Image acquisition system applied to atmospheric turbulence measurement and atmospheric turbulence measurement method

Abstract

The invention relates to the technical field of atmospheric turbulence measurement, in particular to an image acquisition system applied to atmospheric turbulence measurement and an atmospheric turbulence measurement method. The non-redundant interference mask multi-baseline interference imaging near-surface turbulence measurement device can realize all-weather measurement of near-surface layer turbulence, a traditional atmospheric turbulence monitoring device can only perform monitoring in a specific time period or under a specific condition, and the non-redundant interference mask multi-baseline interference imaging near-surface turbulence measurement device adopts a self-carried light source and an all-weather available optical system. All-time and all-weather atmosphere turbulence parameter monitoring is achieved, and more continuous and reliable data support is provided for near-ground layer turbulence, especially for obtaining multiple atmosphere optical turbulence characteristic parameters such as seeing, power spectral density and turbulence direction at the same time, and especially for observation of the interior of a telescope dome. The technical problem that an existing measurement system is difficult to accurately acquire an image used for calculating the atmospheric turbulence parameter, so that the atmospheric turbulence parameter of a near-surface layer is difficult to accurately measure is solved.

Description

Technical Field

[0001] This invention relates to the field of atmospheric turbulence measurement technology, and in particular to an image acquisition system and method for atmospheric turbulence measurement. Background Technology

[0002] Earth's atmosphere is composed of layers of air at varying temperatures, resulting in an unstable refractive index. When light from distant celestial objects propagates through the atmosphere, its wavefront and intensity are distorted—a phenomenon known as atmospheric optical turbulence. This severely degrades the image quality observed by telescopes. For ground-based telescopes, the resolution is significantly reduced after atmospheric interference in actual observations. In the formula Atmospheric coherence length is a parameter describing the intensity of atmospheric optical turbulence, astronomically known as seeing. In this case, the resolution of a telescope is determined not by the size of its aperture but by the atmospheric coherence length. Atmospheric optical turbulence is one of the main sources of reduced image quality and resolution of ground-based astronomical telescopes, and the near-surface atmosphere is the primary region of influence within the entire atmosphere.

[0003] While instruments capable of measuring stratified atmospheric turbulence, such as SCIDAR (Scintillation Detection and Ranging), SHABAR (Shadow Band Array), MASS (Multi-Aperture Scintillation Sensor), and SLODAR (Slope Detection and Ranging), can measure near-surface turbulence, they face challenges in capturing turbulence within telescope domes, including the lack of a guiding star and difficulties in measuring localized areas. Microthermal probes, which indirectly infer turbulence by measuring temperature gradients and provide localized sampling data of refractive index structure constants, typically have low spatial resolution and are susceptible to environmental influences during operation. Furthermore, relying solely on temperature gradients ignores the effects of humidity and pressure changes on the refractive index and cannot directly correlate with optical phase distortion. Additionally, the sensors are structurally fragile, susceptible to mechanical vibration and dust contamination, and struggle to operate stably for extended periods in complex environments such as inside telescope tubes or domes, making them unsuitable for demanding telescope environments. Consequently, existing measurement systems struggle to accurately acquire images for calculating atmospheric turbulence parameters, thus hindering accurate measurement of near-surface atmospheric turbulence parameters. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an image acquisition system and a method for measuring atmospheric turbulence, which solves the technical problem that existing measurement systems are unable to accurately acquire images for calculating atmospheric turbulence parameters, and thus are also unable to accurately measure atmospheric turbulence parameters in the near-surface layer.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an image acquisition system for atmospheric turbulence measurement, the system comprising: The light source system includes an LED light source for emitting a narrow linewidth, a constant current driving device for driving the LED light source, and outputs the light signal emitted by the LED light source to a collimation system through an optical fiber coupling line; A collimation system, the collimation system including a conversion device for converting the optical signal transmitted by the light source system into a parallel beam; The beam splitting system includes a multi-aperture non-redundant mask for controlling a parallel beam through a predetermined path to obtain an optical path composed of multiple baseline pairs and to make the optical path pass through the turbulent region of the atmosphere to be measured. An imaging system, comprising an imaging lens for receiving light passing through a region of atmospheric turbulence to be measured, and a CCD sensor for imaging the light path after passing through the imaging lens, so as to acquire an interferometric image by means of the CCD sensor.

