Deep sea sound source depth estimation method based on complementary integrated empirical mode decomposition

Abstract

The invention particularly relates to a deep sea sound source depth estimation method based on complementary integrated empirical mode decomposition. The deep sea sound source depth estimation method comprises the steps of broadband beam forming, interference feature extraction based on complementary integrated empirical mode decomposition and depth mapping of a frequency-vertical arrival angle spectrum. According to the method, complementary integrated empirical mode decomposition is utilized to decompose a frequency-glancing angle spectrum obtained through broadband beam forming into an intrinsic mode function with a certain cumulative variance contribution rate, and then the intrinsic mode function is mapped into an ambiguity plane of sound source depth; therefore, accurate estimation of the broadband sound source depth under the condition of unknown environmental parameters is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of deep-sea sound source depth passive estimation, and particularly relates to a deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition. BACKGROUND

[0002] In the related art, depth information, as one of the key criteria for distinguishing surface and underwater targets, has important significance for target detection, positioning and identification. In the deep-sea environment, due to the low environmental noise in the direct sound area and the good propagation characteristics, the sensors / arrays placed at a large depth can receive high signal-to-noise ratio radiated noise from the near-surface target, so as to realize passive detection of a wide range of underwater acoustic targets.

[0003] In the prior art, many passive estimation methods for the depth of deep-sea underwater targets have been proposed, which are generally divided into three categories: methods based on matched field processing, methods based on multi-path arrival structure, and methods based on interference characteristics. Among them, matched field processing, as a typical mode-based processing technology, was applied to deep-sea sound source positioning early and verified by sea trials, but this method is greatly affected by environmental mismatch, and usually requires a large-scale array to improve the positioning accuracy, which limits its engineering application in deep-sea underwater target depth estimation. The methods based on deep-sea multi-path arrival structure and based on sound field interference characteristics are essentially the same, both of which utilize the periodic variation characteristics of the received sound field intensity caused by the coherent superposition of direct waves and sea surface reflected waves (Lloyd's mirror interference effect) to realize target depth estimation. Among them, the method based on multi-path arrival structure can solve the distance and depth of the underwater target by extracting the multi-path arrival angle and multi-path time delay difference from the received signal and combining the geometric position relationship between the target and the receiver, but the multi-path arrival structure is not obvious under low signal-to-noise ratio conditions, and the estimation of the time delay difference usually requires longer integration time and larger processing bandwidth, which has higher requirements for the processing capacity and sampling rate of the receiving system. In addition, the distance-frequency interference structure can be obtained by Fourier transform of the multi-path arrival structure at different distances, and the depth of the target sound source can be estimated by using the periodic oscillation characteristics of the frequency domain interference structure.

[0004] At present, in the existing methods for target depth estimation using deep-sea sound field interference structure, most of them are based on the idea of matched beam intensity processing, and environmental mismatch and the accuracy of the sound field model itself are the main factors limiting their application to the actual engineering level.

[0005] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present application, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The application provides a deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition, a computer program product and a storage medium, which can realize accurate estimation of the depth of a wideband sound source under unknown environmental parameters, and can overcome the defects in the prior art to a certain extent.

[0007] Other characteristics and advantages of the application will become apparent from the following detailed description, or will be learned by practice of the application.

[0008] According to a first aspect of the application, a deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition is provided, and the method comprises:

[0009] The bottom-mounted vertical linear array in the direct sound area of the deep sea receives the incoming wave signal of the wideband sound source, and performs wideband beamforming processing to obtain the beam output power of the minimum variance distortionless response of the wideband sound source;

[0010] The beam output power is subjected to complementary ensemble empirical mode decomposition to extract interference characteristics to obtain a reconstructed frequency-vertical angle of arrival spectrum;

[0011] The reconstructed frequency-vertical angle of arrival spectrum is mapped to the grazing angle-depth domain to form an ambiguity plane of the depth of the wideband sound source, and a target depth estimation result of the wideband sound source is obtained based on the ambiguity plane.

[0012] In some example embodiments, the incoming wave signal of the wideband sound source comprises: wideband sound source radiated noise, deep-sea environmental background noise.

