Polar underwater pulse normal mode acoustic ranging method

Abstract

This invention discloses a polar underwater pulse normal wave acoustic ranging method, belonging to the field of polar acoustic ranging. Based on the physical characteristics of low-frequency normal waves in the polar environment, a passive distance estimation method for low-frequency long-distance pulse sound sources in polar seas, based on a single hydrophone, is proposed. The method includes the following steps: acquiring actual polar sound field environmental parameters; collecting and filtering signals with the hydrophone; calculating the power spectral density function of the signal; estimating the normal wave dispersion constant and waveguide invariants; calculating the dispersion reduction transform of the power spectral density function; and determining the sound source distance based on the maximum value principle. Results demonstrate that the proposed method can effectively estimate the distance of pulses in polar underwater environments.

Description

Technical Field

[0001] This invention belongs to the field of polar acoustic ranging, specifically relating to a polar underwater pulse normal wave acoustic ranging method. Background Technology

[0002] The Arctic's unique geographical location creates sound propagation characteristics that differ from other sea areas. The sound speed gradient in the Arctic Ocean generally conforms to a positive sound speed gradient, meaning that the speed of sound in the sea increases with depth. Therefore, sound waves propagating in the Arctic Ocean are usually refracted upwards, interact with the ice layer on the sea surface, and then reflected back into the seawater, creating a cycle that forms the Arctic's unique semi-waveguide deep-sea sound channel.

[0003] Passive underwater acoustic localization methods typically utilize the time of arrival (TOA) and angle of arrival (DOA) of sound waves propagating through the water to a hydrophone array to determine the location of the sound source, suitable for locating high-frequency and near-range sound sources. Matched field processing can also achieve passive localization of underwater sound sources. Its basic principle is to match the sound source signal collected by a vertical hydrophone array placed in the water with a simulated sound field calculated based on an underwater acoustic propagation model, and determine the sound source location based on the matching result. This method has long been successfully applied in the Arctic Ocean. In 2014, Qi Yubo achieved sound source ranging by performing a warping transform on the autocorrelation function of the received signal and utilizing characteristic frequencies, with an estimated error of approximately 10%. In 2016, Wang Dong derived the time-domain warping transform of the signal energy density function, achieving rapid ranging of pulse sound sources with a ranging error of approximately 8%. In 2017, Li Xiaoman et al. extracted normal modes based on warping transform for pulse source ranging, with an error within 10%. In 2019, Wang Dong proposed using the time-domain warping transform and frequency-domain β-warping transform of the autocorrelation function to measure the distance of pulse sources in shallow sea negative gradient layers, with an error within 20%. In 2016, Guo Xiaole et al. introduced a two-parameter anti-dispersion transform for estimating the location of underwater pulse sound sources. In the same year, Zhang Yinquan proposed a distance estimation method for long pulse sound sources based on the two-parameter anti-dispersion transform, pointing out that when the receivers are asynchronous, the anti-dispersion result needs to include a phase term. In 2022, Hu Chunhui performed anti-dispersion beamforming and deconvolution operations on vertical array data, achieving distance estimation.

[0004] Low-frequency sound sources propagating over long distances are affected by the unique sound velocity gradient and sea ice layer of the Arctic, resulting in sound waves of different frequencies propagating as normal modes with different group velocities. This dispersion effect has a complex impact on underwater acoustic signal processing, altering the waveform structure of the original sound signal and also containing information about the sound source's location. Based on the physical characteristics of low-frequency normal modes in the polar environment, this invention proposes a passive distance estimation method for low-frequency, long-distance pulse sound sources in polar waters, based on a single hydrophone. Summary of the Invention

[0005] In order to solve the technical problems existing in the background art, the present invention aims to provide a polar underwater pulse normal wave acoustic ranging method to solve the problem of passive estimation of the distance of polar underwater pulse sound sources.

[0006] To solve the technical problem, the technical solution of the present invention is as follows:

[0007] In polar environments, hydrophones receive acoustic signals. The spectrum of can be simplified as a superposition of multiple normal modes, as follows:

[0008] ;

[0009] in For the frequency of the sound source, It is an integral operator. It is the summation symbol. Let m be the amplitude of the m-th normal mode. , Let m be the horizontal wave number of the m-th normal mode. Let be the distance to the sound source. Therefore, the power spectral density function of the received signal is:

[0010] ;

[0011] in The conjugate symbol, The difference between the m-th and n-th horizontal wavenumbers is expressed in the following form:

[0012] ;

[0013] In the formula The dispersion constants related to the normal mode orders m and n, Let be the waveguide invariant. Substituting this equation into the power spectral density function and removing the normal mode autocorrelation term, we get:

[0014] ;

[0015] When the prior conditions of polar environmental parameters are known, It can be estimated using the following formula.

