Speed-Assisted Thunderstorm Identification and Threat Assessment Method

Abstract

This invention provides a velocity-assisted thunderstorm identification and threat assessment method, comprising the following steps: Step 1, acquiring three-dimensional meteorological echo data from multiple elevation sectors starting at time t0; Step 2, calculating reflectivity and velocity deviation from the meteorological echo data from the multiple elevation sectors; Step 3, using a meteorological radar thunderstorm identification method to discriminate targets based on reflectivity, thereby obtaining characteristic parameters of multiple targets of interest; Step 4, identifying thunderstorms from the multiple targets of interest and acquiring multiple identified thunderstorms; Step 5, calculating the centroid shift and centroid velocity from the multiple identified thunderstorms to determine the degree of thunderstorm threat. This invention improves the accuracy and intuitiveness of thunderstorm identification by emitting a set of coherent electromagnetic pulses to obtain the velocity of raindrops in meteorological targets. Finally, the overall movement velocity of meteorological targets is extracted through displacement changes between trajectories, further assisting in meteorological threat assessment.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and specifically to a speed-assisted thunderstorm identification and threat assessment method. Background Technology

[0002] Aircraft are subject to various weather threats during flight, among which thunderstorms are widely recognized by the global aviation and meteorological communities as a serious threat to aviation safety. Thunderstorms can give rise to severe weather phenomena such as turbulence, wind shear, lightning, and hail, which threaten aviation safety and undergo different development stages over time, posing a significant impact and threat to aircraft flight.

[0003] Thunderstorms are three-dimensional meteorological targets that develop in space. Their development intensity, movement direction, and speed are closely related to the thermal and dynamic forces of the surrounding environment. Airborne weather radar can detect meteorological targets ahead of aircraft and calculate three-dimensional meteorological reflectivity intensity and meteorological speed information. Weather radar identifies thunderstorms as three-dimensional continuous areas with reflectivity exceeding a certain threshold and a certain volume, then displays and warns them, improving pilots' awareness of weather conditions ahead. Summary of the Invention

[0004] In view of this, the embodiments of this specification provide a speed-assisted thunderstorm identification and threat assessment method to improve the confidence level of thunderstorm identification results.

[0005] This specification provides the following technical solution in its embodiments: a speed-assisted thunderstorm identification and threat assessment method, comprising the following steps:

[0006] Step 1: Obtain stereo meteorological echo data of multiple pitch sectors starting from time t0;

[0007] Step 2: Calculate the reflectivity and motion velocity deviation of meteorological echo data from multiple pitch sectors;

[0008] Step 3: Use weather radar thunderstorm identification methods to determine the reflectivity of targets in order to obtain the characteristic parameters of multiple targets of interest;

[0009] Step 4: Identify thunderstorms for multiple targets of interest and acquire multiple identified thunderstorm data;

[0010] Step 5: Calculate the centroid offset and centroid velocity for multiple identified thunderstorms to determine the degree of thunderstorm threat.

[0011] Furthermore, step one includes:

[0012] Step 1.1: The airborne weather radar transmits a set of coherent electromagnetic pulses at the initial elevation angle and the initial azimuth angle, and receives weather echoes to obtain weather echo data at the initial elevation angle and the initial azimuth angle.

[0013] Step 1.2: Change the initial pitch angle by the first set angle and obtain the first meteorological echo data of the corresponding pitch sector; change the initial azimuth angle by the second set angle and obtain the second meteorological echo data of the corresponding pitch sector.

[0014] Step 1.3: Combine the first meteorological echo data with the second echo data to obtain the corresponding three-dimensional meteorological echo data of the elevation sector;

[0015] Step 1.4: Repeat steps 1.2 and 1.3 until three-dimensional meteorological echo data of multiple pitch sectors are obtained.

[0016] Further, step two specifically involves: calculating the reflectivity and velocity deviation of the three-dimensional meteorological echo data from multiple pitching fan surfaces to obtain the three-dimensional meteorological echo reflectivity data and raindrop velocity deviation values ​​from multiple pitching fan surfaces.

