioning result. The method does not need to know the time delay difference between array elements, and is simple to realize.
The specific implementation method comprises the following steps:
step 1: the data received from the hydrophone group is extracted and formed into an array received signal, so that the received signals are approximately located in the same time window, and strict synchronization of the array received signals is not required at this time. And meanwhile, preprocessing array received data, and obtaining frequency information of a sound source signal through technologies such as time-frequency analysis and the like.
Step 2: and selecting a proper sound propagation model according to sea depth and sound source frequency information, determining grid division and a sound source searching range, and inputting array parameters, array receiving data and environment parameter information (sea depth, sound velocity profile, substrate parameters and the like).
Step 3: and normalizing the received data of the asynchronous array and the copy field data calculated by the acoustic propagation model and taking amplitude value for processing.
When noise is not considered, the first frequency domain snapshot y of the N-ary asynchronous vertical receiving array at frequency ω l May be represented by the sound source spectrum and the spectrum of the channel transfer function.
Where S (ω) represents the sound source spectrum,indicating that the sound source is located +.>A channel transfer function spectrum at>Representing sound source position information, & lt + & gt>The phase offset generated in each array element due to asynchronous reception is represented as an unknown, and the superscript T represents the vector transposition. Normalizing the non-synchronous array received signals by using a vector 2 norm and taking amplitude value to obtain the following steps:
in the method, in the process of the invention,for the non-synchronous received signal after normalized amplitude-taking, < >>For normalizing the coefficient, the spectrum normalization of the channel transfer function can be obtained by the same method:
the single snapshot data at this time can be represented as:
in the method, in the process of the invention,for normalizing the channel transfer function after taking the amplitude, < + >>The amplitude of the sound source is taken for the first snapshot when +.>When the sound source exists, the value is 1, otherwise 0,/or the like is taken>Is the noise amplitude data of the first snapshot. When the signal-to-noise ratio of the received signal is high, the influence of noise on the positioning result is negligible.
Step 4: and (3) improving the positioning resolution ratio by using a compressed sensing algorithm, initializing parameters and carrying out iterative solution by using a sparse Bayesian learning update formula.
The frequency spectrum of an unknown sound source and the phase deviation generated by asynchronous receiving are successfully eliminated through normalization amplitude extraction, but the direct positioning side lobe level is higher because only sound field amplitude information is utilized at the moment, so that the positioning resolution is improved through a compressed sensing algorithm by utilizing the sparsity of the sound field.
When a sound field has a plurality of sound sources, and the number of sound sources is assumed to be K, when the number of snapshots is L, it is possible to obtain:
in the method, in the process of the invention,for the normalized amplitude signal received by the asynchronous array for L shots,and D is grid points divided by the area to be searched for the copy field dictionary after the amplitude value is normalized. />Wherein column vector->Representing the sound source amplitude at different grid points under the first snapshot, and taking 1 if the sound source exists at the grid points or taking 0 if the sound source exists at the grid points. />Is noise amplitude data.
In general, the number of underwater sound sources is limited, i.e., D > K, so equation (5) is a system of under-determined equations with sparse constraints. The positioning problem can be converted into an underdetermined equation problem solving the following sparse constraint.
At this time, compressive sensing class calculation can be utilizedSolving the above 0 The norm problem is substituted into the sparse Bayesian framework for iterative solution. Assuming that the unknown sound source amplitude follows a Gaussian distribution with zero mean value, and that different snapshot data are independent of each other, the prior probability of X can be obtained by the following formula
Wherein Γ=diag (γ) 1 ,...,γ D ) =diag (γ) is a diagonal covariance matrix, where vector γ is the sound source power on all grid points in the area to be searched. Assuming that the noise satisfies zero mean, the variance is sigma 2 Is obtainable according to Bayesian theoryProbability density function of (2)
In the covariance matrixI N The super parameter gamma can be obtained by maximizing the formula (8) as an N-order unit array d Sum sigma 2 Is a value of (2).
The sound source power gamma and the noise variance sigma can be obtained through derivation 2 Iterator of (a)
In the method, in the process of the invention,the superscript + represents the mole-penrose generalized inverse of the matrix for a matrix of K non-zero value-corresponding copy field dictionary vectors in γ. />For normalized sampling covariance matrix after taking amplitude, wherein +.>In the iteration process, when the noise variance is smaller than a certain threshold or the iteration reaches the maximum number of times, the iteration is terminated, and the noise threshold is generally 0.001, and the maximum number of iterations is 100.
Step 5: and outputting the sound source estimation position according to the iteration result.
