Tornado Detection Cooperative Tracking Method

Abstract

The present invention discloses a collaborative tracking method for tornado detection, which relates to the technical field of electronic digital data processing. The collaborative tracking method for tornado detection includes the following steps: ultra-fine radar site evaluation; high-speed search radar site evaluation; channel signal evaluation; and drawing an occlusion area map. The present invention determines whether to perform collaborative tracking adjustment by obtaining the ultra-fine radar site evaluation value, then performs high-speed search radar site evaluation based on the obtained relevant data of the high-speed search radar site and determines whether to perform search accuracy adjustment, then determines whether to perform radar signal interference adjustment according to the obtained channel signal evaluation value, and finally draws an occlusion area map based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the relevant data of the channel signal, achieving the effect of improving the accuracy of collaborative tracking data for tornado detection and solving the problem of inaccurate collaborative tracking data for tornado detection in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and particularly to a tornado detection and collaborative tracking method. Background Art

[0002] A multi-beam dual-polarization phased array radar can transmit and receive multiple beams and has the dual-polarization ability, that is, it can receive echo signals of horizontal and vertical polarizations simultaneously. Since it can transmit and receive multiple beams simultaneously, the radar can complete the scanning of the target area in a shorter time. This means that when severe convective weather such as a tornado occurs, the radar can capture its dynamic changes faster, providing valuable time for early warning and tracking. The collaborative work of multiple beams enables the radar to cover a wider geographical area, reducing the detection blind area. This is particularly important for the detection of small-scale and rapidly changing weather phenomena such as tornadoes, because even a tiny spatial scale may contain important meteorological information. The multi-beam technology improves the scanning speed and coverage of the radar, making the detection of tornadoes more timely and accurate. The dual-polarization technology helps to distinguish different types of precipitation particles, improves the accuracy of precipitation estimation, and provides assistance for the identification of severe convective weather such as tornadoes.

[0003] Existing methods mainly calculate the speed and moving direction of a tornado by transmitting microwave beams, receiving the reflected microwave signals, and using the Doppler frequency shift phenomenon.

[0004] For example, an important weather recognition method and system based on a weather radar disclosed in the invention patent announcement with the publication number of CN116975716B includes: data acquisition: acquiring radar base data; important weather discrimination: identifying important weather by setting thresholds; important weather scanning: using RHI, narrow pulse, and unconventional elevation scanning methods to focus on scanning important weather; weather recognition, identifying the weather type based on the products obtained from the focused scanning.

[0005] For example, a multi-band weather radar data fusion method disclosed in the invention patent with the publication number of CN117332365A includes: Step 1, establishing a rain drop size distribution model with constraints; Step 2, establishing an inversion model for multi-band weather radar data; Step 3, meteorological monitoring; Step 4, correcting radar parameters; Step 5, converting multi-band radar parameter data, specifically: Step 5-1, selecting a set conversion band; Step 5-2, determining the rain drop size parameters of the band to be converted; Step 5-3, converting; Step 6, grid interpolation; Step 7, fusing.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0007] In the prior art, due to the obstruction of high-rise buildings and mountains, radar waves cannot effectively capture the core features and dynamic changes of tornadoes, resulting in difficulties in arranging radar stations and inaccurate data for collaborative tracking of tornado detection. Summary of the Invention

[0008] By providing a method for collaborative tracking of tornado detection in an embodiment of the present application, the problem of inaccurate data for collaborative tracking of tornado detection in the prior art is solved, and the accuracy of data for collaborative tracking of tornado detection is improved.

[0009] The embodiment of the present application provides a method for collaborative tracking of tornado detection, including the following steps: S1, based on the obtained relevant data of the ultra-fine radar station, perform an evaluation of the ultra-fine radar station to obtain an ultra-fine radar station evaluation value, and determine whether to perform collaborative tracking adjustment based on the ultra-fine radar station evaluation value. The ultra-fine radar station evaluation value is used to evaluate the accuracy of the ultra-fine radar in collaboratively tracking tornadoes; S2, based on the obtained relevant data of the high-speed search radar station, perform an evaluation of the high-speed search radar station to obtain a high-speed search radar station evaluation value, and determine whether to perform search accuracy adjustment based on the high-speed search radar station evaluation value. The high-speed search radar station evaluation value is used to evaluate the accuracy of the high-speed search radar in searching for tornadoes; S3, based on the ultra-fine radar station evaluation value after collaborative tracking adjustment, the high-speed search radar station evaluation value after search accuracy adjustment, and the channel signal relevant data, perform an evaluation of the radar receiving channel signal to obtain a channel signal evaluation value, and determine whether to perform radar signal interference adjustment based on the channel signal evaluation value. The channel signal evaluation value is used to evaluate the attenuation of the received signal intensity of the ultra-fine radar and the high-speed search radar; S4, draw an occlusion area map based on the relevant data of the ultra-fine radar station, the relevant data of the high-speed search radar station, and the relevant data of the channel signal.

[0010] Furthermore, the relevant data of the ultra-fine radar station includes the obstacle height, obstacle distance, first target distance, and target height; the relevant data of the high-speed search radar station includes the second target distance and the scanning angular velocity; the relevant data of the channel signal includes the first signal frequency and the second signal frequency; the first target distance represents the distance from the ultra-fine radar to the preset tornado monitoring point; the second target distance represents the distance from the high-speed search radar to the preset tornado monitoring point; the first signal frequency represents the signal frequency of the ultra-fine radar; the second signal frequency represents the signal frequency of the high-speed search radar.

[0011] Further, the specific process of obtaining the evaluation value of the ultra-fine radar site based on the acquired data related to the ultra-fine radar site is as follows: Calculate the compliance value of the ultra-fine radar occlusion angle by using the obstacle height, obstacle distance, and the first weight of the reference ultra-fine radar detection obtained from the database; Calculate the compliance value of the ultra-fine radar line-of-sight by using the first target distance, target height, and the second weight of the reference ultra-fine radar detection obtained from the database; Perform a ratio operation on the preset maximum radar occlusion value obtained from the database and the compliance value of the ultra-fine radar occlusion angle to obtain the radar occlusion compliance value; Perform a ratio operation on the compliance value of the ultra-fine radar line-of-sight and the preset maximum radar line-of-sight value obtained from the database to obtain the radar line-of-sight compliance value; Combine the radar occlusion compliance value and the radar line-of-sight compliance value to obtain the evaluation value of the ultra-fine radar site.