[0016] ;

[0017] in Describes the 2-norm of a vector. Calculated using the Kraken normal mode acoustic propagation model.

[0018] This invention defines a frequency dissipation reduction transform.

[0019] ;

[0020] The dispersion constant and waveguide invariants estimated by model fitting Substituting the values ​​into the de-dispersion transform, the distance to the sound source can be directly estimated, as shown below.

[0021] ;

[0022] Only when hour, It has a maximum value. Therefore, the distance to the sound source is determined by the maximum value principle.

[0023] .

[0024] Compared with the prior art, the advantages of the present invention are as follows:

[0025] The data results demonstrate that the positioning method proposed in this invention can effectively estimate the distance to low-frequency sound sources of underwater pulses in polar regions. Compared to traditional positioning methods based on hydrophone arrays, this method uses a single hydrophone to achieve passive distance estimation of underwater sound sources in polar regions, effectively enabling distance estimation of underwater pulses. Attached Figure Description

[0026] Figure 1 This is a flowchart of the polar underwater ranging process in this invention;

[0027] Figure 2 This is a diagram of polar acoustic field environmental parameters in this invention;

[0028] Figure 3 This is the waveform of the hydrophone received in this invention;

[0029] Figure 4 This refers to the signal time-frequency distribution in this invention;

[0030] Figure 5 This is the signal power spectral density function in this invention;

[0031] Figure 6 These are the estimated dispersion parameters and waveguide invariants results in this invention;

[0032] Figure 7 This is the estimation result of the polar underwater sound source in this invention. Detailed Implementation

[0033] The specific implementation of the present invention is described below with reference to embodiments:

[0034] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the conditions under which the present invention can be implemented. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0035] Furthermore, the terms such as "upper," "lower," "left," "right," "middle," and "one" used in this specification are merely for clarity of description and are not intended to limit the scope of the invention. Any changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0036] Example 1:

[0037] like Figure 1 As shown, the polar underwater ranging flowchart provided by this invention is introduced and verified through simulation experiments. The specific steps are as follows:

[0038] Step 1: Obtain the environmental parameters of the polar sound field. These environmental parameters are prerequisites for calculating the sound field, including sea ice thickness and density, and the sound velocity C of the sea ice P-wave. S Sea ice transverse wave sound speed C P Seawater density and sound speed gradient C W The speed of sound of longitudinal waves on the seabed, C B And density. For example... Figure 2 The diagram shows the simulated polar sound field environmental parameters based on the actual Arctic environment, where the sea ice thickness is 2m and the density is 0.9g / cm³. 3 Sea ice longitudinal wave speed C P =3800m / s, sea ice transverse wave speed C S =1900m / s, seawater density 1.0g / cm³ 3 Within a water depth of 0-200m, the sound velocity gradient C W The sound velocity gradient C increases from 1440 m / s to 1460 m / s in the range of 200 m to 3750 m. W The longitudinal wave velocity C below 3750m increases from 1460m / s to 1500m / s. B =1600m / s and density of 1.5 g / cm³ 3 .

[0039] Step 2: Use hydrophones deployed in polar seas to collect sound signals emitted by the sound source. The signal is then filtered to reduce noise interference and retain segments containing normal modes. For example... Figure 3The figure shows the signal waveform received by the hydrophone. The signal emitted by the sound source is a Gaussian pulse with a bandwidth of 100Hz. The depth of the sound source is 10m, the depth of the hydrophone is 10m, and the distance between the sound source and the hydrophone is R=50km. Figure 4 The image shows the time-frequency distribution of the signal, where the two lines are the theoretical dispersion curves of the first two normal modes. It can be seen that there are two normal modes, which is consistent with the typical "upward sweep" dispersion characteristics of signals in polar seas.

[0040] Step 3 obtains the power spectral density function of the signal. First, calculate the autocorrelation function of the signal, which is of the form:

[0041] ;

[0042] The results are as follows Figure 5 As shown. To preserve the cross-correlation component of the normal modes, the autocorrelation component needs to be removed. Therefore, the first few data points of the signal's autocorrelation function are set to zero, typically taking the length of 3-5 wave packets. Finally, a Fourier transform is performed on the autocorrelation function to obtain the signal's power spectral density function, in the form of...

