Method and device for constructing wide-area environment optical turbulence probability prediction model

Abstract

The invention discloses a method and device for constructing a wide-area environment optical turbulence probability prediction model, and the method comprises the steps: S1, obtaining ball-borne turbulence detection historical experiment data, and obtaining a meteorological parameter profile and an atmospheric optical turbulence profile; s2, calculating a product of meteorological parameter gradient quantities according to meteorological parameter profiles corresponding to historical experimental data; s3, calculating a model coefficient profile by using the product of the atmospheric optical turbulence profile and the meteorological parameter gradient quantity, and calculating a typical region atmospheric optical turbulence model coefficient profile library according to the model coefficient profile; s4, calculating according to the atmospheric optical turbulence model coefficient profile library of the typical region to obtain coefficient probability density distribution of the optical turbulence model; and S5, constructing an optical turbulence probability prediction model according to the coefficient probability density distribution of the optical turbulence model. According to the method, the limitation of an existing optical turbulence detection technology and mode is made up, and the problem that an optical turbulence empirical mode (average mode) constructed based on limited turbulence detection test data is not applicable to many application scenes is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of atmospheric optical parameter detection, and in particular to a method for constructing a wide-area environmental optical turbulence probability prediction model, a prediction method and a device. Background Art

[0002] At present, most advanced optoelectronic systems are used in the atmosphere, and their system performance will inevitably be affected by the atmosphere. The degradation effect of atmospheric optical turbulence on beam quality limits the range and effect of advanced optoelectronic systems, becoming a bottleneck for the application of ground-based optoelectronic engineering.

[0003] With the gradual deployment and large-scale trial of optoelectronic systems, the uncertainty of the intensity of atmospheric optical turbulence and its temporal and spatial variation characteristics in a wide-area environment on optoelectronic systems has become a dilemma faced by users.

[0004] The spatial distribution of atmospheric optical turbulence is usually measured using sounding balloons, aircraft, radars, etc., but traditional atmospheric optical turbulence detection methods and technologies have defects such as poor real-time performance, insufficient spatial representativeness, and low cost-effectiveness when acquiring the optical turbulence characteristics of a wide-area environment. There is an urgent need to build a model tool that can serve the evaluation of atmospheric optical turbulence characteristics and their impact on system performance when optoelectronic systems are used in a wide-area environment. Summary of the invention

[0005] The object of the present invention is to provide a method for constructing a wide-area environmental atmospheric optical turbulence probability prediction model, so as to achieve the prediction and characterization of the wide-area environmental atmospheric optical turbulence probability.

[0006] To this end, the present invention provides a method for constructing a wide-area environmental optical turbulence probability prediction model, comprising: S1, obtaining historical experimental data of ball-borne turbulence detection, obtaining meteorological parameter profiles (P(h), T(h), u(h), v(h) and θ(h)) and atmospheric optical turbulence profiles S2. Calculate the product M(h) of the meteorological parameter gradient according to the meteorological parameter profile corresponding to the historical experimental data; S3. Use the atmospheric optical turbulence profile The product of the gradient of the meteorological parameters M(h) is used to calculate the model coefficient profile k(h), and the coefficient profile library of the atmospheric optical turbulence model in typical regions is obtained based on this: k(h)1, k(h)2, k(h)3, ..., k(h) N ; S4, according to the atmospheric optical turbulence model coefficient profile library of typical regions: k(h)1, k(h)2, k(h)3, ..., k(h) N , from the ground to the sky, the probability density distribution k(h) of the optical turbulence model coefficients is calculated in sequence for the data at the same altitude point p , the subscript p is the probability value; S5, according to the probability density distribution k(h) of the optical turbulence model coefficientsp Constructing an optical turbulence probability prediction model: in is the predicted probability distribution of the optical turbulence profile.

