A method for separating wake internal waves and volume internal waves of a vehicle

Abstract

The present application discloses a method for separating wake internal waves and volume internal waves of a vehicle, which relates to the technical field of ship and ocean engineering. The method includes: obtaining a time cloud map of the internal wave height along the target direction induced by the vehicle during navigation; extracting the propagation speed of the internal wave along the target direction at different frequencies; determining a first critical frequency point for dividing the propagation speeds of the internal waves at all frequencies into two groups; and using the first critical frequency point to separate the internal waves into volume internal waves and wake internal waves along the target direction, so as to further separately extract the fluctuation characteristic parameters of the wake internal waves and the volume internal waves subsequently. This method can distinguish the characteristics of volume internal waves and wake internal waves, realize the separation of volume internal waves and wake internal waves, and has important application value for the detection and tracking of the internal wave wake of the vehicle.

Description

Technical Field

[0001] This application relates to the technical field of ship and ocean engineering, and in particular to a method for separating wake internal waves and volume internal waves of a vehicle. Background Art

[0002] The internal waves of a vehicle are internal water body fluctuations generated when the vehicle sails in a temperature, salinity, and density-stratified ocean. The flow field induced by the internal waves will change the nature of the ocean background flow. By studying the fluctuation characteristics and propagation mechanism of the internal waves, the track of the vehicle can be non-acoustically detected, which has important academic significance and military application value.

[0003] However, the internal waves of a vehicle include two parts: the internal waves generated by the vehicle itself and its wake, which are respectively called volume internal waves and wake internal waves. Among them, the volume internal waves are a kind of steady-state internal waves, while the wake internal waves are internal waves generated by large-scale vortices in the turbulent wake of the vehicle and have a certain degree of randomness. After the vehicle exceeds a certain motion speed, the wake internal waves of the vehicle will be generated, and when the vehicle moves at a high speed, the proportion of the wake internal waves in the internal waves gradually increases. Since the fluctuation characteristics of the volume internal waves and the wake internal waves are quite different, directly studying the fluctuation characteristics of the entire internal waves of the vehicle cannot accurately characterize the track of the vehicle, affecting the accuracy of non-acoustic detection. Summary of the Invention

[0004] In view of the above problems and technical requirements, the applicant of this application proposes a method for separating wake internal waves and volume internal waves of a vehicle. The technical solution of this application is as follows:

[0005] A method for separating wake internal waves and volume internal waves of a vehicle, the separation method comprising:

[0006] Obtaining a time cloud map of the internal wave height along a target direction of the internal waves induced by the vehicle during navigation, the time cloud map of the internal wave height reflecting the variation curve of the wave height with time at different positions along the target direction of the internal waves;

[0007] Extracting the propagation speed of the internal waves along the target direction at different frequencies based on the time cloud map of the internal wave height;

[0008] Determining a first critical frequency point for dividing the propagation speeds of the internal waves at all frequencies into two groups;

[0009] Using the first critical frequency point to separate the internal waves induced by the vehicle during navigation into volume internal waves and wake internal waves along the target direction;

[0010] Wherein, the target direction is one or more of the x direction, the y direction, and the z direction. The x direction, the y direction, and the z direction are perpendicular to each other and form a three-dimensional coordinate system. The plane formed by the x direction and the y direction is parallel to the horizontal plane of the geodetic coordinate system, and the vehicle sails along the x direction or the y direction.

[0011] A further technical solution is that the propagation speed of internal waves along the target direction at different frequencies is extracted based on the internal wave height time cloud map, including:

[0012] Convert the internal wave height time cloud map to the frequency domain to obtain the corresponding internal wave spectrum cloud map;

[0013] Convert the data at one frequency in the internal wave spectrum cloud map to the time domain to obtain the internal wave height time cloud map of the internal wave at that frequency;

[0014] Calculate the slope of the internal wave height time cloud map of the internal wave at that frequency to obtain the propagation speed of the internal wave along the target direction at the said frequency.

[0015] A further technical solution is that the method for determining the first critical frequency point includes:

[0016] Cluster the propagation speeds of internal waves at all frequencies into two clusters, each cluster including the propagation speeds of internal waves at all frequencies in a frequency interval, and determine the first critical frequency point for separating the frequency intervals corresponding to the two clusters.