[0006] This invention also provides a method for measuring atmospheric turbulence, which obtains a complete interferometric image by acquiring it in a time series using the image acquisition system. The method specifically includes the following steps: S1. Perform a two-dimensional fast Fourier transform on the acquired interferometric images to extract the phase fluctuations of each baseline pair; S2. Based on the phase fluctuations of each extracted baseline pair, the variance of the phase over time is calculated for each baseline pair to obtain the two-dimensional phase structure function of the turbulence: S3. Set up several theoretical models and select the theoretical model that best fits the two-dimensional phase structure function as the turbulence model; S4. Perform inversion calculations based on the turbulence model to obtain the turbulence parameters of atmospheric turbulence.

[0007] Preferably, step S1 specifically includes the following steps: S11. Perform a two-dimensional fast Fourier transform on each frame of the acquired interferometric image. S12. Extract the phase fluctuations of each baseline pair in the interferometric image after two-dimensional fast Fourier transform using the normalized maximum threshold extraction method. .

[0008] Preferably, in step S11, the expression for the two-dimensional fast Fourier transform is: ,in, In the formula, This is a frequency domain distribution diagram of any frame of the interferometric image after undergoing a two-dimensional fast Fourier transform. Represents the frequency domain coordinates after the two-dimensional fast Fourier transform. To show the light field distribution after passing through the mask, Represents the coordinates of any frame of the interferometric image. Let be the mask aperture distribution function. This indicates the light intensity before it passes through the mask.

[0009] Preferably, in step S2, the expression for the two-dimensional phase structure function is: In the above formula, Represents a two-dimensional phase structure function. This is the spatial separation vector, corresponding to the baseline vector of different aperture spacings in a non-redundant mask. This indicates a spatiotemporal average, which is the averaging of the phase differences between multiple baseline pairs with the same baseline length.

[0010] Preferably, the theoretical models set in step S3 include: the Kolmogorov model, the Von Karman model, and the power-law model.

[0011] By employing the above technical solution, the present invention provides an image acquisition system and a method for measuring atmospheric turbulence, which have at least the following beneficial effects: 1. This invention enables all-weather measurement of near-surface turbulence. Traditional atmospheric turbulence monitoring equipment can usually only monitor under specific time periods or conditions. However, the non-redundant interferometric mask multi-baseline interferometric imaging near-surface turbulence measurement equipment of this invention uses its own light source and an all-weather optical system to achieve all-time, all-weather monitoring of atmospheric turbulence parameters, providing more continuous and reliable data support for near-surface turbulence, especially for observations inside the telescope dome.

[0012] 2. This invention can not only measure turbulence profiles, but also simultaneously acquire multiple atmospheric optical turbulence characteristic parameters such as seeing, power spectral density, and turbulence direction, providing richer data support for atmospheric physics research.

[0013] 3. The integrated design of this invention simplifies operation, and the equipment is convenient and compact. It can be quickly deployed in the telescope truss and tube (including vibration and temperature gradient environments), adapting to the narrow space and harsh conditions inside the dome. Unlike large fixed monitoring systems, its portability supports "mobile measurement and multi-point coverage". That is, it can vertically scan the tube to obtain the vertical distribution of turbulence (such as the layered characteristics of the primary mirror and the top of the tube), and can also conduct comparative studies across observatories. It provides a flexible and universal measurement tool for assessing the turbulence impact of different telescope designs and different site environments.

[0014] 4. This invention adopts a universal optical path design and standardized component design, which has strong versatility and flexibility. It can be customized and upgraded according to actual needs. At the same time, the design concept and operation process of the equipment are simple and clear, making it easy to promote and apply to different research scenarios and observation tasks.

[0015] 5. This invention can reduce operation and maintenance costs. Traditional methods rely on trial and error to adjust the dome environment (such as blindly opening and closing ventilation vents), which is time-consuming and energy-intensive. This invention can dynamically adjust the ventilation and temperature control system through real-time feedback, enriching technology, reducing energy consumption, and promoting the upgrading of adaptive optics technology. It provides direct measurement data of local optical turbulence and helps improve the correction algorithm of adaptive optics system.

