A method for calculating in-situ sound speed in the seabed based on envelope cross weighted cross-correlation

Abstract

The application discloses a seabed in-situ sound velocity calculation method based on envelope cross weighting cross correlation, and belongs to the field of seabed in-situ acoustic detection. The method comprises the following steps: acquiring sound wave signals propagated in water and sediment layers respectively as water reference signals and sediment layer signals, filtering, Hilbert transforming and amplitude normalizing to obtain respective envelope signals and normalized signals; combining the envelope signals and the normalized signals to construct a cross weighting enhancement model and extract an enhanced envelope to obtain respective enhanced envelope signals; slidingly shifting the water enhanced envelope signals in the time domain according to different shift amounts for multiple times, calculating cross correlation values of the sediment layer enhanced envelope signals under each shift amount, and constructing a cross correlation function; and taking a shift amount corresponding to a maximum value of the cross correlation function to calculate a sediment layer sound velocity. The application can highlight effective propagation information shared by the reference signals and the sediment layer signals, and reduce the influence of non-correlation interference components on subsequent analysis.

Description

Technical Field

[0001] This invention belongs to the field of in-situ acoustic detection on the seabed, specifically involving a method for calculating in-situ sound velocity on the seabed based on envelope cross-weighted cross-correlation. Background Technology

[0002] The sound velocity in seabed sediments is a crucial fundamental parameter for marine engineering surveys, seabed resource exploration, marine geophysical investigations, and the construction of underwater acoustic propagation models. In-situ measurement, by preserving in-situ pressure, temperature, and salinity conditions, reproduces the true acoustic state of sediments to the greatest extent possible. It effectively avoids disturbance and damage to the sample structure during sampling and transportation, making it a key technical means for accurately and reliably obtaining the sound velocity in seabed sediments. Existing in-situ measurement methods typically involve inserting a probe integrating a sound source and a transducer into the seabed sediment layer, and calculating the sound velocity by extracting the propagation time from the received sound wave signal.

[0003] Extracting the arrival time (first arrival time) of the direct wave from in-situ acoustic acquisition waveforms is a crucial step in calculating the sound velocity in sedimentary layers. Existing methods largely rely on manually or automatically picking up the first arrival point of the waveform to determine the sound wave propagation time. However, the actual first arrival point is usually located near the zero value of the source wavelet waveform, with extremely weak signal energy, low signal-to-noise ratio, and is easily affected by factors such as marine environmental noise, sedimentary layer attenuation, and measurement system noise, leading to picking errors. This problem is particularly prominent in the far channel of multi-channel acquisition modes. Since first arrival picking essentially relies on a single sampling point, it is highly sensitive to random errors. The time delay error introduced by this directly affects the stability and repeatability of the sound velocity calculation results, limiting the reliability of this method in practical applications.

[0004] To improve the stability of sound velocity calculations, some studies have adopted cross-correlation methods to invert the sound velocity in sedimentary layers by calculating the propagation delay between different received signals. This method utilizes the cross-correlation between the received signals in the water and those in the sedimentary layer, estimating the delay through overall waveform similarity matching, rather than relying on a single first-arrival point. Therefore, compared to traditional first-arrival picking methods, cross-correlation methods can suppress the influence of random noise and local interference to a certain extent, thereby improving the stability and noise resistance of the delay estimation.

[0005] However, the waveforms of transmitting transducers typically employ periodic sinusoidal modulated signals (such as sinusoidal pulse trains or linear frequency modulated signals). This is primarily to improve the source level and signal-to-noise ratio of the transmitted signal, thereby acquiring sufficient echo energy in the highly attenuated and noisy seabed environment. This conventional engineering choice, however, introduces an inherent vulnerability in cross-correlation delay estimation: the waveform structure of the periodic wavelet causes its autocorrelation function to exhibit equally spaced sidelobe peaks on the time axis. These sidelobe amplitudes are often comparable to or even indistinguishable from the main lobe. When the received signal is distorted or attenuated by multipath interference or noise, the cross-correlation operation can easily misidentify the sidelobe peaks as main lobes, leading to incorrect placement in adjacent integer period positions during time difference pickup, resulting in periodic jumps in integer period delay. This deviation is not a random error but a systematic trap determined by the periodic structure of the signal waveform itself. Once it occurs, it directly leads to orders of magnitude errors in the sound velocity inversion results, severely compromising the reliability of the measurement data.

