A universal modified hufnagel-valley model turbulence profile inversion calculation method

Abstract

The application provides a universal correction Hufnagel-Valley model turbulence profile inversion calculation method.The method comprises the following steps: obtaining atmospheric coherence degree data of the region by using a measuring instrument; obtaining the r0 value of the minimum data variance according to the atmospheric coherence length data; determining the value range of the seven parameters of the generalized Hufnagel-Valley model, the accuracy G and the proportional factor M; substituting the above parameters into a simulation formula to obtain the seven parameter values of the generalized Hufnagel-Valley model; and obtaining the turbulence profile and the atmospheric isoplanatic angle profile of the region from the seven parameter values.The above method obtains effective turbulence profile information based on single data, can obtain the atmospheric isoplanatic angle in addition to the turbulence profile, does not need a large amount of meteorological data as input, avoids the complexity of data collection and processing, and has wider applicability in actual engineering applications.

Description

Technical Field

[0001] This invention belongs to the field of turbulence profile technology, and in particular relates to a universal method for inverting and calculating turbulence profiles using the modified Hufnagel-Valley model. Background Technology

[0002] Atmospheric turbulence restricts the development of free-space optical communication. Variations in turbulence intensity cause random fluctuations in the atmospheric refractive index, disrupting the coherence of light waves. This leads to a decrease in the signal-to-noise ratio, an increase in the bit error rate, and a reduction in channel capacity in the communication receiving system, ultimately affecting communication quality. The intensity variation characteristics of atmospheric turbulence are usually characterized by atmospheric parameters, commonly including the atmospheric refractive index structure constant. The isohalo angle θ0 and the atmospheric coherence length r0. Profiles can reflect the changes in atmospheric turbulence intensity at different vertical heights. Besides using weather balloons, SCIDAR (SC Intillation Detection and Ranging), MASS (Multi-Aperture Scintillation Sensor), radar, and other instruments, they can also be used to analyze these profiles. In addition to direct measurement of the profile, inversion is performed using a large amount of meteorological data or θ0 and r0 data as input. Profile methods have always been a focus of research. Robert K. Tyson et al., based on the Hufnagel-Valley (HV) model, inverted the upper-level wind speed parameters and the ground-level atmospheric refractive index structure constant of turbulence parameters from real-time measured isohalo angles θ0 and atmospheric coherence lengths r0, thereby obtaining... In China, Cheng Zhi et al. optimized the inversion formula of Robert K. Tyson et al. Regarding the profile, many researchers in recent years have used machine learning methods such as artificial neural networks and support vector machines based on meteorological data or θ0, r0 data... Turbulence profiles are estimated and predicted. In 2016, Wang Yao et al. used five conventional meteorological parameters as input and artificial neural networks to predict the turbulence profile of the sea surface near Mauna Loa, Hawaii for one month. In 2020, Chen Xiaowei et al. constructed an artificial neural network model to estimate the near-surface turbulence profile in Northwest China based on six meteorological parameters, including temperature, wind speed, wind direction, and air pressure, measured by a temperature pulsator and a WXT520 meteorological sensor. In 2022, Zhu Liming et al. used six measured radiosonde profiles, including temperature, pressure, relative humidity, wind speed, wind speed shear, and temperature shear, to estimate the turbulence profile in coastal areas based on support vector machines.

[0003] Most current methods for inverting, estimating, and predicting turbulence profiles, whether using meteorological parameter data or θ0 and r0 data as input, suffer from problems such as large initial input data volume and multiple parameter types. This leads to a large computational load and complexity in the inversion process, and makes it impossible to extract useful information about the inverted atmospheric turbulence profile from single-parameter data. In addition, the large amount of data acquisition also increases the investment of human and material resources. Therefore, whether from the perspective of simplifying theoretical calculations or reducing practical workload, it is necessary to study a method for inverting atmospheric turbulence profiles based on single-parameter data. Summary of the Invention

[0004] The purpose of this invention is to solve the problems in the prior art by proposing a universal method for inverting and calculating the turbulence profile of the modified Hufnagel-Valley model. This method can measure the turbulence profile and atmospheric iso-halo angles, requires less input data, and yields results with good correlation.