[0017] Furthermore, the meteorological radar thunderstorm identification method was used to identify targets from the three-dimensional meteorological echo reflectivity data of multiple pitch sectors, and the average values ​​of the volume, height, centroid position and velocity deviation of multiple targets of interest were obtained.

[0018] Furthermore, the method for calculating the mean value of the speed deviation is as follows: in, Let σ be the mean velocity deviation, K be the total number of conditions in which the three-dimensional meteorological echo reflectance data exceeds the reflectance threshold for heavy rainfall discrimination, and σ be the mean velocity deviation. k The velocity deviation value is the condition where the three-dimensional meteorological echo reflectance data is greater than the reflectance threshold for heavy rainfall detection.

[0019] Further, step four specifically includes: step 4.1, setting the volume threshold, height threshold, and speed deviation threshold;

[0020] Step 4.2: Compare the mean values ​​of volume, height, and velocity deviation for each target of interest with the volume threshold, height threshold, and velocity deviation threshold, respectively.

[0021] Step 4.3: When the volume of the target of interest is greater than the volume threshold, the height is greater than the height threshold, and the average velocity deviation is greater than the velocity deviation threshold, the target of interest is identified as the identified thunderstorm.

[0022] Step 4.4: Repeat steps 4.2 and 4.3 above until all targets of interest have completed thunderstorm identification, in order to obtain multiple identified thunderstorms.

[0023] Further, step five includes: step 5.1, performing centroid offset calculation, extracting feature parameters from the stereo weather echo data at time t1 for each identified thunderstorm, obtaining the centroid position of the corresponding identified thunderstorm at time t1, and calculating the position change of the corresponding identified thunderstorm between time t0 and time t1 based on the centroid position.

[0024] Furthermore, step five also includes step 5.2, calculating the velocity of the centroid. There is a time difference between time t0 and time t1. The velocity of the thunderstorm centroid is calculated based on the position change and the time difference.

[0025] Furthermore, step five also includes step 5.3, setting a speed threshold. When the speed of the thunderstorm centroid is greater than the speed threshold, the thunderstorm threat level is determined to be severe and an alarm signal is generated; when the speed of the thunderstorm centroid is less than the speed threshold, the thunderstorm threat level is determined to be moderate and the thunderstorm is tracked at all times.

[0026] Compared with existing technologies, the beneficial effects achieved by at least one of the above-mentioned technical solutions adopted in the embodiments of this specification include at least the following: This invention improves the accuracy and intuitiveness of thunderstorm identification by emitting a set of coherent electromagnetic wave pulses to obtain the movement velocity of raindrops in meteorological targets. Finally, it extracts the overall movement velocity of meteorological targets through displacement changes between trajectories, further assisting in meteorological threat assessment. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating an embodiment of the present invention; Detailed Implementation

[0029] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0030] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0031] like Figure 1 As shown, this embodiment of the invention provides a speed-assisted thunderstorm identification and threat assessment method, including the following steps:

[0032] Step 1: Obtain stereo meteorological echo data of multiple pitch sectors starting from time t0;

[0033] Step 2: Calculate the reflectivity and motion velocity deviation of meteorological echo data from multiple pitch sectors;

[0034] Step 3: Use weather radar thunderstorm identification methods to determine the reflectivity of targets in order to obtain the characteristic parameters of multiple targets of interest;

[0035] Step 4: Identify thunderstorms for multiple targets of interest and acquire multiple identified thunderstorm data;

[0036] Step 5: Calculate the centroid offset and centroid velocity for multiple identified thunderstorms to determine the degree of thunderstorm threat.

[0037] This invention improves the accuracy and intuitiveness of thunderstorm identification by emitting a set of coherent electromagnetic pulses to obtain the velocity of raindrops within meteorological targets. Finally, it extracts the overall movement velocity of meteorological targets by analyzing displacement changes between trajectories, further assisting in meteorological threat assessment.