[0006] Therefore, in in-situ measurements of seafloor sediments, it is essential to fully recognize the time delay ambiguity caused by periodic wavelets and to adopt corresponding suppression strategies in signal design or post-processing algorithms.

[0007] In summary, the key issue in improving the accuracy of sedimentary layer sound velocity calculation is how to fully enhance the shared effective propagation information between the reference signal and the received signal before cross-correlation analysis, and reduce the impact of uncorrelated interference components on time delay estimation. Summary of the Invention

[0008] To address the existing technical problems, the purpose of this invention is to provide an in-situ method for calculating the sound velocity of seafloor sedimentary layers based on envelope cross-weighted enhancement.

[0009] The specific technical solution is as follows:

[0010] S1, acquire the acoustic signals propagating through the water medium and the sediment layer medium, and filter them respectively to obtain the filtered signal in the water and the filtered signal in the sediment layer;

[0011] S2, perform Hilbert transform on the filtered signal in the water and the filtered signal in the sediment layer to obtain the envelope signal in the water and the envelope signal in the sediment layer; at the same time, normalize the amplitude of the filtered signal in the water and the filtered signal in the sediment layer to obtain the normalized signal in the water and the normalized signal in the sediment layer.

[0012] S3, using the envelope signal in the water and the envelope signal in the sediment layer, cross-weighted enhancement is performed on the normalized signal in the water and the normalized signal in the sediment layer to obtain the enhanced signal in the water and the enhanced signal in the sediment layer;

[0013] S4, extract the envelopes of the enhanced signal in the water and the enhanced signal in the sediment layer to obtain the enhanced envelope signal in the water and the enhanced envelope signal in the sediment layer;

[0014] S5, the enhanced envelope signal in the water is translated in the time domain by multiple preset translation amounts, and the cross-correlation value between the enhanced envelope signal and the enhanced envelope signal of the sediment layer under each translation amount is calculated, thereby constructing a cross-correlation function;

[0015] S6 converts the translation corresponding to the maximum value of the cross-correlation function into travel time to obtain the propagation time delay difference, and calculates the sound velocity of the sediment layer.

[0016] Furthermore, in S2, the calculation method for each envelope value in the water envelope signal and the sediment layer envelope signal is as follows:

[0017] Based on the filtered signals in the water and the filtered signals in the sediment layer, the analytic signals in the water and the analytic signals in the sediment layer are constructed using the Hilbert transform.

[0018] At each travel time, the modulus of the corresponding analytical signal at the current travel time is calculated using the underwater filtered signal and the sediment layer filtered signal, respectively, and used as the envelope values ​​of the underwater envelope signal and the sediment layer envelope signal at the current travel time.

[0019] Furthermore, the analyzed signal in the water is a complex number containing a real part and an imaginary part, wherein the real part is the filtered signal in the water, and the imaginary part is the Hilbert transform of the filtered signal in the water.

[0020] Furthermore, in S2, the calculation methods for the normalized signal in the water and the normalized signal in the sediment layer are as follows:

[0021] For a normalized signal in water, extract the maximum absolute value of the amplitude of the filtered signal in water over all travel times;

[0022] At each travel time, the amplitude of the current travel time of the filtered signal in the water is divided by the maximum value to obtain the normalized signal in the water.

[0023] The sedimentary layer normalized signal is calculated using the same method as the water normalized signal, and the sedimentary layer filtered signal replaces the water filtered signal.

[0024] Furthermore, in S3, the calculation method for the cross-weighted enhancement model is as follows:

[0025] The enhanced signal in water is obtained by multiplying the normalized signal in water, the envelope signal in water enhanced by the first exponential and the envelope signal of the sediment layer enhanced by the second exponential.

[0026] The sediment layer enhancement signal is obtained by multiplying the sediment layer normalized signal, the sediment layer envelope signal enhanced by the first exponential and the water envelope signal enhanced by the second exponential.

[0027] Furthermore, in step S5, the process of translating according to the translation amount is specifically as follows:

[0028] The enhanced envelope signal in the water is shifted along the time axis by a specified step size to obtain the shifted enhanced envelope signal in the water; the step size is the number of travel sampling points corresponding to the shift amount.

[0029] Furthermore, in S5, the formula for calculating the cross-correlation value under each translation amount is as follows:

[0030] ;

[0031] Where n represents the time-travel sampling points obtained from the sampling, and τ represents the translation amount. To enhance the envelope signal of the sedimentary layer, To obtain the translated enhanced envelope signal in water by shifting the enhanced envelope signal in water by τ, This is the cross-correlation value when the translation is τ.

