An automatic identification method for the bright band of zero-degree layer in radar PPI image

Abstract

The present invention provides an automatic identification method of a zero-degree layer bright band in a radar PPI image, belonging to the field of meteorological technology, and the method comprises: dividing the radar image; finding the target echo; converting the plane rectangular coordinates into polar coordinates; stretching the radar image into a grayscale image, determining the color code serial number of the target echo, reading the echo grayscale value of the color code serial number, and performing 0, 1 binary processing and sequential expansion and corrosion processing; detecting the contour of the target area to be identified, fitting the contour of each target echo respectively, confirming the target echo; calculating the parameters of the target echo; and comprehensively judging whether the target echo is a zero-degree layer bright band. The present invention can automatically identify the zero-degree layer bright band in the radar PPI image, improve the efficiency and accuracy of identifying artificial rainmaking operation conditions, greatly reduce the work intensity of forecasters, timely discover the precious opportunity of aircraft artificial rainmaking operations and ensure safety, and contribute to disaster prevention and mitigation and ecological civilization construction.

Description

Technical Field

[0001] The invention belongs to the field of meteorological technology, and in particular relates to an automatic recognition method for a zero-degree layer bright band in a radar PPI image. Background Art

[0002] All important weather phenomena in the atmosphere occur in the troposphere at the bottom, where the temperature decreases with increasing altitude. For stable precipitation, the cloud layer with heavy precipitation is thicker, so the precipitation is initially produced at a lower temperature (below zero degrees Celsius) and higher altitude, and the initial phase is solid. In the process of falling, the temperature of the lower atmosphere is higher, and the surface of these ice crystals and snowflakes begins to melt when they pass through the 0℃ layer. The water film wraps the ice to increase the dielectric constant of the particles, that is, the scattering ability of electromagnetic waves increases; and because the chances of mutual collision increase, large particles are formed, which further enhances the scattering ability. Therefore, near the 0℃ layer, the precipitation echo observed by the radar is significantly stronger than that above it, and below the 0℃ layer, when the ice crystals and snowflakes melt into raindrops, because the raindrops are close to spherical, their falling speed is much greater than that of ice crystals and snowflakes; and at this time, the water droplets will quickly break into smaller water droplets when they fall at high speed, so the number of large precipitation particles per unit volume is greatly reduced, and the echo detected by the radar is weaker than that near the 0℃ layer.

[0003] Due to the above reasons, when using weather radar to detect stable precipitation processes, the radar reflectivity factor near 0℃ will be higher, and a bright band will appear with greater echo intensity than above and below it.

[0004] Plain Position Indicator, or PPI for short, is a weather radar plane position display. After the radar obtains detection data at a certain elevation angle and the antenna scans 360 degrees in the horizontal direction, different colors are used on the plane map to represent the intensity of electromagnetic wave scattering by particles such as precipitation in the clouds, which is the PPI. This map can reflect the precipitation intensity in various places. The radar reflectivity factor is a physical quantity that represents the radar echo intensity, and its unit is dBz.

[0005] The bright band at the zero-degree layer is the most important feature of stable stratus precipitation, which is manifested as an obvious medium-intensity color-coded ring or arc on the radar PPI map. The ring or arc may be incomplete and discontinuous, and the thickness may not be uniform, such as Figure 1 As shown, Figure 1 The middle bright band is a significantly brighter arc, where the radar reflectivity factor reaches 35 to 40 dBz. Once it exceeds 40 dBz, it is mostly unstable heavy precipitation from convective clouds, and the zero-degree layer bright band cannot be formed. Summary of the invention

[0006] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for automatically identifying the zero-degree layer bright band in the radar PPI image, which automatically identifies the zero-degree layer bright band in the radar PPI image, improves the efficiency and accuracy of identifying artificial rainmaking operation conditions, greatly reduces the workload of forecasters, timely discovers the precious opportunity for aircraft artificial rainmaking operations and ensures safety, and contributes to disaster prevention and mitigation and ecological civilization construction.

[0007] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0008] This scheme provides an automatic identification method of the zero-degree layer bright band in the radar PPI image, comprising the following steps:

[0009] S1. Read the radar image and divide the radar image into a radar PPI echo area image display area on the left and a radar related parameter information area on the right;

[0010] S2. Based on the radar PPI echo area image display area, read the pixel points of the radar PPI echo area image, find the position of the plane rectangular coordinate origin, and based on the radar related parameter information area, respectively obtain the radar detection range, radar detection elevation angle and the strongest echo;

[0011] S3, take the radar PPI echo with an intensity of 35-40 dBz as the target echo, compare the strongest echo with 40 dBz, and find the target echo in the radar PPI echo area;

[0012] S4. For valid pixels whose pixel values ​​are not 0, convert the position (x, y) of the pixel point in the plane rectangular coordinate system to the position (θ, r) in the polar coordinate system, and map the angle θ and the distance coordinate r in the polar coordinate system as the x and y coordinates respectively to the plane rectangular coordinate system;

[0013] S5, assigning a value to the pixel echo intensity according to the echo intensity sequence number of the color code corresponding to the pixel point, and determining the color code sequence number of the target echo;

[0014] S6, stretching the radar PPI echo area image in the plane rectangular coordinate system converted in step S4 into a grayscale image, and marking the echo grayscale value of the read color code serial number;

[0015] S7, assigning a target echo grayscale value of 255, assigning a pixel value of the remaining non-zero-degree layer bright bands to 0, and performing a 0, 1 binary processing on the grayscale image to obtain a target area to be identified;

[0016] S8, keeping the radar PPI echo area image scale unchanged, and based on the target area to be identified, dilating and corroding the grayscale image after 0, 1 binary processing in the x(θ) direction in sequence;

[0017] S9, according to the processing result of step S8, detect the contour of the target area to be identified, and fit the contour of each target echo respectively using the minimum circumscribed rectangle in the polar coordinate system, and according to the fitting result, determine whether there are two target echoes in the north, and the angle θ crosses 0°, if so, merge the two target echoes into the same target echo, and enter step S10, otherwise, directly enter step S10;

[0018] S10, according to the acquired radar detection range and radar detection elevation angle, respectively calculating the distance between the radar and the target echo cloud top and cloud bottom;

[0019] S11. Calculate the length and width of the target echo according to the distance between the radar and the cloud top and cloud bottom of the target echo, and determine whether the target echo is a bright band of the zero-degree layer according to the length and width of the target echo.