[0016] 6. Compared with the disadvantages of laser measurement of turbulence, micro-temperature pulsation instrument and DIMM, which are inconvenient to set up and have limited use areas, this invention provides multiple sets of baselines to the beam, is compact and convenient, has good regional applicability and high-precision measurement, and provides good convenience while meeting measurement requirements. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the image acquisition system of the present invention; Figure 2 This is an optical schematic diagram of the image acquisition system of the present invention; Figure 3 This is a design diagram and program simulation diagram of a nine-hole non-redundant mask according to an embodiment of the present invention; Figure 4 The above are simulation diagrams of the two-dimensional and three-dimensional point spread functions of the image acquisition system of this invention. Figure 5 This is a schematic diagram simulating the threshold extraction of the two-dimensional point spread function in the imaging process of the present invention; Figure 6 This is a flowchart of the atmospheric turbulence measurement method of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. This will allow for a full understanding of how the present application uses technical means to solve technical problems and achieve technical effects, and to facilitate its implementation.

[0019] Near-surface atmospheric turbulence, especially turbulence inside telescope domes (dome seeing), is a significant factor contributing to the degradation of astronomical image quality. This type of turbulence is caused by factors such as temperature gradients, air disturbances (e.g., ventilation design flaws), and structural thermal radiation (e.g., air temperature differences). Its characteristics differ from those of upper-level atmospheric turbulence, typically exhibiting non-uniformity, small-scale turbulence, and localized strong refractive index fluctuations, making it difficult for existing models to accurately describe its properties.

[0020] Adaptive optics and dome ventilation systems have made significant progress in wavefront correction and environmental control, but effective means for quantitative measurement of dome turbulence are still lacking. Traditional turbulence models (such as the Kolmogorov model) are mainly applicable to free atmospheric turbulence, while turbulence inside a dome often has non-Kolmogorov characteristics, making it theoretically difficult to simulate real turbulence changes. Although wide-field adaptive optics systems and high dynamic range imaging techniques are sensitive to the spatial distribution and frequency characteristics of turbulence, adaptive optics systems still have difficulty distinguishing the contributions of dome turbulence from free atmospheric turbulence, resulting in limited correction effects and requiring long-term and real-time data.

[0021] As a key protective structure for telescopes, the design details of the dome (including the layout, size, and orientation of the ventilation openings, as well as the overall geometry of the dome, such as the curvature of the dome and the shape of the bottom profile) can significantly regulate the intensity evolution and spatial distribution pattern of near-surface atmospheric turbulence by altering the flow path, velocity distribution, and pressure field of airflow. However, current research on this influencing process is limited by the lack of quantitative measurement methods, making it difficult to accurately capture the subtle changes in turbulence under dome conditions. It is impossible to establish a clear mathematical relationship between dome design parameters and turbulence characteristics (such as key parameters like refractive index structure constant and turbulence outer scale), nor can it scientifically assess the actual impact of different design schemes on core observation indicators such as seeing and wavefront distortion. For the design of telescope domes, the optimization of their ventilation systems has long relied on empirical rules. Engineers adjust the opening modes and flow guiding structures of the ventilation openings based on qualitative understanding of traditional fluid mechanics and summaries of historical cases. However, due to the lack of a dynamic feedback mechanism based on real-time turbulence data, it is impossible to accurately adapt the ventilation strategy according to the state of the atmospheric boundary layer and the needs of the observation target during the observation process. As a result, the optimization of the turbulent environment inside the dome has always remained in the stage of empirical exploration, making it difficult to overcome the observation performance bottleneck caused by turbulence interference. This also highlights the urgency of establishing a quantitative measurement system for dome turbulence and developing intelligent dome control technology based on real-time turbulence monitoring.

[0022] Traditional atmospheric turbulence measurement devices, such as DIMM (Differential Image Motion Monitor), SDIMM+ (Solar - Differential Image Motion Monitor +), and GSM (Generalized Seeing Monitor), can assess the overall turbulence effect, but they can only measure the integral turbulence intensity of the entire atmosphere and cannot measure the atmospheric turbulence profile. Furthermore, due to their design, they cannot distinguish between the contributions of near-surface turbulence and free atmospheric turbulence.

