High cloud identification method for dynamically adjusting cloud measurement parameters based on aircraft wake cloud

Abstract

The invention discloses a high cloud recognition method for dynamically adjusting cloud measurement parameters based on aircraft wake cloud, and relates to the technical field of cloud observation, the method recognizes aircraft wake cloud generated by an aircraft in high cloud from an infrared cloud picture, and recognizes clear sky and medium and low clouds in combination with a reference infrared cloud picture obtained under the same atmospheric condition. Data fitting is carried out through a least square method in combination with aircraft wake clouds, clear sky and medium and low clouds, and normalization correction is carried out according to the characteristic that the cloud heights of the aircraft wake clouds are consistent so as to dynamically update cloud measurement parameters, so that inversion temperature data deviation caused by different optical transmission paths of different zenith angles can be made up in time; the cloud measurement parameters of the infrared cloud observation instrument better conform to atmospheric conditions, and the high cloud can be identified from the obtained infrared cloud picture by using the dynamically updated cloud measurement parameters in the working process of the infrared cloud observation instrument, so that the high cloud identification capability of the infrared cloud observation instrument can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of cloud observation technology, and in particular to a high cloud identification method based on dynamic adjustment of cloud measurement parameters based on aircraft contrail clouds. Background Art

[0002] Cloud observation is an important source of data for scientific research and business activities such as earth energy budget analysis, weather analysis and forecasting, and aviation flight safety assurance. Ground-based automated full-cloud observation instruments have gradually replaced manual observations, greatly increasing the spatiotemporal density of cloud observation data.

[0003] At present, the common ground-based automatic full-cloud observation instruments mainly include laser cloud height meters, visible light cloud observation instruments and infrared cloud observation instruments. Among them, the laser cloud height meter has a good effect in measuring single-point cloud height, has been put into commercial operation, and is widely used in civil aviation airports to monitor the meteorological conditions in the take-off and landing areas. However, it is difficult for the laser cloud height meter to achieve full-sky cloud situation observation, and the observation space range is relatively limited. The visible light cloud observation instrument can observe the cloud amount in the whole sky and identify some cloud shapes. It currently has a certain business volume and technical maturity, but the visible light cloud observation instrument cannot observe at night, and the observation time range is relatively limited. The infrared cloud observation instrument realizes cloud observation based on the infrared brightness temperature inversion technology system. It has outstanding performance and irreplaceable role in full-sky cloud height situation monitoring and continuous observation day and night.

[0004] The principle of infrared cloud observation instrument is: the ground receives the sky background thermal radiation in any direction. The radiation intensity is composed of water vapor and temperature on the atmospheric path. Since clouds are strong emitters in the thermal infrared band, they can be regarded as black bodies in this band. If there are clouds in any direction, the background thermal radiation value at that place must be higher than that in the cloudless situation, so it can be determined that there are clouds in that direction. Considering that in the propagation process of long atmospheric optical paths, there are still factors such as characteristic band absorption, aerosol scattering and absorption, molecular scattering, and atmospheric refraction that attenuate radiation transmission, resulting in low measured values. For this reason, spectral radiation transmission modes such as MODTRAN are generally used in combination with physical-statistical inversion methods as infrared radiation thresholds, and historical data are used as input to establish statistical relationships, so as to determine whether there are clouds in the observation direction, and then count the cloud amount and cloud height, and count the high, medium and low proportions of cloud amount according to cloud height. However, in actual use, it is found that the statistical results of infrared radiation inversion cloud state are greatly affected by atmospheric transmission conditions, especially the recognition rate of high clouds with energy values ​​close to the background sky thermal radiation is low, resulting in the limited ability of infrared cloud observation instruments to accurately observe high clouds above 6,000 meters. Summary of the invention

[0005] In view of the above problems and technical requirements, this application proposes a high cloud identification method based on dynamic adjustment of cloud measurement parameters of aircraft contrail clouds. The technical solution of this application is as follows:

[0006] A high cloud identification method based on dynamically adjusting cloud measurement parameters of aircraft contrails, the high cloud identification method comprising:

[0007] The infrared cloud image at the current time t is obtained by using an infrared cloud observation instrument. Based on linear cloud recognition, the infrared trail cloud sample set A is detected from the infrared cloud image at the current time t. IR-vis ; Among them, infrared contrail cloud sample set A IR-vis Including the infrared amplitude and pixel coordinates of the aircraft contrail cloud samples reaching the predetermined height H in the infrared cloud image at the current time t;

[0008] Detect the infrared clear sky sample set A from the reference infrared cloud image at the current time t sky and infrared low and medium cloud sample set A c6 ; The reference infrared cloud image at the current time t is the infrared cloud image obtained at the most recent historical moment before the current time t that contains both clear sky and clouds. The infrared clear sky sample set A sky Including infrared amplitude and pixel coordinates of clear sky samples in reference infrared cloud images, infrared medium and low cloud sample set A c6 It includes the infrared amplitude and pixel coordinates of the highest low and medium cloud samples below the predetermined height H in the reference infrared cloud map;

[0009] Based on infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The pixel coordinates and infrared amplitudes of the samples in are fitted by least squares, and normalized according to the cloud height of the aircraft contrail cloud to obtain the updated cloud measurement parameters;

[0010] The high clouds above the predetermined height H are identified from the infrared cloud image obtained from the infrared cloud observation instrument based on the updated cloud measurement parameters.