[0020] The beneficial effects of the present invention are as follows: the present invention can automatically identify the bright band of the zero-degree layer in the radar PPI map, improve the efficiency and accuracy of identifying artificial rainmaking operation conditions, greatly reduce the workload of forecasters, timely discover the precious opportunity of artificial rainmaking operations by aircraft and ensure safety, and contribute to disaster prevention and mitigation and ecological civilization construction.

[0021] Furthermore, the expression of the plane rectangular coordinate origin in step S2 is as follows:

[0022]

[0023] Among them, (cx, cy) represents the origin of the plane rectangular coordinate system, imgw represents the pixel width of the radar PPI echo area image, and imgh represents the pixel height of the radar PPI echo area image.

[0024] The beneficial effect of the above further solution is that the present invention determines the position of the pixel point in the left-hand plane rectangular coordinate system of the screen by calculating the plane rectangular coordinate origin.

[0025] Furthermore, step S4 includes the following steps:

[0026] S401, using (x, y) to represent the position of a pixel point in a plane rectangular coordinate system;

[0027] S402, for valid pixels whose pixel values ​​are not 0, respectively calculating the distance r and the angle θ coordinates in the polar coordinate system according to the position (x, y) of the pixel point in the plane rectangular coordinates;

[0028] S403 , mapping the angle θ and the distance r coordinates in the polar coordinate system to the plane rectangular coordinate system as x and y coordinates respectively.

[0029] The beneficial effects of the above further solution are as follows: By converting the rectangular coordinate system, the present invention determines the position of the pixel point in the polar coordinate system.

[0030] Furthermore, the expression of the distance r is as follows:

[0031]

[0032] Calculating the angle θ in the polar coordinate system according to the position (x, y) of the pixel point in the rectangular coordinate plane, specifically:

[0033] When x > cx and y < cy, the pixel point is northeast of the origin of the rectangular coordinate plane, and the angle θ is in the first quadrant:

[0034]

[0035] When x > cx and y > cy, the pixel point is southeast of the origin of the rectangular coordinate plane, and the angle θ is in the second quadrant:

[0036]

[0037] When x < cx and y > cy, the pixel point is southwest of the origin of the rectangular coordinate plane, and the angle θ is in the third quadrant:

[0038]

[0039] When x < cx and y < cy, the pixel point is northwest of the origin of the rectangular coordinate plane, and the angle θ is in the fourth quadrant:

[0040]

[0041] The beneficial effects of the above further solution are as follows: By calculating the distance r and the angle θ coordinates in the polar coordinate system, the present invention helps to complete the mathematical projection conversion from the screen coordinate system to the polar coordinate system.

[0042] Furthermore, the step S9 includes the following steps:

[0043] S901. According to the processing result of step S8, in the polar coordinate system, use the minimum circumscribed rectangle to detect the contour of the target area to be recognized at two key points with the minimum angle and distance (θmin, rmin) and the minimum angle and distance (θmax, rmax);

[0044] S902. Based on the two key points, fit the contours of each target echo;

[0045] S903. According to the fitting result, determine whether there are two target echoes in the north in the polar coordinates, and the angle θ crosses 0°. If so, merge the two target echoes into the same target echo and proceed to step S10. Otherwise, directly proceed to step S10.

[0046] The beneficial effect of the above further solution is that the present invention determines the target echo by detecting the contour of the target area to be identified and fitting the contour of the target echo.

[0047] Furthermore, the expression of the length of the target echo in step S11 is as follows:

[0048] L=Δθ×Rt

[0049] Where L represents the length of the target echo, Δθ represents the difference in angle θ between two points in polar coordinates, and Rt represents the distance between the radar and the top of the target echo cloud;

[0050] The expression of the width of the target echo is as follows:

[0051] W=Rtcosβ-Rbcosβ

[0052] Where W represents the width of the target echo, β represents the radar detection elevation angle, and Rb represents the distance between the radar and the target echo cloud base.

[0053] The beneficial effect of the above further solution is: according to the calculated target echo parameters, it is further determined whether the target echo is a bright band of the zero-degree layer.

[0054] Furthermore, in step S10, determining whether the target echo is a bright band of the zero-degree layer is specifically as follows:

[0055] A1. For the radar PPI echo area image, if a cross-rectangle of Δθ=360° appears, the target echo is a bright band at the zero-degree layer, where Δθ represents the difference between the length L of the target echo and the angle θ in the polar coordinates;

[0056] A2. For the radar PPI echo area image, if ∑Δθ≥150° is satisfied, the target echo is a bright band at the zero-degree layer, where ∑Δθ represents the sum of the difference between the length L of all target echoes and the corresponding angle θ in the polar coordinates;

[0057] A3. For the radar PPI echo area image, if Δθ≤20°, the target echo is a bright band in the non-zero-degree layer;

[0058] A4. For radar PPI echo area image, if L≤1.5W, the target echo is a bright band in the non-zero-degree layer;

[0059] A5. For the radar PPI echo area image, if Δr≤20, the target echo is a bright band in the non-zero-degree layer, where Δr represents the difference between the target echo width and the distance in the polar coordinates corresponding to W.

[0060] The beneficial effect of the above further scheme is: in the present invention, if condition A1 or condition A2 is met, it is directly determined as a zero-degree layer bright band; if conditions A3-A5 are met, it is directly determined as a non-zero-degree layer bright band; the rest of the cases are non-bright band echoes. Through the above design, the zero-degree layer bright band can be judged. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a schematic diagram of the bright band at the zero-degree layer in the radar PPI diagram in the background technology.

[0062] Figure 2 The present invention is a flow chart of the method.

[0063] Figure 3 Schematic diagram of radar in this embodiment.

[0064] Figure 4 Schematic diagram of the rectangular coordinate system of the radar PPI echo image in the screen plane in this embodiment.

[0065] Figure 5 Schematic diagram of the bright band of the zero-degree layer in the polar coordinate system and the plane rectangular coordinate system in this embodiment.

[0066] Figure 6 Schematic diagram of rectangle fitting in this embodiment.

[0067] Figure 7 Schematic diagram of the display area of ​​the radar PPI echo image in the rectangular coordinate system of the screen plane in this embodiment.

[0068] Figure 8 Schematic diagram of the radar information parameter display area in this embodiment.

[0069] Fig. 9 Schematic diagram of a radar image in the rectangular coordinate system of the screen in this embodiment, with angle θ and distance r as x and y coordinates respectively.

[0070] Fig.10 Schematic diagram of the color code correspondence in this embodiment.