[0013] In some example embodiments, the wideband beamforming processing of the incoming wave signal to obtain the beam output power of the minimum variance distortionless response of the wideband sound source comprises:

[0014] The response vector of the vertical linear array to the incoming wave signal is obtained;

[0015] The response response vector is subjected to beamforming processing based on the sampling covariance matrix to obtain the beam output power of the minimum variance distortionless response.

[0016] In some example embodiments, the beam output power is subjected to complementary ensemble empirical mode decomposition to extract interference characteristics to obtain a reconstructed frequency-vertical angle of arrival spectrum, comprising:

[0017] The total average number N is configured;

[0018] The frequency-vertical angle of arrival spectrum corresponding to the beam output power is extracted to obtain l The column vector B MV corresponding to the grazing angle l , and the column vector BMV (f, sinθ l ) adding white noise signals to obtain a beam output power sequence, comprising:

[0019]

[0020] wherein, l = 1, 2, …, L; W n is the white noise sequence added for the nth time, n = 1, 2, …, N;

[0021] decomposing the and using an empirical mode decomposition method to obtain intrinsic mode function components and residual terms thereof:

[0022]

[0023] wherein, and are the qth order intrinsic mode functions decomposed from and , respectively; and are corresponding residual terms;

[0024] averaging each order intrinsic mode component and residual:

[0025]

[0026] calculating variance contribution rates of each order intrinsic mode and sorting them in descending order according to the contribution rates, and summing the first λ order IMFs whose cumulative variance contribution rates are greater than ε: q

[0027]

[0028] wherein, represents the variance of the qth order intrinsic mode function component;

[0029] performing the above steps on the beam output column vectors at all grazing angles, and reconstructing a new frequency-vertical angle of arrival spectrum:

[0030] In some example embodiments, the reconstructed frequency-vertical angle of arrival spectrum is mapped to a grazing angle-depth domain to form a wideband sound source depth ambiguity plane, and a target depth estimation result of the wideband sound source is obtained based on the ambiguity plane, comprising:

[0031] The reconstructed new frequency-vertical angle of arrival spectrum B IMF (f, sinθ) is mapped to a grazing angle-depth domain to form a sound source depth ambiguity plane:

[0032] ​

[0033] wherein f1 and f2 are upper and lower limits of the processing frequency band, respectively;

[0034] The maximum value of F(sinθ, z) is configured as the target depth estimation result of the underwater sound source.

[0035] In some example embodiments, the wideband sound source comprises one or more;

[0036] The method further comprises:

[0037] When the wideband sound source comprises multiple, the beam output power is subjected to complementary ensemble empirical mode decomposition, and interference features corresponding to the multiple wideband sound sources are extracted to obtain reconstructed frequency-vertical angle of arrival spectra corresponding to each wideband sound source;

[0038] The reconstructed frequency-vertical angle of arrival spectrum corresponding to each wideband sound source is respectively mapped to a grazing angle-depth domain to form a blurring plane of the depth of each wideband sound source;

[0039] The target depth estimation result corresponding to each wideband sound source is obtained based on the blurring plane respectively.

[0040] According to a second aspect of the present application, a deep-sea sound source depth estimation system based on complementary ensemble empirical mode decomposition is provided, and the system comprises:

[0041] A bottom-mounted vertical linear array in a deep-sea direct sound area, configured to receive a wave signal of a wideband sound source;

[0042] A terminal device configured to receive the wave signal and execute the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition, and output a target depth estimation result of the wideband sound source.

[0043] According to a third aspect of the present application, a computer program product is provided, and a computer program is stored on the computer program product, and the computer program is executed by a processor to implement the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition.

[0044] According to a fourth aspect of the present application, a storage medium is provided, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition.

[0045] According to a fifth aspect of the present application, an electronic device is provided, and the electronic device comprises:

[0046] A processor; and

[0047] A memory configured to store executable instructions of the processor;

[0048] The processor is configured to implement the above-mentioned deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition by executing the executable instructions.