[0012] Further, the specific process of obtaining the evaluation value of the high-speed search radar site based on the acquired data related to the high-speed search radar site is as follows: Calculate the initial radar pitch angle through the target height and the second target distance; Perform a ratio operation on the initial radar pitch angle and the preset maximum radar pitch value obtained from the database to obtain the radar pitch compliance value; Perform a ratio operation on the scanning angular velocity and the preset maximum scanning angular velocity value obtained from the database to obtain the scanning angular velocity compliance value; Combine the radar pitch compliance value and the scanning angular velocity compliance value to obtain the evaluation value of the high-speed search radar site.

[0013] Further, the specific process of obtaining the evaluation value of the channel signal is as follows: Combine the compliance value of the ultra-fine radar loss and the compliance value of the high-speed search radar loss to obtain the evaluation value of the channel signal; The compliance value of the ultra-fine radar loss is represented by the result of a ratio operation on the initial ultra-fine radar loss value and the preset maximum ultra-fine radar loss value obtained from the database; The initial ultra-fine radar loss value is obtained by operating on the first signal frequency, the first target distance, and the speed of light obtained from the database; The compliance value of the high-speed search radar loss is represented by the result of a ratio operation on the initial high-speed search radar loss value and the preset maximum high-speed search radar loss value obtained from the database; The initial high-speed search radar loss value is obtained by operating on the second signal frequency, the second target distance, and the speed of light obtained from the database.

[0014] Further, the specific process of determining whether to perform collaborative tracking adjustment based on the ultra-fine radar site evaluation value is as follows: A1, determine whether the ultra-fine radar site evaluation value meets Condition 1. When the ultra-fine radar site evaluation value meets Condition 1, no collaborative tracking adjustment is performed; otherwise, execute A2; A2, perform pulse compression. When the monitored ultra-fine radar site evaluation value meets Condition 1, stop performing collaborative tracking adjustment; otherwise, execute A3; A3, perform phase encoding modulation. When the monitored ultra-fine radar site evaluation value meets Condition 1, stop performing collaborative tracking adjustment; otherwise, send an alarm prompt. Condition 1 means that the ultra-fine radar site evaluation value is not lower than the reference ultra-fine radar evaluation threshold obtained from the database.

[0015] Further, the limiting expression of the ultra-fine radar site evaluation value is as follows:

[0016] ;

[0017] In the formula, represents the ultra-fine radar site evaluation value of the ultra-fine radar at the r-th preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, represents the ultra-fine radar occlusion angle compliance value corresponding to the r-th preset time point of the ultra-fine radar, represents the ultra-fine radar line-of-sight compliance value corresponding to the r-th preset time point of the ultra-fine radar, represents the preset maximum radar occlusion value, represents the preset maximum radar line-of-sight value, and e represents the natural constant.

[0018] Further, the specific process of determining whether to perform search accuracy adjustment based on the high-speed search radar site evaluation value is as follows: B1, determine whether the high-speed search radar site evaluation value meets Condition 2. When the high-speed search radar site evaluation value meets Condition 2, no search accuracy adjustment is performed; otherwise, execute B2; B2, send a prompt to the preset personnel to change the waveform of the high-speed search radar. When the monitored high-speed search radar site evaluation value meets Condition 2, stop performing search accuracy adjustment; otherwise, execute B3; B3, perform coherent detection. When the monitored high-speed search radar site evaluation value meets Condition 2, stop performing search accuracy adjustment; otherwise, send an alarm prompt. Condition 2 means that the high-speed search radar site evaluation value is not lower than the reference high-speed search radar threshold obtained from the database.

[0019] Further, the specific process of determining whether to perform radar signal interference adjustment based on the channel signal evaluation value is as follows: C1, determine whether the channel signal evaluation value meets Condition 3. When the channel signal evaluation value meets Condition 3, no radar signal interference adjustment is performed; otherwise, execute C2; C2, send a prompt to a preset person to amplify the radio frequency signal. When the monitored channel signal evaluation value meets Condition 3, stop performing radar signal interference adjustment; otherwise, execute C3; C3, perform Doppler frequency shift compensation. When the monitored channel signal evaluation value meets Condition 3, stop performing radar signal interference adjustment; otherwise, send an alarm prompt; Condition 3 means that the channel signal evaluation value is not higher than the reference signal interference threshold obtained from the database.

[0020] Further, the specific process of drawing an occlusion area map based on the ultra-fine radar site-related data, high-speed search radar site-related data, and channel signal-related data is as follows: conduct a site clearance environment analysis; draw an occlusion area map in combination with the ultra-fine radar site-related data after collaborative tracking adjustment, the high-speed search radar site-related data after search accuracy adjustment, and the channel signal-related data after radar signal interference adjustment.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. By judging whether to perform collaborative tracking adjustment based on the obtained ultra-fine radar site evaluation value, then evaluating the high-speed search radar site based on the obtained high-speed search radar site-related data and judging whether to perform search accuracy adjustment, then judging whether to perform radar signal interference adjustment according to the obtained channel signal evaluation value, and finally drawing an occlusion area map based on the ultra-fine radar site-related data, high-speed search radar site-related data, and channel signal-related data, the dynamic adjustment of the radar monitoring site is realized, and further the improvement of the accuracy of tornado detection collaborative tracking data is realized, effectively solving the problem of inaccurate tornado detection collaborative tracking data in the prior art.

[0023] 2. By combining the radar occlusion compliance value and the radar line-of-sight compliance value to obtain the ultra-fine radar site evaluation value, then combining the radar pitch compliance value and the scanning angular velocity compliance value to obtain the high-speed search radar site evaluation value, and finally combining the ultra-fine radar loss compliance value and the high-speed search radar loss compliance value to obtain the channel signal evaluation value, the improvement of the accuracy of obtaining radar-related data is realized, and further the improvement of the reliability of radar collaborative detection is realized.

