Tornado detection cooperative tracking method

Abstract

The invention discloses a tornado detection cooperative tracking method, and relates to the technical field of electric digital data processing. The tornado detection cooperative tracking method comprises the following steps: evaluating a hyperfine radar station; evaluating a high-speed search radar station; channel signal evaluation; and drawing an occlusion area map. According to the method, whether collaborative tracking adjustment is carried out or not is judged through the obtained hyperfine radar station evaluation value, then high-speed search radar station evaluation is carried out based on the obtained high-speed search radar station related data, and whether search accuracy adjustment is carried out or not is judged; whether radar signal interference adjustment is carried out or not is judged according to the obtained channel signal evaluation value, finally, a shielding area graph is drawn based on hyperfine radar station related data, high-speed search radar station related data and channel signal related data, and the effect of improving the accuracy of tornado detection cooperative tracking data is achieved. The problem of inaccurate tornado detection cooperative tracking data in the prior art is solved.

Description

Technical Field

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

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

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

[0004] For example, the invention patent with announcement number: CN116975716B announces an important weather identification method and system based on weather radar, including: 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 perform key scanning on important weather; weather identification, identifying the weather type based on the products obtained from the key scanning.

[0005] For example, the invention patent with publication number: CN117332365A discloses a multi-band weather radar data fusion method, including: step 1, establishing a constrained raindrop spectrum distribution model; step 2, establishing a multi-band weather radar data inversion model; step 3, meteorological monitoring; step 4, correcting radar parameters; step 5, multi-band radar parameter data conversion, specifically: step 5-1, selecting and setting the conversion band; step 5-2, determining the raindrop spectrum parameters of the band to be converted; step 5-3, conversion; step 6, grid interpolation; step 7, fusion.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the existing technology, due to obstruction by high-rise buildings and mountains, radar waves cannot effectively capture the core characteristics and dynamic changes of tornadoes, making it difficult to deploy radar sites and leading to inaccurate tornado detection and collaborative tracking data. Summary of the invention

[0007] The embodiments of the present application solve the problem of inaccurate tornado detection collaborative tracking data in the prior art by providing a tornado detection collaborative tracking method, thereby improving the accuracy of tornado detection collaborative tracking data.

[0008] The embodiment of the present application provides a tornado detection collaborative tracking method, comprising the following steps: S1, based on the acquired ultra-fine radar site related data, performing an ultra-fine radar site evaluation to obtain an ultra-fine radar site evaluation value, judging whether to perform collaborative tracking adjustment based on the ultra-fine radar site evaluation value, the ultra-fine radar site evaluation value is used to evaluate the accuracy of the ultra-fine radar collaborative tracking of tornadoes; S2, based on the acquired high-speed search radar site related data, performing a high-speed search radar site evaluation to obtain a high-speed search radar site evaluation value, judging whether to perform a search accuracy adjustment based on the high-speed search radar site evaluation value, the high-speed search radar site evaluation value is used to evaluate the accuracy of the high-speed search radar searching for tornadoes; S3, performing a radar receiving channel signal evaluation to obtain a channel signal evaluation value based on the ultra-fine radar site evaluation value after the collaborative tracking adjustment, the high-speed search radar site evaluation value after the search accuracy adjustment, and the channel signal related data, judging whether to perform a 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 strength of the ultra-fine radar and the high-speed search radar; S4, drawing 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.

[0009] Furthermore, the ultra-fine radar site-related data include obstacle height, obstacle distance, first target distance and target height; the high-speed search radar site-related data include second target distance and scanning angular velocity; the channel signal-related data include a first signal frequency and a second signal frequency; the first target distance represents the distance from the ultra-fine radar to a preset tornado monitoring point; the second target distance represents the distance from the high-speed search radar to a preset tornado monitoring point; the first signal frequency represents the signal frequency of the ultra-fine radar; and the second signal frequency represents the signal frequency of the high-speed search radar.