[0049] The deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition provided by the embodiment of the present application decomposes the beam output sequence of the sound source in the frequency-sweep angle domain (frequency-vertical angle spectrum) into intrinsic modes with a certain cumulative variance contribution rate by using complementary ensemble empirical mode decomposition, and further maps the intrinsic modes to a depth ambiguity plane according to the corresponding relationship between the sound source depth and the interference period, so as to realize the depth estimation of the underwater wideband sound source. The method can effectively overcome the problems of low precision and many pseudo-peak peaks of the traditional Fourier transform method, and can still realize the accurate estimation of the sound source depth under strong environmental noise conditions. Meanwhile, the method of the present application does not require prior information of environmental parameters, and has good environmental adaptability.

[0050] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0051] The drawings incorporated into the specification and forming part of the specification, show embodiments consistent with the present application, and together with the specification, serve to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0052] Figure 1 The schematic diagram of the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition according to an exemplary embodiment of the present application is shown schematically;

[0053] Figure 2 The schematic diagram of the implementation process of the deep-sea sound source depth estimation method according to an exemplary embodiment of the present application is shown schematically;

[0054] Figure 3 The schematic diagram of the deep-sea sound velocity profile according to an exemplary embodiment of the present application is shown schematically;

[0055] Figure 4 The schematic diagram of the Lloyd mirror sound field interference and the schematic diagram of the MVDR wideband beam output power according to an exemplary embodiment of the present application are shown schematically;

[0056] Figure 5 The schematic diagram of the depth estimation results of the sound source by the traditional Fourier transform method and the method proposed in the present application according to an exemplary embodiment of the present application is shown schematically;

[0057] Figure 6Fig. 1 shows a schematic diagram of depth estimation results of a traditional Fourier transform based method and the method proposed in the present application for different depth sound sources;

[0058] Figure 7 Fig. 2 shows a schematic diagram of depth estimation results of a traditional Fourier transform based method and the method proposed in the present application for different horizontal distance sound sources;

[0059] Figure 8 Fig. 3 shows a schematic diagram of depth separation results of a traditional Fourier transform based method and the method proposed in the present application for multiple sound sources;

[0060] Figure 9 Fig. 4 shows a schematic diagram of an electronic device according to an example embodiment of the present application. DETAILED DESCRIPTION

[0061] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0062] In addition, the drawings are to be regarded as being schematic only and therefore are not intended to limit the scope of the application. Like reference numerals are used to designate like parts throughout the several views and the repetitive description thereof will be omitted. Some of the block components shown in the drawings can be functional blocks and do not necessarily correspond to physical or logical independent entities. These functional blocks can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0063] To overcome the disadvantages and deficiencies of the prior art, the present example embodiment provides a deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition, as shown in Figure 1 The method can include the following steps:

[0064] In step S11, the bottom-mounted vertical linear array in the direct sound area of the deep sea receives the incoming wave signal of the broadband sound source and performs broadband beamforming processing to obtain the beam output power of the minimum variance distortionless response of the broadband sound source.

[0065] In step S12, the beam output power is subjected to complementary ensemble empirical mode decomposition to extract interference features and obtain the reconstructed frequency-vertical angle of arrival spectrum.

[0066] Step S13, mapping the reconstructed frequency-vertical angle of arrival spectrum to the grazing angle-depth domain to form a wideband sound source depth ambiguity plane, and obtaining a target depth estimation result of the wideband sound source based on the ambiguity plane.

[0067] In the following, the various steps of the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition in the example embodiment will be described in more details in combination with the accompanying drawings and examples.

[0068] In step S11, the bottom-standing vertical linear array in the direct sound area of the deep sea receives the incoming wave signal of the wideband sound source and performs wideband beamforming processing to obtain the minimum variance distortionless response beam output power of the wideband sound source.

[0069] For example, the step S11 can specifically include:

[0070] Step S111, obtaining a response vector of the vertical linear array to the incoming wave signal;

[0071] Step S112, performing beamforming processing on the response response vector based on the sample covariance matrix to obtain the minimum variance distortionless response beam output power.

[0072] Specifically, the incoming wave signal received by the vertical linear array includes the signal of the wideband sound source, the wideband sound source radiation noise, and the deep-sea environmental background noise. For the wideband sound source, the frequency-vertical angle of arrival spectrum is obtained by performing wideband beamforming processing on the received sound field of the vertical linear array. Under the assumption of far-field plane wave, for the incoming wave signal in the direction of θ0, the response vector (scanning vector) of the array has the following form:

[0073]

[0074] Where f is the frequency of the sound field, M is the number of array elements, d and c0 are the array element spacing and the sound speed of seawater, respectively.