[0007] According to another aspect of the present invention, a method for predicting the probability distribution of optical turbulence profile in a wide-area environment is provided, comprising the following steps: S11, obtaining a probability prediction model for optical turbulence in a wide-area environment, wherein the optical turbulence probability prediction model is obtained according to the above-mentioned method for constructing a probability prediction model for optical turbulence in a wide-area environment; S12, obtaining a meteorological parameter profile (P(h), T(h), u(h), v(h) and θ(h)) corresponding to the atmospheric optical turbulence to be predicted, and calculating the product M(h) of the meteorological parameter gradient quantities based on the profile; S13, inputting the specified probability density distribution of the optical turbulence model coefficients and the calculated product M(h) of the meteorological parameter gradient quantities into the optical turbulence prediction model, and outputting the predicted optical turbulence profile probability distribution.

[0008] The present invention also provides a device for predicting the probability of optical turbulence in a wide-area environment, comprising a computer program, which is used to implement the steps of the above-mentioned method for predicting the probability distribution of optical turbulence profiles in a wide-area environment when executed.

[0009] The present invention focuses on the demand for predicting the spatiotemporal distribution characteristics of atmospheric optical turbulence in a wide-area environment in the deployment and application of advanced optoelectronic systems. It proposes a method for constructing a probability prediction model for atmospheric optical turbulence in a wide-area environment based on atmospheric environmental parameters and the physical laws of atmospheric turbulence, and forms a technology for predicting the spatiotemporal distribution probability of optical turbulence in a wide-area environment. This method provides an effective technical means for obtaining the spatiotemporal distribution characteristics of atmospheric optical turbulence in a wide-area environment, and effectively improves the guarantee capability of the characteristic parameters of atmospheric optical turbulence in optoelectronic engineering applications.

[0010] The wide-area environment optical turbulence spatiotemporal distribution probability prediction and characterization technology formed based on the present invention can effectively make up for the limitations of existing optical turbulence detection technologies and methods, as well as the problem that the optical turbulence empirical model (average model) constructed based on limited turbulence detection test data is not applicable in many application scenarios, and has important engineering application prospects.

[0011] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0013] Figure 1is a schematic diagram of the turbulence sounding measurement device;

[0014] Figure 2 is a schematic diagram of the optical turbulence measurement module;

[0015] Figure 3 It is a flow chart for constructing coefficients of mathematical model of atmospheric optical turbulence;

[0016] Figure 4 It is a flow chart for calculating the probability distribution of the atmospheric optical turbulence model coefficients;

[0017] Figure 5 It is a flow chart of the probability prediction of atmospheric optical turbulence in a wide-area environment. DETAILED DESCRIPTION

[0018] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0019] Based on previous research on atmospheric optical turbulence detection and model construction, the present invention is driven by abundant field observation data and based on the laws of atmospheric physics, and uses mathematical statistics and big data analysis technology to construct a wide-area environmental atmospheric optical turbulence probability prediction model, thereby forming a wide-area environmental optical turbulence spatiotemporal distribution probability prediction technology.

[0020] (1) Optical turbulence detection test and data storage

[0021] The present invention adopts the high-altitude turbulence meteorological detection system developed by the Hefei Institutes of Physical Science, Chinese Academy of Sciences / Anhui Institute of Optics and Precision Mechanics.

[0022] The high-altitude turbulence meteorological detection system is composed of a sounding balloon 20, a measurement system 10 carried by the sounding balloon, a ground receiving system 30 and a big data intelligent statistical learning system 40. Figure 1 shown.

[0023] The high-altitude turbulence meteorological detection system can measure the optical turbulence of the atmosphere from the ground to the high altitude And the vertical profiles of the five common meteorological elements: temperature, humidity, air pressure, wind speed and wind direction.

[0024] Atmospheric optical turbulence The detection is completed by the optical turbulence measurement module, and the detection of temperature, air pressure and humidity is completed by conventional meteorological parameter measurement modules such as temperature, pressure and humidity sensor measurement boards. The ground receiving system 30 composed of a receiving antenna and a receiving device can receive conventional meteorological parameters and atmospheric optical turbulence transmitted by the measurement system 10. The original high-resolution vertical profile data with the same parameters.