[0010] Furthermore, the specific process of performing ultra-fine radar site evaluation based on the acquired ultra-fine radar site related data to obtain an ultra-fine radar site evaluation value is as follows: obtaining an ultra-fine radar obscuration angle compliance value by calculating through obstacle height, obstacle distance and a first weight of a reference ultra-fine radar detection obtained from a database; obtaining an ultra-fine radar sight range compliance value by calculating through a first target distance, target height and a second weight of a reference ultra-fine radar detection obtained from a database; obtaining an radar obscuration compliance value by performing a ratio operation between a preset radar obscuration maximum value obtained from a database and the ultra-fine radar obscuration angle compliance value; obtaining an radar sight range compliance value by performing a ratio operation between an ultra-fine radar sight range compliance value and a preset radar sight range maximum value obtained from a database; and obtaining an ultra-fine radar site evaluation value by combining the radar obscuration compliance value and the radar sight range compliance value.

[0011] Furthermore, the specific process of performing high-speed search radar site evaluation based on the acquired high-speed search radar site related data to obtain a high-speed search radar site evaluation value is as follows: obtaining an initial radar pitch angle by calculating the target height and the second target distance; obtaining a radar pitch compliance value by performing a ratio operation between the initial radar pitch angle and a preset radar pitch maximum value obtained from a database; obtaining a scanning angular velocity compliance value by performing a ratio operation between the scanning angular velocity and a preset scanning angular velocity maximum value obtained from a database; and obtaining a high-speed search radar site evaluation value by combining the radar pitch compliance value and the scanning angular velocity compliance value.

[0012] Furthermore, the specific acquisition process of the channel signal evaluation value is as follows: the channel signal evaluation value is obtained by combining the hyperfine radar loss compliance value and the high-speed search radar loss compliance value; the hyperfine radar loss compliance value is represented by the result of a ratio operation between the initial hyperfine radar loss value and a preset hyperfine radar loss maximum value obtained from a database; the initial hyperfine radar loss value is obtained by calculating 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 a ratio operation between the initial high-speed search radar loss value and the preset high-speed search radar loss maximum value obtained from the database; the initial high-speed search radar loss value is obtained by calculating the second signal frequency, the second target distance and the speed of light obtained from the database.

[0013] Furthermore, the specific process of judging whether to perform collaborative tracking adjustment based on the hyperfine radar site evaluation value is as follows: A1, judging whether the hyperfine radar site evaluation value meets condition one. When the hyperfine radar site evaluation value meets condition one, no collaborative tracking adjustment is performed, otherwise A2 is executed; A2, performing pulse compression, when the monitored hyperfine radar site evaluation value meets condition one, the collaborative tracking adjustment is stopped, otherwise A3 is executed; A3, performing phase coding modulation, when the monitored hyperfine radar site evaluation value meets condition one, the collaborative tracking adjustment is stopped, otherwise an alarm is sent; the condition one indicates that the hyperfine radar site evaluation value is not lower than the reference hyperfine radar evaluation threshold obtained from the database.

[0014] Furthermore, the limiting expression of the ultra-fine radar site evaluation value is as follows: ; In the formula, represents the hyperfine radar site evaluation value at the rth preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, It represents the super-fine radar shielding angle compliance value corresponding to the super-fine radar at the rth preset time point, It represents the hyperfine radar sight range compliance value corresponding to the hyperfine radar at the rth preset time point, Indicates the preset radar shielding maximum value. It represents the preset maximum value of radar sight range, and e represents a natural constant.

[0015] Furthermore, the specific process of judging whether to adjust the search accuracy based on the high-speed search radar site evaluation value is as follows: B1, judging whether the high-speed search radar site evaluation value meets condition two. When the high-speed search radar site evaluation value meets condition two, no search accuracy adjustment is performed, otherwise B2 is executed; B2, sending 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 two, the search accuracy adjustment is stopped, otherwise B3 is executed; B3, performing coherent detection, when the monitored high-speed search radar site evaluation value meets condition two, the search accuracy adjustment is stopped, otherwise an alarm prompt is sent; the condition two indicates that the high-speed search radar site evaluation value is not lower than the reference high-speed search radar threshold obtained from the database.

[0016] Furthermore, the specific process of judging whether to perform radar signal interference adjustment based on the channel signal evaluation value is as follows: C1, judging whether the channel signal evaluation value meets condition three. When the channel signal evaluation value meets condition three, no radar signal interference adjustment is performed, otherwise C2 is executed; C2, sending a prompt to the preset personnel to amplify the RF signal. When the monitored channel signal evaluation value meets condition three, the radar signal interference adjustment is stopped, otherwise C3 is executed; C3, performing Doppler frequency shift compensation. When the monitored channel signal evaluation value meets condition three, the radar signal interference adjustment is stopped, otherwise an alarm prompt is sent; the condition three indicates that the channel signal evaluation value is not higher than the reference signal interference threshold obtained from the database.