[0075] The scanning vector is brought into the MVDR beamformer to calculate the wideband beam output power. Then the minimum variance distortionless response (MVDR) beam output power is:

[0076]

[0077] Where R f is the sample covariance matrix at the frequency f, and H represents the conjugate transpose.

[0078] In step S12, the beam output power is decomposed based on the complementary ensemble empirical mode to extract interference features to obtain the reconstructed frequency-vertical angle of arrival spectrum.

[0079] For example, the above step S12 can specifically include:

[0080] Step S121, configure the overall average number N;

[0081] Step S122, extract θ l corresponding column vector B MV (f,sinθ l ) under each l MV (f,sinθ l ) and add white noise signal to obtain the beam output power sequence;

[0082] Step S123, decompose and using empirical mode decomposition method to obtain intrinsic mode function components and residual terms;

[0083] Step S124, average each order intrinsic mode component and residual;

[0084] Step S125, calculate the variance contribution rate of each order intrinsic mode and sort them in descending order according to the contribution rate, and sum the first λ order IMF' q with cumulative variance contribution rate greater than ε;

[0085] Step S126, execute the above steps on the beam output column vector under all grazing angles, and reconstruct the new frequency-vertical angle of arrival spectrum.

[0086] Specifically, for a fixed underwater broadband sound source, the beam output power (frequency-grazing angle spectrum) of the receiving vertical array will produce a light and dark alternating frequency interference fringe, and the period of this light and dark alternation (interference period) depends on the depth of the underwater sound source. By performing complementary ensemble empirical mode decomposition on the frequency-grazing angle spectrum, the interference period can be accurately obtained. The specific decomposition process includes:

[0087] First step: set the overall average number N.

[0088] Second step: extract θ l (l=1,2,…,L) corresponding column vector B MV (f,sinθ l ) under each l MV (f,sinθ l ) and add white noise signal:

[0089]

[0090] Where W n is the white noise sequence added for the nth time (n=1,2,…,N).

[0091] Third step: decompose the signal using Empirical Mode Decomposition method to obtain its intrinsic mode function components and residual term: and

[0092]

[0093] where, and are the qth order intrinsic mode function components decomposed from and and are the corresponding residual terms, representing the average trend of the data.

[0094] For example, Empirical Mode Decomposition (EMD) is an adaptive signal processing method; the specific implementation process of decomposition step EMD can include:

[0095] 1). Identify extreme points: extract all local maximum and minimum points of the signal;

[0096] 2). Construct envelope: fit upper and lower envelope lines by cubic spline interpolation;

[0097] 3). Calculate mean: calculate the average of the upper and lower envelope lines to generate a local mean function;

[0098] 4). Iterative screening: subtract the local mean from the original signal and repeat the screening until the IMF condition is met;

[0099] 5) Extract residual: separate the decomposed IMF from the original signal, and repeat the above steps for the remaining signal.

[0100] Fourth step: average each order intrinsic mode component and residual (i.e. complementary set of empirical mode decomposition results):

[0101]

[0102] Fifth step: calculate the variance contribution rate of each order intrinsic mode and sort it in descending order according to the contribution rate (IMF' (q)), and sum the first λ order IMF' (q) whose cumulative variance contribution rate is greater than ε: q q

[0103]

[0104] where, represents the variance of the qth order intrinsic mode function component.

[0105] ​​​​Step 6: Perform the previous 5 steps for the beam output column vectors at all grazing angles and reconstruct a new frequency-vertical angle of arrival spectrum as follows:

[0106]

[0107] where, before decomposition, a pair of sign-opposite white noise signal sequences are added to the beam output intensity sequence B MV (f, sinθ l ) to reduce the impact of impulse signals (such as line spectrum fluctuation, distant navigation noise, etc.) and improve the robustness of subsequent decomposition.

[0108] In step S13, the reconstructed frequency-vertical angle of arrival spectrum is mapped to the grazing angle-depth domain to form a wideband sound source depth ambiguity plane, and a target depth estimation result of the wideband sound source is obtained based on the ambiguity plane.