[0025] A single sounding measurement can obtain temperature, humidity, wind speed, wind direction and atmospheric optical turbulence up to 20 km High-resolution vertical profiles of equal parameters.

[0026] The detection system uses the Beidou positioning method to measure wind, and uses the Beidou receiver installed on the sounding balloon to determine the longitude, latitude and altitude of the balloon's location, and calculates the wind speed and direction in the air.

[0027] For visible and near-infrared bands, the fluctuation of atmospheric refractive index is mainly caused by temperature changes. According to the theory of local uniform isotropic turbulence, the atmospheric temperature structure constant It is usually obtained by measuring the square average of the temperature difference between two points in space with a distance r between them using a pair of micro-temperature probes on the micro-temperature sensor.

[0028] The temperature structure constant It can be expressed as:

[0029]

[0030] In the formula, and = represents the position vector in m, T is the temperature in K, and <> represents the ensemble average. L0 and l0 represent the outer and inner scales of turbulence, respectively, in m. Atmospheric optical turbulence Available temperature structure constants It is expressed as:

[0031]

[0032] Among them, the unit of air pressure P is hPa, and the atmospheric refractive index structure constant is The unit is m -2 / 3 .

[0033] The structure of the optical turbulence measurement module is as follows Figure 2 As shown, it is composed of a rod 11, two micro-temperature probes 12 and 13 located at both ends of the rod with a set interval, and a data acquisition and processing unit 14 placed in the middle of the rod.

[0034] Two micro-temperature probes at a certain distance (usually 1m) sense the change in ambient temperature at two points in space as a change in resistance value, which is converted into a voltage change through an unbalanced bridge. The voltage change ΔV output from the voltage amplifier corresponds to a certain temperature change ΔT, and A is the calibration coefficient.

[0035] ΔV=A·ΔT ---------------------------------- (3)

[0036] From equations (1) and (3), we can get the square average of the temperature difference between two points in the measurement space: Then, the atmospheric optical turbulence is obtained by equation (2):

[0037] The present invention first classifies the historical turbulence detection data into meteorological parameters and atmospheric optical turbulence; secondly, the historical turbulence detection data is cleaned and quality controlled to ensure data reliability. In addition, turbulence sounding measurement experiments are carried out in typical areas to effectively increase the amount of data information and form an atmospheric optical parameter data set.

[0038] (2) Constructing a mathematical model of optical turbulence

[0039] In the visible and infrared bands, the influence of water vapor can be ignored. According to the local uniform isotropic theory of turbulence, the intensity of atmospheric optical turbulence can be expressed by meteorological parameters:

[0040]

[0041] Where h is the altitude, T is the air temperature, P is the air pressure, θ is the potential temperature, L is the mixing scale, and k is the coefficient. In the prior art, the k coefficient is a constant, and the k coefficient at each altitude point from the ground to about 30km in the air is usually taken as 2.8. In fact, the spatial distribution difference of atmospheric turbulence from the ground to the air is very obvious. If the k value is determined to be a constant at different altitudes, it is obviously inconsistent with the spatial difference and variation law of atmospheric turbulence. The present invention improves this by changing it to a coefficient profile that varies with altitude, and gives the distribution of the coefficient profile under different probabilities.

[0042] According to the law of atmospheric turbulence, turbulent kinetic energy can be parameterized by wind shear. Therefore, the mixing scale L can be expressed as:

[0043]

[0044] Combining equations (4) and (5), the atmospheric optical turbulence intensity can be expressed as:

[0045]

[0046] Where S is wind shear u and v are the longitudinal and latitudinal horizontal wind components, and g is the acceleration of gravity.