[0032] Furthermore, in S5, the horizontal axis of the constructed cross-correlation function is the translation amount, and the vertical axis is the cross-correlation value.

[0033] Furthermore, in S6, the travel time corresponding to the translation amount is obtained by multiplying the translation amount by the travel time sampling interval of the in-situ detection device.

[0034] Furthermore, in S6, the formula for calculating the sound velocity of the deposition layer is:

[0035] ;

[0036] in, The sound velocity of the sedimentary layer, The transmit / receive distance is the distance between the geometric center of the transmitter and the geometric center of the receiver of the in-situ detection device. The speed of sound in water, The time delay is calculated using the translation amount corresponding to the maximum value of the cross-correlation function.

[0037] The beneficial effects of this invention are:

[0038] (1) An envelope cross-weighted enhancement mechanism is proposed. The enhancement weight is constructed by using the common energy characteristics of the reference signal and the sedimentation layer signal to achieve adaptive enhancement of effective propagation information and adaptive suppression of unrelated noise, thereby improving the separability of effective signal and noise.

[0039] (2) The enhanced envelope cross-correlation uses the overall energy structure of the wave packet for matching, rather than relying on single-point feature recognition, which can obtain more stable time delay estimation results and improve measurement repeatability and robustness.

[0040] (3) No manual or automatic picking of the first arrival point is required, avoiding the influence of strong attenuation of sediment layer, low signal-to-noise ratio and dispersion effect on the first arrival identification, and improving the accuracy of sound velocity calculation.

[0041] (4) Using the reference signal obtained by the same detection system in water as a benchmark can effectively reduce the error caused by the difference in system response and the change of sound source. Attached Figure Description

[0042] Figure 1 This is a schematic flowchart of the method of the present invention;

[0043] Figure 2 These are the original measured waveforms of the reference signal in the water and the signal from the sediment layer;

[0044] Figure 3 The waveforms of the underwater reference signal and sediment layer signal in the fourth channel after bandpass filtering;

[0045] Figure 4 The waveforms are the normalized versions of the underwater reference signal and the sediment layer signal in the fourth channel.

[0046] Figure 5 This is the normalized envelope of the underwater reference signal and the sediment layer signal in the fourth channel;

[0047] Figure 6 The waveform is obtained by cross-weighting the underwater reference signal and the sediment layer signal in the fourth channel;

[0048] Figure 7 The results show a comparison of the cross-correlation between the method of this invention and the conventional cross-correlation method in the fourth channel.

[0049] Figure 8 This is a comparison of the cross-correlation results of all channels of the method of this invention and the conventional cross-correlation method;

[0050] Figure 9 The results show a comparison of sound velocity between the method of this invention and the conventional cross-correlation method;

[0051] Figure 10 The waveforms of the underwater reference signal and sediment layer signal in the fourth channel after channel editing (interference removal);

[0052] Figure 11 The results show a comparison of the signal cross-correlation between the method of this invention and the conventional cross-correlation method for channel editing (interference removal) in the fourth channel; Detailed Implementation

[0053] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. Technical features in the various embodiments of the present invention can be combined accordingly without mutual conflict.

[0054] like Figure 1 As shown, the present invention proposes an in-situ calculation method for sound velocity in seabed sedimentary layers based on envelope cross-weighted enhancement. The method uses the reference signal obtained by the same in-situ detection device in water as a benchmark, extracts the envelope information of the reference signal and the sedimentary layer signal, constructs a cross-weighting factor to characterize the common energy characteristics of the two, and uses the weighting factor to perform synchronous enhancement processing on the two signals.

[0055] Subsequently, the propagation delay difference is estimated by calculating the cross-correlation function of the enhanced signal envelope, and the sound velocity in the sediment layer is obtained by combining the underwater sound velocity measured by CTD with the known transmit and receive distances. This method does not rely on first-arrival pickup, but uses the enhanced overall wave packet information for time delay estimation, thereby improving the stability of propagation delay extraction and the reliability of sediment layer sound velocity calculation, and is suitable for in-situ rapid measurement of acoustic parameters of seafloor sediment layers.

[0056] The specific steps are as follows:

[0057] S1, the probe of the in-situ detection device is placed directly in the water. The transmitter of the in-situ detection device emits a sound wave signal. After the sound wave signal propagates through the water medium, the receiver installed on the probe receives the echo signal, thereby measuring the sound wave signal in the water as a reference signal. The probe is then fully inserted into the sediment layer, and the sediment layer signal propagating through the sediment layer medium is collected in the same way.