[0017] Furthermore, the specific process of drawing the obstruction 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 is as follows: conduct site clearance environment analysis; draw the obstruction 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.

[0018] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Determine whether to make collaborative tracking adjustments based on the obtained ultra-fine radar site evaluation values, then perform high-speed search radar site evaluation based on the obtained high-speed search radar site related data and determine whether to make search accuracy adjustments, then determine whether to make radar signal interference adjustments based on the obtained channel signal evaluation values, and finally 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, thereby realizing dynamic adjustment of radar monitoring sites, and further realizing the improvement of the accuracy of tornado detection collaborative tracking data, effectively solving the problem of inaccurate tornado detection collaborative tracking data in the prior art.

[0019] 2. The ultra-fine radar site evaluation value is obtained by combining the radar obstruction compliance value and the radar line of sight compliance value, and then the high-speed search radar site evaluation value is obtained by combining the radar pitch compliance value and the scanning angular velocity compliance value. Finally, the channel signal evaluation value is obtained by combining the ultra-fine radar loss compliance value and the high-speed search radar loss compliance value, thereby improving the accuracy of obtaining radar-related data and further improving the reliability of radar collaborative detection.

[0020] 3. By judging whether the evaluation value of the ultra-fine radar site meets condition one, when the evaluation value of the ultra-fine radar site meets condition one, no collaborative tracking adjustment is performed, instead pulse compression and phase coding modulation are performed, thereby achieving dynamic adjustment of the ultra-fine radar collaborative tracking of tornadoes, and further improving the accuracy of the ultra-fine radar collaborative tracking of tornadoes. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flow chart of a tornado detection and collaborative tracking method provided in an embodiment of the present application; Figure 2 An overall flow chart provided for the embodiments of the present application; Figure 3 A statistical diagram of changes in scanning angular velocity-scanning angular velocity compliance value provided in an embodiment of the present application; Figure 4 The occlusion area map provided in the embodiment of the present application, wherein Figure (a) is a 1 km equal beam height map, and Figure (b) is a 3 km equal beam height map. DETAILED DESCRIPTION

[0022] The embodiment of the present application solves the problem of inaccurate tornado detection collaborative tracking data in the prior art by providing a tornado detection collaborative tracking method. An ultra-fine radar site evaluation is performed based on the acquired ultra-fine radar site related data to obtain an ultra-fine radar site evaluation value and determine whether to perform collaborative tracking adjustment. Then, a high-speed search radar site evaluation is performed based on the acquired high-speed search radar site related data to obtain a high-speed search radar site evaluation value and determine whether to perform search accuracy adjustment. Subsequently, a radar receiving channel signal is evaluated based on the ultra-fine radar site evaluation value after collaborative tracking adjustment, the high-speed search radar site evaluation value after search accuracy adjustment and channel signal related data to obtain a channel signal evaluation value and determine whether to perform radar signal interference adjustment. Finally, an occlusion area map is drawn based on the ultra-fine radar site related data, the high-speed search radar site related data and the channel signal related data, thereby improving the accuracy of tornado detection collaborative tracking data.

[0023] 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: Whether to make collaborative tracking adjustments is determined by the obtained ultra-fine radar site evaluation values, and then a high-speed search radar site evaluation is performed based on the obtained high-speed search radar site related data to determine whether to make search accuracy adjustments. Next, a determination is made whether to make radar signal interference adjustments based on the obtained channel signal evaluation values. Finally, a blocked area map is drawn based on the ultra-fine radar site related data, the high-speed search radar site related data, and the channel signal related data, thereby achieving the effect of improving the accuracy of tornado detection collaborative tracking data.

