Airborne weather radar-based rapid thunderstorm identification method

Abstract

An airborne weather radar-based rapid thunderstorm identification method, relating to the technical field of airborne weather radars. The method specifically comprises: performing ground clutter suppression processing on acquired three-dimensional echo data of an airborne weather radar; performing reflectivity factor calculation for data at each beam position during a volumetric scanning process, so as to obtain three-dimensional echo reflectivity factor data of the airborne weather radar after the ground clutter suppression; processing the three-dimensional echo reflectivity factor data after the ground clutter suppression, so as to obtain two-dimensional planar reflectivity factor data; extracting potential thunderstorm areas from the two-dimensional planar reflectivity factor data; mapping data of the potential thunderstorm areas back to the three-dimensional reflectivity factor data, so as to derive thunderstorm cell features; and, on the basis of a thunderstorm identification feature threshold, performing determination on the potential thunderstorm areas and the derived thunderstorm cell features. The method can improve the speed and accuracy of thunderstorm identification, and improve pilots' awareness of hazardous weather areas along flight routes.

Description

A thunderstorm rapid identification method for airborne weather radar TECHNICAL FIELD

[0001] The present application relates to the field of airborne weather radar, in particular to a thunderstorm rapid identification method for airborne weather radar. BACKGROUND

[0002] During the flight of an aircraft, it is subjected to various weather threats, among which thunderstorms are currently recognized by the world aviation industry and meteorological departments as a serious threat to aviation flight safety, and are known as the "air killer" in the aviation industry. Thunderstorms can derive adverse weather phenomena such as turbulence, wind shear, lightning, hail, etc. that threaten aviation safety, and will go through different development stages over time, and the impact and threat level on the flight of an aircraft are also different. When an aircraft mistakenly enters a thunderstorm activity area, it may encounter dangers such as turbulence, icing, lightning strikes, hail strikes, etc. which may cause human and machine damage.

[0003] Early airborne weather radar products can only detect rainfall, reflectivity factor, turbulence and wind shear, and the identification of dangerous weather such as thunderstorms requires pilots to combine visual discrimination based on weather radar detection results, which is affected by human factors such as pilot experience.

[0004] The existing methods for judging dangerous weather such as thunderstorms by airborne weather radar mainly include the following: 1) Thunderstorm recognition based on image recognition from the perspective of meteorological characteristics of thunderstorms, such as target intensity, distribution range and specific shape, etc. based on the detection results of airborne weather radar; 2) Thunderstorm recognition based on echo, the principle of which is to regard "thunderstorm" as a three-dimensional continuous region with a certain volume and reflectivity factor exceeding a certain threshold, such as classic thunderstorm recognition algorithms such as TITAN, SCIT, DBSCAN, etc. The first method is simple to implement, but its accuracy of thunderstorm recognition is not as good as that based on data processing due to the limited information of airborne weather radar detection images. The second method uses radar echo to recognize thunderstorms, considering that a thunderstorm body is a three-dimensional continuous body target that meets certain volume requirements, which makes the recognition algorithm complex and the amount of computation large, and it is difficult to implement in engineering. Moreover, this algorithm may not accurately recognize thunderstorms due to phenomena such as splitting and tilting of thunderstorm bodies, such as a thunderstorm being recognized as multiple thunderstorm cells, a thunderstorm being considered as multiple thunderstorms when the tilting degree is large, or a thunderstorm being "missed" when it does not meet the volume requirement, etc., which cannot meet the use requirements of airborne platforms for thunderstorm detection and recognition. SUMMARY

[0005] Therefore, the present application provides a thunderstorm rapid identification method for airborne weather radar, which solves the problems in the prior art, improves the speed and accuracy of thunderstorm recognition, and improves the pilot's perception ability of dangerous weather regions on the flight route.

[0006] The application provides a storm rapid identification method for an airborne weather radar, which adopts the following technical scheme:

[0007] A storm rapid identification method for an airborne weather radar, comprising the following steps:

[0008] Obtaining three-dimensional echo data of the airborne weather radar;

[0009] Performing ground clutter suppression processing on the three-dimensional echo data of the airborne weather radar;

[0010] Performing reflectivity factor calculation on each wave position data in the stereoscopic scanning process to obtain three-dimensional echo reflectivity factor data of the airborne weather radar after ground clutter suppression;

[0011] Processing the three-dimensional echo reflectivity factor data after ground clutter suppression to obtain two-dimensional planar reflectivity factor data;

[0012] Extracting potential storm regions from the two-dimensional planar reflectivity factor data;

[0013] Tracing back the potential storm region data to the three-dimensional reflectivity factor data to count storm body features;

[0014] Judging the potential storm regions and the counted storm body features according to storm identification feature threshold values, determining a target as a storm if the target meets the storm identification feature threshold value condition, and performing alarm on the determined storm region.