[0023] To address the technical problem of existing measurement systems being easily affected by interference when measuring atmospheric turbulence, thus hindering accurate measurement of near-surface atmospheric turbulence parameters, and considering laser-based turbulence measurement methods based on wavefront arrival angle undulations, this invention provides an image acquisition system for atmospheric turbulence measurement, and a method for calculating atmospheric turbulence parameters from interferometric images acquired by the image acquisition system. The image acquisition system of this invention is as follows: Figure 1 and Figure 2As shown, the system includes: Light source system 1: employing a narrow-linewidth LED light source with an embedded constant current drive device to ensure the stability of the light intensity. Efficient, low-loss signal transmission of the output beam is achieved through an optical fiber coupling line to generate a stable beam; Collimation system 2: achieving collimated beam output. Specifically, the collimation process uses a conversion device (generally an aspherical lens) to convert the relatively divergent beam into a parallel beam, also known as a collimated beam, thereby reducing energy loss and signal noise caused by beam divergence. This process not only improves the system's signal-to-noise ratio but also ensures that subsequent optical components can accurately process the beam; Beam splitting system 3: inspired by the Differential Image Motion Atmospheric Seeing Monitor (DIMM), a multi-aperture non-redundant mask is introduced after collimation system 2. This mask design ensures that the collimated beam is aligned with the optical output. Following a specific path, the aperture distribution enables beam filtering, thus achieving precise sampling of the light spot. The number of masks with different apertures can be changed as needed. Therefore, the non-redundant mask acts as both a filter and a beam splitter, separating the collimated parallel beam into multiple baseline pairs forming an optical path distribution. The beam then passes through the atmospheric turbulence region to be measured. Imaging system 4 consists of an imaging lens and a CCD sensor. After passing through the turbulence region, the imaging lens re-images the beam onto the CCD sensor at a certain scale. The CCD sensor acquires interferometric images of the atmospheric turbulence region in real time. A computer is connected to the other end of the CCD sensor to acquire image data, including exposure time, acquisition time, and image gain. The computer's built-in algorithm calculates atmospheric turbulence parameters, such as... Figure 4 The image shown is a simulation of the two-dimensional and three-dimensional point spread function of the image acquisition system. The initial light source power is set to 3W. Figure 3 The mask information is used to simulate and generate the image. Figure 5 This is a simulation diagram of the two-dimensional point spread function threshold extraction of the present invention (extraction results with a normalized threshold of -5). Specifically, points with a threshold greater than -5 after image normalization are marked in blue, presenting the special processing ideas for turbulence information brought about by the mask design.

[0024] The entire image acquisition system can be fixed using an embedded mechanical structure, providing a measurement length adjustable for the atmospheric turbulence region to be measured. This design effectively reduces the inconvenience caused by environmental factors and its own weight, even in more diverse data acquisition and application scenarios.

[0025] This invention also provides a method for measuring atmospheric turbulence, such as... Figure 3 and Figure 6 As shown, Figure 3The diagram shows the design and simulation of a nine-hole non-redundant mask for a non-redundant interferometric multi-baseline interferometric imaging near-surface turbulence measurement device, as an example of this invention. The left diagram shows the design of the nine-hole non-redundant mask, with a circular mask diameter of 50 mm and a single hole diameter of 1.82 mm. The right diagram is a schematic diagram generated by a Python program simulation, used to provide the aperture distribution information of the mask. The substrate is white to represent 0% transmittance, and the black circular area represents the light-passing hole with 100% transmittance. First, the beam after being split by the non-redundant mask reaches the imaging lens, and finally the point image is received by the CCD camera to acquire the time series of the interferometric image, so as to obtain a complete interferometric image containing the entire or part of the continuous time series.

[0026] Subsequently, due to the unique characteristic of non-redundant masks separating collimated beams into multiple baseline pairs, it is necessary to convert the optical path difference caused by the turbulent path into phase fluctuations. The process of this transformation is as follows: A two-dimensional fast Fourier transform is performed on the image using the mask's unique aperture distribution information to obtain the frequency domain distribution information map. Based on the mask's geometric layout, the frequency domain peak positions of multiple baselines are located. The phase values ​​of each baseline pair are extracted using a maximum threshold extraction algorithm. It should be noted that a non-redundant mask can generate multiple non-redundant baselines. For example, a 7-aperture non-redundant mask can generate 24 baseline vectors, and a 9-aperture non-redundant mask can generate 36 baseline vectors. The specific process can be further described as follows: A two-dimensional Fourier transform is performed on each frame of the image, i.e.: ,in, In the formula, This is a frequency domain distribution diagram of any frame of the interferometric image after undergoing a two-dimensional fast Fourier transform. Represents the frequency domain coordinates after the two-dimensional fast Fourier transform. To show the light field distribution after passing through the mask, Represents the coordinates of any frame of the interferometric image. Let be the mask aperture distribution function. This represents the light intensity before passing through the mask. Due to the non-redundant mask design, after Fourier transforming the image, constructive and destructive interference points will form a sharp contrast, and the constructive interference points will relatively uniformly cover the central region of the acquired image. The phase fluctuations of each baseline pair can then be extracted using the normalized maximum threshold extraction method. .