[0017] A further technical solution is that the method for determining the first critical frequency point includes:

[0018] Use the target frequency interval as the initial frequency band to be divided;

[0019] Divide the frequency band to be divided into several sub-bands;

[0020] Extract the propagation speeds of internal waves along the target direction in each sub-band based on the internal wave height time cloud map;

[0021] Determine the frequency band for dividing the propagation speeds of internal waves in all sub-bands into two groups as the updated frequency band to be divided;

[0022] Preset the target accuracy. For the updated frequency band to be divided, re-execute the step of dividing the frequency band to be divided into several sub-bands until the frequency range of the updated frequency band to be divided reaches the target accuracy. The frequency ranges of the sub-bands obtained by dividing the frequency band to be divided in each iteration process decrease in turn, obtain the target frequency interval that reaches the target accuracy, and take a certain point on the target frequency interval that reaches the target accuracy as the first critical frequency point.

[0023] A further technical solution is that using the first critical frequency point to separate the internal waves induced by the vehicle during navigation into volume internal waves and wake internal waves along the target direction includes:

[0024] When determining the first critical frequency point of the target direction based on the internal waves induced by the vehicle during navigation in the first fluid environment After that, according to Convert the first critical frequency point Into the second critical frequency point

[0025] According to the second critical frequency point Separate the internal waves induced when the vehicle is sailing in the second fluid environment into volume internal waves and wake internal waves along the target direction;

[0026] Among them, Is the maximum buoyancy frequency of the first fluid environment, Is the maximum buoyancy frequency of the said fluid environment.

[0027] Its further technical solution is that, according to the second critical frequency point, separate the internal waves induced when the vehicle is sailing in the second fluid environment into volume internal waves and wake internal waves along the target direction, including:

[0028] Convert the internal wave height time cloud diagram along the target direction of the internal waves induced during the sailing process of the vehicle into the frequency domain range to obtain the corresponding internal wave spectrum cloud diagram;

[0029] After filtering the data with frequencies less than the first critical frequency point in the internal wave spectrum cloud diagram, convert it into the time domain range to obtain the internal wave height time cloud diagram of the wake internal wave;

[0030] After filtering the data with frequencies greater than or equal to the first critical frequency point in the internal wave spectrum cloud diagram, convert it into the time domain range to obtain the internal wave height time cloud diagram of the volume internal wave.

[0031] Its further technical solution is that the method for obtaining the internal wave height time cloud diagram along the target direction includes:

[0032] Obtain the voltage time cloud diagram along the target direction through the detection linear array. The voltage time cloud diagram reflects the voltage change curve with time at different positions of the internal wave along the target direction. The detection linear array includes detection probes arranged at intervals in sequence along the target direction, and all the detection probes along the target direction sample synchronously;

[0033] Based on the density stratification curve, convert the voltage time cloud diagram into the internal wave height time cloud diagram along the target direction; The density stratification curve reflects the density of the fluid at different depths.

[0034] Its further technical solution is that, based on the density stratification curve, convert the voltage time cloud diagram into the internal wave height time cloud diagram along the target direction, including:

[0035] Convert the voltage-time cloud map into a density fluctuation time history according to the voltage-density calibration relationship of each detection probe; convert the density fluctuation time history into a z-direction displacement fluctuation time history through a density stratification curve, and subtract the z-direction reference depth from the z-direction displacement fluctuation time history of each detection probe 1 to obtain an internal wave height time cloud map;

[0036] The density fluctuation time history reflects the density change curve of the internal wave at different positions along the target direction over time; the z-direction displacement fluctuation time history reflects the z-direction displacement change curve of the internal wave at different positions along the target direction over time; the z-direction reference depth represents the fluid depth of the detection probe in the fluid static state.

[0037] A further technical solution thereof is that the separation method further includes: separately extracting the fluctuation characteristic parameters of the separated wake internal wave and volume internal wave, and the fluctuation characteristic parameters include at least one of wave amplitude, period, propagation speed, wavelength, wave peak-to-peak value, and waveform opening angle.