[0043] ;

[0044] Step 4: Estimate the dispersion constant and waveguide invariants. Substitute the polar acoustic field environmental parameters obtained in Step 1 into the Kraken normal mode acoustic propagation model to solve for the horizontal wavenumber within the signal frequency band. Because the approximate formula for the horizontal wavenumber difference is:

[0045] ;

[0046] In the formula The dispersion constants related to the normal mode orders m and n, For waveguide invariants, The estimation is performed using the following formula:

[0047] ;

[0048] in Describes the 2-norm of a vector. .

[0049] like Figure 6 As shown, the dotted data represents the difference between the first and second order horizontal wavenumbers calculated by Kraken. The curve represents the fitting result. (Fitted curve) The dispersion parameter and waveguide invariant in the figure are respectively =1.39e-4, = -2.52. For polar positive gradient sea areas, waveguide invariants are usually negative.

[0050] Step 5: Calculate the dispersion reduction transform of the signal power spectral density function.

[0051] ;

[0052] in This represents the integral operator. The search distance r is set to 0-300km, with distance intervals of 10m. The result is as follows... Figure 7 As shown.

[0053] Step 6 estimates the sound source distance based on the maximum value principle as follows:

[0054] ;

[0055] Figure 7 The display shows that when r = 51.6 km, The value has a maximum value, therefore the distance to the sound source is 51.69 km, and the ranging error is approximately 3.38%.

[0056] The results demonstrate that the method proposed in this invention can effectively estimate the distance of polar underwater pulses.

[0057] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

[0058] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

[0059] Many other changes and modifications can be made without departing from the concept and scope of this invention. It should be understood that this invention is not limited to the specific embodiments, and the scope of this invention is defined by the appended claims.

Claims

1. A polar underwater pulse normal wave acoustic ranging method, characterized in that, The method includes: The sound signal received by the hydrophone The spectrum of the signal can be simplified as a superposition of multiple normal modes. The power spectral density function of the received signal is calculated as follows: ； in, Let m be the amplitude of the m-th normal mode. Distance from the sound source; The conjugate symbol, The difference between the m-th and n-th horizontal wavenumbers is expressed in the following form: ； Let m be the horizontal wave number of the m-th normal mode. Let n be the horizontal wave number of the nth normal mode. The frequency of the sound source; In the formula The dispersion constants related to the normal mode orders m and n, Let be the waveguide invariant; substituting this equation into the power spectral density function and removing the normal mode autocorrelation term, we get: ； Prior conditions for obtaining polar environmental parameters The estimation is performed using the following formula: ； in Describes the 2-norm of a vector. Calculated using the Kraken normal mode acoustic propagation model; The dispersion constant and waveguide invariants estimated by model fitting Substituting the values ​​into the preset frequency dissipation reduction transform model, the distance to the sound source is estimated, and the results are as follows: ； For search distance, Distance from the sound source; Only when hour, There is a maximum value; therefore, the distance to the sound source is determined by the maximum value principle as follows: 。 2. The polar underwater pulse normal wave acoustic ranging method according to claim 1, characterized in that, Use hydrophones deployed in polar seas to collect sound signals emitted by sound sources. The signal is filtered to reduce noise interference and retain segments containing normal modes.

3. The polar underwater pulse normal wave acoustic ranging method according to claim 1, characterized in that, The sound signal received by the hydrophone The spectrum of is simplified as a superposition of multiple normal modes, as follows: ； in, For the frequency of the sound source, It is an integral operator. It is the summation symbol. Let m be the amplitude of the m-th normal mode. , Let m be the horizontal wave number of the m-th normal mode. The distance to the sound source.

4. The polar underwater pulse normal wave acoustic ranging method according to claim 1, characterized in that, Obtain the environmental parameters of the polar sound field. These environmental parameters are prerequisites for calculating the sound field, including: sea ice thickness and density, and the sound velocity C of the sea ice P-wave. S Sea ice transverse wave sound speed C P Seawater density and sound speed gradient C W The speed of sound of longitudinal waves on the seabed, C B and density.

5. The polar underwater pulse normal wave acoustic ranging method according to claim 1, characterized in that, The predefined frequency dissipation reduction transform model is as follows: 。

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