[0011] A further technical solution is to obtain updated cloud measurement parameters including:

[0012] According to the atmospheric transmission parameter fitting formula in the statistical inversion method, the infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 Perform atmospheric parameter inversion on the samples in the image to obtain the atmospheric transmission parameters at the pixel coordinates of each sample;

[0013] The atmospheric transmission parameters at each pixel coordinate of the aircraft contrail cloud sample, clear sky sample and medium and low cloud sample were fitted with the least square method to obtain the atmospheric transmission parameters at each zenith angle.

[0014] Based on the characteristic that the cloud height of the same aircraft contrail is consistent, the atmospheric transmission parameters at the zenith angle of the same aircraft contrail are normalized according to the cloud height at the minimum zenith angle of the aircraft contrail, and the updated cloud measurement parameters include the normalized atmospheric transmission parameters at the zenith angle of the aircraft contrail.

[0015] A further technical solution is to obtain the atmospheric transmission parameters at each zenith angle, including:

[0016] According to the atmospheric transmission parameter fitting formula T=c+aT in the statistical inversion method G +b1P+b2P 2 Inverted infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The atmospheric transmission parameters c, a, b1, b2 at the pixel coordinates of each sample in the , where T is the temperature obtained by inverting the infrared amplitude of the sample based on the current cloud measurement parameters, T G is the ground temperature at the current time t, P is the water vapor pressure at the current time t;

[0017] The pixel coordinates of each sample are transformed into polar coordinates with the zenith angle of 0° as the pole, and the average value of the atmospheric transmission parameters of the infrared trail cloud samples on the same polar diameter is calculated to obtain the first parameter F at the zenith angle corresponding to the polar diameter. IR Calculate the average value of the atmospheric transmission parameter of the clear sky sample on the same polar diameter obtained by the conversion of polar coordinates to obtain the second parameter F at the zenith angle corresponding to the polar diameter sky Calculate the average value of the atmospheric transmission parameters of the low and medium cloud samples on the same polar diameter obtained by the conversion of polar coordinates to obtain the third parameter F at the zenith angle corresponding to the polar diameter c6 ;

[0018] For each zenith angle, the first parameter F IR , the second parameter F sky and the third parameter F c6 The atmospheric transmission parameters at different zenith angles are obtained by fitting using the least squares method.

[0019] A further technical solution is to obtain updated cloud measurement parameters including:

[0020] For infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The samples in are fitted by the least square method to obtain the infrared amplitude of the pixel coordinates where the aircraft contrail cloud is located;

[0021] The infrared amplitude of the pixel coordinates where the aircraft contrail is located is normalized according to the cloud height at the minimum zenith angle of the aircraft contrail to obtain the infrared threshold, and the updated cloud measurement parameters include the infrared threshold at the pixel coordinates where the aircraft contrail is located.

[0022] A further technical solution is to detect the infrared trail cloud sample set A from the infrared cloud image at the current time t based on linear cloud recognition. IR-vis include:

[0023] Use the Canny edge detection algorithm to detect the cloud edges in the infrared cloud image at the current time t;

[0024] The infrared linear cloud samples are detected based on the cloud edges in the infrared cloud image at the current time t using Hough transform;

[0025] The height of the infrared line cloud samples is calculated according to the statistical inversion method, and the infrared trail cloud sample set A is obtained according to the infrared amplitude and pixel coordinates of the infrared line cloud samples whose height reaches the predetermined height H. IR-vis .

[0026] A further technical solution is to use the Canny edge detection algorithm to detect the cloud edge in the infrared cloud image at the current time t, including:

[0027] The reference infrared cloud image at the current time t is gradient processed according to the Sobel operator, and the 2σ value of the clear sky gradient in the reference infrared cloud image at the current time t is counted as the upper threshold of the Canny double threshold processing. The 2σ value of the cloud gradient in the reference infrared cloud image at the current time t is counted as the lower threshold of the Canny double threshold processing. Based on the determined upper and lower thresholds, the Canny edge detection algorithm is used to detect the cloud edges in the infrared cloud image at the current time t.