[0047] By further simplifying the above physical parameterization model, the atmospheric optical turbulence intensity can be expressed as:

[0048]

[0049] It can be seen from formula (7) that, except for the coefficient k, all other parameters on the right side of the equation can be calculated from the atmospheric parameters. Let M be the product of the gradients of various meteorological parameters, that is

[0050]

[0051] Combining equations (7) and (8), the coefficient k of the atmospheric optical turbulence model can be expressed as:

[0052]

[0053] Where subscript N is the number of samples.

[0054] In a turbulent meteorological sounding measurement experiment, the meteorological parameter profiles (P(h), T(h), u(h), v(h) and θ(h)) and the atmospheric optical turbulence profiles can be obtained simultaneously. The product of the meteorological parameter gradients M(h) is calculated by formula (8). Using the measured values ​​of the atmospheric optical turbulence profile Combined with formula (9), the model coefficient profile k(h) is obtained by reverse deduction. Technical process, such as Figure 4 An example of calculating the coefficient k of the atmospheric optical turbulence model is shown in Table 1.

[0055] Table 1 Example of building coefficients of atmospheric optical turbulence model

[0056]

[0057] (3) Constructing a probability prediction model for atmospheric optical turbulence in a wide-area environment

[0058] Based on the atmospheric optical parameter data set formed by a large number of turbulent meteorological sounding measurement experiments carried out in typical areas (such as Gobi Desert, coastal areas, plateaus and mountains, etc.), the atmospheric optical turbulence model coefficient profile k(h) is calculated through mathematical and statistical analysis, forming a typical area atmospheric optical turbulence model coefficient profile library: k(h)1, k(h)2, k(h)3, ..., k(h) N .

[0059] The role of the k coefficient in the turbulence model is equivalent to the weight coefficient. The present invention not only provides the variation of the weight coefficient with height (i.e., the coefficient profile), but also provides the distribution of the weight coefficient profile under different probabilities according to statistical laws.

[0060] According to mathematical statistics theory, the normal distribution expression can be expressed as:

[0061]

[0062] In the formula, x is the independent variable, is the mean value, and σ is the standard deviation. Replacing the variable x with the atmospheric optical turbulence model coefficient k can represent the probability density function of the optical turbulence model coefficient. Therefore, the wide-area atmospheric optical turbulence model coefficient profile can be statistically analyzed and processed to calculate the probability density distribution of the optical turbulence model coefficient profile.

[0063] Specifically, based on the atmospheric optical turbulence model coefficient profile data, the optical turbulence model coefficient probability density distribution is calculated from the ground to the data of the same altitude point, and then the probability distribution of the model coefficient at 1%, 15%, 50%, 85%, and 99% can be obtained. The calculation process of the atmospheric optical turbulence model coefficient profile probability distribution is as follows: Figure 4 An example of calculating the probability distribution of the coefficient profile of the wide-area environmental optical turbulence model is shown in Table 2.

[0064] Table 2 Example of calculation of probability distribution of coefficient profiles of wide-area environmental optical turbulence model

[0065]

[0066] According to the probability distribution of the optical turbulence model coefficient profile calculated by the above method, the wide-area optical turbulence probability prediction model (named: Probabilistic prediction model for wide-area optical turbulence, ProMOT) can be obtained by combining equations (7) and (8). The ProMOT model can be expressed as:

[0067]

[0068] Where subscript p is a probability distribution of 1%, 15%, 50%, 85%, 99%, etc.

[0069] Based on meteorological sounding data, numerical model data, reanalysis data and satellite remote sensing data, atmospheric environmental data are extracted to construct a wide-area atmospheric meteorological data set containing wind speed, temperature, air pressure and other elements. Combined with the wide-area atmospheric optical turbulence probability prediction model, the wide-area atmospheric optical turbulence probability distribution is predicted and the wide-area atmospheric optical turbulence profile probability distribution is characterized.