[0071] Fig.11 It is a schematic diagram of the echo grayscale image displayed in terms of angle and distance in the rectangular coordinate system of the screen in this embodiment.

[0072] Fig.12 Schematic diagram of the image after binary processing of 0 and 1 in this embodiment.

[0073] Fig.13It is a schematic diagram of lateral expansion in this embodiment.

[0074] Fig.14 In this embodiment, Fig.10 Schematic diagram of the image after dilation and erosion.

[0075] Fig.15 Schematic diagram of target echo in this embodiment.

[0076] Fig.16 Schematic diagram of various parameters of mid-layer clouds in this embodiment.

[0077] Fig.17 Schematic diagram of radar scanning profile in this embodiment.

[0078] Fig.18 Schematic diagram of the bright band range of the radar scanning at different elevation angles in this embodiment. DETAILED DESCRIPTION

[0079] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0080] Example

[0081] At present, most of the artificial weather modification work in my country is carried out by aircraft artificial precipitation, but not all clouds can be used for precipitation, because stratus clouds have stable characteristics, while convective clouds often produce disastrous high-intensity precipitation, often accompanied by lightning, strong winds and even hail, and the drastic changes in airflow in the clouds endanger flight safety, so only stratus clouds can be used for aircraft artificial precipitation. The bright band of the zero-degree layer on the weather radar PPI map is an indicative feature of stable precipitation in stratus clouds, indicating that it is stratus clouds rather than convective clouds that produce precipitation, so the discovery of the bright band is a prerequisite for aircraft artificial precipitation operations.

[0082] my country has established a new generation of Doppler weather radar network consisting of multiple weather radars. In the summer half of the year, each radar operates continuously for 24 hours a day, and completes a volume scan (referred to as volume scan) composed of different elevation angles every 6 minutes, which is equivalent to conducting uninterrupted CT examinations of the sky across the country 10 times an hour at the same time. At present, each volume scan data requires business personnel to make judgments based on their own experience. Because a radar can obtain the latest data every 6 minutes, each radar can provide dozens of detection products. Under normal circumstances, it is impossible to manually complete the analysis of dozens of radar detection professional products within these 6 minutes. Therefore, while monitoring the complex changes in the weather, forecasters must also pay attention to analyzing whether there is a bright band in the zero-degree layer and looking for favorable opportunities for artificial rainfall. The pressure is extremely huge. Manual analysis is not only too intense, but also has the disadvantages of possible misjudgment, low efficiency, and failure to grasp the opportunity in time. It is very easy to fatigue, which seriously affects the artificial rainfall operation of aircraft. Based on the above, the present invention can automatically identify the bright band of the zero-degree layer in the radar PPI map, improve the efficiency and accuracy of identifying artificial rainfall operation conditions, significantly reduce the workload of forecasters, timely discover the precious opportunity of artificial rainfall operation by aircraft and ensure safety, and contribute to disaster prevention and mitigation and ecological civilization construction. Figure 2 As shown, the present invention provides an automatic recognition method for the bright band of the zero-degree layer in the radar PPI image, and its implementation method is as follows: An automatic recognition method for the bright band of the zero-degree layer in the radar PPI image, and its implementation method is as follows:

[0083] S1. Read the radar image and divide the radar image into a radar PPI echo area image display area on the left and a radar related parameter information area on the right;

[0084] S2. Based on the radar PPI echo area image display area, read the pixel points of the radar PPI echo area image, find the position of the plane rectangular coordinate origin, and based on the radar related parameter information area, respectively obtain the radar detection range, radar detection elevation angle and the strongest echo;

[0085] The expression of the plane rectangular coordinate origin is as follows:

[0086]

[0087] Among them, (cx, cy) represents the origin of the plane rectangular coordinates, imgw represents the pixel width of the radar PPI echo area image, and imgh represents the pixel height of the radar PPI echo area image;

[0088] S3, take the radar PPI echo with an intensity of 35-40 dBz as the target echo, compare the strongest echo with 40 dBz, and find the target echo in the radar PPI echo area;

[0089] S4. For valid pixels with non-zero pixel values, convert the position (x, y) of the pixel point in the rectangular coordinate system to the position (θ, r) in the polar coordinate system, and map the angle θ and the distance coordinate r in the polar coordinate system to the x and y coordinates in the rectangular coordinate system respectively. The implementation method is as follows:

[0090] S401. Represent the position of the pixel point in the rectangular coordinate system as (x, y);

[0091] S402. For valid pixels with non-zero pixel values, calculate the distance r and the angle θ coordinates in the polar coordinate system according to the position (x, y) of the pixel point in the rectangular coordinate system;

[0092] S403. Map the angle θ and the distance r coordinates in the polar coordinate system to the x and y coordinates in the rectangular coordinate system respectively;

[0093] The expression of the distance r is as follows:

[0094]

[0095] The calculation of the angle θ in the polar coordinate system according to the position (x, y) of the pixel point in the rectangular coordinate system is specifically as follows:

[0096] When x > cx and y < cy, the pixel point is northeast of the origin of the rectangular coordinate system, and the angle θ is in the first quadrant:

[0097]

[0098] When x > cx and y > cy, the pixel point is southeast of the origin of the rectangular coordinate system, and the angle θ is in the second quadrant:

[0099]

[0100] When x < cx and y > cy, the pixel point is southwest of the origin of the rectangular coordinate system, and the angle θ is in the third quadrant:

[0101]

[0102] When x < cx and y < cy, the pixel point is northwest of the origin of the rectangular coordinate system, and the angle θ is in the fourth quadrant:

[0103]

[0104] S5. Assign values to the pixel echo intensities according to the echo intensity serial numbers of the corresponding color scales of the pixel points, and determine the color scale serial number of the target echo;

[0105] S6, stretching the radar PPI echo area image in the plane rectangular coordinate system converted in step S4 into a grayscale image, and marking the echo grayscale value of the read color code serial number;

[0106] S7, assigning a target echo grayscale value of 255, assigning a pixel value of the remaining non-zero-degree layer bright bands to 0, and performing a 0, 1 binary processing on the grayscale image to obtain a target area to be identified;

[0107] S8, keeping the radar PPI echo area image scale unchanged, and based on the target area to be identified, dilating and corroding the grayscale image after 0, 1 binary processing in the x(θ) direction in sequence;

[0108] The expression for the expansion process is as follows:

[0109]

[0110] The expression for the corrosion treatment is as follows:

[0111]