[0005] This invention is achieved through the following technical solution: This invention proposes a universal method for inverting and calculating the turbulence profile of the modified Hufnagel-Valley model, specifically including:

[0006] Data on atmospheric coherence in a certain region are obtained using measuring instruments;

[0007] The minimum data variance value r0 is obtained based on atmospheric coherence length data;

[0008] Determine the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, as well as the accuracy G and the scaling factor M;

[0009] The seven parameter values ​​of the generalized Hufnagel-Valley model are obtained by substituting the parameters determined above into the simulation formula;

[0010] The turbulence profile and atmospheric iso-halo profile of the region are obtained from seven parameter values.

[0011] Furthermore, the acquisition of atmospheric coherence data for a certain region using measuring instruments includes:

[0012] The atmospheric coherence length data of this region was accurately measured using an atmospheric coherence length measuring instrument, an atmospheric coherence length and isohalo angle measuring instrument, and a lidar instrument, and denoted as r0.

[0013] Furthermore, the formula for obtaining the minimum data variance r0 value based on atmospheric coherence length data is as follows:

[0014]

[0015] In the formula: N is the sample data variance; n represents the sample data values ​​for the entire day; r 0iR represents the i-th r0 data value; R represents the r0 value that minimizes N; it can be calculated that when When the variance N of the r0 data for the whole day is minimized.

[0016] Furthermore, determining the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, the accuracy G, and the scaling factor M includes:

[0017] The theoretical formula for the generalized Hufnagel-Valley model is as follows:

[0018]

[0019] In the formula: a1, b1, and c together characterize the changes in turbulence intensity in the region above the tropopause; a2 and b2 together characterize the changes in turbulence intensity in the troposphere; a3 and b3 together characterize the changes in turbulence intensity in the boundary layer; a2 represents the turbulence intensity at the beginning of the troposphere; a3 represents the changes in turbulence near the ground; b1, b2, and b3 represent the rate at which the turbulence decreases with increasing height in each turbulent layer; h is the height.

[0020] Furthermore, the value ranges of the seven parameters a1, c, b1, a2, b2, a3, and b3 are determined based on historical turbulence profile data for the region; the accuracy G is less than or equal to 0.0001; and the scaling factor M is determined by the ratio of the average atmospheric coherence length to the atmospheric isohalo angle for the region.

[0021] Furthermore, the seven parameter values ​​of the generalized Hufnagel-Valley model obtained by substituting the aforementioned determined parameters into the simulation formula include:

[0022] First, the simulation formulas are established. Both the isohalo angle θ0 and the atmospheric coherence length r0 characterize the intensity variation of atmospheric turbulence along the propagation path. r0 represents the diffraction limit of the light wave after propagating through atmospheric turbulence, and θ0 represents the angular correlation of the wavefront after the beacon light propagates through atmospheric turbulence. Both contain... The path integral term, the coherence length of the entire atmosphere, and the theoretical formulas for the halo angle of the entire atmosphere are as follows:

[0023]

[0024]

[0025] In the formula: k=2π / λ, k is the wave number, λ is the wavelength; z is the transmission path; h is the height; Substituting equation (2) into equation (3) and equation (4) respectively, the expansions of r0 and θ0 of the entire layer are obtained as follows:

[0026]

[0027]

[0028] Simplify equations (5) and (6) using equation (7).

[0029]

[0030] The Γ(z) function is the Gamma function, and the simplified result is as follows:

[0031]

[0032]

[0033] Combining equations (8) and (9), we get:

[0034]

[0035] From equation (10) above, it can be seen that there is a certain relationship between the coherence length of the entire atmosphere and the isohalo angle of the entire atmosphere; equation (10) is transformed as follows:

[0036]

[0037] θ0 can be solved from equation (11).

[0038] Furthermore, to solve for θ0 through r0, it is necessary to determine the values ​​of the seven parameters a1, c, b1, a2, b2, a3, and b3. The specific method for determining the values ​​of the seven parameters is as follows: Given the r0 data value for a certain day, firstly, calculate the R value when N reaches its minimum value using equation (1). Then, input the selected ranges of the seven parameters a1, c, b1, a2, b2, a3, and b3, the range of the scaling factor M, and the accuracy G. The values ​​of the seven parameters can then be simulated and obtained using equation (12).