[0024] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0025] like Figure 1 As shown, it is a flow chart of the tornado detection collaborative tracking method provided in an embodiment of the present application, and the method includes the following steps: S1, ultra-fine radar site evaluation: based on the acquired ultra-fine radar site related data, an ultra-fine radar site evaluation is performed to obtain an ultra-fine radar site evaluation value, and based on the ultra-fine radar site evaluation value, it is determined whether to perform collaborative tracking adjustment, and the ultra-fine radar site evaluation value is used to evaluate the accuracy of ultra-fine radar collaborative tracking of tornadoes, and the occlusion adjustment is used to improve the accuracy of ultra-fine radar collaborative tracking; S2, high-speed search radar site evaluation: based on the acquired high-speed search radar site related data, a high-speed search radar site evaluation is performed to obtain a high-speed search radar site evaluation value, and based on the high-speed search radar site evaluation value, it is determined whether to perform search accuracy adjustment, and the high-speed search radar site evaluation value is used to evaluate high The accuracy of high-speed search radar searching for tornadoes, the search accuracy adjustment is used to improve the accuracy of high-speed search radar searching; S3, channel signal evaluation: the radar receiving channel signal is evaluated 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 to obtain the channel signal evaluation value, and 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 received signal strength of the ultra-fine radar and the high-speed search radar, and the radar signal interference adjustment is used to improve the accuracy of the received signals of the ultra-fine radar and the high-speed search radar; S4, drawing of the obstruction area map: drawing the obstruction 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.

[0026] It should be added that the data related to the ultra-fine radar site include obstacle height, obstacle distance, first target distance and target height; the data related to the high-speed search radar site include second target distance and scanning angular velocity; the channel signal related data include first signal frequency and second signal frequency; the obstacle height indicates the height of the preset obstacle detected by the ultra-fine radar; the obstacle distance indicates the horizontal distance between the ultra-fine radar and the preset obstacle; the first target distance indicates the distance between the ultra-fine radar and the preset tornado monitoring point; the target height indicates the distance between the preset top center point of the preset target object (tornado) and the corresponding point on the vertical ground; the second target distance indicates the distance between the high-speed search radar and the preset tornado monitoring point; the scanning angular velocity indicates the scanning angular velocity of the high-speed search radar; the first signal frequency indicates the signal frequency of the ultra-fine radar; the second signal frequency indicates the signal frequency of the high-speed search radar.

[0027] In this embodiment, the ultra-fine radar site evaluation value, the high-speed search radar site evaluation value and the channel signal evaluation value influence 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 ultra-fine radar site evaluation value, the lower the tracking accuracy, and the need for collaborative tracking adjustment. The lower the high-speed search radar site evaluation value, the lower the search accuracy, and the need for search accuracy adjustment. Through mutual adjustment and optimization, the ultra-fine radar site evaluation value, the high-speed search radar site evaluation value and the channel signal evaluation value can promote each other and jointly improve the overall performance of detecting and tracking the preset target (tornado), thereby achieving an improvement in the accuracy of tornado detection and collaborative tracking data.

[0028] It needs to be explained that, at a preset time point, the preset obstacle is scanned by the ultra-fine radar to obtain the obstacle height and obstacle distance of the preset obstacle, the preset target monitoring point is locked by the ultra-fine radar and the distance from the ultra-fine radar to the monitoring point is measured to obtain the first target distance, the preset center point of the preset target is locked by the ultra-fine radar or the high-speed search radar and the distance from the point to the vertical ground is measured to obtain the target height, the preset target monitoring point is locked by the high-speed search radar and the distance from the high-speed search radar to the monitoring point is measured to obtain the second target distance, 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, and the second signal frequency is measured by the high-speed search radar.

[0029] Furthermore, the specific process of evaluating the hyperfine radar site based on the acquired hyperfine radar site related data to obtain the hyperfine radar site evaluation value is as follows: the hyperfine radar obstruction angle compliance value (i.e., the value in the restriction expression of the hyperfine radar site evaluation value) is obtained by calculating the obstacle height, obstacle distance and the reference hyperfine radar detection first weight obtained from the database. ,and is not 0); the ultra-fine radar obstruction angle compliance value is used to reflect the obstruction of the preset obstacle of the ultra-fine radar; the reference ultra-fine radar detection first weight is used to reflect the influence of the radar obstruction angle on the ultra-fine radar obstruction angle compliance value; the ultra-fine radar sight range compliance value (i.e., the value in the restriction expression of the ultra-fine radar site evaluation value) is obtained by calculating the first target distance, target height and the reference ultra-fine radar detection second weight obtained from the database. ); the ultra-fine radar sight range compliance value is used to reflect the detection distance of the ultra-fine radar; the reference ultra-fine radar detection second weight is used to reflect the influence of the radar sight range on the ultra-fine radar sight range compliance value; the radar obstruction compliance value is obtained by performing a ratio operation between the preset radar shielding maximum value obtained from the database and the ultra-fine radar shielding angle compliance value; the radar obstruction compliance value is used to reflect the compliance of the ultra-fine radar shielding angle compliance value; the radar sight range compliance value is obtained by performing a ratio operation between the ultra-fine radar sight range compliance value and the preset radar sight range maximum value obtained from the database; the radar sight range compliance value is used to reflect the compliance of the ultra-fine radar sight range compliance value; the ultra-fine radar site evaluation value is obtained by combining the radar obstruction compliance value and the radar sight range compliance value.