[0028] A further technical solution is to obtain an infrared trail cloud sample set A according to the infrared amplitude and pixel coordinates of the infrared line cloud samples reaching a predetermined height H. IR-vis include:

[0029] Use the visible light cloud observation instrument to obtain the visible light cloud image at the current time t;

[0030] When it is determined that the visible light cloud image at the current time t reaches a predetermined brightness level, the cloud edge in the visible light cloud image at the current time t is detected using the Canny edge detection algorithm, and the visible light cloud samples are detected based on the cloud edge in the visible light cloud image at the current time t using the Hough transform, and a visible light cloud sample set A containing the pixel coordinates of the visible light cloud samples is obtained. vis ; Retain infrared cloud samples that reach a predetermined height H as candidate samples, and use the visible light cloud sample set A visThe candidate samples are corrected to remove interference data, and the remaining candidate samples are used as aircraft contrail samples to obtain the infrared contrail sample set A. IR-vis ;

[0031] When it is determined that the visible light cloud image at the current time t does not reach the predetermined brightness level, the infrared line cloud samples reaching the predetermined height H are directly used as aircraft contrail cloud samples to obtain the infrared contrail cloud sample set A. IR-vis .

[0032] A further technical solution is to use the visible light cloud sample set A vis Data correction of candidate samples to remove interfering data includes:

[0033] According to the pixel coordinate mapping relationship between the visible light cloud image and the infrared cloud image, the pixel coordinates of each candidate sample are mapped to obtain the pixel coordinates of the corresponding mapping sample. When the pixel coordinates of the mapping sample are included in the visible light cloud sample set A vis When the pixel coordinates of the mapped sample are not included in the visible light cloud sample set A, the candidate sample is retained; when the pixel coordinates of the mapped sample are not included in the visible light cloud sample set A vis When the candidate samples are identified as interference data, they are removed.

[0034] A further technical solution is to use the Canny edge detection algorithm to detect the cloud edge in the visible light cloud image at the current time t, including:

[0035] The 2σ value of the red-blue ratio of the clear sky image in the historical statistical results of the area where the visible light cloud observer is located is used as the upper threshold of the Canny double threshold processing, and the 2σ value of the red-blue ratio of the cloud cluster in the historical statistical results of the area where the visible light cloud observer is located is used as the lower threshold of the Canny double threshold processing. Based on the determined upper and lower thresholds, the Canny edge detection algorithm is used to detect the cloud edges in the visible light cloud image at the current time t.

[0036] A further technical solution is to use Hough transform to detect linear cloud samples based on cloud edges in the cloud image, including:

[0037] The upper limit of the line width is determined based on the spatial resolution θ of the cloud image and the reference width W of the trail cloud that continues to develop for a predetermined time at a predetermined height H.

[0038] Hough transform is used to detect candidate linear clouds based on the cloud edges in the cloud image, and the line width is retained within the upper limit of the line width W. max The candidate linear clouds are obtained by deriving linear cloud samples.

[0039] The beneficial technical effects of this application are:

[0040] The present application discloses a high cloud identification method based on dynamically adjusting cloud measurement parameters of aircraft contrails. The method identifies aircraft contrails generated by aircraft in high clouds from infrared cloud images, and identifies clear sky and medium and low clouds in combination with reference infrared cloud images acquired under the same atmospheric conditions. The aircraft contrails, clear sky and medium and low clouds are fitted with the least squares method, and the cloud measurement parameters are dynamically updated by normalizing and correcting them according to the consistent cloud height characteristics of the aircraft contrails. The deviation of inverted temperature data caused by different optical transmission paths at different zenith angles can be compensated in time, so that the cloud measurement parameters of the infrared cloud observation instrument are more in line with the atmospheric conditions, thereby effectively improving the high cloud identification capability of the infrared cloud observation instrument.

[0041] This method uses Canny edge detection and Hough transform to identify linear clouds in infrared cloud images and visible light cloud images at the same time, and then combines infrared cloud images and visible light cloud images to detect aircraft contrails, which can eliminate interference data and improve the detection accuracy of aircraft contrails. In addition, when using Canny edge detection to identify linear clouds in infrared cloud images and visible light cloud images, the threshold used by the Canny edge detection algorithm is dynamically updated according to the observation results of cloud observation instruments, which is conducive to improving the detection accuracy of linear clouds, thereby improving the detection accuracy of aircraft contrails. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a method flow chart of a high cloud identification method according to an embodiment of the present application.

[0043] Figure 2 It is a flow chart of a method for extracting an infrared contrail cloud sample set in one embodiment of the present application. DETAILED DESCRIPTION

[0044] The specific implementation of the present application is further described below in conjunction with the accompanying drawings.

[0045] This application discloses a high cloud identification method based on the dynamic adjustment of cloud measurement parameters of aircraft contrails. Please refer to Figure 1 As shown in the flowchart, the high cloud identification method comprises the following steps:

[0046] Step 1: Use an infrared cloud observer to obtain the infrared cloud image at the current time t, and detect the infrared trail cloud sample set A from the infrared cloud image at the current time t based on linear cloud recognition. IR-vis .

[0047] Among them, the infrared trail cloud sample set A IR-vis It includes the infrared amplitude and pixel coordinates of the aircraft contrail cloud samples that reach the predetermined height H in the infrared cloud image at the current time t. The predetermined height H is the height dividing line for high clouds in this field. Clouds that reach the predetermined height H are high clouds. In the meteorological field, the predetermined height H is generally taken as 6000 meters.

