A method for underwater acoustic target warning based on energy passing characteristics

Abstract

The present application relates to a kind of water acoustic target warning methods based on energy passing characteristics, comprising the following steps, step 1, obtain the water acoustic target noise digital signal collected by hydrophone linear array;Step 2, multi-channel signal band-pass filtering and time-frequency spectrum analysis;Step 3, the channel time-frequency spectrum in the specified bandwidth is integrated in frequency domain, obtains wideband space-time energy distribution, detects and tracks line spectrum, obtains the line spectrum space-time energy distribution corresponding to the tracking line spectrum frequency;Step 4, wideband and line spectrum space-time energy distribution are filtered in two dimensions, and random background noise is inhibited;Step 5, the trend curve of the concentration degree of wideband and line spectrum space-time energy distribution is calculated.The present application provides a kind of water acoustic target warning methods based on energy passing characteristics, and the method can be realized in near-field conditions, with a certain speed through the automatic warning of the water acoustic target of hydrophone linear array.

Description

Technical Field

[0001] This invention belongs to the field of underwater acoustic target detection technology, specifically relating to an underwater acoustic target warning method based on energy transmission characteristics. Background Technology

[0002] Currently, underwater acoustic target detection still primarily relies on centralized hydrophone arrays for long-range detection, mainly utilizing the energy or characteristics of beamforming from various directions for passive long-range detection. However, in complex marine environments, the radiated noise level of underwater acoustic targets is constantly decreasing while the ambient noise level is significantly increasing, making long-range detection and target identification of underwater acoustic targets increasingly difficult. Under these circumstances, deploying continuous, distributed hydrophone arrays underwater is an effective means of underwater acoustic target detection. For horizontally deployed distributed hydrophone arrays covering the width of the warning area, when an underwater acoustic target travels from one side of the array to the other, it will inevitably pass above or below the array. The closest distance between the underwater acoustic target and the array is no greater than the ocean depth. Compared to the received radiated noise from distant underwater acoustic targets, the ocean sound propagation loss is significantly reduced, and the signal-to-noise ratio is improved. In this situation, conventional far-field-based early warning algorithms are no longer applicable when underwater acoustic targets pass through the hydrophone linear array. It is necessary to propose an effective underwater acoustic target early warning method that utilizes the characteristics of the radiated noise field through the underwater acoustic target. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for underwater acoustic target warning based on energy transmission characteristics, which can achieve reliable warning of underwater acoustic targets passing through hydrophone arrays under near-field conditions.

[0004] The technical solution of this invention is to provide a method for underwater acoustic target detection based on energy transmission characteristics, comprising the following steps:

[0005] Step 1: Acquire digital signals of underwater acoustic target noise from a hydrophone linear array.

[0006] Step 2: Bandpass filtering and time-spectrum analysis of multi-channel signals;

[0007] Step 3: Perform frequency domain integration on the channel time spectrum within the specified bandwidth to obtain the broadband spatiotemporal energy distribution; detect and track the line spectrum to obtain the spatiotemporal energy distribution of the line spectrum corresponding to the tracking line spectrum frequency;

[0008] Step 4: Perform two-dimensional spatiotemporal filtering on the broadband and line spectrum spatiotemporal energy distributions to suppress random background noise;

[0009] Step 5: Calculate the trend curves of the spatial-temporal energy distribution concentration of broadband and line spectra;

[0010] Step 6: Detect the trend of broadband and line spectrum spatiotemporal energy distribution concentration to determine whether an underwater acoustic target has passed through;

[0011] Step 7: Estimate the time and location of the underwater acoustic target.

[0012] The underwater acoustic target warning method based on energy transmission characteristics differs from the underwater acoustic signal characteristics utilized in far-field underwater acoustic target warning and detection. This method utilizes the energy transmission characteristics of underwater acoustic targets to achieve underwater acoustic target warning and detection, enabling the differentiation between passing targets and environmental noise and far-field interference targets.

[0013] When an underwater acoustic target approaches and passes through a hydrophone array at a certain speed, the amplitude of the target's radiated noise received by the array exhibits a two-dimensional passing characteristic. In terms of space-time energy characteristics, this manifests as an energy maxima centered on the location of the target's passage through the array and at the moment of passage. The energy distribution decreases with increasing distance from the space-time center. Although energy fluctuations exist due to multipath interference, the trends of broadband energy and narrowband spatial local average energy remain unchanged.

[0014] The specific steps of the underwater acoustic target detection method based on time-frequency transmission characteristics of the present invention are as follows:

[0015] Step 1 is performed as follows: the M elements of the hydrophone linear array continuously acquire underwater target radiated noise, forming an M-channel underwater target radiated noise digital signal. , Where M is the number of linear array elements, and the element positions are... .