And when the iteration is terminated, the first K maximum peaks in the sound source power gamma are taken to be the corresponding sound source positions.
The technical effects of the present invention will be described in detail with reference to a demonstration test.
The demonstration test adopts a workbench 93 environment model, as shown in fig. 2, which is an environment schematic diagram, in the simulation, the sound source frequency is 250Hz, the sound source depth is 50m, the receiving and transmitting horizontal distance is 7.5km,10 receiving hydrophones are uniformly distributed at the depth of 10-100 m, the array element distance is 10m, and the signal to noise ratio is set to be 0dB under the condition of additive Gaussian white noise.
As shown in fig. 3 (a) and fig. 3 (b), the signal diagram is a simulated array received signal diagram, fig. 3 (a) is a synchronous array received signal diagram, and fig. 3 (b) is an asynchronous array received signal diagram, and it can be seen by comparison that the arrival delay difference of the received signal between different array elements cannot be determined under the asynchronous array receiving condition.
And processing the asynchronous received signal, intercepting a time window of 0.2-0.8 s for processing, taking 10 snapshots, taking 50% of signal overlapping rate, and selecting a rectangular window function. Depth search step length is 1m, and the range is 0-100 m; the distance searching step length is 1m, and the range is 0-10 km.
Fig. 4 (a) and 4 (b) are graphs of positioning results, in which circle symbols represent real sound source positions and cross symbols represent algorithm estimation results. Fig. 4 (a) is a positioning result diagram of a conventional Bartlett matching field method, and the positioning result has a large deviation, so that the conventional matching field method cannot be applied to asynchronous array signal processing, and fig. 4 (b) is a positioning result diagram of the method provided by the invention, wherein the depth positioning result is 50m, the distance positioning result is 7.489km, and the method does not require strict synchronization of array receiving signals, and has higher precision and resolution.
The method provided by the invention is suitable for the asynchronous array positioning scene under the high signal-to-noise ratio, and has simple steps and good reliability.
Claims (2)
1. The method for locating the underwater sound source of the matching field suitable for the asynchronous array is characterized by comprising the following steps of:
step 1: extracting data received by the hydrophone from the hydrophone group and forming an array receiving signal, so that the receiving signals are approximately positioned in the same time window, and the array receiving signals are not required to be strictly synchronized at the moment;
preprocessing array received data to obtain frequency information of a sound source signal;
step 2: selecting a proper sound propagation model according to sea depth and sound source frequency information, determining grid division and a sound source searching range, and inputting array parameters, array receiving data and environment parameter information;
step 3: normalizing the received data of the asynchronous array and the copy field data calculated by the acoustic propagation model, and taking amplitude value for processing;
the normalization and amplitude value taking process in the step 3 is described as follows:
when noise is not considered, the first frequency domain snapshot y of the N-ary asynchronous vertical receiving array at frequency ω l Represented by the sound source spectrum and the spectrum of the channel transfer function;
simultaneously, carrying out normalization amplitude value extraction processing on the asynchronous array receiving signals and the channel transfer function, and adopting vector 2 norm normalization in the processing;
where S (ω) represents the sound source spectrum,indicating that the sound source is located +.>A channel transfer function spectrum at>Representing sound source position information, & lt + & gt>Representing phase offsets generated at each array element due to asynchronous reception, belonging to an unknown quantity, the superscript T representing a vector transpose;for normalizing the coefficient, +.>And->Respectively normalizing the asynchronous receiving signal and the channel transfer function after amplitude value acquisition; the frequency spectrum of an unknown sound source and the phase deviation generated by asynchronous receiving are successfully eliminated through normalization amplitude-taking processing;
step 4: the positioning resolution is improved by using a compressed sensing algorithm, and parameters are initialized and are subjected to iterative solution through a sparse Bayesian learning updating formula;
step 5: and outputting the sound source estimation position according to the iteration result.
2. A matched field underwater sound source localization method suitable for use in an unsynchronized array according to claim 1, wherein: the sparse Bayes learning update formula described in step 4 is described as:
where γ is the power of the sound source at all grid points in the area to be searched, L is the number of snapshots, I N Is an N-order unit array,normalized amplitude signal received for asynchronous array under L shots, +.>The matrix formed by the copy field dictionary vectors corresponding to K non-zero values in gamma is marked with the superscript +to represent the mole-Penrose generalized inverse of the matrix; />For normalized sampling covariance matrix after taking amplitude, wherein +.>The iteration is terminated during the iteration when the noise variance is less than a threshold or the iteration reaches a maximum number of iterations.
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