[0048] The current moment t in this step refers to any moment. Every time the infrared cloud observation instrument obtains the infrared cloud image, it will directly use the method of the present application to dynamically adjust the cloud measurement parameters by identifying the aircraft contrails. Aircraft contrails are special cloud systems formed by the condensation of water vapor generated by the exhaust gas discharged by jet aircraft during flight in high clouds at 7000m to 14000m, mixed with weak ice phase supersaturated air. They can persist for a long time in the high troposphere. Aircraft contrails have the following characteristics: the altitude of aircraft contrails is between 7000m and 14000m, and aircraft contrails are often generated by aircraft in stable cruising. Therefore, the physical characteristics of the same aircraft contrails are similar, the height is basically the same, and they have a linear structure.

[0049] When the infrared cloud image at the current time t does not contain aircraft contrails, the detected infrared contrails sample set A IR-vis If it is an empty set, the subsequent steps will not be executed. Instead, the current cloud measurement parameters will be kept unchanged, and high clouds will be identified from the infrared cloud image based on the current cloud measurement parameters, and the infrared cloud image collected at the next moment will be waited for to continue the judgment.

[0050] When the infrared cloud image at the current time t contains aircraft contrails, the detected infrared contrails sample set A IR-vis If it is not empty, the cloud measurement parameters are updated by the method of the present application, and then high clouds are identified from the infrared cloud image based on the updated cloud measurement parameters, and the infrared cloud image collected at the next moment is waited for to continue the judgment.

[0051] That is, each time the infrared cloud observation instrument obtains an infrared cloud image, it will first detect whether it contains aircraft contrails, and dynamically update the cloud measurement parameters when the aircraft contrails are detected for high cloud detection at the current and subsequent moments. When the aircraft contrails are not detected, the current cloud measurement parameters are used for high cloud detection at the current and subsequent moments. In this way, the cloud measurement parameters are continuously and dynamically updated, making them more consistent with the atmospheric conditions, which is beneficial to improving the accuracy of high cloud identification.

[0052] When detecting and identifying aircraft contrails, the linear structure of aircraft contrails is used. This step is based on linear cloud recognition to identify aircraft contrails samples. The steps include the following: Figure 2 The flowchart shown:

[0053] (1) Using the Canny edge detection algorithm to detect cloud edges in the infrared cloud image at the current time t. In order to further improve the accuracy of cloud edge detection, in one embodiment, the threshold used by the Canny edge detection algorithm is dynamically adjusted according to the actual observation situation, including:

[0054] First, obtain the reference infrared cloud image at the current time t. The reference infrared cloud image at the current time t is the infrared cloud image obtained at the most recent historical moment before the current time t that contains both clear sky and clouds. The acquisition time of the reference infrared cloud image at the current time t is generally very close to the current time t, so it can be considered that the atmospheric conditions at the acquisition time of the reference infrared cloud image are similar to those at the current time t. In actual operation, generally step by step from the current time t to the infrared cloud images of each historical moment, first traverse the infrared cloud image of the historical moment before the current time t. If it contains both clear sky and clouds, the infrared cloud image of the historical moment before the current time t is directly used as the reference infrared cloud image of the current time t. If the infrared cloud image of the historical moment before the current time t is full of clouds or cloudless, continue to traverse the previous historical moment until the reference infrared cloud image of the current time t is found.

[0055] Then, the reference infrared cloud image at the current time t is gradient processed according to the Sobel operator, and the 2σ value of the clear sky gradient in the reference infrared cloud image at the current time t is counted as the upper threshold of the Canny double threshold processing, and the 2σ value of the cloud gradient in the reference infrared cloud image at the current time t is counted as the lower threshold of the Canny double threshold processing. Based on the determined upper and lower thresholds, the Canny edge detection algorithm is used to detect the cloud edges in the infrared cloud image at the current time t, which can effectively optimize the detection effect of the cloud edges.

[0056] (2) The infrared cloud samples are detected based on the cloud edges in the infrared cloud image at the current time t using the Hough transform.

[0057] In another embodiment, the detection result of the Hough transform is further screened based on the line width of the linear cloud. First, the upper limit of the line width is determined according to the spatial resolution θ of the infrared cloud image at the current time t and the reference width W of the trail cloud that continues to develop for a predetermined time at a predetermined height H. If the infrared cloud image at the current time t is a distorted image, the spatial resolution θ needs to be the spatial resolution angle at the zenith angle of 60°. The reference width W is generally the width of the contrail cloud that has been developing for 2 hours at an altitude of 6000m.

[0058] Then, after detecting the candidate linear cloud based on the cloud edge in the infrared cloud image at the current time t using the Hough transform, the line width is retained not exceeding the above line width upper limit value W max The candidate linear clouds are used as linear cloud samples, thereby improving the accuracy of the detected infrared linear cloud samples.