[0024] 3. By determining whether the evaluation value of the ultra-fine radar site meets Condition 1, when the evaluation value of the ultra-fine radar site meets Condition 1, no collaborative tracking adjustment is performed. Otherwise, pulse compression and phase coding modulation are performed, thereby realizing the dynamic adjustment of the ultra-fine radar for collaborative tracking of tornadoes, and further improving the accuracy of the ultra-fine radar for collaborative tracking of tornadoes. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flowchart of the tornado detection collaborative tracking method provided by an embodiment of the present application;

[0026] Figure 2 It is the overall flowchart provided by an embodiment of the present application;

[0027] Figure 3 It is a statistical chart of the change of the scanning angular velocity - scanning angular velocity compliance value provided by an embodiment of the present application;

[0028] Figure 4 It is an occlusion area map provided by an embodiment of the present application. Among them, Fig. (a) is a 1-kilometer equal beam height map, and Fig. (b) is a 3-kilometer equal beam height map. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The embodiment of the present application provides a tornado detection collaborative tracking method, which solves the problem of inaccurate data in tornado detection collaborative tracking in the prior art. The evaluation value of the ultra-fine radar site is obtained by obtaining the relevant data of the ultra-fine radar site for the evaluation of the ultra-fine radar site, and it is judged whether to perform collaborative tracking adjustment. Then, based on the obtained relevant data of the high-speed search radar site, the evaluation value of the high-speed search radar site is obtained for the evaluation of the high-speed search radar site, and it is judged whether to perform search accuracy adjustment. Then, according to the evaluation value of the ultra-fine radar site after collaborative tracking adjustment, the evaluation value of the high-speed search radar site after search accuracy adjustment, and the channel signal related data, the evaluation value of the radar receiving channel signal is obtained for the evaluation of the radar receiving channel signal, and it is judged whether to perform radar signal interference adjustment. Finally, based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the channel signal related data, an occlusion area map is drawn, realizing the improvement of the accuracy of tornado detection collaborative tracking data.

[0030] The technical solution in the embodiment of the present application is to solve the problem of inaccurate tornado detection collaborative tracking data. The overall idea is as follows:

[0031] Based on the obtained evaluation value of the ultra-fine radar site, it is determined whether to perform cooperative tracking adjustment. Then, based on the relevant data of the high-speed search radar site obtained, the high-speed search radar site is evaluated and it is determined whether to perform search accuracy adjustment. Next, based on the obtained channel signal evaluation value, it is determined whether to perform radar signal interference adjustment. Finally, an occlusion area map is drawn based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the relevant data of the channel signal, achieving the effect of improving the accuracy of tornado detection cooperative tracking data.

[0032] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0033] As Figure 1 shown, it is a flowchart of the tornado detection cooperative tracking method provided by an embodiment of the present application. The method includes the following steps: S1, ultra-fine radar site evaluation: Based on the relevant data of the obtained ultra-fine radar site, the ultra-fine radar site is evaluated to obtain an ultra-fine radar site evaluation value. Based on the ultra-fine radar site evaluation value, it is determined whether to perform cooperative tracking adjustment. The ultra-fine radar site evaluation value is used to evaluate the accuracy of the ultra-fine radar in cooperatively tracking tornadoes, and the occlusion adjustment is used to improve the accuracy of the ultra-fine radar in cooperative tracking; S2, high-speed search radar site evaluation: Based on the relevant data of the obtained high-speed search radar site, the high-speed search radar site is evaluated to obtain a high-speed search radar site evaluation value. Based on the high-speed search radar site evaluation value, it is determined whether to perform search accuracy adjustment. The high-speed search radar site evaluation value is used to evaluate the accuracy of the high-speed search radar in searching for tornadoes, and the search accuracy adjustment is used to improve the accuracy of the high-speed search radar in searching; S3, channel signal evaluation: According to the ultra-fine radar site evaluation value after performing cooperative tracking adjustment, the high-speed search radar site evaluation value after performing search accuracy adjustment, and the relevant data of the channel signal, the radar receiving channel signal is evaluated to obtain a channel signal evaluation value. Based on the channel signal evaluation value, it is determined whether to perform radar signal interference adjustment. The channel signal evaluation value is used to evaluate the attenuation of the signal intensities received by the ultra-fine radar and the high-speed search radar, and the radar signal interference adjustment is used to improve the accuracy of the signals received by the ultra-fine radar and the high-speed search radar; S4, draw an occlusion area map: Draw an occlusion area map based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the relevant data of the channel signal.

[0034] It should be added that the data related to the ultra-fine radar site includes the obstacle height, obstacle distance, first target distance, and target height; the data related to the high-speed search radar site includes the second target distance and scanning angular velocity; the data related to the channel signal includes the first signal frequency and the second signal frequency; the obstacle height represents the height of the preset obstacle detected by the ultra-fine radar; the obstacle distance represents the horizontal distance from the ultra-fine radar to the preset obstacle; the first target distance represents the distance from the ultra-fine radar to the preset tornado monitoring point; the target height represents the distance between the preset top center point of the preset target (tornado) and the corresponding point on the vertical ground; the second target distance represents the distance from the high-speed search radar to the preset tornado monitoring point; the scanning angular velocity represents the scanning angular velocity of the high-speed search radar; the first signal frequency represents the signal frequency of the ultra-fine radar; the second signal frequency represents the signal frequency of the high-speed search radar.

[0035] In this embodiment, the evaluation value of the ultra-fine radar site, the evaluation value of the high-speed search radar site, and the evaluation value of the channel signal affect each other. The accuracy of the ultra-fine radar site and the high-speed search radar site directly affects the quality of the channel signal. The lower the evaluation value of the ultra-fine radar site, the lower the accuracy of tracking, and collaborative tracking adjustment is required. The lower the evaluation value of the high-speed search radar site, the lower the accuracy of search, and search accuracy adjustment is required. Through mutual adjustment and optimization, the evaluation value of the ultra-fine radar site, the evaluation value of the high-speed search radar site, and the evaluation value of the channel signal can promote each other and jointly improve the overall performance of detecting and tracking the preset target (tornado), achieving an improvement in the accuracy of tornado detection collaborative tracking data.