[0015] Optionally, the method for processing the three-dimensional echo reflectivity factor data after ground clutter suppression comprises:

[0016] Calculating the distance gate position after slant range projection to ground range according to radar echo parameters;

[0017] Performing alignment processing on the three-dimensional weather reflectivity factor data;

[0018] Performing fusion processing on different elevation scanning data at the same projection distance to obtain reflectivity data after planar projection of multi-layer weather data.

[0019] Optionally, the method for extracting potential storm regions from the two-dimensional planar reflectivity factor data comprises:

[0020] Setting a reflectivity threshold value DBZ reflecting storm echo features threshold Setting the two-dimensional planar reflectivity factor data greater than or equal to the reflectivity threshold value as 1 and the two-dimensional planar reflectivity factor data less than the reflectivity threshold value as 0 to obtain binary data distribution of the two-dimensional planar reflectivity factor data;

[0021] According to the distribution of the binarized data, a boundary of the binarized data is searched and extraction of a potential thunderstorm region boundary is implemented, and then the extracted thunderstorm region is labeled.

[0022] Optionally, the extracted potential thunderstorm regions are merged and deleted, if the correlation of several potential thunderstorm regions is higher than a first preset value, the corresponding several potential thunderstorm regions are merged into one thunderstorm region, otherwise no merging is performed, if the area of the thunderstorm region after merging is smaller than a second preset value, the corresponding thunderstorm region is deleted.

[0023] Optionally, the method for obtaining the three-dimensional echo data of the airborne weather radar comprises:

[0024] The airborne weather radar obtains the three-dimensional echo data in a specified airspace range in front of the aircraft through stereoscopic scanning, and the obtained three-dimensional echo data contains weather data and ground clutter data;

[0025] The stereoscopic scanning mode is:

[0026] first fixing the pitch angle to implement one azimuth scanning line, then turning to the next pitch angle until the azimuth scanning of all pitch angles is completed; or

[0027] first fixing the azimuth angle to implement one pitch scanning line, then turning to the next azimuth angle until the pitch scanning of all azimuths is completed; or

[0028] implementing stereoscopic scanning on the specified range airspace in a way of scanning and tracking at the same time.

[0029] Optionally, the characteristics of the thunderstorm body include thunderstorm volume, echo top height, bottom height and cloud height.

[0030] In summary, the present application has the following beneficial technical effects:

[0031] The method of the present application is based on the characteristics and distribution characteristics of thunderstorm targets, adopts a stereoscopic scanning mode to obtain three-dimensional echo data of weather targets such as thunderstorms, extracts the combined reflectivity factor of the three-dimensional echo data and performs binarization, discriminates possible thunderstorm target regions and extracts relevant information, and extracts features for each associated region, and considers it as a thunderstorm if it exceeds the threshold requirement. This method does not need to perform one-dimensional thunderstorm segment search, two-dimensional thunderstorm component synthesis and three-dimensional thunderstorm body synthesis and other processing steps, and directly realizes extraction and identification of thunderstorm regions on the basis of three-dimensional echoes. This method is easy to implement, has a significantly lower computational load, and at the same time can ensure better thunderstorm identification performance, can greatly improve the perception ability of pilots to dangerous weather regions such as thunderstorms, help pilots to evaluate the threat level of weather targets, improve flight safety and improve flight efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only illustrate some of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained from these drawings without creative labor.

[0033] FIG. 1 is a flowchart of a method for quickly identifying a thunderstorm by an airborne weather radar according to the present application. DETAILED DESCRIPTION

[0034] The embodiments of the present application will be described in detail below with reference to the drawings.

[0035] The above embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. The present application can also be implemented or applied through other different specific embodiments, and each detail in the present application can be modified or changed based on different views and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0036] It should be noted that the various aspects described below are within the scope of the embodiments described in the appended claims. It should be apparent that the aspects described herein can be embodied in a wide variety of forms and that any specific structure and / or function described herein is merely illustrative. Based on the teachings herein one skilled in the art should appreciate that an aspect described herein can be implemented independently of any other aspects and that an aspect described herein can be implemented both as any number of software and / or hardware structures and as any number of processes and / or operations. For example, an aspect can be implemented as a software program running on hardware that can process information such as, for example, information stored in a computer-readable storage medium. As another example, an aspect can be implemented as a software program running on hardware that can process information such as, for example, information stored in a computer-readable storage medium.