[0016] Step 2 is performed as follows: [Regarding the signal] Perform time-frequency spectrum analysis to obtain the time-frequency two-dimensional spectrum data of the M channel. ,

[0017] , (1)

[0018] In the formula, Indicates frequency, This represents the length of the time window.

[0019] Step 3 is as follows: Calculate the broadband or line spectrum space-time energy distribution. The broadband space-time energy distribution represents the two-dimensional distribution of the total signal energy within a specified frequency band in space (represented by the channel number) and time.

[0020]

[0021] in, It represents the broadband energy distribution of the i-th channel over time, calculated by integrating the energy of the channel's time-frequency spectrum in the frequency domain.

[0022] (2)

[0023] The line spectrum space-time energy distribution represents the two-dimensional distribution of signal line spectrum energy in space (represented by channel number) and time:

[0024] (3)

[0025] in, It is the distribution of the line spectrum energy corresponding to the i-th channel over time, based on the peak decision condition and threshold, from Stable line spectra were detected, and the frequency of the line spectra was estimated. Calculate the corresponding spectral values:

[0026] (4)

[0027] Step 5 is as follows: Based on the M-channel bandwidth and the spatiotemporal energy distribution of the line spectrum, calculate the centroid coordinates and mean of the bandwidth and line spectrum spatiotemporal energy distribution data at time t. mean The calculation method is as follows:

[0028] (5)

[0029] (6)

[0030] The methods for calculating the centroid and mean of narrowband space-time energy distribution data are the same as those for broadband space-time energy distribution data.

[0031] Construct statistics , , ,

[0032] (7)

[0033] (8)

[0034] (9)

[0035] Using statistics Estimate the trend of broadband spatiotemporal energy distribution concentration, and use the same method to estimate the trend of narrowband spatiotemporal energy distribution concentration. .

[0036] Step 6 is performed as follows: and The system performs peak or extreme value detection to determine if any underwater acoustic targets are passing through. When the concentration exceeds the threshold, an underwater acoustic target passage warning is issued, and the target is confirmed based on the trend of the concentration.

[0037] By taking into account the spatiotemporal characteristics of broadband energy and line spectrum energy, the extreme value is taken on the spatiotemporal distribution map. The time corresponding to the extreme value is the moment when the underwater acoustic target passes through the hydrophone linear array. The spatial position of the channel number of the hydrophone linear array where the maximum energy value is located at this moment is the position point where the underwater acoustic target passes through.

[0038] Compared with the prior art, the present invention has the following advantages:

[0039] This invention utilizes the energy transmission characteristics of unknown underwater acoustic targets passing through a hydrophone array to extract the spatiotemporal energy variation trend characteristics of broadband and narrowband line spectra when the underwater acoustic targets pass through, determine whether an underwater acoustic target has passed through, estimate the target's passage time and location, and realize the function of underwater acoustic target early warning and detection in the sea area where the hydrophone array is deployed. Attached Figure Description

[0040] Figure 1 This is a flowchart of an underwater acoustic target warning method based on energy transmission characteristics according to the present invention.

[0041] Figure 2 A schematic diagram of a hydrophone linear array used to detect underwater acoustic targets.

[0042] Figure 3 The spatiotemporal distribution diagram of broadband energy of target radiated noise received by the elements of the hydrophone array before and after the underwater acoustic target passes through the hydrophone array.

[0043] Figure 4 The spatiotemporal distribution diagram of the radiation noise line spectrum energy received by the elements of the hydrophone array before and after the underwater acoustic target passes through the hydrophone array.

[0044] Figure 5 Comparison of spatiotemporal two-dimensional filtering of the spatiotemporal distribution of line spectrum energy before and after filtering.

[0045] Figure 6 The trend curves of the spatial-temporal distribution concentration of broadband and line spectrum energy. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0047] Figure 1 This is a flowchart of an underwater acoustic target detection method based on energy transmission characteristics according to the present invention, as shown below. Figure 1 As shown, the method includes steps 101-107.

[0048] Step 1: Corresponding Figure 1In section 101, a hydrophone linear array with M elements continuously acquires underwater target radiated noise, forming an M-channel underwater target radiated noise signal. , Where M is the number of linear array elements, and the element positions are... .

[0049] Step 2: Corresponding to 102 in the diagram, match the signal number. Time-frequency spectrum analysis was performed to obtain the time-frequency two-dimensional spectrum data of the M channel. .

[0050] , (1)

[0051] (1) In the formula, Represents frequency, with values ​​ranging from 1 to 2. , This represents the length of the time window.

[0052] Step 3: Calculate the broadband or line spectrum spatiotemporal energy distribution corresponding to 103 in the diagram. The broadband spatiotemporal energy distribution represents the two-dimensional distribution of the total signal energy within a relatively wide frequency band in space (represented by the channel number) and time.