[0058] In one specific embodiment of the present invention, a total of eight receivers are installed on the probe of the in-situ detection device. The final measured signals in the water and sediment layer of the eight channels are as follows: Figure 2 As shown, the red curve represents the measured signal in the water in each channel, and the black curve represents the measured signal in the sediment layer in each channel.

[0059] The reference signal in the water and the signal from the sediment layer are bandpass filtered separately, with the passband range determined based on the dominant frequency of the emitted sound source. In this invention, a zero-phase Butterworth filter is used for the bandpass filtering to avoid introducing additional phase distortion during the filtering process.

[0060] After filtering, the depositional layer signal varying with travel time t is obtained. and underwater reference signals .

[0061] Figure 3 This is a schematic diagram showing the amplitude of the filtered signal of the fourth channel changing with travel time in a specific embodiment of the present invention. The red curve represents the reference signal in the water, and the black curve represents the sediment layer signal. It can be seen that the received sound wave is affected by multipath propagation, transducer response and environmental noise, and most of the interference cannot be effectively removed after filtering.

[0062] S2, performs amplitude normalization processing on the filtered deposition layer signal and the reference signal:

[0063]

[0064]

[0065] in, This is the normalized sedimentary layer signal. This is the normalized reference signal in water. The symbol represents the absolute value, and T represents the total duration.

[0066] Normalization ensures that the strength of the two signals is at the same level, eliminating amplitude differences caused by different measurement conditions. This ensures that subsequent analysis focuses only on the similarity of the waveforms and is not affected by the overall signal magnitude.

[0067] Figure 4 In one specific embodiment of the present invention, the amplitude of the normalized underwater reference signal (red curve) and sediment signal (black curve) of the fourth channel varies with travel time.

[0068] S3, construct an envelope cross-weighted enhancement model.

[0069] First, Hilbert transforms are performed on the sediment layer signal and the reference signal in water, respectively, and the corresponding envelopes are calculated. and :

[0070]

[0071]

[0072] in, For Hilbert transform, Let be the signal envelope, and j be the imaginary unit (j squared is -1).

[0073] It is important to note that the Hilbert Transform is a linear operator primarily used to convert real signals into analytic signals. Its core function is to transform a real signal into a complex analytic signal, essentially by introducing a -90° phase shift to each frequency component of the signal, thereby allowing the extraction of instantaneous amplitude, frequency, and phase information. This invention uses it to generate the signal envelopes of underwater reference signals and sediment layer signals, effectively characterizing the time-varying nature of acoustic energy and reducing the impact of waveform oscillations on subsequent time delay estimation.

[0074] Figure 5 In one specific embodiment of the present invention, the amplitudes of the Hilbert-transformed underwater reference signal (red curve) and sediment signal (black curve) of the fourth channel change with travel time.

[0075] Subsequently, a cross-weighted enhancement model was constructed using the envelope of the sedimentation layer signal and the envelope of the reference signal.

[0076]

[0077]

[0078] in, , The positive real number enhancement index is preferred. ; This is the cross-weighted signal of the sedimentary layer; This is the cross-weighted reference signal in the water.

[0079] The aforementioned cross-weighted model utilizes the common energy characteristics between the envelopes of the sedimentation layer signal and the reference signal to construct enhancement weights. For example... Figure 6 As shown in a specific embodiment of the present invention, the amplitudes of the underwater reference signal (red curve) and sediment signal (black curve) obtained after the fourth channel is processed by the cross-weighted enhancement model change with travel time. It can be found that when the envelopes of the two signals have high energy at the same time, the corresponding waveform components are enhanced; when the energy exists only in a single signal or both signals are in a low energy state, the corresponding components are suppressed.

[0080] This processing can highlight the effective propagation information shared by the two signals and reduce the impact of unrelated interference components on subsequent time delay estimation.

[0081] S4, for the cross-weighted enhanced signal and The envelope was recalculated using the Hilbert transform to obtain the enhanced deposition layer signal envelope. and the enhanced reference signal envelope The cross-correlation function is calculated using the enhanced envelope. :

[0082]

[0083] Where n is the discrete sampling point number obtained by sampling the travel time, which is obtained by the in-situ detection device according to a fixed sampling rate; τ is the translation amount, which can take positive or negative values, and is used to... By shifting the corresponding amplitude-travel time curve by τ travel time sampling points in the positive or negative direction and multiplying it by the travel time sampling interval of the in-situ detection device, the actual time delay can be converted.