[0037] It should also be noted that the drawings provided in the following embodiments are only schematically illustrating the basic concept of the present application, and only the components related to the present application are shown in the drawings, not the number, shape and size of the components when actually implemented. The shape, number and ratio of each component when actually implemented can be arbitrarily changed, and the layout pattern of the components can also be more complex.

[0038] Also in the following description, specific details are provided to thoroughly understand examples. However, one of ordinary skill in the art will understand that the aspects can be practiced without these specific details.

[0039] Embodiments of the present application provide a method for rapid identification of thunderstorm by airborne weather radar.

[0040] As shown in FIG. 1, a method for rapid identification of thunderstorm by airborne weather radar includes the following steps:

[0041] Obtain three-dimensional echo data of airborne weather radar.

[0042] Perform ground clutter suppression processing on the three-dimensional echo data of airborne weather radar. In order to avoid the influence of ground clutter on thunderstorm identification, the data should be processed by ground clutter suppression before thunderstorm identification, so that there is no influence of ground clutter in the area where thunderstorm identification is located. The selected ground clutter processing method is not limited in the process of the present application, but the precondition is that the ground clutter suppression processing has no influence on weather echo.

[0043] Perform reflectivity factor calculation on each wave position data in the stereoscopic scanning process to obtain three-dimensional echo reflectivity factor data S(n az ,n el ,n r ) of airborne weather radar after ground clutter suppression, where n az ,n el ,n r represent azimuth scan count, elevation scan count, and distance gate count, respectively.

[0044] Perform processing on the three-dimensional echo reflectivity factor data after ground clutter suppression to obtain reflectivity factor data of two-dimensional plane.

[0045] Extract potential thunderstorm area from the reflectivity factor data of two-dimensional plane.

[0046] For the extracted potential thunderstorm area, backtrack the data of each potential thunderstorm area to the three-dimensional reflectivity factor data to count the characteristics of thunderstorm body.

[0047] According to the thunderstorm identification characteristic threshold, judge the potential thunderstorm area and the counted characteristics of thunderstorm body, determine the target as thunderstorm if it meets the condition of the thunderstorm identification characteristic threshold, and perform alarm on the determined thunderstorm area.

[0048] The application extracts the boundary of the potential thunderstorm area quickly and effectively through the planar projection mode of the three-dimensional body scanning data, extracts the features of the potential thunderstorm body on this basis, and realizes the recognition of the thunderstorm body. Compared with other thunderstorm recognition algorithms, the algorithm does not need to perform one-dimensional thunderstorm component search, two-dimensional component synthesis, storm body synthesis, and consider the correlation problem between components due to target characteristics, effectively simplifies the algorithm process, reduces the operation amount; at the same time, the algorithm can effectively improve the problems of target splitting and merging in the thunderstorm recognition process, make the thunderstorm recognition result and the dangerous area more accurate, and more meet the use demand of the airborne platform for the thunderstorm recognition function.

[0049] The method for acquiring three-dimensional echo data of an airborne weather radar includes:

[0050] The airborne weather radar acquires three-dimensional echo data in a specified airspace range in front of the aircraft through stereoscopic scanning. The acquired three-dimensional echo data includes weather data and ground clutter data. The stereoscopic scanning should be able to cover most of the height range where weather targets exist.

[0051] The stereoscopic scanning mode is: first fix the pitch angle to realize one azimuth scanning line, and then turn to the next pitch angle until the azimuth scanning of all pitch angles is completed.

[0052] The stereoscopic scanning mode can be: first fix the azimuth angle to realize one elevation scanning line, and then turn to the next azimuth angle until the elevation scanning of all azimuths is completed.

[0053] The stereoscopic scanning mode can also be: stereoscopic scanning of the specified range airspace in the mode of scanning and tracking at the same time.

[0054] The method for processing the three-dimensional echo reflectivity factor data after ground clutter suppression includes:

[0055] The distance gate position projected to the ground distance from the radar echo parameter is calculated; the distance gate position projected to the ground distance is calculated based on the echo slant range and the pitch angle, and the distance gate position projected to the ground distance from the radar echo parameter is calculated. groud = ceil(R(n r )×cos(El) / △R); wherein ceil(·) represents rounding up, R(n r ) represents the slant range corresponding to the nth r distance gate, El is the radar stability pitch angle, and △R is the distance gate resolution unit.