[0039]

[0040] In the formula: R i It is the calculated i-th r0 value; θ i It is the calculated i-th θ0 value; G is the accuracy; M is the precision. max M min These are the upper and lower limits of the scaling factor M, respectively.

[0041] Furthermore, the turbulence profile and atmospheric isohedral profile of the region obtained from the seven parameter values ​​include:

[0042] Substituting the obtained seven parameter values ​​into the generalized Hufnagel-Valley model yields the turbulence profile of the region; substituting the obtained seven parameter values ​​into equation (11) yields the atmospheric iso-halo profile of the region through the atmospheric coherence length profile value.

[0043] This invention proposes an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of a universal modified Hufnagel-Valley model turbulence profile inversion calculation method.

[0044] This invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of a universal modified Hufnagel-Valley model turbulence profile inversion calculation method.

[0045] The method described in this invention retrieves turbulence profiles from measured atmospheric coherence length data of the region. It requires less data, is simple to calculate, avoids the input of a large amount of meteorological data, extracts turbulence profile information from a single data point, and can also calculate the atmospheric isohalo angle values ​​of the region. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart illustrating a universal method for inverting turbulence profiles using a modified Hufnagel-Valley model, provided as an embodiment of the present invention;

[0048] Figure 2 A comparison of the turbulence profile of the Nanshan area of ​​Xinjiang on December 12, 2020, obtained by the inversion calculation method, with the Xianghe model, provided for embodiments of the present invention;

[0049] Figure 3 This is a comparison chart of calculated and measured values ​​of the isotropic profile of the Nanshan area of ​​Xinjiang on December 12, 2020, provided as an embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Combination Figures 1-3This invention proposes a universal method for inverting turbulence profiles using the modified Hufnagel-Valley model, specifically including:

[0052] Data on atmospheric coherence in a certain region are obtained using measuring instruments;

[0053] The minimum data variance value r0 is obtained based on atmospheric coherence length data;

[0054] Determine the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, as well as the accuracy G and the scaling factor M;

[0055] The seven parameter values ​​of the generalized Hufnagel-Valley model are obtained by substituting the parameters determined above into the simulation formula;

[0056] The turbulence profile and atmospheric iso-halo profile of the region are obtained from seven parameter values.

[0057] The method of obtaining atmospheric coherence data for a certain region using measuring instruments includes:

[0058] The atmospheric coherence length data of this region was accurately measured using an atmospheric coherence length measuring instrument (DIMM), an atmospheric coherence length and isohalo angle measuring instrument, and a lidar instrument, and denoted as r0.

[0059] The formula for obtaining the minimum data variance r0 value based on atmospheric coherence length data is as follows:

[0060]

[0061] In the formula: N is the sample data variance; n represents the sample data values ​​for the entire day; r 0i R represents the i-th r0 data value; R represents the r0 value that minimizes N; it can be calculated that when When the variance N of the r0 data for the whole day is minimized.

[0062] The determination of the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, the accuracy G, and the scaling factor M includes:

[0063] The theoretical formula for the generalized Hufnagel-Valley model is as follows:

[0064]

[0065] In the formula: a1, b1, and c together characterize the changes in turbulence intensity in the region above the tropopause; a2 and b2 together characterize the changes in turbulence intensity in the troposphere; a3 and b3 together characterize the changes in turbulence intensity in the boundary layer; a2 represents the turbulence intensity at the beginning of the troposphere; a3 represents the changes in turbulence near the ground; b1, b2, and b3 represent the rate at which the turbulence decreases with increasing height in each turbulent layer; h is the height.

[0066] The range of values ​​for the seven parameters a1, c, b1, a2, b2, a3, and b3 is determined based on historical turbulence profile data for the region; the accuracy G is less than or equal to 0.0001; and the scaling factor M is determined by the ratio of the average atmospheric coherence length to the atmospheric isohalo angle for the region.