[0038] The beneficial technical effects of this application are:

[0039] This application discloses a method for separating wake internal waves and volume internal waves of a vehicle. This method obtains a cloud map of the internal wave height changing with time, extracts the propagation speed of the internal wave at different frequencies, and uses the characteristic that the propagation speeds of the wake internal wave and the volume internal wave are different to determine the critical frequency point for dividing the wake internal wave and the volume internal wave. Finally, the wake internal wave and the volume internal wave can be separated, so as to facilitate the separate study of the fluctuation characteristics of the wake internal wave and the volume internal wave, can more accurately characterize the wave-current characteristics of the internal wave, and is beneficial to improving the accuracy of non-acoustic detection.

[0040] After obtaining the first critical frequency point in the first fluid environment, the separation method can be converted to obtain the second critical frequency point applicable to the second fluid environment through the Froude number similarity relationship, which can be used for the separation of internal waves in the second fluid environment, making the method applicable to different fluid environments and having strong versatility.

[0041] After separating the wake internal wave and the volume internal wave in this application, the fluctuation characteristic parameters of the wake internal wave and the volume internal wave can be separately extracted. The fluctuation characteristic parameters include at least one of wave amplitude, period, propagation speed, wavelength, wave peak-to-peak value, and waveform opening angle, which can be used for the detection and tracking of the vehicle by underwater / air sensors, and have important application value for the detection of the internal wave wake of the vehicle and the development of stealth technology. Brief Description of the Drawings

[0042] Figure 1 is a schematic flow chart of an embodiment of this application.

[0043] Figure 2 is a schematic flow chart of another embodiment of this application.

[0044] Figure 3 In an example of the present application, it is a schematic diagram of the xoy plane of the vehicle and the detection probe arranged along the y direction.

[0045] Figure 4 In an example of the present application, it is a schematic diagram of the yoz plane of the vehicle and the detection probe arranged along the y direction.

[0046] Figure 5 In an example of the present application, it is a schematic diagram of the fluid density stratification in the stratified flow test tank.

[0047] Figure 6 In an example of the present application, it is a schematic diagram of obtaining the first critical frequency point by sequentially dividing sub-frequency bands starting from the target frequency range.

[0048] Explanation of reference numerals: 1. Detection probe; 2. Vehicle; 3. Internal wave of volume; 4. Internal wave of wake; 5. Initial position of vehicle. Detailed implementation manners

[0049] The following further describes the detailed implementation manners of the present application with reference to the accompanying drawings.

[0050] As Figure 1 shown, the method for separating the internal wave of the wake of the vehicle and the internal wave of volume in the present application includes:

[0051] Step S110, obtaining the time cloud map of the internal wave height along the target direction of the internal wave induced by the vehicle during navigation. The target direction is one or more of the x direction, y direction, and z direction. The x direction, y direction, and z direction are perpendicular to each other and form a three-dimensional coordinate system. The plane formed by the x direction and the y direction is parallel to the horizontal plane of the geodetic coordinate system, and the vehicle sails along the x direction or the y direction.

[0052] The time cloud map of the internal wave height reflects the variation curve of the wave height with time at different positions along the target direction of the internal wave.

[0053] Step S120, extracting the propagation speed of the internal wave along the target direction at different frequencies based on the time cloud map of the internal wave height.

[0054] Step S130, determining the first critical frequency point for dividing the propagation speeds of the internal wave at all frequencies into two groups.

[0055] Step S140, separating the internal wave induced by the vehicle during navigation into the internal wave of volume and the internal wave of wake along the target direction by using the first critical frequency point.

[0056] The method for separating wake internal waves and volume internal waves of the present application determines the critical frequency point for dividing wake internal waves and volume internal waves by studying the time-frequency characteristics of internal waves and using the characteristic that the propagation speeds of wake internal waves and volume internal waves are different. Finally, the wake internal waves and volume internal waves can be separated, which is convenient for separately studying the wave characteristics of wake internal waves and volume internal waves, can more accurately characterize the wave-current characteristics of internal waves, and is beneficial to improving the accuracy of non-acoustic detection.

[0057] To more clearly illustrate a method for separating wake internal waves and volume internal waves of the present application, the following will elaborate on the method embodiments of the present application in conjunction with the accompanying drawings, as Figure 2 shown.

[0058] Step S210: Obtain the time cloud map of the internal wave height along the target direction of the internal waves induced by the vehicle during navigation.