[0056] The three-dimensional weather reflectivity factor data is aligned: S(n az , n el , R groud ) = S(n az , n el , n r ).

[0057] The reflectivity data of the multi-layer weather data after planar projection is obtained by fusing the different elevation scan data at the same projection distance. The fusion processing adopts the maximum selection processing, that is, the point with the strongest reflectivity of the different elevation layer data at the same projection distance is extracted as the processing result, S1(n az ,R groud ) = max(S(n az ,:,R groud )), and the distance projection calculation can also adopt other calculation manners and is not limited to the above calculation formula.

[0058] The fusion processing can also adopt other processing methods and is not limited to the maximum selection processing method.

[0059] The method for extracting the potential thunderstorm area from the two-dimensional planar reflectivity factor data comprises the following steps:

[0060] A reflectivity threshold DBZ threshold is set to reflect the characteristics of thunderstorm echoes, and the two-dimensional planar reflectivity factor data greater than or equal to the reflectivity threshold is set to 1, and the two-dimensional planar reflectivity factor data less than the reflectivity threshold is set to 0, that is:

[0061] The binary data distribution of the two-dimensional planar reflectivity factor data is obtained; in the thunderstorm processing process, the reflectivity threshold reflecting the characteristics of thunderstorm echoes is set, and only the echoes higher than the reflectivity threshold are processed and analyzed; at the same time, the specific reflectivity value is not concerned in the thunderstorm search stage.

[0062] According to the binary data distribution, the boundary of the binary data is searched and the extraction of the boundary of the potential thunderstorm area is realized, then the extracted thunderstorm area is marked and numbered, and is recorded as Info Storm {n cell}, which represents the boundary information of the nth cell potential thunderstorm area, n cell is the number of the extracted potential thunderstorm area, Info Storm {n cell}.Az and Info Storm {n cell}.Edge respectively represent the azimuth boundary and the distance boundary of the nth cell potential thunderstorm area. The boundary information of each potential thunderstorm area is recorded. The searched data of each potential thunderstorm area belongs to a closed loop state, and the subsequent data processing is also carried out on the basis of the closed loop state; the subsequent thunderstorm recognition will be individually processed for each thunderstorm body data.

[0063] The extracted potential thunderstorm regions are merged and deleted. During the search of the potential thunderstorm regions, some special conditions can cause incomplete data extraction. Therefore, the regions with high correlation are merged after the extraction, which avoids the splitting of the thunderstorm body in the thunderstorm recognition process and can display the same target as much as possible. The potential thunderstorm regions with small correlation regions are deleted, which considers that the area of the region is small and is not a thunderstorm body. This processing can effectively avoid the false alarm of small area meteorological regions. The merging and deleting processes are as follows. If the correlation of a plurality of potential thunderstorm regions is higher than a first preset value, the corresponding potential thunderstorm regions are merged into one thunderstorm region, otherwise, no merging is performed. If the area of the thunderstorm region after merging is smaller than a second preset value, the thunderstorm region is deleted.

[0064] The thunderstorm region after the merging and deleting processes is recorded as Info Storm_New {m cell}, wherein m cell is the number of the current stereoscopic scanning line potential thunderstorm regions, and satisfies m cell ≤n cell . Info Storm_New {m cell}. Az, Info Storm_New {m cell}. Edge respectively represent the azimuth boundary and the distance boundary of the m cell th potential thunderstorm region after updating.

[0065] The specific method of feature extraction and thunderstorm discrimination is as follows.

[0066] For the extracted potential thunderstorm regions, the data of each potential thunderstorm region is traced back to the three-dimensional reflectivity data, the characteristics of the thunderstorm body are counted, and the characteristics of the thunderstorm body include the thunderstorm volume, the echo top height, the bottom height and the cloud height, which are used as the thunderstorm recognition characteristics. For the m cell th potential thunderstorm region, the boundary region is extracted, and the vertical direction is searched in the boundary region to obtain the integral volume, the echo top height, the bottom height and the cloud height of the thunderstorm region.

[0067] The specific method of thunderstorm recognition and alarm display is as follows.

[0068] According to the meteorological characteristics of the thunderstorm, the thunderstorm characteristic threshold is set, such as the thunderstorm volume threshold Vmax, the echo top height threshold Htop, the cloud height threshold Hmax, etc., which are used as the judgment basis of the thunderstorm recognition. One of the characteristics can be selected, or multiple characteristics can be selected simultaneously. The potential thunderstorm region and the corresponding characteristics are judged according to the thunderstorm recognition characteristic threshold. The target is considered to be a thunderstorm if it meets the conditions of the thunderstorm recognition characteristic threshold, and a specific icon is used for alarm display in the region where the thunderstorm is recognized.