[0059] (3) The height of the infrared line cloud samples is calculated according to the statistical inversion method, and the infrared trail cloud sample set A is obtained according to the infrared amplitude and pixel coordinates of the infrared line cloud samples whose height reaches the predetermined height H. IR-vis .

[0060] In another embodiment, the infrared cloud samples whose height reaches the predetermined height H are not directly used as aircraft contrail cloud samples, but are further combined with the visible light cloud image to perform data correction to improve the infrared contrail cloud sample set A. IR-vis The accuracy of the Figure 2 The flowchart shown:

[0061] When using the infrared cloud observation instrument to obtain the infrared cloud image at the current time t, the visible light cloud observation instrument is also used to obtain the visible light cloud image at the current time t. Since the visible light cloud image has a better observation effect when the brightness is high, but the observation effect is not ideal when the brightness is low, it is first determined whether the visible light cloud image at the current time t reaches the predetermined brightness level.

[0062] There are two ways to detect whether the visible light cloud image at the current time t reaches the predetermined brightness level. Any one of the two methods or a combination of the two methods can be used for detection: One method is to detect according to the solar time. When the current time t belongs to the night time period of the area where the visible light cloud observation instrument is located, it is determined that the visible light cloud image at the current time t does not reach the predetermined brightness level, otherwise it is determined that the visible light cloud image at the current time t reaches the predetermined brightness level. The night time period of the area where the visible light cloud observation instrument is located can be determined based on the latitude and longitude information of the area where the visible light cloud observation instrument is located and the local sunrise and sunset time calculated by the astronomical calendar. For example, the period from 1 hour after sunset to 1 hour before sunrise is determined as the night time period, and the specific period can also be customized. Another method is to perform grayscale threshold detection, calculate the average grayscale value of the visible light cloud image at the current time t, when the average grayscale value reaches the grayscale value threshold, it means that the brightness of the visible light cloud image is low, at this time it is determined that the visible light cloud image at the current time t does not reach the predetermined brightness level, otherwise it is determined that the visible light cloud image at the current time t reaches the predetermined brightness level. The gray value threshold can be customized. For example, the average gray value of the visible light cloud image of the cloudless sky 1 hour before and after sunrise actually obtained by the visible light cloud observation instrument can be used as the gray value threshold.

[0063] When it is determined that the visible light cloud image at the current time t does not reach the predetermined brightness level, it means that the observation effect of the visible light cloud image is not ideal at this time. The infrared line cloud samples are not corrected using the visible light cloud image. All infrared line cloud samples reaching the predetermined height H are directly used as aircraft contrail cloud samples, thereby obtaining the infrared contrail cloud sample set A. IR-vis .

[0064] When it is determined that the visible light cloud image at the current time t reaches the predetermined brightness level, it means that the observation effect of the visible light cloud image is good at this time. Then, the infrared line cloud samples with a height reaching the predetermined height H are corrected using the visible light cloud image to obtain the infrared trail cloud sample set A. IR-vis ,include:

[0065] (a) First, the cloud edges in the visible light cloud image at the current time t are detected using the Canny edge detection algorithm. In one embodiment, in order to improve the detection accuracy of the cloud edges in the visible light cloud image, the threshold used by the Canny edge detection algorithm is reasonably set according to the historical statistical results of the area where the visible light cloud observer is located, including: using the 2σ value of the red-blue ratio of the clear sky image in the historical statistical results of the area where the visible light cloud observer is located as the upper threshold of the Canny double threshold processing, using the 2σ value of the red-blue ratio of the cloud cluster in the historical statistical results of the area where the visible light cloud observer is located as the lower threshold of the Canny double threshold processing, and then using the Canny edge detection algorithm based on the determined upper and lower thresholds to detect the cloud edges in the visible light cloud image at the current time t.

[0066] (b) Using Hough transform, the visible light cloud samples are detected based on the cloud edges in the visible light cloud image at the current time t, and a visible light cloud sample set A containing the pixel coordinates of the visible light cloud samples is obtained. vis Similarly, lines with a width exceeding the upper limit W will be filtered out. max The candidate linear clouds are obtained to obtain a more accurate visible line cloud sample set A. vis .

[0067] (c) The infrared cloud samples that reach the predetermined height H are retained as candidate samples. Due to various interferences, the candidate samples will contain interference data. Therefore, not all candidate samples are directly used as aircraft contrail cloud samples. Instead, the visible light cloud sample set A is further used. vis The candidate samples are corrected to remove interference data, and the remaining candidate samples are used as aircraft contrail samples to obtain the infrared contrail sample set A. IR-vis ,include:

[0068] According to the pixel coordinate mapping relationship between the visible light cloud image and the infrared cloud image, the pixel coordinates of each candidate sample are mapped to obtain the pixel coordinates of the corresponding mapping sample. vis When the pixel coordinates of the mapped sample of a candidate sample are not included in the visible light cloud sample set A vis When the candidate sample is determined to be interference data, it is removed. The remaining candidate samples are used as aircraft contrail samples to obtain the infrared contrail sample set.