[0112] Among them, B represents the convolution template image, A represents the original image, x represents the element point in the image, and the image B is translated according to the element point x. The set of points obtained is recorded as B(x), and B(x) represents the structural element moved in image A. represents the dilation operation, represents the erosion operation; the result of the dilation operation on A using B(x) is the set of points that make the intersection of B and A non-empty after the structural element B is translated; the result of the erosion operation on A using B(x) is the set of all points that make B included in A after the structural element B is translated;

[0113] S9, according to the processing result of step S8, detect the contour of the target area to be identified, and fit the contour of each target echo respectively using the minimum circumscribed rectangle in the polar coordinate system, and according to the fitting result, judge whether there are two target echoes in the north, and the angle θ crosses 0°, if so, merge the two target echoes into the same target echo, and enter step S10, otherwise, directly enter step S10, and its implementation method is as follows:

[0114] S901, according to the processing result of step S8, in the polar coordinate system, using the minimum circumscribed rectangle to take the two key points with the minimum angle and distance (θmin, rmin) and the minimum angle and distance (θmax, rmax) to detect the contour of the target area to be identified;

[0115] S902, fitting the contour of each target echo based on two key points;

[0116] S903, according to the fitting result, determine whether there are two target echoes in the north in the polar coordinates, and the angle θ crosses 0°, if so, merge the two target echoes into the same target echo, and proceed to step S10, otherwise, directly proceed to step S10;

[0117] S10, according to the acquired radar detection range and radar detection elevation angle, respectively calculating the distance between the radar and the target echo cloud top and cloud bottom;

[0118] S11, according to the distance between the radar and the cloud top and cloud bottom of the target echo, respectively calculate the length and width of the target echo, and determine whether the target echo is a bright band of the zero-degree layer according to the length and width of the target echo;

[0119] The expression of the length of the target echo is as follows:

[0120] L=Δθ×Rt

[0121] Where L represents the length of the target echo, Δθ represents the difference in angle θ between two points in polar coordinates, and Rt represents the distance between the radar and the top of the target echo cloud;

[0122] The expression of the width of the target echo is as follows:

[0123] W=Rtcosβ-Rbcosβ

[0124] Where W represents the width of the target echo, β represents the radar detection elevation angle, and Rb represents the distance between the radar and the target echo cloud base;

[0125] Determine whether the target echo is a bright band at the zero-degree layer. The specific steps are:

[0126] A1. For the radar PPI echo area image, if a cross-rectangle of Δθ=360° appears, the target echo is a bright band at the zero-degree layer, where Δθ represents the difference between the length L of the target echo and the angle θ in the polar coordinates;

[0127] A2. For the radar PPI echo area image, if ∑Δθ≥150° is satisfied, the target echo is a bright band at the zero-degree layer, where ∑Δθ represents the sum of the difference between the length L of all target echoes and the corresponding angle θ in the polar coordinates;

[0128] A3. For the radar PPI echo area image, if Δθ≤20°, the target echo is a bright band in the non-zero-degree layer;

[0129] A4. For radar PPI echo area image, if L≤1.5W, the target echo is a bright band in the non-zero-degree layer;

[0130] A5. In the radar PPI echo area image, if Δr ≤ 20, the target echo is the non-zero-degree bright band, where Δr represents the difference in distance in the polar coordinates corresponding to the width W of the target echo.

[0131] In this embodiment, the description of the radar PPI image is as Figure 3 shown. Figure 3 In it, the relatively bright arc part with a reflectivity factor intensity of 35 - 40 dBz is the zero-degree bright band in the radar PPI map. The core feature of the zero-degree bright band on the radar PPI is that the reflectivity factor intensity is 35 - 40 dBz, presenting an arc or circular ring shape centered on the radar station. Figure 3 On the left side in it is the radar echo display area, and on the right side are the radar-related parameter information, including parameters such as the product name Base Reflectivity, detection range Range, resolution Resolution, antenna height Height of the radar, detection elevation angle Elev of the radar, and the reflectivity factor corresponding to each color scale.

[0132] In this embodiment, the coordinate system conversion includes converting the screen rectangular coordinate system to the polar coordinate system and the mapping of the bright band in the polar coordinate system to the plane rectangular coordinate system.

[0133] In this embodiment, for the conversion from the screen rectangular coordinate system to the polar coordinate system, the regulations of angles in meteorology are as follows: The due north direction is taken as 0°, and it increases clockwise. Then the corresponding angles in the east, south, and west directions are 90°, 180°, and 270° respectively. In the radar screen rectangular coordinate system, taking cx, cy as the origin, as Figure 4 shown. Figure 4 In it, (cx, cy) is the coordinate origin. Then for a certain point (x, y), when x = cx, if y = cy, the point is located at the origin; if y < cy, the point is due north of the origin, and the corresponding angle is 0°; if y > cy, the point is due south of the origin, and the corresponding angle is 180°. Now, (x, y) represents the position of the pixel point in the screen left-handed plane rectangular coordinate system. From the radar working principle, the center point of the echo area:

[0134]

[0135] where (cx, cy) represents the origin of the plane rectangular coordinates, imgw represents the pixel width of the radar PPI echo area image, and imgh represents the pixel height of the radar PPI echo area image, thereby determining the specific values of the polar coordinate origin (cx, cy).

[0136] In this embodiment, regarding the calculation of the r value in the polar coordinates, for any point at the screen coordinate (x, y) position, the distance from it to the polar coordinate origin is:

[0137]

[0138] In this embodiment, regarding the calculation of the θ value in polar coordinates, as Figure 4 shown, when x > cx and y < cy, the point is northeast of the origin and the angle is in the first quadrant.

[0139]

[0140] When x > cx and y > cy, the point is southeast of the origin and the angle is in the second quadrant.

[0141]

[0142] When x < cx and y > cy, the point is southwest of the origin and the angle is in the third quadrant.

[0143]

[0144] When x < cx and y < cy, the point is northwest of the origin and the angle is in the fourth quadrant.

[0145]

[0146] Thus, the θ coordinate value of the point (x, y) in the polar coordinate system can be calculated. Any point within the radar display area can be calculated to obtain the polar coordinates from the rectangular coordinates (x, y) of the screen according to the above formula and take the integer value. Using dBz[θ, r] as the image matrix after the coordinate axis mapping transformation, the mathematical projection conversion from the screen coordinate system to the polar coordinate system is completed. If the scattered echo area of the cloud mass is limited, this matrix is a sparse matrix.