[0109] For example, the above step S13 can specifically include:

[0110] Step S131, the reconstructed new frequency-vertical angle of arrival spectrum B IMF (f, sinθ) is mapped to the grazing angle-depth domain to form a sound source depth ambiguity plane;

[0111] Step S132, the maximum value of F(sinθ, z) corresponds to the depth estimation result of the underwater sound source, and is configured as the target depth estimation result.

[0112] Specifically, the reconstructed new frequency-vertical angle of arrival spectrum in the foregoing step is mapped to the grazing angle-depth domain to form a sound source depth ambiguity plane by the following formula:

[0113]

[0114] Where f1 and f2 are the upper and lower limits of the processing frequency band, respectively.

[0115] Then, the maximum value of F(sinθ, z) can correspond to the depth estimation result of the underwater sound source.

[0116] For example, the wideband sound source includes one or more. When the wideband sound source includes multiple, the method further includes:

[0117] Step S21, based on the complementary ensemble empirical mode decomposition, the beam output power is decomposed to extract the interference features corresponding to the multiple wideband sound sources to obtain the reconstructed frequency-vertical angle of arrival spectrum corresponding to each wideband sound source;

[0118] Step S22, respectively, the reconstructed frequency-vertical angle of arrival spectrum corresponding to each wideband sound source is mapped to the grazing angle-depth domain to form the ambiguity plane of each wideband sound source depth;

[0119] Step S23, respectively, based on each ambiguity plane, the target depth estimation result corresponding to each wideband sound source is obtained.

[0120] Specifically, when the received incoming wave signal includes sound signals of multiple different wideband sound sources, the spectral features corresponding to each wideband sound source can be extracted in the step of interference feature extraction based on complementary ensemble empirical mode decomposition, so that the reconstructed new frequency-vertical angle of arrival spectrum of each wideband sound source can be mapped to the corresponding grazing angle-depth domain in the step of depth mapping of the frequency-vertical angle of arrival spectrum, thereby realizing the depth estimation of each wideband sound source.

[0121] For example, the simulation environment is a typical deep sea area, the local water depth is 4000 m, the seabed topography is flat and isotropic, the sound speed profile is as shown in Figure 3 , the sound channel axis depth is about 1250 m, and it is a typical non-full deep sea sound channel. The receiving end is a deep-sea bottom-mounted 40-element vertical linear array (element spacing is 4 m, and the array center depth is 3918 m). The underwater sound source radiated noise level is 119.8 dB@300 Hz, and the background noise is a deep-sea environmental noise field with vertical spatial directivity. In addition, the calculation of the sound field is realized by the BELLHOP ray tracing model.

[0122] The specific implementation process of the deep-sea sound source depth estimation method is as follows:

[0123] Step 1: Wideband MVDR beamforming

[0124] In the above simulation environment, assuming that the underwater wideband sound source depth = 100 m, and the distance from the receiving vertical array = 5 km Figure 4 a), the frequency-vertical angle of arrival spectrum can be obtained by performing wideband MVDR beamforming processing on the array receiving signal according to formula (2). In the simulation process, the response vector can be constructed in advance, also known as the pre-beam scanning vector, and then substituted into the MVDR beamformer to calculate the wideband beam output power.

[0125] Step 2: interference feature extraction based on complementary ensemble empirical mode decomposition

[0126] As shown in Figure 4 b, the outgoing sound waves of the underwater sound source reach the receiving array through the direct path D and the sea surface once-reflected path SR respectively, and the coherent superposition of the two sound signals forms the frequency interference stripes with light and dark alternation in the wideband beam output diagram of the array Figure 4The period of the bright and dark fringes implies the depth information of the sound source. The beam output sequence corresponding to each grazing angle is extracted, and then is decomposed by complementary ensemble empirical mode decomposition (CEEMD) as follows:

[0127] Step 1: Set the total average number N.

[0128] Step 2: Extract the frequency-zenith angle spectrum (B Figure 4 (f, sinθ l ) corresponding to each grazing angle (l = 1, 2, …, L) from the frequency-zenith angle spectrum (B MV (f, sinθ l ) obtained in step 1. MV (f, sinθ l ) and add white noise signal to B q (f, sinθ q ).

[0129] Step 3: Decompose B and B by empirical mode decomposition (EMD) to obtain intrinsic mode function (IMF) components and residual terms; wherein, and are the qth order intrinsic mode functions decomposed from B and B , respectively. and are the corresponding residual terms.