[0059] Generally, the first critical frequency point is determined through the above steps S110 - S130 in the scenario of a tank test. In this embodiment, first, a test platform is built using a stratified flow test tank, and a navigation test is carried out using this test platform to obtain the time cloud map of the internal wave height. A fluid with density stratification is set in the stratified flow test tank used for building the test platform to simulate the effect of stratified flow in seawater. A virtual three-dimensional coordinate system is established such that the plane formed by the x-direction and the y-direction is parallel to the horizontal plane of the geodetic coordinate system, and the z-direction is perpendicular to the horizontal plane of the geodetic coordinate system. The vehicle is placed at the starting section of the stratified flow test tank, and the vehicle is controlled to navigate along the x-direction or the y-direction.

[0060] A detection line array is also set in the test tank. The detection line array includes detection probes arranged at intervals along the target direction. In one embodiment, the detection line array only includes detection probes arranged along the target direction. Or in another embodiment, the detection line array simultaneously includes detection probes arranged along multiple directions among the x-direction, the y-direction, and the z-direction. During the navigation of the vehicle and when it passes through the detection line array, all the detection probes of the detection line array perform synchronous sampling to obtain the time cloud map of the internal wave height along the target direction.

[0061] All the detection probes are generally arranged at equal intervals, and for each detection probe along the target direction, except for the coordinate in the target direction being different, the coordinates in the other two directions are the same. For example, in an instance, taking the navigation direction of the vehicle as the x-direction, the ship width direction of the vehicle as the y-direction for navigation, and the target direction as the y-direction as an example, the detection probes 1 arranged at intervals along the target direction are as Figure 3 , 4As shown, a series of detection probes 1 are arranged symmetrically and equidistantly along the transverse direction (y-direction) of the water tank with respect to the navigation body's navigation route at the same depth and the same longitudinal position in the test section of the stratified flow test water tank. That is, the coordinates of all detection probes 1 along the y-direction are different, but the coordinates along the z-direction are all z0 and the coordinates along the x-direction are all x0. In one example, the detection probe 1 can be an electrical conductivity meter.

[0062] In Figure 3 the example shown, after the navigation body 3 accelerates from the initial position 5 of the navigation body to the set speed U0 along the x-direction, it moves uniformly through the detection line array. The detection probe 1 synchronously samples at a set sampling frequency (which can be selected to be greater than 10 Hz) and outputs a voltage signal that changes with time and records it in the computer to obtain a voltage-time cloud map along the target direction. The voltage-time cloud map reflects the voltage-time change curve of the internal wave at different positions along the target direction.

[0063] Based on the density stratification curve ρ(z) of the fluid environment where the navigation body is located, the voltage-time cloud map is converted into an internal wave height-time cloud map along the target direction. The density stratification curve reflects the density of the fluid at different depths.

[0064] Including:

[0065] First, according to the voltage-density calibration relationship volp(ρ) of each detection probe 1, the voltage-time cloud map is converted into a density fluctuation time history, and the density fluctuation time history reflects the density-time change curve of the internal wave at different positions along the target direction.

[0066] Then, through the density stratification curve, the density fluctuation time history is converted into a z-direction displacement fluctuation time history, and the z-direction displacement fluctuation time history reflects the z-direction displacement-time change curve of the internal wave at different positions along the target direction. In Figure 3 and Figure 4 the example shown, when t = 0 in the fluid static state, a certain detection probe 1 is located at a certain fluid depth dep0 in the stratified fluid, as Figure 5 (a) shown. When t = t0, although the installation position of the detection probe 1 is fixed, due to the fluid fluctuation caused by the internal wave induced by the navigation body, the fluid density detected by this detection probe 1 at the depth corresponding to t = 0 is dep1, as Figure 5 (b) shown. Therefore, according to the density at the detection probe 1, its z-direction displacement (dep1 - dep0) can be determined, and thus the z-direction displacement fluctuation time history can be obtained.

[0067] Finally, the z-direction reference depth is subtracted from the z-direction displacement fluctuation time history of each detection probe 1 to obtain the internal wave height time cloud diagram h(σ,t); wherein σ represents the target direction, which is any one of the x-direction, y-direction, and z-direction; and the z-direction reference depth of each detection probe 1 represents the fluid depth of the detection probe 1 when the fluid is in a static state.

[0068] Step S220, based on the internal wave height time cloud map, the propagation speed of the internal wave along the target direction at different frequencies is extracted. It includes: converting the internal wave height time cloud map h(σ,t) that changes along the target direction σ with time t to the frequency domain range, and obtaining the corresponding internal wave spectrum cloud map G(σ,f) that changes along the target direction σ with frequency f. Fourier transform can be selected to realize the operation of converting the time domain to the frequency domain range, and its expression is G(σ,f)=F[h(σ,t)], and function F represents Fourier transform.