[0036] It should be explained that at the preset time point, the obstacle height and obstacle distance of the preset obstacle are obtained by scanning the preset obstacle with the ultra-fine radar. The first target distance is obtained by locking the preset target monitoring point with the ultra-fine radar and measuring the distance from the ultra-fine radar to this monitoring point. The target height is obtained by locking the preset center point of the preset target with the ultra-fine radar or the high-speed search radar and measuring the distance from this point to the vertical ground. The second target distance is obtained by locking the preset target monitoring point with the high-speed search radar and measuring the distance from the high-speed search radar to this monitoring point. The scanning angular velocity corresponding to the high-speed search radar is measured by the high-speed search radar. The first signal frequency is measured by the ultra-fine radar. The second signal frequency is measured by the high-speed search radar.

[0037] Furthermore, the specific process of obtaining the evaluation value of the ultra-fine radar site based on the obtained data related to the ultra-fine radar site is as follows: Calculate the occlusion angle compliance value of the ultra-fine radar (i.e., in the limit expression of the evaluation value of the ultra-fine radar site) through the obstacle height, obstacle distance, and the first weight of the reference ultra-fine radar detection obtained from the database and (not zero); The hyperfine radar occlusion angle compliance value is used to reflect the occlusion situation of the preset obstacles of the hyperfine radar; The reference hyperfine radar detection first weight is used to reflect the influence degree of the radar occlusion angle on the hyperfine radar occlusion angle compliance value; The hyperfine radar line-of-sight compliance value (i.e., in the limit expression of the hyperfine radar site evaluation value) is calculated through the first target distance, the target height, and the reference hyperfine radar detection second weight obtained from the database. ); The hyperfine radar line-of-sight compliance value is used to reflect the detection distance situation of the hyperfine radar; The reference hyperfine radar detection second weight is used to reflect the influence degree of the radar line-of-sight on the hyperfine radar line-of-sight compliance value; The radar occlusion compliance value is obtained by performing a ratio operation on the preset radar occlusion maximum value obtained from the database and the hyperfine radar occlusion angle compliance value; The radar occlusion compliance value is used to reflect the compliance situation of the hyperfine radar occlusion angle compliance value; The radar line-of-sight compliance value is obtained by performing a ratio operation on the hyperfine radar line-of-sight compliance value and the preset radar line-of-sight maximum value obtained from the database; The radar line-of-sight compliance value is used to reflect the compliance situation of the hyperfine radar line-of-sight compliance value; The hyperfine radar site evaluation value is obtained by combining the radar occlusion compliance value and the radar line-of-sight compliance value.

[0038] Among them, the limit expression of the hyperfine radar site evaluation value is as follows:

[0039] ;

[0040] ;

[0041] ;

[0042] In the formula, represents the hyperfine radar site evaluation value of the hyperfine radar at the r-th preset time point, , r represents the number of the preset time point, m represents the total number of the preset time points, represents the hyperfine radar occlusion angle compliance value corresponding to the hyperfine radar at the r-th preset time point, represents the hyperfine radar line-of-sight compliance value corresponding to the hyperfine radar at the r-th preset time point, represents the obstacle height corresponding to the hyperfine radar at the r-th preset time point, represents the obstacle distance corresponding to the hyperfine radar at the r-th preset time point, represents the target height corresponding to the preset target at the r-th preset time point, represents the first target distance corresponding to the hyperfine radar at the r-th preset time point, represents the reference hyperfine radar detection first weight, represents the reference hyperfine radar detection second weight, Represents the maximum value of the preset radar occlusion, Represents the maximum value of the preset radar line-of-sight, and e represents the natural constant.

[0043] In this embodiment, the aforementioned database is a database established before the design of the tornado detection and cooperative tracking method provided in the embodiments of the present application for storing various setting data. The database includes but is not limited to signal frequency, target distance, obstacle height, etc. The various values therein are directly set by technicians. For example, the maximum value of the preset radar occlusion is represented by the maximum value of the ultra-fine radar occlusion angle compliance value in the historical time period in the database, and the maximum value of the preset radar line-of-sight is represented by the maximum value of the ultra-fine radar line-of-sight compliance value in the historical time period in the database.

[0044] Specifically, the first weight of the reference ultra-fine radar detection and the second weight of the reference ultra-fine radar detection respectively reflect the influence degree of the occlusion angle of the ultra-fine radar on the ultra-fine radar occlusion angle compliance value and the influence degree of the line-of-sight on the ultra-fine radar line-of-sight compliance value. A mapping set of the occlusion angle and line-of-sight of the ultra-fine radar and the corresponding weights is preset in the database. This mapping set reflects the mapping relationship between the occlusion angle and line-of-sight of the ultra-fine radar and the corresponding weights. For example, the occlusion angle and line-of-sight of the ultra-fine radar and the weights corresponding to the preset occlusion angle and line-of-sight of the ultra-fine radar in the database form a mapping set. The real-time occlusion angle and line-of-sight of the ultra-fine radar are input into the mapping set to obtain the weights corresponding to the occlusion angle and line-of-sight of the ultra-fine radar. The mapping relationship therein can be a one-to-one or many-to-one relationship, and the value range in this embodiment is 0-1.

[0045] It should be understood that the algorithm of this embodiment combines the relevant data analysis of the ultra-fine radar site to obtain the evaluation value of the ultra-fine radar site. The relevant data of the ultra-fine radar site in the algorithm of this embodiment do not exist independently and are mutually related. The obstacle height and obstacle distance may jointly affect the detection range and accuracy of the ultra-fine radar. The increase of the obstacle height, target height, and the first target distance does not necessarily lead to an increase in the evaluation value of the ultra-fine radar site. The influence of the obstacle distance should also be comprehensively considered. When the obstacle height and obstacle distance increase simultaneously, the interference of the obstacle to the ultra-fine radar detection may be greater, resulting in a significant decline in the detection performance of the ultra-fine radar. When the height of the obstacle is higher than the target height, the ultra-fine radar may not be able to accurately measure the target height because the obstacle will block or interfere with the reception of the radar beam. The detection performance of the ultra-fine radar may be greatly affected, resulting in a decrease in the evaluation value of the ultra-fine radar site. The closer the obstacle is to the ultra-fine radar, the more radar beams it may block, resulting in the ultra-fine radar being unable to accurately measure the first target distance. As the first target distance increases, the radar beam may be affected by more refraction and diffraction during the propagation process. This may lead to a greater deviation between the target position detected by the radar and the actual position, thereby causing a decrease in the evaluation value of the ultra-fine radar site. The parameters of the algorithm of this embodiment need to jointly consider the impact on the results. The accuracy of evaluating the collaborative tracking of tornadoes by the ultra-fine radar is accurately quantified; furthermore, the accuracy of the collaborative tracking data of tornado detection is improved.