[0130] Step 4: Average each order intrinsic mode function.

[0131] Step 5: Calculate the variance contribution rate of each order intrinsic mode and sort them in descending order according to the contribution rate (IMF' q ), and sum the first λ order IMF' q whose cumulative variance contribution rate is greater than ε.

[0132] Step 6: Perform steps 1-5 on the beam output column vectors under all grazing angles, and reconstruct a new frequency-zenith angle spectrum as follows.

[0133] Step 3: Depth mapping of frequency-zenith angle spectrum

[0134] Map the new frequency-zenith angle spectrum B IMF (f, sinθ) reconstructed in step 2 to the grazing angle-depth domain by formula (8) to form the ambiguity plane F (sinθ, z) of the sound source depth, and the maximum value is the depth estimation result of the underwater sound source.

[0135] For example, Figure 5The image shows the sound source depth ambiguity planes obtained by the traditional Fourier method (FTB) and the method proposed in this invention, respectively. It can be seen that due to the presence of environmental noise, there are strong spurious peaks near the sea surface in the ambiguity plane of the FTB method. Figure 5 a) obscures the true location of the sound source (grazing angle and depth), while the proposed method can largely eliminate the spurious peaks of the FTB method and present significant peaks at the true location of the sound source. Figure 5 b) It can obtain accurate sound source depth estimation results.

[0136] Furthermore, the performance of the FTB method and the proposed method under different sound source depths and horizontal distances was compared and analyzed. Figure 6 The depth-fixed results of the FTB method and the proposed method are presented at different sound source depths. It can be seen that the sound source is almost "masked" in the depth ambiguity plane obtained by the FTB method when z S When the distance is increased to 150m, a "weak" peak value only appears near the actual location of the sound source. Figure 6 c). Compared to the FTB method, the ambiguity plane obtained by the proposed method shows significant "bright spots" near the true location of the sound source. In particular, for sound sources located within the depth estimation blind zone of the FTB method (the area above the white dashed line), the proposed method can still achieve accurate estimation of the sound source depth. Figure 6 d). Furthermore, the FTB method still struggles to estimate the depth of sound sources at different horizontal distances, especially when r... S At a grazing angle of 9km, the sound source completely "disappears" into the background noise due to the small grazing angle. Conversely, as r... S As the depth of the sound source increases, the proposed method gradually reduces its depth estimation resolution and increases its sidelobes. Figure 7 While it may not be accurate (df), it can still provide relatively accurate depth estimation results overall.

[0137] To verify the depth estimation and resolution capabilities of the proposed method in multi-sound-source scenarios, three underwater sound sources at different locations were considered (S1, S2 and S3 are 6km, 7km and 5.5km horizontally, and 40m, 205m and 120m deep, respectively). Figure 8 The depth estimation results for multiple sound sources are presented by the FTB method and the proposed method, respectively. It can be seen that because S1 and S3 are close to each other and the grazing angle is not sensitive to changes in the horizontal distance of the sound sources, the FTB method has difficulty identifying S1, which has a lower source level. Figure 8a) In comparison, the method proposed in the present application can not only achieve effective separation of the depth of each sound source, but also maintain high depth estimation accuracy (the depth estimation error rates of S1, S2 and S3 are 5.0%, 2.4% and 0.8% respectively), thereby verifying the effectiveness of the method in a complex multi-source environment.

[0138] The embodiment shows that the method of the present application can be applied to the depth estimation of a wideband sound source in a complex deep-sea environment. In view of the problems of pseudo-peak and high sidelobe caused by the influence of environmental noise on the traditional Fourier transform method, the present application proposes a sound source depth estimation method based on complementary ensemble empirical mode decomposition, which improves the accuracy of sound source depth estimation, and does not require prior information of environmental parameters in the depth estimation process, and has good environmental adaptability.

[0139] The depth estimation method proposed in the present application, as shown in Figure 2 , is divided into three steps, which are wideband beamforming, interference feature extraction based on complementary ensemble empirical mode decomposition and depth mapping of frequency-vertical angle of arrival spectrum. The method uses complementary ensemble empirical mode decomposition to decompose the frequency-grazing angle spectrum obtained by wideband beamforming into intrinsic mode functions with certain cumulative variance contribution rate, and then maps the intrinsic mode functions to the ambiguity plane of sound source depth, so as to realize accurate estimation of the depth of a wideband sound source under the condition that the environmental parameters are unknown.