[0084] Using the cross-correlation function, different The cross-correlation value under the given values ​​is used to obtain the correlation with... The relevant cross-correlation function value fluctuation curve, and the shift corresponding to the maximum value of the cross-correlation function. Recorded as ,Will The converted time delay is defined as the difference in propagation time delay between the deposition layer signal and the reference signal. .

[0085] S5, Calculate the sound velocity in the sediment layer based on the propagation time delay difference:

[0086]

[0087] in, The sound velocity of the sedimentary layer, The transmit / receive distance is the distance between the geometric center of the transmitter of the in-situ detection device and the geometric center of the receiver corresponding to the current channel. The speed of sound in water, This represents the difference between the propagation time in the sediment layer and the propagation time in the water.

[0088] To demonstrate the effectiveness of the method proposed in this invention, further comparative experiments were conducted.

[0089] exist Figures 2 to 5 Based on the processed signals from the water and sediment layers, Figure 7 Taking the fourth channel as an example, the cross-correlation function curves calculated by the cross-weighted cross-correlation method proposed in this invention and the conventional cross-correlation method (i.e., without envelope weighting) are compared to obtain the comparison results. Figure 8 The comparison results for all channels are shown, where the black curve represents the cross-weighted cross-correlation method and the red curve represents the conventional cross-correlation method. Extraction is performed from these results. The results are shown in Table 1.

[0090] Table 1

[0091]

[0092] Based on the travel time difference calculated from Table 1, and combined with the measured underwater sound velocity of 1484.6 m / s and the transmit / receive distance of 1.0308 m, the sound velocity calculation results for all channels are as follows, according to the formula in S5. Figure 9 As shown, the black curve represents the cross-weighted cross-correlation method, and the red curve represents the conventional cross-correlation method.

[0093] It can be observed that the sound velocity of each channel in the sedimentary layer calculated by the conventional cross-correlation method has a large degree of dispersion and obvious fluctuations, which does not conform to the objective law that the physical properties of shallow seabed sediments are uniform and the sound velocity should tend to be consistent; while the multi-channel sound velocity results obtained by the envelope cross-weighted cross-correlation method are stable and the values ​​are close.

[0094] Taking the fourth channel as an example, the cross-weighted cross-correlation method proposed in this invention is further compared with the cross-correlation function curves calculated by the conventional cross-correlation method that incorporates channel editing (interference removal). Figure 10 In the fourth channel, the amplitude of the reference signal (red curve) and sediment signal (black curve) in the water and the original water reference signal and sediment signal are edited to show the changes in amplitude with travel time. After the channel is edited, the interference of the wake wave on the cross-correlation calculation results is removed. Figure 11 The results show a comparison between the cross-weighted cross-correlation method and the conventional cross-correlation method that incorporates channel editing. The red curve represents the cross-weighted cross-correlation method, and the black curve represents the conventional cross-correlation method.

[0095] Combination Figure 8 and Figure 11 It can be observed that in the fourth channel, the peak values ​​of both the conventional cross-correlation function and the conventional cross-correlation function after channel editing preprocessing correspond to negative time delays. This result means that the travel time of acoustic waves in the sediment layer is shorter than that of acoustic waves in the water. The peak value of the envelope cross-weighted cross-correlation function corresponds to a positive time delay, indicating that the travel time of acoustic waves in the water is faster.

[0096] Comparison Figure 3 The original measured waveforms can be directly verified that the initial arrival of the reference signal in the water is significantly earlier than the signal received by the sediment layer, that is, the travel time in the water is shorter than the travel time in the sediment layer. This proves that the calculation results of the envelope cross-weighted cross-correlation method proposed in this invention are more in line with the measured physical laws and have higher calculation accuracy.

[0097] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, all technical solutions obtained through equivalent substitution or transformation fall within the protection scope of the present invention.