[0069] Step 2: Detect the infrared clear sky sample set A from the reference infrared cloud image at the current time t sky and infrared low and medium cloud sample set A c6The definition and acquisition method of the reference infrared cloud image at the current time t in this step can refer to the relevant introduction of step 1, which will not be repeated here.

[0070] The obtained infrared clear sky sample set A sky Including infrared amplitude and pixel coordinates of clear sky samples in reference infrared cloud images, infrared medium and low cloud sample set A c6 Including the infrared amplitude and pixel coordinates of the highest low and medium cloud samples below the predetermined height H in the reference infrared cloud image. According to the statistical inversion method, the cloud height of the reference infrared cloud image at the current time t can be statistically inverted to extract clear sky samples and low and medium cloud samples, thus obtaining the infrared clear sky sample set A. sky and infrared low and medium cloud sample set A c6 .

[0071] Step 3: Based on infrared trail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The pixel coordinates and infrared amplitudes of the samples in are fitted with the least square method and normalized according to the cloud height of the aircraft contrail cloud to obtain the updated cloud measurement parameters.

[0072] This step can be implemented in two different ways according to different cloud measurement requirements, so that cloud measurement parameters of different contents can be obtained:

[0073] (1) One situation is that when high cloud identification is performed, cloud height inversion is also required. In this case:

[0074] Firstly, according to the atmospheric transmission parameter fitting formula in the statistical inversion method, the infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The atmospheric parameters of the samples in the inversion are used to obtain the atmospheric transmission parameters at the pixel coordinates of each sample. Including:

[0075] According to the atmospheric transmission parameter fitting formula T=c+aT in the statistical inversion method G +b1P+b2P 2 Inverted infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The atmospheric transmission parameters c, a, b1, b2 at the pixel coordinates of each sample in the . Where T is the temperature obtained by inverting the infrared amplitude of the sample based on the current cloud measurement parameters, T G is the ground temperature at the current time t, and P is the water vapor pressure at the current time t.

[0076] Then, the least squares fitting is performed on the atmospheric transmission parameters at the pixel coordinates of the aircraft contrail cloud samples, clear sky samples, and medium and low cloud samples to obtain the atmospheric transmission parameters at each zenith angle. Including:

[0077] First, establish a polar coordinate system. Since the infrared cloud observation instrument is placed horizontally, the image center of the infrared cloud image is the zenith angle 0° direction. The polar coordinate system is established with the zenith angle 0° as the pole and the pole pointing to the direction of the pixel where the north azimuth on the infrared cloud image is located as the polar axis direction. The current azimuth can be read from the electromagnetic compass equipped on the infrared cloud observation instrument, and then the pixel position where the north azimuth on the edge of the current infrared cloud image is located can be obtained based on the factory north pointing relationship between the image device and the electromagnetic compass and the current azimuth.

[0078] By performing polar coordinate conversion on the pixel coordinates of each sample, we can get the distribution of each sample in the polar coordinate system. The angle between the line connecting each sample and the pole and the polar axis is the azimuth of the sample, and the polar diameter between the sample and the pole is the zenith angle of the sample. Each polar diameter corresponds to a zenith angle, and the samples on the same polar diameter are located at the azimuth of 0° to 360° of the same zenith angle.

[0079] Then the average value of the atmospheric transmission parameters of the infrared trail cloud samples on the same polar diameter obtained by the conversion of polar coordinates is calculated to obtain the first parameter F at the zenith angle corresponding to the polar diameter. IR , that is, calculate the mean value of the atmospheric transmission parameters of infrared trail cloud samples at different azimuths at the same zenith angle. As mentioned above, each sample contains four atmospheric transmission parameters. When calculating the mean value, the mean value is calculated for the same atmospheric transmission parameter. Similarly, the second parameter F at the zenith angle corresponding to the polar diameter is obtained by calculating the mean value of the atmospheric transmission parameters of the clear sky samples with polar coordinates converted on the same polar diameter. sky The third parameter F at the zenith angle corresponding to the polar diameter is obtained by calculating the average value of the atmospheric transmission parameters of the low and medium cloud samples on the same polar diameter with the converted polar coordinates. c6 .

[0080] Then the first parameter F at each zenith angle IR , the second parameter F sky and the third parameter F c6 The atmospheric transmission parameters at different zenith angles are obtained by fitting using the least squares method.

[0081] Finally, since the cloud height of the same aircraft contrail is basically the same, the temperature inverted at the zenith angle of the same aircraft contrail is also consistent in theory. Based on this feature, the atmospheric transmission parameters at the zenith angle of the same aircraft contrail are normalized according to the cloud height at the minimum zenith angle of the aircraft contrail, and the updated cloud measurement parameters include the normalized atmospheric transmission parameters at the zenith angle of the aircraft contrail. The deviation of the inverted temperature data caused by the different optical transmission paths at different zenith angles can be normalized according to the cloud height at the minimum zenith angle of the aircraft contrail to achieve data correction. Subsequent infrared cloud observation instruments can use the updated cloud measurement parameters to perform high-altitude infrared cloud measurement statistical inversion on infrared cloud images.