[0070] It should be pointed out that in the iterative process of the wide-area atmospheric optical turbulence probability model, it is necessary to continuously use multi-source measured data to evaluate the model prediction results and continuously optimize the atmospheric optical turbulence probability prediction model. Figure 5 shown.

[0071] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for constructing a wide-area environmental optical turbulence probability prediction model, characterized in that: include: S1. Obtain historical experimental data of ball-borne turbulence detection and obtain meteorological parameter profiles (P(h), T(h), u(h), v(h) and θ(h)) and atmospheric optical turbulence profiles S2. Calculate the product M(h) of the meteorological parameter gradient according to the meteorological parameter profile corresponding to the historical experimental data; S3. Using atmospheric optical turbulence profiles The product of the gradient of the meteorological parameters M(h) is used to calculate the model coefficient profile k(h), and the coefficient profile library of the atmospheric optical turbulence model in typical regions is obtained based on this: k(h)1, k(h)2, k(h)3, ..., k(h) N ; S4. Based on the atmospheric optical turbulence model coefficient profile library of typical regions: k(h)1, k(h)2, k(h)3, ..., k(h) N , from the ground to the sky, the probability density distribution k(h) of the optical turbulence model coefficients is calculated in sequence for the data at the same altitude point p , subscript p is the probability value; S5. According to the probability density distribution of the optical turbulence model coefficients k(h) p Constructing an optical turbulence probability prediction model: in is the predicted probability distribution of the optical turbulence profile.

2. The method for constructing a wide-area environmental optical turbulence probability prediction model according to claim 1, characterized in that: The calculation formula of the product of meteorological parameter gradient M(h) is as follows: Where S(h) is wind shear u and v are the longitudinal and latitudinal horizontal wind components, h is the altitude, T(h) is the air temperature profile, P(h) is the pressure profile, and θ(h) is the potential temperature profile.

3. The method for constructing a wide-area environmental optical turbulence probability prediction model according to claim 1, characterized in that: The atmospheric optical turbulence profile The atmospheric refractive index structure constant The calculation results are: Among them, the atmospheric refractive index structure constant Measured by the optical turbulence measurement module of the sounding.

4. The method for constructing a wide-area environmental optical turbulence probability prediction model according to claim 1, characterized in that: The optical turbulence model coefficient probability density distribution k(h) p Includes: k(h) 1％ 、k(h) 15％ 、k(h) 50％ 、k(h) 85％ 、k(h) 99％ .

5. A method for predicting the probability distribution of optical turbulence profiles in a wide-area environment, characterized in that: The following steps are involved: S11, obtaining a wide-area environmental optical turbulence probability prediction model, wherein the optical turbulence probability prediction model is obtained according to the method for constructing a wide-area environmental optical turbulence probability prediction model according to any one of claims 1 to 4; S12, obtaining the meteorological parameter profile (P(h), T(h), u(h), v(h) and θ(h)) corresponding to the atmospheric optical turbulence to be predicted, and calculating the product M(h) of the meteorological parameter gradient amount based on the profile; S13. Input the product M(h) of the specified optical turbulence model coefficient probability density distribution and the calculated meteorological parameter gradient into the optical turbulence prediction model, and output the predicted optical turbulence profile probability distribution.

6. The method for predicting the probability distribution of optical turbulence profiles in a wide-area environment according to claim 5, characterized in that: The meteorological parameter profiles (P(h), T(h), u(h), v(h) and θ(h)) corresponding to the atmospheric optical turbulence to be predicted are measured data.

7. The method for predicting the probability distribution of optical turbulence profiles in a wide-area environment according to claim 5, characterized in that: The meteorological parameter profiles (P(h), T(h), u(h), v(h) and θ(h)) corresponding to the atmospheric optical turbulence to be predicted are meteorological prediction data.

8. A device for predicting the probability of optical turbulence in a wide-area environment, comprising a computer program, characterized in that: When executed, the program is used to implement each step of the wide-area environment optical turbulence profile probability distribution prediction method according to claim 5.

Images