[0053] ,

[0054] in, This represents the broadband energy distribution over time corresponding to the i-th channel. The calculation method involves integrating the energy of the channel's time-frequency spectrum in the frequency domain.

[0055] (2)

[0056] The line spectrum space-time energy distribution represents the two-dimensional distribution of signal line spectrum energy in space (represented by channel number) and time:

[0057] (3)

[0058] in, This represents the time distribution of the line spectrum energy corresponding to the i-th channel. Based on the peak decision condition and threshold, from... Stable line spectra were detected, and the frequency of the line spectra was estimated. Calculate the corresponding spectral values:

[0059] (4)

[0060] Step 4: Corresponding to 104 in the figure, perform two-dimensional spatiotemporal filtering on the broadband and line spectrum spatiotemporal energy distribution to suppress random background noise.

[0061] Step 5: Corresponding to 105 in the figure, based on the M-channel broadband and line spectrum spatiotemporal energy distribution, calculate the centroid coordinates and mean of the broadband and line spectrum spatiotemporal energy distribution data at time t. (Centroid of broadband spatiotemporal energy distribution data) mean The calculation method is as follows:

[0062] (5)

[0063] (6)

[0064] The methods for calculating the centroid and mean of narrowband space-time energy distribution data are the same as those for broadband space-time energy distribution data.

[0065] Construct statistics , , ,

[0066] (7)

[0067] (8)

[0068] (9)

[0069] Using statistics Estimate the trend of broadband spatiotemporal energy distribution concentration and estimate the trend of narrowband spatiotemporal energy distribution concentration. .

[0070] Step 6: Corresponding to 106 in the figure, and The system performs peak or extreme value detection to determine if any underwater acoustic targets are passing through. When the concentration exceeds a threshold, an alert is issued for the passing of an underwater acoustic target, and the target is confirmed based on the trend of the concentration.

[0071] Step 7: Corresponding to 107 in the figure, based on the spatiotemporal characteristics of broadband energy and line spectrum energy, take the extreme value on the spatiotemporal distribution map. The time corresponding to this extreme value is the moment when the underwater acoustic target passes through the hydrophone linear array. The spatial position of the hydrophone linear array channel number where the maximum energy value is located at this moment is the position point where the underwater acoustic target passes through.

[0072] Figure 2 This is a schematic diagram of the underwater acoustic target passing through the hydrophone linear array in this embodiment. In the diagram, the array elements are distributed along a straight line in the range [-1000, 1000], with an element spacing of 1m. The underwater acoustic target is at a depth d from the hydrophone linear array and moves in a straight line at an angle θ with the array, passing through the hydrophone linear array at time t0. The velocity of the straight-line motion is v. The distance between the underwater acoustic target and the array element shown in the figure is the closest distance.

[0073] Figure 3 This diagram illustrates the spatiotemporal distribution of broadband noise radiated by the underwater acoustic target before and after it passes through the hydrophone array in this embodiment. Due to seabed reflection and multipath effects, the broadband energy distribution is an ellipse centered at the vertex, with intensity gradually decreasing over time and space, and isointense lines forming an ellipse. The higher the target's speed, the flatter the ellipse, and one axis of the ellipse aligns with the direction of passage. In this embodiment, the underwater acoustic target passes directly above the center of the array, moving in a straight line at a 90° angle to the array, with a speed of 3 m / s. The target's travel depth is 25 m, and the water depth is 200 m. The diagram shows the spatiotemporal distribution of broadband energy from 75 Hz to 150 Hz.

[0074] Figure 4 This figure shows the spatiotemporal distribution of the line spectrum energy of the underwater acoustic target before and after it passes through the hydrophone array in this embodiment. The line spectrum energy spatiotemporal distribution shows similar characteristics to the broadband energy spatiotemporal distribution, but the bright and dark fringes caused by multipath interference are clearer. The figure shows the line spectrum energy spatiotemporal distribution at 75Hz.

[0075] Figure 5 Comparison of the spatiotemporal distribution of line spectrum energy before and after two-dimensional spatiotemporal filtering. Before filtering, the spatiotemporal distribution of line spectrum energy has strong random background noise; after filtering, the random background noise is suppressed. Figure 5 The white line segment in the right figure represents the centroid trace of the data.

[0076] Figure 6 Here are the trend curves of the spatiotemporal concentration of broadband and line spectrum energy, where... Figure 6 (a) is the trend curve of the concentration of broadband energy in space-time distribution. Figure 6 (b) shows the trend curve of the spatial-temporal concentration of the line spectrum energy. The broadband energy spatial-temporal distribution concentration trend curve shows a clear monotonically increasing trend before passing and a clear monotonically decreasing trend after passing. It reaches its maximum value near the passing moment. Based on this characteristic, a concentration threshold is set, and the passing target is predicted for the spectral lines that reach the threshold. The target is then confirmed based on its changing trend. This moment is the passing moment, and the location of the maximum value of the frequency change rate is the passing position of the underwater acoustic target.