[0147] In this embodiment, for the mapping of the bright band in the polar coordinate system to the rectangular coordinate system, regarding the shape of the bright band at the zero-degree layer (hereinafter referred to as the bright band), if directly identifying the bright band, it is necessary to identify a circle or arc with a relatively high reflectivity factor in the radar display area. Therefore, it is necessary to determine the center position and the radius length. However, the distribution of the bright band is not uniform, not necessarily complete, often irregular and non-standard, and due to the differences in the precipitation layer cloud itself, there may be many discontinuities in the middle of the bright band, and the result is not a complete and continuous circle or arc. In Figure 3 the example, it can be seen that on the one hand, there are obvious discontinuities in the lower left of the bright band, and on the other hand, there are also some small discontinuities in other positions, and the width of the bright band also fluctuates. Therefore, for the work of identifying the bright band, what is faced is a target that is not necessarily continuous, has an uncertain width, may be in the form of discontinuous blocks, and is generally approximately a circular ring or circular arc. There are certain difficulties in directly identifying it. Changing the thinking, if the recognition target is a horizontally distributed long band or strip, the difficulty will be significantly reduced compared with a circular ring or circular arc. Therefore, it can be considered: converting the recognition target into a rectangle in a certain mathematical space. As Figure 3 As shown in the figure, on a common computer monitor, the radar PPI image is displayed as a very irregular ring or arc in the XY rectangular coordinate system. It is known that the center of these rings or arcs is the position of the radar antenna, so this point can be taken as the origin for coordinate transformation to map the radar echo to polar coordinates. In polar coordinates, the position of the irregular rings or arcs on the bright band is expressed in angles and distances. In this case, the angle coordinates of the bright band should be basically adjacent to each other, and the values ​​have a certain degree of continuity; and the distance coordinates of the bright band are the radius of the ring or arc, and their values ​​are relatively concentrated.

[0148] In this embodiment, Figure 5 It can be seen that Figure 5 middle, Figure 5 (a) is the original PPI image on the screen, Figure 5 (b) is the echo image displayed on the screen after conversion to polar coordinates, with the angle coordinate as x and the distance coordinate as y. Since the center of the circle or arc corresponding to the bright band is at the origin of the polar coordinates, the angle value range of its coordinates should be within 360° after this coordinate system transformation. The width of the bright band is reflected in the distance coordinate, and the distance values ​​of the bright band at different angles are relatively concentrated. Figure 5 As shown in the figure, the angle θ and the distance coordinate r in the polar coordinate system are respectively expressed on the screen of the rectangular coordinate system (x, y), and the bright band is a rectangle with a length of 0 to 360° and a roughly determined width. After the coordinate system transformation, the bright band ring or arc displayed on the original recognition target screen can be mapped to another mathematical space to become a very regular rectangle, making the recognition process simpler and more convenient, and more efficient and accurate.

[0149] In this embodiment, rectangle fitting is used to detect the contour of the area to be identified. In the polar coordinate system, the contour of each target echo is respectively wrapped and fitted by the minimum circumscribed rectangle. Among the four endpoints of the rectangle, two key points (θmin, rmin) and (θmax, rmax) are taken, that is, the two extreme points with the smallest angle and distance, and the largest angle and distance for calculation. In polar coordinates, when the target appears in the north, the angle often crosses 0°. At this time, one continuous target will be misjudged as two. Therefore, after reading the image, it is necessary to perform contour detection and fitting on the area to be identified, and merge the targets that cross 0 degrees. The number of rectangles of the suspected target echo is recorded in num, which is initially 0. In this case, if Figure 6 As shown, Figure 6 In the example, target 0 across 0 degrees is merged with target n. Figure 6In the figure, the key points of target 0 are labeled as (0, rmin0) and (θmax0, rmax0). The key points of target n are labeled as (θminn, rminn) and (θmaxn, rmaxn). If there is a target that crosses 0 degrees, θmaxn = 359°. Figure 6 As shown in the figure, 0 and n are connected in the north direction, and are actually the same target, so target n is merged into target 0 and the number of target n is cancelled. Re-adjust the relevant parameters and take:

[0150]

[0151] In the above formula, min(·) and max(·) are the operations of taking the minimum and maximum values, respectively. After the two connected targets are merged, the parameters are adjusted as follows: the starting point of the arc is the starting point of the original last target, and the end point of the arc is the end point of the original first target No. 0 plus 360° to ensure data continuity. At the same time, the minimum and maximum distances of the target from the radar are adjusted downward and upward respectively to ensure that the merged rectangular target area completely covers the range of the target echo.

[0152] In this embodiment, the radar echo image is read, and the radar PPI echo image is as follows: Figure 3 As shown, according to the rules of the rectangular coordinate system on the left-hand plane of the screen, the radar PPI image is read, such as Figure 7 As shown, the upper left corner of the image is taken as the origin O, the X axis points horizontally to the right, and the Y axis points vertically downward. From formula (1), we can know that the corresponding pixel points are:

[0153]

[0154]

[0155] The coordinate origin (cx, cy) is (301, 300).

[0156] In this embodiment, the reading of radar parameter information is described. Figure 2 As shown, the radar related information area is as follows Figure 8 , using mature image text recognition OCR technology, obtain the letters and numbers, obtain the radar antenna height Height, recorded as h; radar detection range Range, recorded as R; radar detection elevation angle Elev, recorded as β; then:

[0157]

[0158] Among them, the unit of radar antenna height h is m; the unit of radar detection range R is km; the unit of radar detection elevation angle β is °.

[0159] In this embodiment, the search for target echo is described, and the value of the reflectivity factor dBz is generally [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75]. The maximum reflectivity factor in the echo is read out, that is, the strongest echo dBz_max. It is known that the bright band is a relatively strong echo of stratus clouds, and the intensity can reach 35-40dBz. The stronger echo is not stratus clouds but convective clouds, which does not correspond to the bright band. In business forecasts, the echo with an intensity of 35-40dBz is often used as a standard to determine whether it is a bright band echo. If the maximum intensity of the echo map is dBz_max and is less than 40, it indicates that there is no bright band echo at this time. Therefore, dBz_max is compared with 40, and 40dBz is selected as the upper limit of the intensity in the program. Searching for echoes in the echo area can find the target faster.