[0027] Phase fluctuations of each baseline pair were extracted. Then, the extracted phase fluctuations were used The variance of the phase information for each baseline pair is calculated over time to obtain the two-dimensional phase structure function of the turbulence: In the above formula, Represents a two-dimensional phase structure function. This is the spatial separation vector, corresponding to the baseline vector of different aperture spacings in a non-redundant mask. This indicates a spatiotemporal average, which is the averaging of the phase differences between multiple baseline pairs with the same baseline length.

[0028] The obtained two-dimensional phase structure function can be used to analyze turbulence characteristics. This involves comparing actual measured data with theoretical models and selecting the best-fitting model as the turbulence model. The theoretical models selected for comparison include: Kolmogorov model: In the formula, The length of atmospheric coherence; Von Karman model: In the formula, Indicates the spatial separation distance; Power-law model: In the formula, C represents the proportionality coefficient. Indicates the power-law exponent; Based on the comparison and fitting of the obtained two-dimensional phase structure function with the theoretical model, the theoretical model with the best fit is selected as the turbulence model. That is, the final turbulence model is determined by the fitting coefficient, which allows the type of turbulence to be identified. Then, the atmospheric coherence length can be calculated based on the selected turbulence model. Vertical profile of refractive index structure constant and turbulent outer scale Inversion calculation of turbulence parameters; If the Von Karman theoretical model is the chosen turbulence model, the propagation of light waves or laser beams in a turbulent environment is affected by refractive index fluctuations, resulting in phase fluctuations in the laser beam. The baseline length is... caliber is The wavefront arrival angle covariance of the two-aperture telescope is: ;in Baseline length For telescope aperture, For external scale, For wavelength, For spatially correlated frequencies, represent Bessel function of order 1 It is the fluctuation of the wavefront arrival angle and the baseline. The angle between them The spatial power spectral density given by the Von Karman model can then be obtained by inversion using the covariance matrix. ; The formula for calculating the spatial power spectral density given by the Von Karman model is: ;in For wave number, The atmospheric refractive index structure constant is used; the above fitting can obtain a spatial assessment of turbulence type, turbulence source, and directionality. , and Equal turbulence parameters.

[0029] This invention utilizes a precisely designed non-redundant mask to achieve beam separation and filtering. It can perform real-time and accurate measurement of wavefront arrival angle jitter of atmospheric turbulence using phase structure functions, thereby improving measurement accuracy. By optimizing the sub-aperture arrangement pattern and effectively correcting the background, it effectively reduces noise interference and scintillation effects, thus improving the accuracy and reliability of the data.

[0030] This invention not only enables the measurement of turbulence profiles but also allows for the simultaneous acquisition of multiple atmospheric optical turbulence characteristic parameters, such as seeing and turbulence properties, providing richer data support for atmospheric physics research. It employs an integrated design, making it simple and easy to use. The automatic timed image acquisition function of the camera reduces human error and improves the efficiency and consistency of data acquisition.

[0031] The turbulent region to be measured in the image acquisition system of this invention can be moved and adjusted to match the requirements of the measurement environment. At the same time, the non-redundant mask can also be replaced according to actual needs. When the equipment needs to be applied to an environment with high turbulence intensity, a non-redundant mask with a smaller aperture distribution can be used for measurement. This invention has strong versatility and flexibility and can be customized and upgraded according to actual needs.

[0032] The present invention is smaller in size than laser turbulence measurement devices based on wavefront arrival angle fluctuations, and has better spatial adaptability to potential turbulence sources in domes, while providing more baseline pairs and beams with better small-scale turbulence measurement capabilities.

[0033] This invention employs a non-redundant mask design, which not only optimizes the optical path design based on laser measurement turbulence equipment with wavefront arrival angle fluctuations, but also provides more baseline beam pairs. It is compact yet provides more accurate measurement of small-scale turbulence. Compared with micro-temperature pulsators, SCIDAR and other equipment, it has all-weather operating conditions, lower manufacturing requirements, and strong adaptability to measurement space.