[0077] This invention constructs statistical measures of the concentration trend of spatiotemporal energy variation in broadband and narrowband line spectra for identifying underwater acoustic targets passing through a hydrophone array. Simultaneously, by utilizing the concentration trend characteristics of the concentration of broadband and narrowband line spectra of the target radiated noise received by each array element during the time the underwater acoustic target passes through the hydrophone array, it achieves early warning of underwater acoustic targets passing through the hydrophone array at a certain speed under near-field conditions.

[0078] The above description only illustrates preferred embodiments of the present invention and should not be construed as limiting the scope of the claims. Any equivalent procedural modifications made using this specification are included within the patent protection scope of this invention.

Claims

1. A method for underwater acoustic target detection based on energy transmission characteristics, characterized in that: Includes the following steps, Step 1: Acquire digital signals of underwater acoustic target noise from a hydrophone linear array. Step 2: Bandpass filtering and time-spectrum analysis of multi-channel signals; Step 3: Perform frequency domain integration on the channel time spectrum within the specified bandwidth to obtain the broadband spatiotemporal energy distribution; detect and track the line spectrum to obtain the spatiotemporal energy distribution of the line spectrum corresponding to the tracking line spectrum frequency; Step 4: Perform two-dimensional spatiotemporal filtering on the broadband and line spectrum spatiotemporal energy distributions to suppress random background noise; Step 5: Calculate the trend curves of the spatial-temporal energy distribution concentration of broadband and line spectra; Step 6: Detect the trend of broadband and line spectrum spatiotemporal energy distribution concentration to determine whether an underwater acoustic target has passed through; Step 7: Estimate the time and location of the underwater acoustic target.

2. The underwater acoustic target detection method based on energy transmission characteristics according to claim 1, characterized in that: Step 1 is performed as follows: the M elements of the hydrophone linear array continuously acquire underwater target radiated noise, forming an M-channel underwater target radiated noise digital signal. , Where M is the number of linear array elements, and the element positions are... .

3. The underwater acoustic target detection method based on energy transmission characteristics according to claim 2, characterized in that: Step 2 is performed as follows: [Regarding the signal] Time-frequency spectrum analysis was performed to obtain the time-frequency two-dimensional spectrum data of the M channel. , , （1） In the formula, The frequency is represented by T, and the time window length is T.

4. The underwater acoustic target detection method based on energy transmission characteristics according to claim 3, characterized in that: Step 3 involves calculating the broadband and line spectrum spatiotemporal energy distributions. The broadband spatiotemporal energy distribution represents the two-dimensional spatial and temporal distribution of the total signal energy within a specified frequency band. ， in, It represents the broadband energy distribution of the i-th channel over time, calculated by integrating the energy of the channel's time-frequency spectrum in the frequency domain. （2） The line spectrum space-time energy distribution represents the two-dimensional distribution of signal line spectrum energy in space and time: , （3） in, It is the distribution of the line spectrum energy corresponding to the i-th channel over time, based on the peak decision condition and threshold, from Stable line spectra were detected, and the frequency of the line spectra was estimated. Calculate the corresponding spectral values: （4）。 5. The underwater acoustic target detection method based on energy transmission characteristics according to claim 4, characterized in that: Step 5 is as follows: Based on the M-channel bandwidth and the spatiotemporal energy distribution of the line spectrum, calculate the centroid coordinates and mean of the bandwidth and line spectrum spatiotemporal energy distribution data at time t. mean The calculation method is as follows: （5） （6） Construct statistics , , , （7） （8） （9） Using statistics Estimate the trend of broadband spatiotemporal energy distribution concentration and estimate the trend of narrowband spatiotemporal energy distribution concentration. .

6. The underwater acoustic target detection method based on energy transmission characteristics according to claim 5, characterized in that: Step 6 is performed as follows: and The system performs peak or extreme value detection to determine if any underwater acoustic targets are passing through. When the concentration exceeds the threshold, an underwater acoustic target passage warning is issued, and the target is confirmed based on the trend of the concentration.

7. The underwater acoustic target warning method based on energy transmission characteristics according to claim 1, characterized in that... Step 7 is operated as follows: taking into account the spatiotemporal characteristics of broadband energy and line spectrum energy, take the extreme value on the spatiotemporal distribution map. The time corresponding to the extreme value is the moment when the underwater acoustic target passes through the hydrophone linear array. The spatial position of the hydrophone linear array channel number where the maximum energy value is located at this moment is the position point where the underwater acoustic target passes through.

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