[0069] The area where the internal wave propagates along the target direction σ is identified by the internal wave spectrum cloud map G(σ,f), and the frequency range of the area where the internal wave propagates along the target direction σ is selected as the target frequency interval 1(0,f max1 ) to analyze the internal wave characteristics.

[0070] In one embodiment, considering the frequency interval 1 (0, f max1 ) may contain the frequency of surface waves and other components, so the frequency interval 2(0,f max ) as the target frequency interval. Target frequency interval 2(0,f max ) has the maximum value f max It is determined by the buoyancy frequency of the stratified fluid. In a stable stratified fluid, the fluid particles move in the vertical direction after being disturbed. The combined effect of gravity and buoyancy always makes it return to the equilibrium position and oscillate due to inertia. The frequency of the oscillation is called the buoyancy frequency. The expression of the buoyancy frequency is: Where g represents the acceleration due to gravity, ρ represents the fluid density at the z-direction coordinate, It represents the partial derivative of the potential density with respect to the z-direction coordinate z. Take the maximum value of the buoyancy frequency N max Determine the target frequency range (0,f max ), whose expression is: max =N max / 2π.

[0071] In one embodiment, the data at a frequency in the internal wave spectrum cloud map G(σ,f) is converted to the time domain to obtain the internal wave height time cloud map at the frequency. The inverse Fourier transform can be selected to realize the operation of converting the frequency domain to the time domain. The slope of the internal wave height time cloud map at the frequency is calculated as the propagation speed of the internal wave along the target direction σ at the frequency, and the expression is Cσ = Δσ / Δt. The propagation speed is calculated for each frequency in the target frequency range (0, f max ) to obtain the propagation speed of internal waves along the target direction σ at different frequencies.

[0072] Step S230: Determine the first critical frequency point for dividing the propagation speeds of internal waves along the target direction σ at all frequencies into two groups

[0073] The propagation speed of internal waves along the target direction σ is related to the motion speed of the vehicle and the buoyancy frequency of the stratified fluid. There are obvious differences in the propagation speeds of wake internal waves and volume internal waves, and the difference in propagation speed increases with the increase in the motion speed of the vehicle. Based on this variation characteristic of the propagation speed, after calculating the propagation speeds at various frequencies, by dividing the propagation speeds into two groups, the target frequency range (0, f max ) can be correspondingly divided into two groups, thereby obtaining the first critical frequency point

[0074] Determine the first critical frequency point The method includes:

[0075] Cluster the calculated propagation speeds of internal waves along the target direction σ at all frequencies into two clusters. Each cluster includes the propagation speeds of internal waves at all frequencies in a frequency range. The frequency ranges corresponding to the two clusters do not overlap, then determine the frequency for separating the frequency ranges corresponding to the two clusters as the first critical frequency point

[0076] Step S240: Use the first critical frequency point to separate the internal waves induced by the vehicle during navigation into volume internal waves and wake internal waves along the target direction.

[0077] In one embodiment, when the vehicle is navigating in the first fluid environment and the first critical frequency point in the target direction is determined by the above method After that, this first critical frequency point can be directly used in the same first fluid environment to achieve internal wave separation. However, in actual situations, the fluid environment where the vehicle is located may change, and the density stratification curves of different fluid environments are different. Therefore, it is necessary to convert the obtained first critical frequency point For example, as described above, usually the first critical frequency point is determined through tests in the first fluid environment of the pool test scenario while the marine environment of actual ship navigation is often different from the pool test scenario.

[0078] Then, based on the internal waves induced when the vehicle is navigating in the first fluid environment, the first critical frequency point of the target direction is determined. After that, through the Froude number similarity relationship, according to the first critical frequency point is converted into the second critical frequency point is the maximum buoyancy frequency of the first fluid environment, is the maximum buoyancy frequency of the second fluid environment.