[0030] Among them, the limiting expression of the evaluation value of the hyperfine radar site is as follows: ; ; ; In the formula, represents the hyperfine radar site evaluation value at the rth preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, It represents the super-fine radar shielding angle compliance value corresponding to the super-fine radar at the rth preset time point, It represents the hyperfine radar sight range compliance value corresponding to the hyperfine radar at the rth preset time point, represents the obstacle height corresponding to the rth preset time point by the ultra-fine radar, represents the obstacle distance corresponding to the ultra-fine radar at the rth preset time point, represents the target height of the preset target object at the rth preset time point, represents the first target distance corresponding to the ultra-fine radar at the rth preset time point, represents the first weight of reference hyperfine radar detection, represents the second weight of the reference hyperfine radar detection, Indicates the preset radar shielding maximum value. It represents the preset maximum value of radar sight range, and e represents a natural constant.

[0031] In this embodiment, the aforementioned database is a database for storing various types of setting data established before the design of the tornado detection collaborative tracking method provided in the embodiment of the present application. The database includes but is not limited to signal frequency, target distance, obstacle height, etc., and the various numerical values ​​therein are directly set by technical personnel. For example, the preset radar obstruction maximum value is represented by the maximum value of the ultra-fine radar obstruction angle compliance value in the historical time period in the database, and the preset radar sight range maximum value is represented by the maximum value of the ultra-fine radar sight range compliance value in the historical time period in the database.

[0032] Specifically, the reference hyperfine radar detection first weight and the reference hyperfine radar detection second weight respectively reflect the influence of the hyperfine radar's obstruction angle on the hyperfine radar obstruction angle compliance value and the influence of the line of sight on the hyperfine radar line of sight compliance value. A mapping set of the hyperfine radar's obstruction angle and line of sight and the corresponding weights is pre-set in the database. The mapping set reflects the mapping relationship between the hyperfine radar's obstruction angle and line of sight and the corresponding weights. For example, the hyperfine radar's obstruction angle and line of sight and the weights of the hyperfine radar's obstruction angle and line of sight preset in the database form a mapping set. The real-time hyperfine radar's obstruction angle and line of sight are input into the mapping set to obtain the weights corresponding to the hyperfine radar's obstruction angle and line of sight. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, the value range is 0-1.

[0033] It should be understood that the algorithm of this embodiment combines the analysis of the relevant data 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 does not exist independently, but is interrelated. 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, the target height and the first target distance may 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 considered comprehensively. When the obstacle height and the obstacle distance increase at the same time, the interference of the obstacle to the ultra-fine radar detection may be greater, resulting in a significant decrease in the detection performance of the ultra-fine radar. When the obstacle height 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 may be blocked, resulting in the inability of the ultra-fine radar to accurately measure the first target distance. As the distance to the first target 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, which in turn reduces the evaluation value of the ultra-fine radar site. The parameters of the algorithm in this embodiment need to jointly consider the impact on the results. The accuracy of the ultra-fine radar collaborative tracking of tornadoes is accurately quantified, thereby improving the accuracy of tornado detection and collaborative tracking data.

[0034] Furthermore, the specific process of evaluating the high-speed search radar site based on the acquired high-speed search radar site related data to obtain the high-speed search radar site evaluation value is as follows: the initial radar elevation angle is obtained by calculating the target height and the second target distance (the second target distance is not 0); the initial radar elevation angle is used to reflect the coverage of the high-speed search radar; the radar elevation compliance value (i.e., the maximum value of the high-speed search radar site evaluation value in the restriction expression) is obtained by performing a ratio operation between the initial radar elevation angle and the preset radar elevation maximum value 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 scanning angular velocity compliance value is obtained by performing a ratio operation between the scanning angular velocity and the preset scanning angular velocity maximum value obtained from the database (i.e., the value in the restriction expression of the high-speed search radar site evaluation value). ); The scanning angular velocity compliance value is used to reflect the compliance of the pitch angle change rate of the high-speed search radar; the high-speed search radar site evaluation value is obtained by combining the radar pitch compliance value and the scanning angular velocity compliance value.