[0034] This invention addresses the limitations of traditional turbulence measurement methods, which typically only adapt to a single theoretical model (such as the Kolmogorov model) and struggle to accurately describe the non-uniformity and non-stationary characteristics of near-surface turbulence (e.g., localized turbulence within domes or ventilation-induced anisotropic turbulence). By introducing a multi-model fitting framework encompassing Kolmogorov, Von Karman, and power-law models, combined with multi-directional phase structure function analysis using non-redundant baselines, this invention effectively distinguishes turbulence types (e.g., determining whether it is non-Kolmogorov turbulence) and quantifies its directional characteristics. This provides crucial parameter support for refined modeling of complex flow fields within domes, significantly improving the accuracy of parameter inversion compared to traditional single-model methods.

[0035] In summary, the redundant interferometric mask multi-baseline interferometric imaging near-ground turbulence measurement device of the present invention has significant advantages in terms of real-time performance, accuracy, multi-parameter measurement, ease of operation and versatility, bringing important technological breakthroughs and practical value to the fields of atmospheric physics research and astronomical observation.

[0036] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0037] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Since the above embodiments are substantially similar to the method embodiments, their descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0038] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present 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 the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. An image acquisition system for measuring atmospheric turbulence, the system comprising: The light source system (1) includes an LED light source for emitting a narrow linewidth, a constant current driving device for driving the LED light source, and outputs the light signal emitted by the LED light source to the collimation system (2) through an optical fiber coupling line. The collimation system (2) includes a conversion device for converting the optical signal transmitted by the light source system (1) into a parallel beam; The beam splitting system (3) includes a multi-aperture non-redundant mask for controlling the parallel beam through a predetermined path to obtain an optical path composed of multiple sets of baseline pairs and to make the optical path pass through the turbulent region of the atmosphere to be measured. The imaging system (4) includes an imaging lens for receiving the light path passing through the atmospheric turbulence region to be measured, and a CCD sensor for imaging the light path after passing through the imaging lens, so as to acquire an interference image through the CCD sensor.

2. A method for measuring atmospheric turbulence, comprising acquiring a complete interferometric image in a time-series manner using the image acquisition system described in claim 1, characterized in that, The method for measuring atmospheric turbulence specifically includes the following steps: S1. Perform a two-dimensional fast Fourier transform on the acquired interferometric images to extract the phase fluctuations of each baseline pair; S2. Based on the phase fluctuations of each extracted baseline pair, the variance of the phase over time is calculated for each baseline pair to obtain the two-dimensional phase structure function of the turbulence: S3. Set up several theoretical models and select the theoretical model that best fits the two-dimensional phase structure function as the turbulence model; S4. Perform inversion calculations based on the turbulence model to obtain the turbulence parameters of atmospheric turbulence.

3. The atmospheric turbulence measurement method according to claim 2, characterized in that, Step S1 specifically includes the following steps: S11. Perform a two-dimensional fast Fourier transform on each frame of the acquired interferometric image. S12. Extract the phase fluctuations of each baseline pair in the interferometric image after two-dimensional fast Fourier transform using the normalized maximum threshold extraction method. .

4. The atmospheric turbulence measurement method according to claim 3, characterized in that, In step S11, the expression for the two-dimensional fast Fourier transform is: ,in, In the formula, This is a frequency domain distribution diagram of any frame of the interferometric image after undergoing a two-dimensional fast Fourier transform. Represents the frequency domain coordinates after the two-dimensional fast Fourier transform. To show the light field distribution after passing through the mask, Represents the coordinates of any frame of the interferometric image. Let be the mask aperture distribution function. This indicates the light intensity before it passes through the mask.

5. The atmospheric turbulence measurement method according to claim 2, characterized in that, In step S2, the expression for the two-dimensional phase structure function is: In the above formula, Represents a two-dimensional phase structure function. This is the spatial separation vector, corresponding to the baseline vector of different aperture spacings in a non-redundant mask. This indicates a spatiotemporal average, which is the averaging of the phase differences between multiple baseline pairs with the same baseline length.

6. The atmospheric turbulence measurement method according to claim 2, characterized in that, In step S3, the theoretical models set include: the Kolmogorov model, the Von Karman model, and the power-law model.

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