[0079] Then, according to the second critical frequency point the internal waves induced when the vehicle is navigating in the second fluid environment are separated into volume internal waves and wake internal waves along the target direction. It includes: converting the time cloud map of the internal wave height along the target direction σ of the internal waves induced during the navigation of the vehicle into the frequency domain to obtain the corresponding internal wave spectrum cloud map. The implementation method is similar to the above step S210 and will not be elaborated here. Then, after filtering the data with frequencies less than the second critical frequency point in the internal wave spectrum cloud map and converting it to the time domain, the time cloud map h Wiw (y, t) of the internal wave height of the wake internal wave is obtained. After filtering the data with frequencies greater than or equal to the second critical frequency point in the internal wave spectrum cloud map and converting it to the time domain, the time cloud map h Lee (y, t) of the internal wave height of the volume internal wave is obtained. Thus, the volume internal wave and the wake internal wave along the target direction are separated.

[0080] The above filtering process is used to remove interference noise, and a Butterworth filter can be selected for filtering.

[0081] Step S250, after separating the wake internal wave and the volume internal wave, the fluctuation characteristic parameters of the wake internal wave and the volume internal wave are extracted respectively. The fluctuation characteristic parameters include at least one of wave amplitude, period, propagation speed, wavelength, peak-to-peak value, and waveform opening angle.

[0082] In the above steps S220 and S230, for the continuous internal wave spectrum cloud map G(σ, f), different frequencies are taken and the sampling amount of the propagation speed of the internal wave at this frequency is calculated respectively, and the sampling accuracy will also affect the calculation result. Therefore, in another embodiment, the frequency range is used as the calculation unit, and the first critical frequency point is determined by dividing the internal wave spectrum cloud map into frequency bands and calculating the propagation speed of the internal wave within the frequency band. Then the methods implemented in the above steps S220 and S230 include, as Figure 5 、 6 shown:

[0083] Step S310, for the target frequency interval (0, fmax ) As the initial frequency band R1 to be divided.

[0084] Step S320, initialize the iteration number n = 1.

[0085] Step S330, divide the frequency band R to be divided in the nth iteration n into M n sub - frequency bands. The frequency band R to be divided can be evenly divided or unevenly divided, that is, the frequency ranges covered by any two sub - frequency bands obtained are equal or not equal. When the value of the iteration number n is different, the number M of sub - frequency bands obtained by division n can be equal or not equal. n

[0086] Step S340, based on the internal wave height - time cloud map h(σ,t), respectively extract the propagation speed of the internal wave along the target direction σ in each sub - frequency band. It is similar to the method of extracting the propagation speed along the target direction σ at each frequency in the above - mentioned step S220.

[0087] First, convert the internal wave height - time cloud map h(σ,t) to the frequency domain range to obtain the internal wave spectrum cloud map G(σ,f). Then, convert the data of the internal wave spectrum cloud map G(σ,f) within a sub - frequency band to the time domain range to obtain the internal wave height - time cloud map of the internal wave in this sub - frequency band, and calculate the slope of the internal wave height - time cloud map of the internal wave in this sub - frequency band as the propagation speed of the internal wave along the target direction σ in this sub - frequency band.

[0088] Step S350, determine the frequency band used to divide the propagation speeds of the internal wave in all sub - frequency bands into two groups as the updated frequency band to be divided. Since this embodiment will continuously iterate and optimize, the updated frequency band to be divided extracted each time does not need to be very accurate, as long as the propagation speeds of the internal wave along the target direction σ in each sub - frequency band with a frequency less than the updated frequency band to be divided belong to the same clustering cluster, and the propagation speeds of the internal wave along the target direction σ in each sub - frequency band with a frequency greater than the updated frequency band to be divided belong to the same clustering cluster. Thus, the propagation speeds in the frequency band intervals on both sides can be divided into two groups using the updated frequency band to be divided, and thus the first critical frequency point f c 1 can be determined within the updated frequency band to be divided.

[0089] Step S360, detect whether the frequency range of the updated frequency band to be divided reaches the set target accuracy. If it reaches the set target accuracy, the wake internal wave and volume internal wave noise interference within the frequency range of the updated frequency band to be divided are less than the set threshold, and the noise interference components of the internal wave between each sub - frequency band within the frequency range are less than the set threshold.