[0140] It should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not for limiting purposes. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0141] Further, in the embodiment of the present example, a deep-sea sound source depth estimation system based on complementary ensemble empirical mode decomposition is also provided, which can be applied to the depth estimation of a wideband sound source. The system can include:

[0142] A bottom-mounted vertical linear array in the direct path sound region of the deep sea, used for receiving the incoming wave signal of the wideband sound source;

[0143] A terminal device, used for receiving the incoming wave signal and executing the above-mentioned deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition, and outputting the target depth estimation result of the wideband sound source.

[0144] The functions of the modules in the system are realized in the corresponding method embodiments, which are described in detail herein, and will not be repeated here.

[0145] It should be noted that, although several modules or units of the devices for action execution are mentioned in the above detailed description, such a division is not mandatory. Indeed, according to an embodiment of the application, the features and functionalities of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functionalities of one module or unit described above can be further divided into embodied by a plurality of modules or units.

[0146] Figure 9 A schematic diagram of an electronic device suitable for use in implementing embodiments of the application is shown.

[0147] It should be noted that, Figure 9 The electronic device 1000 shown is merely an example and should not be taken as limiting the functionality or use of embodiments of the application.

[0148] As Figure 9 shown, the electronic device 1000 includes a central processing unit (CPU) 1001 which can perform various appropriate actions and processes in accordance with a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage section 1008 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for system operation are also stored. The CPU 1001, the ROM 1002, and the RAM 1003 are connected to each other through a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0149] The following components are connected to the I / O interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as necessary. A removable recording medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 1010 as necessary, so that a computer program read therefrom is installed into the storage section 1008 as necessary.

[0150] In particular, according to embodiments of the present application, the processes described below with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a storage medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 1009, and / or installed from the removable medium 1011. When the computer program is executed by the central processing unit (CPU) 1001, various functions defined in the system of the present application are performed.

[0151] Specifically, the electronic device described above can be an onboard electronic device. Alternatively, the electronic device described above can also be a smart wearable device cooperating with a helmet display.

[0152] It should be noted that the storage medium shown in the embodiments of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer readable program code. Such a propagated data signal can take many forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any storage medium other than the computer readable storage medium, which can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or component. The program code contained on the storage medium can be transmitted by any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination of the above.

[0153] The computer program product of the present application includes a computer program, which, when executed by a processor, implements the steps of the above-mentioned method embodiments.

[0154] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can be located in a single processor, or distributed over multiple processors.

[0155] It should be noted that, as another aspect, the present application also provides a storage medium, which can be included in an electronic device, or exist separately without being assembled into the electronic device. The storage medium carries one or more programs, which, when executed by an electronic device, cause the electronic device to implement the method described in the above embodiments. For example, the electronic device can implement the steps of the method shown in Figure 1 and / or Figure 2 the method shown in the above embodiments.

[0156] In one embodiment, the present application provides a computer program product, which includes a computer program, which, when executed by a processor, implements the steps of the above-mentioned method embodiments.

[0157] In addition, the above-mentioned drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to limit the purpose. It is easy to understand that the processes shown in the above-mentioned drawings do not indicate or limit the time sequence of the processes. In addition, it is also easy to understand that the processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0158] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

[0159] It is to be understood that the application is not limited to the precise structures hereinabove described and shown in the drawings, for purposes of illustration and education only, and that variations in changes can be made by persons skilled in the art without departing from the scope of the present application. The scope of the application should be determined only by the claims appended hereto.

Claims

1. A method for deep-sea sound source depth estimation based on complementary ensemble empirical mode decomposition, characterized in that, The method comprises: a bottom-mounted vertical linear array in a deep-sea direct sound area receives a wave signal of a wideband sound source and performs wideband beamforming processing to obtain a beam output power of a minimum variance distortionless response of the wideband sound source; complementary ensemble empirical mode decomposition is performed on the beam output power to extract interference characteristics to obtain a reconstructed frequency-vertical angle of arrival spectrum; the reconstructed frequency-vertical angle of arrival spectrum is mapped to a grazing angle-depth domain to form an ambiguity plane of the depth of the wideband sound source, and a target depth estimation result of the wideband sound source is obtained based on the ambiguity plane.