[0046] Further, the specific process of obtaining the evaluation value of the high-speed search radar site based on the obtained relevant data of the high-speed search radar site is as follows: The initial radar pitch angle is obtained through the operation of the target height and the second target distance (the second target distance is not zero); the initial radar pitch angle is used to reflect the coverage range of the high-speed search radar; the radar pitch compliance value (i.e., in the limit expression of the evaluation value of the high-speed search radar site) is obtained through the ratio operation of the initial radar pitch angle and the preset maximum radar pitch angle obtained from the database; the radar pitch compliance value is used to reflect the compliance of the pitch angle of the high-speed search radar; the scan angular velocity compliance value (i.e., in the limit expression of the evaluation value of the high-speed search radar site) is obtained through the ratio operation of the scan angular velocity and the preset maximum scan angular velocity obtained from the database; the scan angular velocity compliance value is used to reflect the compliance of the pitch angle change rate of the high-speed search radar; the evaluation value of the high-speed search radar site is obtained by combining the radar pitch compliance value and the scan angular velocity compliance value.

[0047] Among them, the evaluation value of the high-speed search radar site is obtained by the following method:

[0048] ;

[0049] ;

[0050] ;

[0051] In the formula, represents the evaluation value of the high-speed search radar site at the r-th preset time point of the high-speed search radar, , r represents the number of the preset time point, and m represents the total number of preset time points, represents the radar pitch compliance value corresponding to the high-speed search radar at the r-th preset time point, represents the scan angular velocity compliance value corresponding to the high-speed search radar at the r-th preset time point, represents the target height corresponding to the preset target at the r-th preset time point, represents the second target distance corresponding to the high-speed search radar at the r-th preset time point, represents the scan angular velocity corresponding to the high-speed search radar at the r-th preset time point, represents the maximum preset radar pitch, represents the maximum preset scan angular velocity, and e represents the natural constant.

[0052] In this embodiment, the maximum preset radar pitch is represented by the maximum value of the high-speed search radar pitch angle in the historical time period in the database, and the maximum preset scan angular velocity is represented by the maximum value of the high-speed search radar scan angular velocity in the historical time period in the database.

[0053] It should be understood that the algorithm of this embodiment combines the analysis of the data related to the high-speed search radar site to obtain the evaluation value of the high-speed search radar site. The data related to the high-speed search radar site in the algorithm of this embodiment do not exist independently and are interrelated. The increase of the target height and the scan angular velocity does not necessarily lead to the increase of the evaluation value of the high-speed search radar site. The influence of the second target distance should also be comprehensively considered. When the second target distance increases, the detection range of the high-speed search radar expands accordingly, but this may also lead to the reduction of the resolution of the high-speed search radar. In order to maintain a certain resolution, the high-speed search radar may need to increase the scan angular velocity so as to cover a larger area in a shorter time. However, with the increase of the scan angular velocity, the residence time of the high-speed search radar on each target will be shortened, which may lead to the inability to fully accumulate the target echo signal, thus affecting the detection accuracy. When the signal of the high-speed search radar is weaker, if the target echo signal cannot be fully accumulated, then these signals may not be effectively detected, which will lead to the decrease of the detection ability of the radar on distant or low-reflectivity targets, which will directly affect the detection accuracy because weaker signals may not be effectively detected. The parameters of the algorithm of this embodiment need to jointly consider the influence on the result.

[0054] Specifically, assume that the scanning angular velocity ranges from 50 to 100 (radians / second), and the preset maximum scanning angular velocity is fixed at 100 (radians / second). As Figure 3 shown, it is a statistical chart of the change of the scanning angular velocity - scanning angular velocity compliance value provided by the embodiment of the present application. It can be seen from Figure 3 that as the scanning angular velocity gradually increases, the scanning angular velocity compliance value gradually increases, which means that the compliance of the pitch angle change rate of the high-speed search radar is gradually improved, realizing the precise quantification of the accuracy of evaluating the high-speed search radar for searching tornadoes; furthermore, the accuracy of the tornado detection collaborative tracking data is improved.

[0055] Further, the specific process of obtaining the channel signal evaluation value by evaluating the radar receiving channel signal according to the ultra-fine radar site evaluation value after collaborative tracking adjustment, the high-speed search radar site evaluation value after search accuracy adjustment, and the channel signal related data is as follows: Combine the ultra-fine radar loss compliance value (i.e., in the limit expression of the channel signal evaluation value) and the high-speed search radar loss compliance value (i.e., in the limit expression of the channel signal evaluation value) to obtain the channel signal evaluation value; the ultra-fine radar loss compliance value is represented by the result of the ratio operation of the initial ultra-fine radar loss value and the preset maximum ultra-fine radar loss value obtained from the database; the ultra-fine radar loss compliance value is used to reflect the compliance of the ultra-fine radar signal loss; the initial ultra-fine radar loss value is obtained by operating the first signal frequency, the first target distance, and the speed of light obtained from the database; the high-speed search radar loss compliance value is represented by the result of the ratio operation of the initial high-speed search radar loss value and the preset maximum high-speed search radar loss value obtained from the database; the high-speed search radar loss compliance value is used to reflect the compliance of the high-speed search radar signal loss; the initial high-speed search radar loss value is obtained by operating the second signal frequency, the second target distance, and the speed of light obtained from the database.