[0038] Step one includes:

[0039] Step 1.1: The airborne weather radar transmits a set of coherent electromagnetic pulses at the initial elevation angle and the initial azimuth angle, and receives weather echoes to obtain weather echo data at the initial elevation angle and the initial azimuth angle.

[0040] Step 1.2: Change the initial pitch angle by the first set angle and obtain the first meteorological echo data of the corresponding pitch sector; change the initial azimuth angle by the second set angle and obtain the second meteorological echo data of the corresponding pitch sector.

[0041] Step 1.3: Combine the first meteorological echo data with the second echo data to obtain the corresponding three-dimensional meteorological echo data of the elevation sector;

[0042] Step 1.4: Repeat steps 1.2 and 1.3 until three-dimensional meteorological echo data of multiple pitch sectors are obtained.

[0043] Step two specifically involves calculating the reflectivity and velocity deviation of the three-dimensional meteorological echo data from multiple pitch sectors, resulting in three-dimensional meteorological echo reflectivity data and raindrop velocity deviation values ​​for multiple pitch sectors.

[0044] Step 3 specifically involves using the meteorological radar thunderstorm identification method to identify targets from the three-dimensional meteorological echo reflectivity data of multiple pitch sectors, and obtaining the average values ​​of the volume, height, centroid position, and velocity deviation of multiple targets of interest.

[0045] Furthermore, the method for calculating the mean value of the speed deviation in step three is as follows: in, Let σ be the mean velocity deviation, K be the total number of conditions in which the three-dimensional meteorological echo reflectance data exceeds the reflectance threshold for heavy rainfall discrimination, and σ be the mean velocity deviation. k The velocity deviation value is the condition where the three-dimensional meteorological echo reflectance data is greater than the reflectance threshold for heavy rainfall detection.

[0046] Step four specifically involves: Step 4.1, setting the volume threshold, height threshold, and speed deviation threshold;

[0047] Step 4.2: Compare the mean values ​​of volume, height, and velocity deviation for each target of interest with the volume threshold, height threshold, and velocity deviation threshold, respectively.

[0048] Step 4.3: When the volume of the target of interest is greater than the volume threshold, the height is greater than the height threshold, and the average velocity deviation is greater than the velocity deviation threshold, the target of interest is identified as the identified thunderstorm.

[0049] Step 4.4: Repeat steps 4.2 and 4.3 above until all targets of interest have completed thunderstorm identification, in order to obtain multiple identified thunderstorms.

[0050] Step 5 includes: Step 5.1, performing centroid offset calculation, extracting feature parameters from the stereo weather echo data at time t1 for each identified thunderstorm, obtaining the centroid position of the corresponding identified thunderstorm at time t1, and calculating the position change of the corresponding identified thunderstorm between time t0 and time t1 based on the centroid position.

[0051] Step 5.2: Calculate the velocity of the center of mass. There is a time difference between time t0 and time t1. Calculate the velocity of the thunderstorm's center of mass based on the position change and the time difference.

[0052] Step 5.3: Set a speed threshold. When the speed of the thunderstorm centroid is greater than the speed threshold, the thunderstorm threat level is determined to be severe and an alarm signal is generated. When the speed of the thunderstorm centroid is less than the speed threshold, the thunderstorm threat level is determined to be moderate and the thunderstorm is tracked at all times.

[0053] Specific application examples of the embodiments of the present invention are as follows:

[0054] 1. Echo data acquisition from time t0: Airborne weather radar at elevation angle θ el = 0 degrees (positive at the top, negative at the bottom), azimuth θ az A set of Na coherent electromagnetic pulses is emitted at an angle of -90 degrees (positive on the right, negative on the left), where 4 ≤ Na ≤ 128, and meteorological echoes are received to obtain the data WXdata(n) for that angle. a ,n r ), where n a = (1,...,Na) represents the number of coherent pulses, nr = (1,...,Nr) represents the number of distance points, changing the azimuth angle θ az =θ az +igΔθ az Where i = (1,...,N) z ),Δθ az =0.5 degrees, to obtain echo data of an elevation sector covering ±90 degrees in azimuth angle, then change the elevation angle θ el =θ el +j·Δθ el , where j = (1,...,N) e ), Δθ el =0.5°, and obtained stereo echo data of multiple pitch sectors.