2. The method of claim 1, wherein, The wave signal of the wideband sound source comprises: wideband sound source radiation noise and deep-sea environment background noise.

3. The method according to claim 1 or 2, characterized in that, The wideband beamforming processing on the wave signal comprises: obtaining a response vector of the vertical linear array to the wave signal; performing beamforming processing on the response vector based on a sample covariance matrix to obtain the beam output power of the minimum variance distortionless response.

4. The method of claim 1, wherein, The complementary ensemble empirical mode decomposition performed on the beam output power to extract interference characteristics to obtain the reconstructed frequency-vertical angle of arrival spectrum comprises: configuring a total average number N; θ is extracted from the frequency-vertical angle of arrival spectrum corresponding to the beam output power. l The column vector B corresponding to the grazing angle MV (f,sinθ l ), and for column vector B MV (f,sinθ l Add white noise to obtain the beam output power sequence, including: wherein, l = 1, 2, …, L; W n white noise sequence added for the nth time, n = 1, 2, …, N; The empirical mode decomposition method is used to decompose the signal and to obtain the intrinsic mode function components and residual terms thereof. wherein, and are the qth eigenmode functions decomposed from and and are the corresponding residual terms;​ averaging each intrinsic mode component and a residual: The variance contribution rate of each order intrinsic mode is calculated and sorted in descending order according to the contribution rate, and the first λ order IMF' whose cumulative variance contribution rate is greater than ε is selected q Summation is performed: wherein denotes the variance of the qth eigenmode function component; The above steps are performed for the beam output column vectors at all grazing angles, and a new frequency-vertical angle of arrival spectrum is reconstructed:

5. The method of claim 1, wherein, The reconstructed frequency-vertical angle of arrival spectrum is mapped to a grazing angle-depth domain to form an ambiguity plane of the depth of the wideband sound source, and a target depth estimation result of the wideband sound source is obtained based on the ambiguity plane, which comprises: The new frequency-vertical angle of arrival spectrum B is reconstructed IMF The (f, sinθ) mapping to the grazing angle-depth domain forms the ambiguity plane of the sound source depth: wherein f1 and f2 are upper and lower limits of a processing frequency band, respectively; a maximum value of F(sinθ, z) corresponds to a depth estimation result of an underwater sound source, and is configured as the target depth estimation result.

6. The method of claim 1, wherein, The wideband sound source comprises one or more; The method further comprises: when the wideband sound source comprises multiple sound sources, performing complementary ensemble empirical mode decomposition on the beam output power to extract interference characteristics corresponding to the multiple wideband sound sources to obtain reconstructed frequency-vertical angle of arrival spectra corresponding to the multiple wideband sound sources; mapping the reconstructed frequency-vertical angle of arrival spectra corresponding to the multiple wideband sound sources to a grazing angle-depth domain respectively to form ambiguity planes of the depths of the multiple wideband sound sources; obtaining target depth estimation results corresponding to the multiple wideband sound sources based on the ambiguity planes respectively.

7. A deep-sea sound source depth estimation system based on complementary ensemble empirical mode decomposition, characterized in that, The system comprises: a bottom-mounted vertical linear array in a deep-sea direct sound area for receiving a wave signal of a wideband sound source; a terminal device for receiving the wave signal and performing the complementary ensemble empirical mode decomposition-based deep-sea sound source depth estimation method according to any one of claims 1 to 6 to output a target depth estimation result of the wideband sound source.

8. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by a processor to implement the complementary ensemble empirical mode decomposition-based deep-sea sound source depth estimation method according to any one of claims 1 to 6.

9. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the complementary ensemble empirical mode decomposition-based deep-sea sound source depth estimation method according to any one of claims 1 to 6.

10. An electronic device, comprising: comprises: a processor; and a memory for storing executable instructions of the processor; The processor is configured to execute the deep-sea sound source depth estimation method based on complementary ensemble empirical mode decomposition in any one of claims 1 to 6 by executing the executable instructions.

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