[0056] Among them, the channel signal evaluation value is obtained by the following method:

[0057] ;

[0058] ;

[0059] ;

[0060] In the formula, represents the channel signal evaluation value at the r-th preset time point, , r represents the number of the preset time point, and m represents the total number of the preset time points. represents the hyperfine radar loss compliance value at the r-th preset time point, represents the high-speed search radar loss compliance value at the r-th preset time point, represents the first signal frequency corresponding to the hyperfine radar at the r-th preset time point, represents the first target distance corresponding to the hyperfine radar after collaborative tracking adjustment at the r-th preset time point, represents the second signal frequency corresponding to the high-speed search radar at the r-th preset time point, represents the second target distance corresponding to the high-speed search radar after search accuracy adjustment at the r-th preset time point, represents the preset maximum hyperfine radar loss, represents the preset maximum high-speed search radar loss, c represents the speed of light, and e represents the natural constant.

[0061] In this embodiment, the preset maximum hyperfine radar loss is represented by the maximum value of the hyperfine radar loss in the historical time period in the database, and the preset maximum high-speed search radar loss is represented by the maximum value of the high-speed search radar loss in the historical time period in the database. c represents the speed of light, and in this embodiment, (m / s).

[0062] It should be understood that the algorithm in this embodiment combines the analysis of channel signal correlation data to obtain the channel signal evaluation value. The channel signal correlation data in the algorithm of this embodiment does not exist independently and has mutual relevance. When the first signal frequency and the second signal frequency increase, it does not necessarily lead to an increase in the channel signal evaluation value. The influence of the second target distance and the first target distance should also be comprehensively considered. The higher the first signal frequency and the second signal frequency, the farther the first target distance and the second target distance may be. The higher the frequency of the radar signal, the shorter its wavelength and the more concentrated its energy. However, the first signal frequency and the second signal frequency cannot increase infinitely because the higher the signal frequency, the greater the possibility of absorption and scattering during propagation in the air. As the first target distance and the second target distance increase, the signals of the hyperfine radar and the high-speed search radar will experience greater attenuation during propagation, resulting in a weakening of the signal intensity. The parameters of the algorithm in this embodiment need to jointly consider the influence on the results.

[0063] Specifically, assume that the hyperfine radar loss compliance value ranges from 0.1 to 0.6, and the high-speed search radar loss compliance value ranges from 0.1 to 0.6. As shown in Table 1, it is a statistical table of the changes in the channel signal evaluation value provided by the embodiment of the present application:

[0064] Table 1 Statistical table of changes in channel signal evaluation value

[0065]

[0066] As can be seen from the above table, as the compliance value of the ultra-fine radar loss and the compliance value of the high-speed search radar loss gradually increase, the channel signal evaluation value gradually increases, which means that the attenuation of the received signals by the ultra-fine radar and the high-speed search radar gradually intensifies, achieving a precise quantification of the accuracy of the high-speed search radar in searching for tornadoes; furthermore, it realizes the improvement of the accuracy of the tornado detection collaborative tracking data.

[0067] Furthermore, the specific process of judging whether to perform collaborative tracking adjustment based on the evaluation value of the ultra-fine radar site is as follows: A1, judge whether the evaluation value of the ultra-fine radar site meets Condition 1. When the evaluation value of the ultra-fine radar site meets Condition 1, no collaborative tracking adjustment is performed; otherwise, execute A2; A2, perform pulse compression. When the monitored evaluation value of the ultra-fine radar site meets Condition 1, stop performing collaborative tracking adjustment; otherwise, execute A3. Pulse compression means suppressing the multipath effect through the pulse compression method; A3, perform phase encoding modulation. When the monitored evaluation value of the ultra-fine radar site meets Condition 1, stop performing collaborative tracking adjustment; otherwise, send an alarm prompt. Phase encoding modulation means improving the range resolution of the ultra-fine radar through the phase encoding method; Condition 1 means that the evaluation value of the ultra-fine radar site is not lower than the reference ultra-fine radar evaluation threshold obtained from the database.

[0068] In this embodiment, the reference ultra-fine radar evaluation threshold is represented by the average value of the evaluation values of the ultra-fine radar sites in the historical time period in the database. In this embodiment, the linear frequency modulation pulse compression method is used to increase the time-bandwidth product of the radar signal to improve the range resolution, thereby reducing the influence of the multipath effect on the range measurement accuracy. The pulse compression method can form a narrowband signal from a broadband signal through matched filtering, thereby improving the resolution ability of the radar system. Phase encoding modulation is based on the phase modulation principle and carries more information by changing the phase of the signal. Phase encoding modulation can divide a wide pulse into many short sub-pulses and control the phases of these sub-pulses through coding. After these encoded sub-pulses are transmitted, a complex reflected signal will be formed at the target. When these reflected signals are received and processed by the radar receiver, the original phase information can be restored through decoding technology, which can improve the range resolution of the ultra-fine radar and realize the improvement of the accuracy of the tornado detection collaborative tracking data.

[0069] Further, the specific process of determining whether to adjust the search accuracy based on the evaluation value of the high-speed search radar site is as follows: B1, determine whether the evaluation value of the high-speed search radar site meets Condition 2. When the evaluation value of the high-speed search radar site meets Condition 2, no search accuracy adjustment is performed; otherwise, execute B2; B2, send a prompt to the preset personnel to change the waveform of the high-speed search radar. When the monitored evaluation value of the high-speed search radar site meets Condition 2, stop the search accuracy adjustment; otherwise, execute B3. The waveforms of the high-speed search radar include linear frequency modulation signals, phase-coded signals, etc.; B3, perform coherent detection. When the monitored evaluation value of the high-speed search radar site meets Condition 2, stop the search accuracy adjustment; otherwise, send an alarm prompt. Coherent detection means improving the detection ability of the high-speed search radar signal through the coherent detection method; Condition 2 means that the evaluation value of the high-speed search radar site is not lower than the reference high-speed search radar threshold obtained from the database.

[0070] In this embodiment, the reference high-speed search radar threshold is represented by the average value of the evaluation values of the high-speed search radar sites in the historical time period in the database. The phase-coded signal is a high-speed search radar waveform that carries information by changing the signal phase. It usually divides the signal into multiple sub-pulses and encodes the phase of each sub-pulse to form a complex high-speed search radar signal. Coherent detection extracts the information of the preset target (tornado) by comparing the coherence (such as phase difference, amplitude ratio, etc.) between the received echo signal and the known transmitted signal. The linear frequency modulation signal can achieve pulse compression at the receiving end through the matched filtering technique, thereby improving the signal-to-noise ratio and detection performance of the high-speed search radar signal, and improving the accuracy of the tornado detection collaborative tracking data.