[0082] (2) Another situation is that when high cloud identification is performed, it is not necessary to invert the cloud height.

[0083] In this case, there is no need to perform statistical inversion, and the infrared contrail cloud sample set A is directly IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The samples in are fitted by the least squares method to obtain the infrared amplitude of the pixel coordinates where the aircraft contrail is located. Then, the infrared amplitude of the pixel coordinates where the aircraft contrail is located is normalized according to the cloud height at the minimum zenith angle of the aircraft contrail to obtain the infrared threshold, and the updated cloud measurement parameters include the infrared threshold at the pixel coordinates where the aircraft contrail is located. Similarly, the deviation of the inverted temperature data caused by the different optical transmission paths at different zenith angles can be normalized according to the cloud height at the minimum zenith angle of the aircraft contrail to achieve data correction. Subsequent infrared cloud observation instruments can use the updated cloud measurement parameters to determine whether there are high clouds in the infrared cloud map.

[0084] The above is only a preferred embodiment of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the protection scope of the present application.

Claims

1. A high cloud identification method based on dynamic adjustment of cloud measurement parameters of aircraft contrails, characterized in that: The high cloud identification method comprises: The infrared cloud image at the current time t is obtained by using an infrared cloud observation instrument. Based on linear cloud recognition, the infrared trail cloud sample set A is detected from the infrared cloud image at the current time t. IR-vis ; Among them, infrared contrail cloud sample set A IR-vis Including the infrared amplitude and pixel coordinates of the aircraft contrail cloud samples reaching the predetermined height H in the infrared cloud image at the current time t; Detect the infrared clear sky sample set A from the reference infrared cloud image at the current time t sky and infrared low and medium cloud sample set A c6 ; The reference infrared cloud image at the current time t is the infrared cloud image obtained at the most recent historical moment before the current time t that contains both clear sky and clouds. The infrared clear sky sample set A sky Including the infrared amplitude and pixel coordinates of the clear sky samples in the reference infrared cloud map, infrared medium and low cloud sample set A c6 The infrared amplitude and pixel coordinates of the medium and low cloud samples with the highest altitude below the predetermined altitude H in the reference infrared cloud image; Based on infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The pixel coordinates and infrared amplitudes of the samples in the image are fitted by least squares, and normalized according to the cloud height of the aircraft contrail cloud to obtain the updated cloud measurement parameters; Based on the updated cloud measurement parameters, high clouds above a predetermined height H are identified from the infrared cloud image obtained from the infrared cloud observation instrument.

2. The high cloud identification method according to claim 1, characterized in that: The updated cloud measurement parameters include: According to the atmospheric transmission parameter fitting formula in the statistical inversion method, the infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 Perform atmospheric parameter inversion on the samples in the image to obtain the atmospheric transmission parameters at the pixel coordinates of each sample; The atmospheric transmission parameters at each pixel coordinate of the aircraft contrail cloud sample, clear sky sample and medium and low cloud sample were fitted with the least square method to obtain the atmospheric transmission parameters at each zenith angle. Based on the characteristic that the cloud height of the same aircraft contrail is consistent, the atmospheric transmission parameters at the zenith angle of the same aircraft contrail are normalized according to the cloud height at the minimum zenith angle of the aircraft contrail, and the updated cloud measurement parameters obtained include the normalized atmospheric transmission parameters at the zenith angle of the aircraft contrail.

3. The high cloud identification method according to claim 2, characterized in that: The atmospheric transmission parameters at each zenith angle include: According to the atmospheric transmission parameter fitting formula T=c+aT in the statistical inversion method G +b1P+b2P 2 Inverted infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The atmospheric transmission parameters c, a, b1, b2 at the pixel coordinates of each sample in ; where T is the temperature obtained by inverting the infrared amplitude of the sample based on the current cloud measurement parameters, T G is the ground temperature at the current time t, P is the water vapor pressure at the current time t; The pixel coordinates of each sample are transformed into polar coordinates with the zenith angle of 0° as the pole, and the average value of the atmospheric transmission parameters of the infrared trail cloud samples on the same polar diameter is calculated to obtain the first parameter F at the zenith angle corresponding to the polar diameter. IR , calculate the average value of the atmospheric transmission parameter of the clear sky sample on the same polar diameter obtained by the conversion of polar coordinates to obtain the second parameter F at the zenith angle corresponding to the polar diameter sky , calculate the average value of the atmospheric transmission parameters of the low and medium cloud samples on the same polar diameter obtained by the conversion of polar coordinates to obtain the third parameter F at the zenith angle corresponding to the polar diameter c6 ; For each zenith angle, the first parameter F IR , the second parameter F sky and the third parameter F c6 The atmospheric transmission parameters at different zenith angles are obtained by fitting using the least squares method.