[0067] The seven parameter values ​​of the generalized Hufnagel-Valley model obtained by substituting the aforementioned determined parameters into the simulation formula include:

[0068] First, the simulation formulas are established. Both the isohalo angle θ0 and the atmospheric coherence length r0 characterize the intensity variation of atmospheric turbulence along the propagation path. r0 represents the diffraction limit of the light wave after propagating through atmospheric turbulence, and θ0 represents the angular correlation of the wavefront after the beacon light propagates through atmospheric turbulence. Both contain... The path integral term, the coherence length of the entire atmosphere, and the theoretical formulas for the halo angle of the entire atmosphere are as follows:

[0069]

[0070]

[0071] In the formula: k=2π / λ, k is the wave number, λ is the wavelength; z is the transmission path; h is the height; Substituting equation (2) into equation (3) and equation (4) respectively, the expansions of r0 and θ0 of the entire layer are obtained as follows:

[0072]

[0073]

[0074] Simplify equations (5) and (6) using equation (7).

[0075]

[0076] The Γ(z) function is the Gamma function, and the simplified result is as follows:

[0077]

[0078]

[0079] Combining equations (8) and (9), we get:

[0080]

[0081] From equation (10) above, it can be seen that there is a certain relationship between the coherence length of the entire atmosphere and the isohalo angle of the entire atmosphere; equation (10) is transformed as follows:

[0082]

[0083] θ0 can be solved from equation (11).

[0084] To solve for θ0 using r0, it is necessary to determine the values ​​of seven parameters: a1, c, b1, a2, b2, a3, and b3. The specific method for determining the values ​​of these seven parameters is as follows: Given the r0 data value for a certain day, firstly, calculate the R value when N reaches its minimum using equation (1). Then, input the selected ranges of the seven parameters a1, c, b1, a2, b2, a3, and b3, the range of the scaling factor M, and the accuracy G. The values ​​of the seven parameters can then be simulated using equation (12).

[0085]

[0086] In the formula: R i It is the calculated i-th r0 value; θ i It is the calculated i-th θ0 value; G is the accuracy; M is the precision. max M min These are the upper and lower limits of the scaling factor M, respectively.

[0087] The turbulence profile and atmospheric isotropic profile of the region, obtained from the seven parameter values, include:

[0088] Substituting the obtained seven parameter values ​​into the generalized Hufnagel-Valley model yields the turbulence profile of the region; substituting the obtained seven parameter values ​​into equation (11) yields the atmospheric iso-halo profile of the region through the atmospheric coherence length profile value.

[0089] Example

[0090] This invention provides a universal method for inverting turbulence profiles in a modified Hufnagel-Valley model, such as... Figure 1 As shown, it mainly includes the following steps:

[0091] Step 1: Obtain atmospheric coherence data for the region using measuring instruments, including:

[0092] The atmospheric coherence length data of this region was accurately measured using instruments such as the Atmospheric Coherence Length Measuring Instrument (DIMM), the Atmospheric Coherence Length and Isohalate Measuring Instrument, and lidar, and denoted as r0.

[0093] For example, the atmospheric coherence length data r0 of the Nanshan region of Xinjiang was measured.

[0094] Step 2: The formula for obtaining the minimum data variance r0 value based on atmospheric coherence length data is as follows:

[0095]

[0096] In the formula: N is the sample data variance; n represents the sample data values ​​for the entire day; r 0i Let represent the i-th r0 data value; R represents the r0 value that minimizes N. Calculations show that when... When the variance N of the r0 data for the whole day is minimized.

[0097] For example, the atmospheric coherence length data for the Nanshan area of ​​Xinjiang on December 12, 2020, is R = 4.9984 cm.

[0098] Step 3: Determine the value ranges of the seven parameters of the generalized Hufnagel-Valley model, including accuracy G and scaling factor M:

[0099] The theoretical formula for the generalized Hufnagel-Valley model is as follows:

[0100]

[0101] In the formula: a1, b1, and c together characterize the changes in turbulence intensity in the region above the tropopause; a2 and b2 together characterize the changes in turbulence intensity in the troposphere; a3 and b3 together characterize the changes in turbulence intensity in the boundary layer; a2 represents the turbulence intensity at the beginning of the troposphere; a3 represents the changes in turbulence near the ground; b1, b2, and b3 represent the rate at which the turbulence decreases with increasing height in each turbulent layer; h is the height.

[0102] The range of values ​​for the seven parameters a1, c, b1, a2, b2, a3, and b3 is determined using historical turbulence profile data for the region. The accuracy G is generally less than or equal to 0.0001; the scale factor M is determined by the ratio of the average atmospheric coherence length to the atmospheric isohalo angle for the region.