[0069] The present application is directed to the problems that the existing airborne weather radar thunderstorm recognition algorithm is complex, the operation amount is large, and the thunderstorm recognition performance is reduced due to the splitting of the thunderstorm target, the tilting of the cloud body and other phenomena in the recognition process, a kind of thunderstorm fast recognition method is proposed, three-dimensional scanning data of airborne weather radar is used, the spatial distribution characteristics of thunderstorm are fully considered, the strong echo area is determined by using the combined reflectivity mode, on this basis, the three-dimensional data of the strong echo is associated and the features are extracted, the recognition of thunderstorm and the division of the influence area of thunderstorm are realized.The method can improve the speed and accuracy of thunderstorm recognition, and improve the perception ability of pilots to dangerous weather areas on the flight route.

[0070] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An airborne weather radar thunderstorm quick identification method, characterized in that, The method comprises the following steps: acquiring three-dimensional echo data of airborne weather radar; performing ground clutter suppression on the three-dimensional echo data of airborne weather radar; calculating reflectivity factor for each wave position data in the stereoscopic scanning process to obtain three-dimensional echo reflectivity factor data of airborne weather radar after ground clutter suppression; processing the three-dimensional echo reflectivity factor data after ground clutter suppression to obtain two-dimensional planar reflectivity factor data; extracting potential thunderstorm regions from the two-dimensional planar reflectivity factor data; backtracking the potential thunderstorm region data to the three-dimensional reflectivity factor data to count characteristics of thunderstorm bodies; judging the potential thunderstorm regions and the counted characteristics of thunderstorm bodies according to a thunderstorm identification characteristic threshold, and determining a target as a thunderstorm if the target meets the thunderstorm identification characteristic threshold condition, and alarming the determined thunderstorm region.

2. The airborne weather radar thunderstorm quick identification method according to claim 1, characterized in that, The method for processing the three-dimensional echo reflectivity factor data after ground clutter suppression comprises: calculating a slant range projection distance gate position after ground range projection according to radar echo parameters; aligning the three-dimensional weather reflectivity factor data; fusing different pitch scanning data at the same projection distance to obtain reflectivity data after planar projection of multi-layer weather data.

3. The airborne weather radar thunderstorm quick-identification method of claim 1, wherein, The method for extracting potential thunderstorm regions from the two-dimensional planar reflectivity factor data comprises: Setting reflectivity threshold DBZ reflecting thunderstorm echo characteristics threshold The reflectivity factor data of the two-dimensional plane greater than or equal to the reflectivity threshold is set to 1, and the reflectivity factor data of the two-dimensional plane less than the reflectivity threshold is set to 0, to obtain a binary data distribution of the reflectivity factor data of the two-dimensional plane. searching for boundaries of the binary data according to the distribution of the binary data to extract boundaries of potential thunderstorm regions, and then marking the extracted thunderstorm regions.

4. The airborne weather radar thunderstorm quick-identification method of claim 3, wherein, merging and deleting the extracted potential thunderstorm regions, merging several potential thunderstorm regions into one thunderstorm region if the correlation of the several potential thunderstorm regions is higher than a first preset value, and otherwise not merging, and deleting the corresponding thunderstorm region if the area of the thunderstorm region after merging is smaller than a second preset value.

5. The airborne weather radar thunderstorm quick-identification method of claim 1, wherein, The method for acquiring three-dimensional echo data of airborne weather radar comprises: acquiring three-dimensional echo data of a specified airspace range in front of an aircraft by the airborne weather radar through stereoscopic scanning, the acquired three-dimensional echo data containing weather data and ground clutter data; the stereoscopic scanning mode is: first fixing a pitch angle to implement one azimuth scanning line, then turning to the next pitch angle until all azimuth scanning lines of all pitch angles are completed; or first fixing an azimuth angle to implement one pitch scanning line, then turning to the next azimuth angle until all pitch scanning lines of all azimuths are completed; or stereoscopically scanning the specified range airspace in a way of scanning and tracking at the same time.

6. The airborne weather radar thunderstorm quick-identification method of claim 1, wherein, The characteristics of the thunderstorm bodies include thunderstorm volume, echo top height, bottom height and cloud height.

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