[0090] Step S370: when it is determined that the frequency range of the updated frequency band to be divided has not reached the target accuracy, the updated frequency band group to be divided is used as the frequency band to be divided R of the n+1th iteration. n+1 , let n = n + 1 and execute steps S330 to S360 again, and enter the next iteration to continue subdividing. And the frequency range of the sub-bands obtained by dividing the frequency band to be divided in each iteration process is reduced successively, that is, in any n + 1th iteration, the frequency band R to be divided is n+1 The frequency range of the sub-bands obtained by division is smaller than the frequency band R to be divided in the nth iteration. n The frequency range of the sub-frequency bands obtained by division is gradually reduced to approach the target accuracy.

[0091] Step S380: when it is determined that the frequency range of the updated frequency band to be divided reaches the target accuracy, a certain frequency on the frequency band to be divided that reaches the target accuracy is taken as the first critical frequency point. For example, the common frequency endpoint of the frequency band to be divided that reaches the target accuracy is taken as the first critical frequency point

[0092]

[0093] For example, in one instance, Figure 6 As shown, the target frequency interval (0,f max ) is used as the initial frequency band R1 to be divided, and the frequency band R1 to be divided is divided into 10 sub-bands, which are respectively recorded as the first-level sub-band 1 to the first-level sub-band 10. The propagation speed of the internal wave along the target direction σ in the first-level sub-band 1 to the first-level sub-band 10 is calculated respectively, and then the frequency range formed by the first-level sub-band 4 and the first-level sub-band 5 after the update of the frequency band to be divided is determined. Since the frequency range of the updated frequency band to be divided has not yet reached the target accuracy, the updated frequency band to be divided is used as the frequency band R2 to be divided for the second iteration, and the frequency band R2 to be divided is divided into 8 sub-bands, which are respectively recorded as the second-level sub-band 1 to the second-level sub-band 8, and the frequency range of each second-level sub-band is smaller than the frequency range of each first-level sub-band. The above method is continued to be used to further determine the frequency range formed by the second-level sub-band 6 and the first-level sub-band 7 after the update of the frequency band to be divided. Since the frequency range of the updated frequency band to be divided reaches the target accuracy, a certain frequency is finally selected from the updated frequency band to be divided as the first critical frequency point

[0094] The above is only a preferred embodiment of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the protection scope of the present application.

Claims

1. A method for separating internal waves in the wake of a vehicle from internal waves in the volume, characterized in that The separation method includes: Obtaining a time cloud map of internal wave heights along a target direction induced by a vehicle during navigation, where the time cloud map of internal wave heights reflects the variation curve of the wave height with time at different positions along the target direction of the internal wave; Extracting the propagation speed of the internal wave along the target direction at different frequencies based on the time cloud map of internal wave heights; Using the characteristic that the propagation speeds of wake internal waves and volume internal waves are different to determine a first critical frequency point for dividing the propagation speeds of the internal wave at all frequencies into two groups; Separating the internal wave induced by the vehicle during navigation into volume internal waves and wake internal waves along the target direction by using the first critical frequency point; Wherein, the target direction is one or more of the x-direction, y-direction, and z-direction. The x-direction, y-direction, and z-direction are perpendicular to each other and form a three-dimensional coordinate system. The plane formed by the x-direction and y-direction is parallel to the horizontal plane of the geodetic coordinate system, and the vehicle sails along the x-direction or y-direction.

2. The method for separating internal waves in the wake of a vehicle and internal waves in a volume according to claim 1, wherein The extracting the propagation speed of the internal wave along the target direction at different frequencies based on the time cloud map of internal wave heights includes: Converting the time cloud map of internal wave heights to a frequency domain range to obtain a corresponding internal wave frequency spectrum cloud map; Converting the data at one frequency in the internal wave frequency spectrum cloud map to the time domain range to obtain a time cloud map of internal wave heights of the internal wave at the frequency; Calculating the slope of the time cloud map of internal wave heights of the internal wave at the frequency to obtain the propagation speed of the internal wave along the target direction at the frequency.

3. The method for separating internal waves in the wake of a vehicle and internal waves in a volume according to claim 1, characterized in that, The method for determining the first critical frequency point includes: Clustering the propagation speeds of the internal wave at all frequencies into two clusters, where each cluster includes the propagation speeds of the internal wave at all frequencies in a frequency interval, and determining the first critical frequency point for separating the frequency intervals corresponding to the two clusters.