[0160] In this embodiment, the coordinate axis mapping transformation is explained. In the radar PPI image, black indicates no echo. In the process of stratus precipitation, there are often relatively few echo areas. In order to improve the recognition efficiency, only the precipitation cloud system echo, that is, the valid pixels with non-zero pixel values, are mathematically mapped, thereby greatly improving the recognition efficiency. First, the rectangular coordinates are converted to the polar coordinates, and the pixel position (x, y) is converted to the position (θ, r) in the polar coordinates by formulas (1)-(6). Then, according to the mapping of the bright band in the polar coordinates to the plane rectangular coordinates, Figure 6 The angle and distance coordinate data (θ, r) in the polar coordinate system are mapped to the plane rectangular coordinate system, such as Fig. 9 As shown, Fig. 9 It is a radar image in the rectangular coordinate system of the screen with angle θ and distance r as x and y coordinates respectively.

[0161] In this embodiment, regarding the description of pixel color assignment, the pixel in the echo is the radar reflectivity factor, and its pixel color is converted into the corresponding echo intensity through the corresponding relationship of the color code. The color of each pixel is compared with the color in the color code. If the two are the same, the serial number value of the corresponding color code is taken to re-assign the echo intensity of the pixel. For example, Fig.10 As shown, in the color scale, its color indicates that the echo intensity is 40-45 dBz, and it is ranked 9th in the color scale, so the color value of this point is 9.

[0162] In this embodiment, the possible target echo is detected, and the range of the bright band reflectivity factor is 35-40dBz. 35-40dBz is selected. After the previous step, the color code number corresponding to the pixel is as follows: Fig.10 As shown, the serial number of the color code of the target echo can be determined to be 8.

[0163] In this embodiment, the grayscale image conversion is explained by redefining the color value in the color code as grayscale, so that the original image is converted from multiple colors to grayscale images, so as to facilitate the subsequent conversion to a binary black and white image, and the grayscale level is linearly stretched to the value range of 0 to 255 to improve the visual distinction. After the original image is converted to a grayscale image, the grayscale value of the target echo with the color code number 8 is read and recorded as k8. In this example, k8 = 255. After conversion to grayscale, dBz[θ, r] is used as the transformed image matrix, where dBz[θ, r] represents the transformed image matrix, then Fig. 9 The display effect in the screen coordinate system is as follows Fig.11 shown.

[0164] In this embodiment, the image is converted to 0, 1 and binary processing is performed to filter out non-important information. In case of possible bright bands, the grayscale image of the echo is further converted to 0, 1 and binary processing is performed to highlight the target area to be identified. For the target echo in the previous step, the grayscale value of the echo with color code number 8 is uniformly assigned a value of 255, that is, white. Other stronger and weaker pixels are not bright bands and are therefore assigned a value of 0, that is, black. The dBz[θ, r] grayscale image is converted to 0, 1 and binary processing is performed using the selected range. The values ​​of the pixels outside the range are converted to 0 (black), and the values ​​of the pixels within the range are converted to white to highlight the area that may be a bright band, that is, the area to be identified. The converted image matrix dst[θ, r] has the following effect: Fig.12 , Fig.12 The image is binary processed to 0 and 1 (the target echo area is the white part), and there are discontinuities in between.

[0165] In this embodiment, after the black and white binary processing is converted to 0 and 1, Fig.10 The white target area in the middle is a possible bright band. Because there will be some isolated scattered convections mixed in a large range of stratus clouds, and there will be some areas with weak echo intensity due to low water vapor content, it is inevitable that there will be some stronger and weaker echoes in the target echo. At the same time, due to the conversion of the coordinate system, when the resolution is the same everywhere, the area close to the origin will be denser after conversion to polar coordinates, while the image is relatively rough at a farther distance. Therefore, there will be some discontinuities in the target echo area. In order to better reflect the overall effect of the target echo and eliminate the influence of the intermediate breakpoints, the white target echo is subjected to image expansion processing. The basic principle is to merge the background points that are in contact with the target into the object to expand the boundary. All black pixels adjacent to white are assigned the value of white. The mathematical expression is as follows: Expansion is defined as a set operation. A is expanded by B, recorded as Defined as:

[0166]

[0167] Indicates that B is used to dilate image A. Fig.13In the figure, the gray pixel value is 1, and the black pixel value is 0, where B is the convolution template, i.e., the convolution kernel. The convolution kernel B is used to perform convolution calculation with image A. Scan each pixel in the image, and use the convolution kernel element and the binary image element to perform an "AND" operation. If both are 0, then the target pixel is 0, otherwise it is 1. Thus, the maximum value of the pixel in the area covered by B is calculated, and the pixel value of the original point is replaced with this value to achieve expansion. The expansion process can be performed multiple times. After completion, on the one hand, the noise points with a grayscale of 0 inside the target echo can be effectively eliminated, and on the other hand, the outer edge of the target echo will expand outward, so that its range will be expanded compared with before processing.

[0168] In this embodiment, in order to restore its original normal range, the target is subjected to image corrosion. Image corrosion is the inverse operation of image dilation. Its principle is to merge the points where the target touches the background into the background to shrink the boundary. Here, the white echo is the target and the black area is the background. All white pixels adjacent to black are assigned black. Its mathematical expression is that the corrosion operation A is corroded by B, which is recorded as Defined as:

[0169]

[0170] It means that image A is corroded with convolution kernel B. By convolving kernel B with image A, the minimum value of the pixel in the area covered by B is obtained, and the pixel value of the original point is replaced with this value to achieve corrosion. The morphological closing operation of A by B is recorded as A●B, which is the result of dilation first and then corrosion:

[0171]

[0172] right Fig.12 The masked image is first expanded and then eroded, such as Fig.14 As shown, Fig.14 In the figure above, Fig.10 The following figure is the image after dilation and erosion. Through the above image dilation and erosion, the interruption point in the middle of the original target is eliminated, which enhances the integrity of the target echo and maintains the original scale. In this example, there are 3 target echoes to be identified. Fig.15 .

[0173] In this embodiment, the target area contour detection and fitting are performed. For the detection contour of the target area, the contour of each target echo is respectively wrapped by the minimum circumscribed rectangle for fitting. Among the four endpoints of the rectangle, two key points (θmin, rmin) and (θmax, rmax) are selected, i.e., the two extreme points with the minimum angle and distance, and the maximum angle and distance, for calculation. Fig.15, Target 0 and Target 2 appear in the north, and the angle spans 0°. If not processed, the original one continuous target will be misjudged as two. Perform contour detection and fitting on the area to be identified. Merge Target 2 into Target 0. The two are connected in the true north direction and identified as the same target. Cancel the number of Target 2, and merge Target 2 and Target 0 into Target 1.