[0055] 2. Reflectivity and velocity deviation calculation: The reflectivity of meteorological echo data from multiple elevation sectors is calculated using the meteorological radar equations to obtain three-dimensional meteorological echo reflectivity data Z(n). r ,θ az ,θ el The velocity deviation is calculated using the phase relationship between Na coherent pulses, yielding the cloud droplet velocity distribution deviation value σ(n) at each distance point. r ,θ az ,θ el ).

[0056] 3. Feature Parameter Extraction and Volume Target Discrimination: Using conventional meteorological radar thunderstorm identification methods, volume target discrimination is performed on N three-dimensional reflectivity data points to obtain the feature parameters of each volume target: volume V n Height H n Centroid Position POS n =(R n ,θ az_n ,θ el_n ), and the newly added characteristic parameter in this method: mean velocity deviation. This represents the mean velocity deviation at locations where the reflectivity of a volumetric target exceeds a threshold. Where n = (1,...,N) represents the number of volumetric targets, and R... n θ represents the distance from the center of mass of the nth individual target to the aircraft. az_n θ represents the azimuth angle with the radar. el_n Indicates the elevation angle relative to the radar.

[0057] in The calculation method is as follows:

[0058] 1) According to the distance point n r Azimuth θ az and pitch angle θ el The increasing order is for reflectivity Z(n) r,θ az ,θ el Perform a full matrix traversal and judgment to obtain Z(n) r ,θ az ,θ el )>Z thre σ at the corresponding position k , k=(1,...K), Z thre Z is taken as the reflectance threshold for heavy rainfall detection. thre =35, K is the value that satisfies Z(n) r ,θ az ,θ el )>Z thre Total number of conditions;

[0059] 2)

[0060] 4. Thunderstorm Identification: Identify the nth individual target as a thunderstorm, where n = (1, ..., N), e.g., volume V. n Exceeding the volume threshold V thre =40km 3 And height H n Exceeding the height threshold H thre =6km, and Exceeding the speed deviation threshold σ thre =7m / s, then the target body is identified as thunderstorm S. n .

[0061] 5. Centroid shift calculation: Extract feature parameters from the data at the next time step t1 = t + Δt of the nth thunderstorm to obtain the centroid POS' at the next time step t1. n =(R n ',θ' az_n ,θ' el_n The position change ΔR between two time points is calculated based on the shift in the centroid position. n .

[0062] 6. Calculation of the velocity of the center of mass: Based on the time difference Δt = t1 - t0 between the displacement of the center of mass and times t0 and t1, the velocity V of the thunderstorm's center of mass can be calculated. n =ΔR n / Δt.

[0063] 7. Threat level assessment: such as the velocity V of the thunderstorm's centroid. s Exceeding the speed threshold V s-thre If the speed is 7 m / s, the thunderstorm is classified as a "severe" threat level; if it is below the threshold, it is classified as a "moderate" threat level.

[0064] The above description is merely a specific embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any substitution of equivalent components or equivalent changes and modifications made within the scope of protection of this patent should still fall within the scope of this patent. Furthermore, the technical features, technical features and technical solutions, and technical solutions in this invention can be freely combined and used.