[0103] For example, the range of values ​​for the seven parameters in the Nanshan area of ​​Xinjiang on December 12, 2020 is as follows: a1∈[10e-53,10e-51], c∈[8,10], b1∈[800,1200], a2∈[10e-18,10e-15], b2∈[1500,3000], a3∈[10e-17,10e-14], b3∈[200,800], accuracy G=0.0001, M∈[0.45440,0.45450].

[0104] Step 4: Substitute the above parameters into the simulation formula to obtain the seven parameter values ​​of the generalized Hufnagel-Valley model, including:

[0105] First, the simulation formulas are established. Both the isohalo angle θ0 and the atmospheric coherence length r0 characterize the intensity variation of atmospheric turbulence along the propagation path. r0 represents the diffraction limit of the light wave after propagating through atmospheric turbulence, and θ0 represents the angular correlation of the wavefront after the beacon light propagates through atmospheric turbulence. Both contain... The path integral term, the coherence length of the entire atmosphere, and the theoretical formulas for the halo angle of the entire atmosphere are as follows:

[0106]

[0107]

[0108] In the formula: k=2π / λ, k is the wave number, λ is the wavelength; z is the transmission path; h is the height. Substituting equation (2) into equations (3) and (4) respectively, the expansions of r0 and θ0 for the entire layer are obtained as follows:

[0109]

[0110]

[0111] Simplify equations (5) and (6) using equation (7).

[0112]

[0113] The Γ(z) function is the Gamma function, and the simplified result is as follows:

[0114]

[0115] Combining equations (8) and (9), we get:

[0116]

[0117] From equation (10) above, it can be seen that there is a certain relationship between the coherence length of the entire atmosphere and the isohalo angle of the entire atmosphere. Equation (10) can be transformed as follows:

[0118]

[0119] As shown in equation (11), to solve for θ0 using r0, it is necessary to determine the values ​​of the seven parameters a1, c, b1, a2, b2, a3, and b3. Therefore, the following solution method is proposed. Given the r0 data value for a certain day, firstly, the R value when N reaches its minimum value is obtained using equation (1). Then, input the selected ranges of the seven parameters a1, c, b1, a2, b2, a3, and b3, the range of the scaling factor M, and the accuracy G. The values ​​of the seven parameters can be simulated and obtained using equation (12).

[0120]

[0121] In the formula: R i It is the calculated i-th r0 value; θ i It is the calculated i-th θ0 value; G is the accuracy; M is the precision. max M min These are the upper and lower limits of the scaling factor M, respectively.

[0122] For example, the values ​​of the seven parameters in the Nanshan area of ​​Xinjiang on December 12, 2020 are a1 = 6.73e-52, c = 10, b1 = 933.33, a2 = 3.74e-16, b2 = 2200, a3 = 1.64e-15, and b3 = 350.

[0123] Step 5: The turbulence profile and atmospheric isotropic profile for this region are obtained from the seven parameter values, including:

[0124] Substituting the obtained seven parameter values ​​into the generalized Hufnagel-Valley model yields the turbulence profile of the region; substituting the obtained seven parameter values ​​into equation (11) yields the atmospheric iso-halo profile of the region through the atmospheric coherence length profile value.

[0125] For example, a comparison of the turbulence profiles of seven parameters in the Nanshan area of ​​Xinjiang on December 12, 2020, with those in the Xianghe area. Figure 2 As shown; the obtained atmospheric isohalo profiles are, for example... Figure 3 As shown.

[0126] The above-described solutions in the embodiments of the present invention have the following main beneficial effects:

[0127] This invention retrieves turbulence profiles from measured atmospheric coherence length data in the region. It requires less data, is simple to calculate, avoids the input of a large amount of meteorological data, and extracts turbulence profile information from a single data point. It can also calculate the atmospheric isohalo angle values ​​for the region.

[0128] This invention proposes an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of a universal modified Hufnagel-Valley model turbulence profile inversion calculation method.

[0129] This invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of a universal modified Hufnagel-Valley model turbulence profile inversion calculation method.