[0071] Further, the specific process of determining whether to adjust the radar signal interference based on the evaluation value of the channel signal is as follows: C1, determine whether the evaluation value of the channel signal meets Condition 3. When the evaluation value of the channel signal meets Condition 3, no radar signal interference adjustment is performed; otherwise, execute C2; C2, send a prompt to the preset personnel to amplify the radio frequency signal. When the monitored evaluation value of the channel signal meets Condition 3, stop the radar signal interference adjustment; otherwise, execute C3. Radio frequency signal amplification means reducing the loss of signal reflection through a low-noise amplifier; C3, perform Doppler frequency shift compensation. When the monitored evaluation value of the channel signal meets Condition 3, stop the radar signal interference adjustment; otherwise, send an alarm prompt. Doppler frequency shift compensation is used to enhance the receiving sensitivity of the signal through the Doppler effect and adaptive filtering; Condition 3 means that the evaluation value of the channel signal is not higher than the reference signal interference threshold obtained from the database.

[0072] In this embodiment, the reference signal interference threshold is represented by the average value of the channel signal evaluation values in the historical time period in the database. The low-noise amplifier has the characteristics of high gain and low noise coefficient, and can more effectively amplify the signal and reduce the interference of noise. The low-noise amplifier can minimize the introduction of noise while amplifying the signal. The Doppler frequency shift compensation is used to correct the signal frequency change caused by the Doppler effect. The adaptive filter can dynamically adjust the parameters of the filter according to the characteristics of the input signal, further reducing the influence of noise and interference and enhancing the receiving sensitivity of the signal.

[0073] Furthermore, the specific process of drawing the occlusion area map based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the relevant data of the channel signal is as follows: Conduct a site clearance environment analysis, which means analyzing the site clearance environment through GIS (Geographic Information System) technology; Combine the relevant data of the ultra-fine radar site after collaborative tracking adjustment, the relevant data of the high-speed search radar site after search accuracy adjustment, and the relevant data of the channel signal after radar signal interference adjustment to draw the occlusion area map, and the occlusion area map includes the masking angle map and the equal beam height map.

[0074] In this embodiment, as Figure 4 shown, it is the occlusion area map provided by the embodiment of the present application. Among them, Figure (a) is the 1-kilometer equal beam height map, and Figure (b) is the 3-kilometer equal beam height map. Due to the obstruction of high-rise buildings and mountains, the key to radar layout is site selection and layout. For example, adopt the "4 + 1 + 1 + N" layout of "quadrilateral + center + mobile + auxiliary", that is, 4 refined radars at the four corners, 1 all-airspace high-speed search radar in the center, 1 mobile tracking radar, and several auxiliary devices such as microbarometers and lookout cameras. Use GIS technology to analyze the site clearance environment, combine the relevant data of the ultra-fine radar site after collaborative tracking adjustment, the relevant data of the high-speed search radar site after search accuracy adjustment, and the relevant data of the channel signal after radar signal interference adjustment, obtain the occlusion area through the digital elevation model, draw the equal beam height map, realize the visual display of the detection ability of the radar in all directions, and further realize the improvement of the accuracy of tornado detection collaborative tracking data.

[0075] In summary, in the embodiments of the present application, it is determined whether to perform collaborative tracking adjustment by using the obtained ultra-fine radar site evaluation value, then the high-speed search radar site is evaluated based on the obtained relevant data of the high-speed search radar site and it is determined whether to perform search accuracy adjustment. Next, it is determined whether to perform radar signal interference adjustment according to the obtained channel signal evaluation value. Finally, an occlusion area map is drawn based on the relevant data of the ultra-fine radar site, the relevant data of the high-speed search radar site, and the relevant data of the channel signal, thereby realizing the dynamic adjustment of the radar monitoring site, further improving the accuracy of the collaborative tracking data for tornado detection, and effectively solving the problem of inaccurate collaborative tracking data for tornado detection in the prior art.

[0076] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can be implemented in the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can be implemented in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0077] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0078] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide means for implementing the specified functions in the flowFigure 1 one process or multiple processes and / or blocks Figure 1 steps of functions specified in one block or multiple blocks

[0080] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A collaborative tracking method for tornado detection, characterized in that, Including the following steps: S1. Based on the obtained data related to the ultra-fine radar site, perform an evaluation of the ultra-fine radar site to obtain an ultra-fine radar site evaluation value. Determine whether to perform collaborative tracking adjustment based on the ultra-fine radar site evaluation value, and the ultra-fine radar site evaluation value is used to evaluate the accuracy of the ultra-fine radar in collaboratively tracking tornadoes; S2. Based on the obtained data related to the high-speed search radar site, perform an evaluation of the high-speed search radar site to obtain a high-speed search radar site evaluation value. Determine whether to perform search accuracy adjustment based on the high-speed search radar site evaluation value, and the high-speed search radar site evaluation value is used to evaluate the accuracy of the high-speed search radar in searching for tornadoes; S3. According to the ultra-fine radar site evaluation value after collaborative tracking adjustment, the high-speed search radar site evaluation value after search accuracy adjustment, and the channel signal related data, perform an evaluation of the radar receiving channel signal to obtain a channel signal evaluation value. Determine whether to perform radar signal interference adjustment based on the channel signal evaluation value, and the channel signal evaluation value is used to evaluate the attenuation of the received signal intensity of the ultra-fine radar and the high-speed search radar; S4. Draw an occlusion area map based on the ultra-fine radar site related data, the high-speed search radar site related data, and the channel signal related data; The specific process of performing an evaluation of the ultra-fine radar site based on the obtained ultra-fine radar site related data to obtain an ultra-fine radar site evaluation value is as follows: Calculate the ultra-fine radar occlusion angle compliance value by using the obstacle height, obstacle distance, and the first weight of the reference ultra-fine radar detection obtained from the database; Calculate the ultra-fine radar line-of-sight compliance value by using the first target distance, target height, and the second weight of the reference ultra-fine radar detection obtained from the database; Perform a ratio operation between the preset maximum radar occlusion value obtained from the database and the ultra-fine radar occlusion angle compliance value to obtain a radar occlusion compliance value; Perform a ratio operation between the ultra-fine radar line-of-sight compliance value and the preset maximum radar line-of-sight value obtained from the database to obtain a radar line-of-sight compliance value; Combine the radar occlusion compliance value and the radar line-of-sight compliance value to obtain the ultra-fine radar site evaluation value; The preset maximum radar occlusion value is represented by the maximum value of the ultra-fine radar occlusion angle compliance value in the historical time period in the database.