[0174] In this embodiment, after contour detection and fitting of the recognition area, two target echoes are obtained. The pixel positions of the two endpoints of the two circumscribed rectangles are read in the rectangular coordinate system, which are the endpoints of target 0 img1 (285, 306), img2 (332, 298), and the endpoints of target 1 img3 (318, 297), img4 (300, 334). The pixel position (x, y) is converted to the position (θ, r) in the polar coordinate system, and the r value of the point (x, y) in the polar coordinate system is calculated by formula (1):

[0175]

[0176] Among them, r1, r2, r3, and r4 are the polar diameters of the endpoints img1, img2, img3, and img4 in polar coordinates. The θ coordinate value of the point (x, y) in the polar coordinate system is calculated using formulas (2), (3), (4), and (5):

[0177]

[0178]

[0179] Among them, θ1, θ2, θ3, and θ4 are the polar angles of the endpoints img1, img2, img3, and img4 in polar coordinates respectively.

[0180] In this embodiment, for a target identified by radar scanning, its thickness H, width W, and length L can be calculated as follows: Fig.16 , to determine whether the target is a bright band in the zero-degree layer. According to the atmospheric height measurement formula in radar meteorology, the target height H is:

[0181]

[0182] Where H represents the height of the measured target, h represents the antenna height, β represents the radar elevation angle, Rt represents the distance between the radar and the target echo cloud top, and Rm represents the equivalent earth radius. Rm = 8.5 × 10 3 km.

[0183] The target thickness T can be obtained by measuring the difference between the upper and lower heights of the target:

[0184]

[0185] The target width W is obtained by measuring the difference between the inner and outer radii of the ring mapped by the target in the plane coordinates:

[0186] W=Rtcosβ-Rbcosβ (19)

[0187] Among them, Rb represents the distance between the radar and the target echo cloud base.

[0188] The target length L can be obtained by calculating the arc length:

[0189] L=Δθ×Rt (20)

[0190] Where L represents the length of the target echo, and Δθ represents the difference in angle θ between two points in polar coordinates.

[0191] Depend on Fig.17 It can be seen that the mathematical mapping relationship between the parameters is Fig.17 In the figure, R represents the radar detection range, Rn represents the measured distance of the target from the radar; rn represents the pixel distance from the origin of the radar image in the rectangular coordinate system of the screen after the target is mapped on the plane. It can be seen that the relationship between the parameters is:

[0192]

[0193] Substituting the radar information parameters into formula (10), we can obtain R1 = 1.31 × 10 4 m, R2=2.37×10 4 m, R3=1.32×10 4 m, R4=2.60×10 4 m, where R1 and R3 represent the radar distance Rb from the cloud base of target 0 and target 1 respectively, and R2 and R4 represent the radar distance Rt from the cloud top of target 0 and target 1 respectively. For target 0, the target cloud base height is:

[0194]

[0195] The target cloud top height is:

[0196]

[0197] The target thickness is:

[0198]

[0199] The target width is:

[0200] W0=R2cosβ-R1cosβ=1.06×10 4 (25)

[0201] The target length is:

[0202] L0=Δθ1×R2=4.47×10 4 (26)

[0203] For target 1, the target cloud base height is:

[0204]

[0205] The target cloud top height is:

[0206]

[0207] The target thickness is:

[0208]

[0209] The target width is:

[0210] W1=R4cosβ-R3cosβ=1.28×10 4 (30)

[0211] The target length is:

[0212] L1=Δθ2×R4=4.47×10 4 (31)

[0213] The unit of the above numerical values ​​is m.

[0214] In this embodiment, the comprehensive judgment is as follows: the length of the rectangle L corresponds to the difference Δθ of the angle θ in the polar coordinates, that is, the degree of the arc formed by the target echo area. The width of the rectangle W corresponds to the difference Δr of the distance r in the polar coordinates, that is, the distance that the target echo area extends outward from the radar.

[0215] (1) Determine condition 1: Based on experience in the use of weather radars, as long as a completely closed circle appears, that is, a horizontal rectangle of Δθ=360° appears in the current figure, then no other conditions are required to identify the target as a bright band. For other situations, because stratus clouds have good stability and their scale is much larger than that of general convective clouds, their corresponding arcs are relatively large. In addition, because the scanning elevation angle Elev of the radar antenna in the working state is very low, the maximum is only 19.5°, and the cloud base height of the stratus clouds is relatively high, the location detected by the radar is relatively remote, so the intersection angle between the radar beam and the stratus clouds is very small during detection, thus generating a large range of echoes. The lower the scanning elevation angle, the larger the echo range of the same bright band. For example Fig.18 As shown, Fig.18Among them, the echo ΔR2 at low elevation angles is larger (the echo of the target bright band is between the dashed lines, the dotted line is the large scan elevation angle Elev1, and the bright band echo range is ΔR1; the solid line is the small scan elevation angle Elev2, and the bright band echo range is ΔR2). Elev1 < Elev2, and the bright band range ΔR2 detected when the radar scan elevation angle is Elev2 is much larger than the bright band range ΔR1 detected when the radar scan elevation angle is Elev1. From the above analysis, it can be seen that rectangles with smaller scales should be excluded, that is, the small-range echo is not a bright band.

[0216] (2) Determination condition 2: According to the experience of using weather radar, it can be determined that if the sum of the arcs of all rectangles reaches more than 150°, that is, when ∑Δθ≥150°, the target can be identified as a bright band without other conditions.

[0217] (3) Exclusion condition 1: During the comprehensive discrimination, it is observed that when the arc corresponding to the target: Δθ≤20°, the echo is too small to be a bright band echo.

[0218] (4) Exclusion condition 2: If the above conditions are met, the overall aspect ratio also needs to be analyzed. If it is roughly block-shaped rather than strip-shaped, it is not a bright band echo. Through comparative analysis, it is found that when L≤1.5W, it is not a bright band echo.

[0219] (5) Exclusion condition 3: If the width of the echo is small, that is, Δr≤20, it is not a bright band echo.

[0220] After excluding through the above conditions, the detected target rectangle can be determined as a bright band echo. In this example, from determination condition 1: In this example, the target is significantly broken and cannot be directly identified as the zero-degree layer bright band. From determination condition 2: The sum of the arcs of all rectangles that appear in this example is 212°, that is, ∑Δθ≥150°. Without other conditions, the target can be identified as a bright band echo.

[0221] In this embodiment, according to the comprehensive discrimination result after calculation, both of the two targets identified in this example are bright band echoes; the cloud base height of target 0 is 1283m, the cloud top height is 2101m, the thickness is 818m, the width is 1.06×10 4 m, and the length is 4.47×10 4 m; the cloud base height of target 1 is 1291m, the cloud top height is 2280m, the thickness is 989m, the width is 1.28×10 4 m, and the length is 4.47×10 4 m.