4. The high cloud identification method according to claim 1, characterized in that: The updated cloud measurement parameters include: For infrared contrail cloud sample set A IR-vis 、Infrared clear sky sample set A sky and infrared low and medium cloud sample set A c6 The samples in are fitted by the least square method to obtain the infrared amplitude of the pixel coordinates where the aircraft contrail cloud is located; The infrared amplitude of the pixel coordinates where the aircraft contrail cloud is located is normalized according to the cloud height at the minimum zenith angle of the aircraft contrail cloud to obtain an infrared threshold, and the updated cloud measurement parameters include the infrared threshold at the pixel coordinates where the aircraft contrail cloud is located.

5. The high cloud identification method according to claim 1, characterized in that: The infrared trail cloud sample set A is detected from the infrared cloud image at the current time t based on the linear cloud recognition. IR-vis include: Use the Canny edge detection algorithm to detect the cloud edges in the infrared cloud image at the current time t; The infrared linear cloud samples are detected based on the cloud edges in the infrared cloud image at the current time t using Hough transform; The height of the infrared line cloud samples is calculated according to the statistical inversion method, and the infrared trail cloud sample set A is obtained according to the infrared amplitude and pixel coordinates of the infrared line cloud samples whose height reaches the predetermined height H. IR-vis .

6. The high cloud identification method according to claim 5, characterized in that: The method of detecting the cloud edge in the infrared cloud image at the current time t by using the Canny edge detection algorithm includes: The reference infrared cloud image at the current time t is gradient processed according to the Sobel operator, and the 2σ value of the clear sky gradient in the reference infrared cloud image at the current time t is counted as the upper threshold of the Canny double threshold processing. The 2σ value of the cloud gradient in the reference infrared cloud image at the current time t is counted as the lower threshold of the Canny double threshold processing. Based on the determined upper and lower thresholds, the Canny edge detection algorithm is used to detect the cloud edges in the infrared cloud image at the current time t.

7. The high cloud identification method according to claim 5, characterized in that: The infrared trail cloud sample set A is obtained according to the infrared amplitude and pixel coordinates of the infrared line cloud samples whose height reaches the predetermined height H. IR-vis include: Use the visible light cloud observation instrument to obtain the visible light cloud image at the current time t; When it is determined that the visible light cloud image at the current time t reaches a predetermined brightness level, the cloud edge in the visible light cloud image at the current time t is detected using the Canny edge detection algorithm, and the visible light cloud samples are detected based on the cloud edge in the visible light cloud image at the current time t using the Hough transform, and a visible light cloud sample set A containing the pixel coordinates of the visible light cloud samples is obtained. vis ; Retain the infrared cloud samples whose height reaches the predetermined height H as candidate samples, and use the visible light cloud sample set A vis The candidate samples are corrected to remove interference data, and the remaining candidate samples are used as aircraft contrail cloud samples to obtain the infrared contrail cloud sample set A. IR-vis ; When it is determined that the visible light cloud image at the current time t does not reach the predetermined brightness level, the infrared line cloud samples reaching the predetermined height H are directly used as aircraft contrail cloud samples to obtain the infrared contrail cloud sample set A. IR-vis .

8. The high cloud identification method according to claim 7, characterized in that: The method uses the visible light cloud sample set A vis Data correction of candidate samples to remove interfering data includes: According to the pixel coordinate mapping relationship between the visible light cloud image and the infrared cloud image, the pixel coordinates of each candidate sample are mapped to obtain the pixel coordinates of the corresponding mapping sample. When the pixel coordinates of the mapping sample are included in the visible light cloud sample set A vis When the pixel coordinates of the mapped sample are not included in the visible light cloud sample set A, the candidate sample is retained; when the pixel coordinates of the mapped sample are not included in the visible light cloud sample set A vis When the candidate samples are detected, it is determined that the candidate samples are interference data and are removed.

9. The high cloud identification method according to claim 7, characterized in that: The method of detecting the cloud edge in the visible light cloud image at the current time t by using the Canny edge detection algorithm includes: The 2σ value of the red-blue ratio of the clear sky image in the historical statistical results of the area where the visible light cloud observer is located is used as the upper threshold of the Canny double threshold processing, and the 2σ value of the red-blue ratio of the cloud cluster in the historical statistical results of the area where the visible light cloud observer is located is used as the lower threshold of the Canny double threshold processing. Based on the determined upper and lower thresholds, the Canny edge detection algorithm is used to detect the cloud edges in the visible light cloud image at the current time t.

10. The high cloud identification method according to claim 5 or 7, characterized in that: The linear cloud samples detected based on the cloud edges in the cloud image using Hough transform include: The upper limit of the line width is determined according to the spatial resolution θ of the cloud image and the reference width W of the trail cloud at a predetermined height H that continues to develop for a predetermined time. The candidate linear clouds are detected based on the cloud edges in the cloud image using the Hough transform, and the line width is retained without exceeding the upper limit of the line width W. max The candidate linear clouds are obtained by deriving linear cloud samples.

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