2. The tornado detection collaborative tracking method according to claim 1, wherein The ultra-fine radar site related data includes obstacle height, obstacle distance, first target distance, and target height; The high-speed search radar site related data includes second target distance and scanning angular velocity; The channel signal related data includes first signal frequency and second signal frequency; The first target distance represents the distance from the ultra-fine radar to the preset tornado monitoring point; The second target distance represents the distance from the high-speed search radar to the preset tornado monitoring point; The first signal frequency represents the signal frequency of the ultra-fine radar; The second signal frequency represents the signal frequency of the high-speed search radar.

3. The tornado detection collaborative tracking method according to claim 2, wherein The specific process of performing an evaluation of the high-speed search radar site based on the obtained high-speed search radar site related data to obtain a high-speed search radar site evaluation value is as follows: Calculate the initial radar pitch angle by operating on the target height and the second target distance; Obtain the radar pitch compliance value through ratio operation of the initial radar pitch angle and the preset maximum radar pitch value obtained from the database; Obtain the scanning angular velocity compliance value through ratio operation of the scanning angular velocity and the preset maximum scanning angular velocity value obtained from the database; Combine the radar pitch compliance value and the scanning angular velocity compliance value to obtain the high-speed search radar site evaluation value.

4. The tornado detection collaborative tracking method according to claim 2, characterized in that, The specific process of obtaining the channel signal evaluation value is as follows: Combine the ultra-fine radar loss compliance value and the high-speed search radar loss compliance value to obtain the channel signal evaluation value; The ultra-fine radar loss compliance value is represented by the result of ratio operation of the initial ultra-fine radar loss value and the preset maximum ultra-fine radar loss value obtained from the database; The initial ultra-fine radar loss value is obtained through operation of the first signal frequency, the first target distance, and the speed of light obtained from the database; The high-speed search radar loss compliance value is represented by the result of ratio operation of the initial high-speed search radar loss value and the preset maximum high-speed search radar loss value obtained from the database; The initial high-speed search radar loss value is obtained through operation of the second signal frequency, the second target distance, and the speed of light obtained from the database.

5. The tornado detection collaborative tracking method according to claim 1, characterized in that The specific process of determining whether to perform cooperative tracking adjustment based on the ultra-fine radar site evaluation value is as follows: A1. Determine whether the ultra-fine radar site evaluation value meets Condition 1. When the ultra-fine radar site evaluation value meets Condition 1, do not perform cooperative tracking adjustment. Otherwise, execute A2; A2. Perform pulse compression. When the monitored ultra-fine radar site evaluation value meets Condition 1, stop performing cooperative tracking adjustment. Otherwise, execute A3; A3. Perform phase encoding modulation. When the monitored ultra-fine radar site evaluation value meets Condition 1, stop performing cooperative tracking adjustment. Otherwise, send an alarm prompt; Condition 1 means that the ultra-fine radar site evaluation value is not lower than the reference ultra-fine radar evaluation threshold obtained from the database.

6. The tornado detection collaborative tracking method according to claim 5, wherein, The limit expression of the ultra-fine radar site evaluation value is as follows: ； In the formula, represents the evaluation value of the hyperfine radar site at the r-th preset time point, , where r represents the number of the preset time point, and m represents the total number of preset time points, represents the hyperfine radar occlusion angle compliance value corresponding to the r-th preset time point of the hyperfine radar, represents the hyperfine radar line-of-sight compliance value corresponding to the r-th preset time point of the hyperfine radar, represents the maximum preset radar occlusion value, represents the maximum preset radar line-of-sight value, and e represents the natural constant.

7. The tornado detection collaborative tracking method according to claim 3, wherein, The specific process of determining whether to perform search accuracy adjustment based on the high-speed search radar site evaluation value is as follows: B1. Determine whether the high-speed search radar site evaluation value meets Condition 2. When the high-speed search radar site evaluation value meets Condition 2, do not perform search accuracy adjustment. Otherwise, execute B2; B2. Send a prompt to the preset person to change the waveform of the high-speed search radar. When the monitored high-speed search radar site evaluation value meets Condition 2, stop performing search accuracy adjustment. Otherwise, execute B3; B3. Perform coherent detection. When the monitored high-speed search radar site evaluation value meets Condition 2, stop performing search accuracy adjustment. Otherwise, send an alarm prompt; Condition 2 means that the high-speed search radar site evaluation value is not lower than the reference high-speed search radar threshold obtained from the database.

8. The tornado detection collaborative tracking method according to claim 4, wherein, The specific process of determining whether to perform radar signal interference adjustment based on the channel signal evaluation value is as follows: C1. Determine whether the channel signal evaluation value meets Condition 3. When the channel signal evaluation value meets Condition 3, do not perform radar signal interference adjustment. Otherwise, execute C2; C2, Send a prompt to a preset person for RF signal amplification. When the evaluated value of the monitored channel signal meets Condition 3, stop the radar signal interference adjustment; otherwise, execute C3. C3, Perform Doppler frequency shift compensation. When the evaluated value of the monitored channel signal meets Condition 3, stop the radar signal interference adjustment; otherwise, send an alarm prompt. Condition 3 means that the evaluated value of the channel signal is not higher than the reference signal interference threshold obtained from the database.

9. The tornado detection collaborative tracking method according to claim 1, characterized in that, The specific process of drawing the occlusion area map based on the hyperfine radar site-related data, high-speed search radar site-related data, and channel signal-related data is as follows: Conduct a site clearance environment analysis. Draw the occlusion area map by combining the hyperfine radar site-related data after collaborative tracking adjustment, the high-speed search radar site-related data after search accuracy adjustment, and the channel signal-related data after radar signal interference adjustment.

Images