Claims

1. A speed-assisted thunderstorm identification and threat assessment method, characterized in that, Includes the following steps: Step 1: Obtain stereo meteorological echo data of multiple pitch sectors starting from time t0; Step 2: Calculate the reflectivity and motion velocity deviation of meteorological echo data from multiple pitch sectors; Step 3: Use weather radar thunderstorm identification methods to determine the reflectivity of targets in order to obtain the characteristic parameters of multiple targets of interest; Step 4: Identify thunderstorms for multiple targets of interest and acquire multiple identified thunderstorm data; Step 5: Calculate the centroid offset and centroid velocity for multiple identified thunderstorms to determine the degree of thunderstorm threat. The meteorological radar thunderstorm identification method was used to identify targets from the three-dimensional meteorological echo reflectivity data of multiple pitch sectors, and the mean value, volume value, height value and centroid position of multiple targets of interest were obtained. The method for calculating the mean of speed deviation is as follows: ,in, Let K be the mean velocity deviation, and K be the total number of conditions in which the three-dimensional meteorological echo reflectance data exceeds the reflectance threshold for heavy rainfall identification. The velocity deviation value is the condition where the three-dimensional meteorological echo reflectance data is greater than the reflectance threshold for heavy rainfall identification. The fourth step specifically includes: Step 4.1, setting the volume threshold, height threshold, and speed deviation threshold; Step 4.2: Compare the mean values ​​of volume, height, and velocity deviation for each target of interest with the volume threshold, height threshold, and velocity deviation threshold, respectively. Step 4.3: When the volume of the target of interest is greater than the volume threshold, the height is greater than the height threshold, and the average velocity deviation is greater than the velocity deviation threshold, the target of interest is identified as the identified thunderstorm. Step 4.4: Repeat steps 4.2 and 4.3 above until all targets of interest have completed thunderstorm identification, in order to obtain multiple identified thunderstorms.

2. The speed-assisted thunderstorm identification and threat assessment method according to claim 1, characterized in that, Step one includes: Step 1.1: The airborne weather radar transmits a set of coherent electromagnetic pulses at the initial elevation angle and the initial azimuth angle, and receives weather echoes to obtain weather echo data at the initial elevation angle and the initial azimuth angle. Step 1.2: Change the initial pitch angle by the first set angle and obtain the first meteorological echo data of the corresponding pitch sector; change the initial azimuth angle by the second set angle and obtain the second meteorological echo data of the corresponding pitch sector. Step 1.3: Combine the first meteorological echo data with the second echo data to obtain the corresponding three-dimensional meteorological echo data of the elevation sector; Step 1.4: Repeat steps 1.2 and 1.3 until three-dimensional meteorological echo data of multiple pitch sectors are obtained.

3. The speed-assisted thunderstorm identification and threat assessment method according to claim 2, characterized in that, Step two specifically involves: calculating the reflectivity and velocity deviation of the three-dimensional meteorological echo data from multiple pitch sectors, resulting in three-dimensional meteorological echo reflectivity data and raindrop velocity deviation values ​​for multiple pitch sectors.

4. The method for thunderstorm identification and threat assessment based on speed assistance according to claim 1, characterized in that, Step 5 includes: Step 5.1, performing centroid offset calculation, extracting feature parameters from the stereo weather echo data at time t1 of each identified thunderstorm, obtaining the centroid position of the corresponding identified thunderstorm at time t1, and calculating the position change of the corresponding identified thunderstorm between time t0 and time t1 based on the centroid position.

5. The speed-assisted thunderstorm identification and threat assessment method according to claim 4, characterized in that, Step 5 also includes step 5.2, calculating the velocity of the centroid. There is a time difference between time t0 and time t1. The velocity of the thunderstorm centroid is calculated based on the position change and the time difference.

6. The method for thunderstorm identification and threat assessment based on velocity assistance according to claim 5, characterized in that, Step 5 also includes step 5.3: setting a speed threshold. When the speed of the thunderstorm centroid is greater than the speed threshold, the thunderstorm threat level is determined to be severe and an alarm signal is generated. When the speed of the thunderstorm centroid is less than the speed threshold, the thunderstorm threat level is determined to be moderate and the thunderstorm is tracked at all times.

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