4. The method for separating internal waves in the wake of a vehicle and internal waves of volume according to claim 1, characterized in that, The method for determining the first critical frequency point includes: Taking a target frequency interval as the initial frequency band to be divided; Dividing the frequency band to be divided into several sub-bands; Extracting the propagation speeds of the internal wave along the target direction at each sub-band based on the time cloud map of internal wave heights; Determining the frequency band for dividing the propagation speeds of the internal wave at all sub-bands into two groups as the updated frequency band to be divided; Presetting a target accuracy. For the updated frequency band to be divided, re-execute the step of dividing the frequency band to be divided into several sub-bands until the frequency range of the updated frequency band to be divided reaches the target accuracy. The frequency ranges of the sub-bands obtained by dividing the frequency band to be divided in each iteration process decrease in sequence, obtaining a target frequency interval that reaches the target accuracy, and taking a certain point on the target frequency interval that reaches the target accuracy as the first critical frequency point.

5. The method for separating internal waves in the wake of a vehicle and internal waves in the volume according to claim 4, characterized in that, The calculation method of the target frequency interval includes: Calculate the buoyancy frequency of the stratified fluid and take the maximum value of the buoyancy frequency Determine that the target frequency range is , .

6. The method for separating wake internal waves and volume internal waves of a navigating body according to claim 1, characterized in that The separating the internal wave induced by the vehicle during navigation into volume internal waves and wake internal waves along the target direction by using the first critical frequency point includes: Determine the first critical frequency point of the target direction based on the internal wave induced when the vehicle sails in the first fluid environment After that, according to Convert the first critical frequency point Into the second critical frequency point ; According to the second critical frequency point Separate the internal waves induced when the vehicle sails in the second fluid environment into volume internal waves and wake internal waves along the target direction; wherein, is the maximum buoyancy frequency of the first fluid environment, is the maximum buoyancy frequency of the second fluid environment.

7. The method for separating internal waves in the wake of a vehicle and internal waves of volume according to claim 6, characterized in that, According to the second critical frequency point Separating the internal waves induced when the vehicle sails in the second fluid environment into volume internal waves and wake internal waves along the target direction, including: Convert the time cloud map of the internal wave height along the target direction induced by the vehicle during navigation into the frequency domain to obtain the corresponding internal wave spectrum cloud map; After filtering the data with frequencies less than the second critical frequency point in the internal wave spectrum cloud map and then converting it to the time domain, obtain the time cloud map of the internal wave height of the wake internal wave; After filtering the data with frequencies greater than or equal to the second critical frequency point in the internal wave spectrum cloud map and then converting it to the time domain, obtain the time cloud map of the internal wave height of the volume internal wave.

8. The method for separating internal waves in the wake of a vehicle and internal waves in the volume according to claim 1, wherein The method for obtaining the time cloud map of the internal wave height along the target direction includes: Obtain the voltage time cloud map along the target direction through a detection linear array. The voltage time cloud map reflects the voltage change curve over time at different positions along the target direction of the internal wave. The detection linear array includes detection probes arranged at intervals in sequence along the target direction, and all the detection probes along the target direction sample synchronously; Convert the voltage time cloud map into the time cloud map of the internal wave height along the target direction based on the density stratification curve; the density stratification curve reflects the density of the fluid at different depths.

9. The method for separating internal waves in the wake of a vehicle and internal waves in the volume according to claim 8, wherein The conversion of the voltage time cloud map into the time cloud map of the internal wave height along the target direction based on the density stratification curve includes: Convert the voltage time cloud map into the density fluctuation time history according to the voltage density calibration relationship of each detection probe; convert the density fluctuation time history into the z-direction displacement fluctuation time history through the density stratification curve, and subtract the z-direction reference depth from the z-direction displacement fluctuation time history of each detection probe to obtain the time cloud map of the internal wave height; The density fluctuation time history reflects the density change curve over time at different positions along the target direction of the internal wave; the z-direction displacement fluctuation time history reflects the z-direction displacement change curve over time at different positions along the target direction of the internal wave; the z-direction reference depth represents the fluid depth of the detection probe in the static state of the fluid.

10. The method for separating internal waves in the wake of a vehicle and internal waves of volume according to claim 1, characterized in that, The separation method further includes: respectively extracting the fluctuation characteristic parameters of the separated wake internal wave and volume internal wave, and the fluctuation characteristic parameters include at least one of wave amplitude, period, propagation speed, wavelength, wave peak-to-peak value, and waveform opening angle.

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