Claims

1. A method for automatically identifying the bright band of the zero-degree layer in a radar PPI image, characterized in that: The following steps are involved: S1. Read the radar image and divide the radar image into a radar PPI echo area image display area on the left and a radar related parameter information area on the right; S2. Based on the radar PPI echo area image display area, read the pixel points of the radar PPI echo area image, find the position of the plane rectangular coordinate origin, and based on the radar related parameter information area, respectively obtain the radar detection range, radar detection elevation angle and the strongest echo; S3, take the radar PPI echo with an intensity of 35-40 dBz as the target echo, compare the strongest echo with 40 dBz, and find the target echo in the radar PPI echo area; S4. For valid pixels whose pixel values ​​are not 0, convert the position (x, y) of the pixel point in the plane rectangular coordinate system to the position (θ, r) in the polar coordinate system, and map the angle θ and the distance coordinate r in the polar coordinate system as the x and y coordinates respectively to the plane rectangular coordinate system; S5, assigning a value to the pixel echo intensity according to the echo intensity sequence number of the color code corresponding to the pixel point, and determining the color code sequence number of the target echo; S6, stretching the radar PPI echo area image in the plane rectangular coordinate system converted in step S4 into a grayscale image, and marking the echo grayscale value of the read color code serial number; S7, assigning a target echo grayscale value of 255, assigning a pixel value of the remaining non-zero-degree layer bright bands to 0, and performing a 0, 1 binary processing on the grayscale image to obtain a target area to be identified; S8, keeping the radar PPI echo area image scale unchanged, and based on the target area to be identified, dilating and corroding the grayscale image after 0, 1 binary processing in the x(θ) direction in sequence; S9, according to the processing result of step S8, detect the contour of the target area to be identified, and fit the contour of each target echo respectively using the minimum circumscribed rectangle in the polar coordinate system, and according to the fitting result, determine whether there are two target echoes in the north, and the angle θ crosses 0°, if so, merge the two target echoes into the same target echo, and enter step S10, otherwise, directly enter step S10; S10, according to the acquired radar detection range and radar detection elevation angle, respectively calculating the distance between the radar and the target echo cloud top and cloud bottom; S11. Calculate the length and width of the target echo according to the distance between the radar and the cloud top and cloud bottom of the target echo, and determine whether the target echo is a bright band of the zero-degree layer according to the length and width of the target echo.

2. The method for automatically identifying the bright band of the zero-degree layer in the radar PPI image according to claim 1 is characterized in that: The expression of the plane rectangular coordinate origin in step S2 is as follows: Among them, (cx, cy) represents the origin of the plane rectangular coordinate system, imgw represents the pixel width of the radar PPI echo area image, and imgh represents the pixel height of the radar PPI echo area image.

3. The automatic identification method of the zero-degree layer bright band in the radar PPI image according to claim 2 is characterized in that: The step S4 comprises the following steps: S401, using (x, y) to represent the position of a pixel point in a plane rectangular coordinate system; S402, for valid pixels whose pixel values ​​are not 0, respectively calculating the distance r and the angle θ coordinates in the polar coordinate system according to the position (x, y) of the pixel point in the plane rectangular coordinates; S403 , mapping the angle θ and the distance r coordinates in the polar coordinate system to the plane rectangular coordinate system as x and y coordinates respectively.

4. The method for automatically identifying the bright band of the zero-degree layer in the radar PPI image according to claim 3 is characterized in that: The distance r is expressed as follows: The angle θ in the polar coordinate system is calculated according to the position (x, y) of the pixel point in the plane rectangular coordinate system, which is specifically: When x>cx and y<cy, the pixel point is northeast of the plane rectangular coordinate origin, and the angle θ is in the first quadrant: When x>cx and y>cy, the pixel is southeast of the plane rectangular coordinate origin, and the angle θ is in the second quadrant: When x<cx and y>cy, the pixel point is southwest of the plane rectangular coordinate origin, and the angle θ is in the third quadrant: When x<cx and y<cy, the pixel point is northwest of the plane rectangular coordinate origin, and the angle θ is in the fourth quadrant:

5. The automatic identification method of the zero-degree layer bright band in the radar PPI image according to claim 4 is characterized in that: The step S9 comprises the following steps: S901, according to the processing result of step S8, in the polar coordinate system, using the minimum circumscribed rectangle to take the two key points with the minimum angle and distance (θmin, rmin) and the minimum angle and distance (θmax, rmax) to detect the contour of the target area to be identified; S902, fitting the contour of each target echo based on two key points; S903. According to the fitting result, determine whether there are two target echoes in the north in the polar coordinates, and the angle θ crosses 0°. If so, merge the two target echoes into the same target echo and proceed to step S10. Otherwise, directly proceed to step S10.

6. The method for automatically identifying the bright band of the zero-degree layer in the radar PPI image according to claim 5 is characterized in that: The expression of the length of the target echo in step S11 is as follows: L=Δθ×Rt Where L represents the length of the target echo, Δθ represents the difference in angle θ between two points in polar coordinates, and Rt represents the distance between the radar and the top of the target echo cloud; The expression of the width of the target echo is as follows: W=Rtcosβ-Rbcosβ Where W represents the width of the target echo, β represents the radar detection elevation angle, and Rb represents the distance between the radar and the target echo cloud base.

7. The method for automatically identifying the bright band of the zero-degree layer in the radar PPI image according to claim 6 is characterized in that: In step S10, it is determined whether the target echo is a bright band of the zero-degree layer, which is specifically: A1. For the radar PPI echo area image, if a cross-rectangle of Δθ=360° appears, the target echo is a bright band at the zero-degree layer, where Δθ represents the difference between the length L of the target echo and the angle θ in the polar coordinates; A2. For the radar PPI echo area image, if ∑Δθ≥150° is satisfied, the target echo is a bright band at the zero-degree layer, where ∑Δθ represents the sum of the difference between the length L of all target echoes and the corresponding angle θ in the polar coordinates; A3. For the radar PPI echo area image, if Δθ≤20°, the target echo is a bright band in the non-zero-degree layer; A4. For radar PPI echo area image, if L≤1.5W, the target echo is a bright band in the non-zero-degree layer; A5. For the radar PPI echo area image, if Δr≤20, the target echo is a bright band in the non-zero-degree layer, where Δr represents the difference between the target echo width and the distance in the polar coordinates corresponding to W.

Images