Claims

1. A method for calculating in-situ seabed sound velocity based on envelope cross-weighted cross-correlation, characterized in that, include: S1, acquire the acoustic signals propagating through the water medium and the sediment layer medium, and filter them respectively to obtain the filtered signal in the water and the filtered signal in the sediment layer; S2, perform Hilbert transform on the filtered signal in the water and the filtered signal in the sediment layer to obtain the envelope signal in the water and the envelope signal in the sediment layer; at the same time, normalize the amplitude of the filtered signal in the water and the filtered signal in the sediment layer to obtain the normalized signal in the water and the normalized signal in the sediment layer. S3, using the envelope signal in the water and the envelope signal in the sediment layer, cross-weighted enhancement is performed on the normalized signal in the water and the normalized signal in the sediment layer to obtain the enhanced signal in the water and the enhanced signal in the sediment layer; S4, extract the envelopes of the enhanced signal in the water and the enhanced signal in the sediment layer to obtain the enhanced envelope signal in the water and the enhanced envelope signal in the sediment layer; S5, the enhanced envelope signal in the water is translated in the time domain by multiple preset translation amounts, and the cross-correlation value between the enhanced envelope signal and the enhanced envelope signal of the sediment layer under each translation amount is calculated, thereby constructing a cross-correlation function; S6 converts the translation corresponding to the maximum value of the cross-correlation function into travel time to obtain the propagation time delay difference, and calculates the sound velocity of the sediment layer.

2. The seabed in-situ sound velocity calculation method based on envelope cross-weighted cross-correlation as described in claim 1, characterized in that, In S2, the calculation method for each envelope value in the water envelope signal and the sediment layer envelope signal is as follows: Based on the filtered signals in the water and the filtered signals in the sediment layer, the analytic signals in the water and the analytic signals in the sediment layer are constructed using the Hilbert transform. At each travel time, the modulus of the corresponding analytical signal at the current travel time is calculated using the underwater filtered signal and the sediment layer filtered signal, respectively, and used as the envelope values ​​of the underwater envelope signal and the sediment layer envelope signal at the current travel time.

3. The seabed in-situ sound velocity calculation method based on envelope cross-weighted cross-correlation as described in claim 2, characterized in that, The analytical signal in the water is a complex number containing a real part and an imaginary part, wherein the real part is the filtered signal in the water and the imaginary part is the Hilbert transform of the filtered signal in the water.

4. The seabed in-situ sound velocity calculation method based on envelope cross-weighted cross-correlation as described in claim 1, characterized in that, In S2, the calculation methods for the normalized signal in water and the normalized signal in the sediment layer are as follows: For a normalized signal in water, extract the maximum absolute value of the amplitude of the filtered signal in water over all travel times; At each travel time, the amplitude of the current travel time of the filtered signal in the water is divided by the maximum value to obtain the normalized signal in the water. The sedimentary layer normalized signal is calculated using the same method as the water normalized signal, and the sedimentary layer filtered signal replaces the water filtered signal.

5. The method for calculating seabed sound velocity based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In S3, the calculation methods for the enhanced signal in water and the enhanced signal in the sediment layer are as follows: The enhanced signal in water is obtained by multiplying the normalized signal in water, the envelope signal in water enhanced by the first exponential and the envelope signal of the sediment layer enhanced by the second exponential. The sediment layer enhancement signal is obtained by multiplying the sediment layer normalized signal, the sediment layer envelope signal enhanced by the first exponential and the water envelope signal enhanced by the second exponential.

6. The seabed in-situ sound velocity calculation method based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In step S5, the translation process based on the translation amount is specifically as follows: The enhanced envelope signal in the water is shifted along the time axis by a specified step size to obtain the shifted enhanced envelope signal in the water; the step size is the number of travel sampling points corresponding to the shift amount.

7. The method for calculating seabed sound velocity based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In S5, the formula for calculating the cross-correlation value under each translation is as follows: ； Where n represents the time-travel sampling points obtained from the sampling, and τ represents the translation amount. To enhance the envelope signal of the sedimentary layer, To obtain the translated enhanced envelope signal in water by shifting the enhanced envelope signal in water by τ, This is the cross-correlation value when the translation is τ.

8. The method for calculating seabed sound velocity based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In S5, the horizontal axis of the cross-correlation function is the translation amount, and the vertical axis is the cross-correlation value.

9. The method for calculating seabed sound velocity based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In S6, the propagation delay difference is the travel time corresponding to the translation amount, which is obtained by multiplying the translation amount by the travel time sampling interval of the in-situ detection device.

10. The method for calculating seabed sound velocity based on envelope cross-weighted cross-correlation according to claim 1, characterized in that, In S6, the formula for calculating the sound velocity of the deposition layer is: ； in, The sound velocity of the sedimentary layer, The transmit / receive distance is the distance between the geometric center of the transmitter and the geometric center of the receiver of the in-situ detection device. The speed of sound in water, This is due to the time delay difference in propagation.

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