[0130] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the methods described in this invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0131] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0132] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0133] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0134] The foregoing has provided a detailed description of a universal modified Hufnagel-Valley model turbulence profile inversion calculation method proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A universal method for inverting turbulence profiles in a modified Hufnagel-Valley model, characterized in that, Specifically, it includes: Data on atmospheric coherence in a certain region are obtained using measuring instruments; The minimum data variance was obtained based on atmospheric coherence length data. value; Determine the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, as well as the accuracy G and the scaling factor M; The seven parameter values ​​of the generalized Hufnagel-Valley model are obtained by substituting the parameters determined above into the simulation formula; The turbulence profile and atmospheric iso-halo profile of the region are obtained from seven parameter values; The determination of the range of values ​​for the seven parameters of the generalized Hufnagel-Valley model, the accuracy G, and the scaling factor M includes: The theoretical formula for the generalized Hufnagel-Valley model is as follows: （2） In the formula: 、 、 These three factors together characterize the changes in turbulence intensity in the tropopause and above. 、 Both characterize the variation in turbulence intensity within the troposphere; , The two, when combined, characterize the variation in turbulence intensity within the boundary layer; Indicates the turbulence intensity at the beginning of the troposphere. This represents the changes in near-surface turbulence. 、 , This represents the rate at which the turbulence layer decays with increasing altitude; It is height; The seven parameter values ​​of the generalized Hufnagel-Valley model obtained by substituting the aforementioned determined parameters into the simulation formula include: The first step is to establish the simulation formula, including the isocyanate angle. Coherence length with the atmosphere Both can characterize the intensity variation of atmospheric turbulence along the transport path. This represents the diffraction limit of light waves after propagating through atmospheric turbulence. This indicates the angular correlation of the wavefront after the beacon light propagates through atmospheric turbulence; both contain... The path integral term, the coherence length of the entire atmosphere, and the theoretical formulas for the halo angle of the entire atmosphere are as follows: （3） （4） In the formula: , It is the wave number. It is the wavelength; It is the transmission path; It is the height; substituting equation (2) into equations (3) and (4) respectively, we can obtain the height of the entire floor. , The expansion is as follows: （5） （6） Simplify equations (5) and (6) using equation (7). （7） The function is the Gamma function, and the simplified result is as follows: （8） （9） Combining equations (8) and (9), we get: （10） From the above equation (10), it can be seen that there is a certain relationship between the coherence length of the entire atmosphere and the isohalo angle of the entire atmosphere; Equation (10) is transformed as follows: （11） The solution can be obtained from equation (11). ; pass Solve The premise is to determine 、 、 , 、 、 , The values ​​of the seven parameters are determined as follows: Given the values ​​of a certain day... The data value is first obtained using equation (1). When the minimum value is reached Value, then enter the selected value. 、 、 , 、 、 , Seven parameter ranges, scaling factor The range and precision of values The seven parameter values ​​can be obtained by simulation using equation (12): （12） In the formula: It is the calculated number of indivual value; It is the calculated number of indivual value; It's about accuracy; , These are the scaling factors. The upper and lower limits.

2. The method according to claim 1, characterized in that, The use of measuring instruments to obtain atmospheric data for a certain region Coherence data includes: The atmospheric coherence length data for this region was accurately measured using an atmospheric coherence length measuring instrument, an atmospheric coherence length and isohalo angle measuring instrument, and a lidar instrument, and denoted as [reference needed]. .

3. The method according to claim 2, characterized in that, The minimum data variance is obtained based on atmospheric coherence length data. The formula for the value is: （1） In the formula: It is the variance of the sample data; Represents the sample data values ​​for the entire day; Representing the indivual Data value; Representative When the minimum value is reached Value; calculation shows that when At that time, all day data variance N Minimum.

4. The method according to claim 1, characterized in that, The above was determined based on historical turbulence profile data for the region. 、 、 , 、 、 , The range of values ​​for the seven parameters; the accuracy G is less than or equal to 0.0001; the scaling factor M is determined by the ratio of the average atmospheric coherence length to the atmospheric isohalo angle in the region.

5. The method according to claim 1, characterized in that, The turbulence profile and atmospheric isotropic profile of the region, obtained from the seven parameter values, include: Substituting the obtained seven parameter values ​​into the generalized Hufnagel-Valley model yields the turbulence profile of the region; substituting the obtained seven parameter values ​​into equation (11) yields the atmospheric iso-halo profile of the region through the atmospheric coherence length profile value of the region.

6. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-5.

7. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-5.

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