[0035] Among them, the high-speed search radar site evaluation value is obtained by the following method: ; ; ; In the formula, represents the high-speed search radar site evaluation value at the rth preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, It indicates the radar pitch coincidence value corresponding to the rth preset time point of the high-speed search radar. Indicates the scanning angular velocity compliance value corresponding to the rth preset time point of the high-speed search radar, represents the target height of the preset target object at the rth preset time point, represents the second target distance corresponding to the high-speed search radar at the rth preset time point, represents the scanning angular velocity of the high-speed search radar at the rth preset time point, Indicates the preset maximum radar pitch value. represents the preset maximum scanning angular velocity, and e represents a natural constant.

[0036] In this embodiment, the preset radar pitch maximum value is represented by the maximum value of the radar pitch angle searched at high speed in the historical time period in the database, and the preset scanning angular velocity maximum value is represented by the maximum value of the radar scanning angular velocity searched at high speed in the historical time period in the database.

[0037] It should be understood that the algorithm of this embodiment combines the high-speed search radar site related data analysis to obtain the high-speed search radar site evaluation value. The high-speed search radar site related data in the algorithm of this embodiment does not exist independently, but has mutual correlation. The increase of target height and scanning angular velocity does not necessarily lead to an increase in the high-speed search radar site evaluation value. The influence of the second target distance should also be considered comprehensively. When the second target distance increases, the detection range of the high-speed search radar will expand accordingly, but this may also lead to a decrease in 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 scanning angular velocity so as to cover a larger area in a shorter time. However, with the increase of scanning angular velocity, the high-speed search radar will stay on each target for a shorter time, which may lead to the inability to fully accumulate the target echo signal, thereby affecting the accuracy of detection. When 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 a decrease in the detection capability of the radar on long-distance or low-reflectivity targets, which will directly affect the accuracy of detection, because the weaker the signal may not be effectively detected, the parameters of the algorithm of this embodiment need to consider the impact on the results together.

[0038] Specifically, assuming the scanning angular velocity The range is 50-100 (radians / second), and the maximum scanning angular velocity is preset Fixed to 100 (radians / second), such as Figure 3 As shown, it is a statistical diagram of the change of the scanning angular velocity-scanning angular velocity coincidence value provided by the embodiment of the present application, Figure 3 It can be seen 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 gradually improves, achieving accurate quantification of the accuracy of the high-speed search radar searching for tornadoes, and thus achieving the improvement of the accuracy of tornado detection collaborative tracking data.

[0039] Further, the specific process of evaluating the radar receiving channel signal to obtain the channel signal evaluation value is as follows: Combined with the ultra-fine radar loss compliance value (i.e., the channel signal evaluation value in the restriction expression) ) and the high-speed search radar loss compliance value (i.e., the channel signal evaluation value in the restricted expression ) to obtain a channel signal evaluation value; the hyperfine radar loss compliance value is represented by the result of a ratio operation between the initial hyperfine radar loss value and a preset hyperfine radar loss maximum value obtained from a database; the hyperfine radar loss compliance value is used to reflect the compliance of the hyperfine radar signal loss; the initial hyperfine radar loss value is obtained by calculating the first signal frequency, the first target distance and the speed of light obtained from a database; the high-speed search radar loss compliance value is represented by the result of a ratio operation between the initial high-speed search radar loss value and a preset high-speed search radar loss maximum value obtained from a 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 calculating the second signal frequency, the second target distance and the speed of light obtained from a database.

[0040] Among them, the channel signal evaluation value is obtained by the following method: ; ; ; In the formula, represents the channel signal evaluation value at the rth preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, represents the hyperfine radar loss compliance value at the rth preset time point, Indicates the high-speed search radar loss compliance value at the rth preset time point, represents the first signal frequency of the hyperfine radar corresponding to the rth preset time point, It indicates the first target distance corresponding to the rth preset time point of the ultra-fine radar after coordinated tracking adjustment. represents the second signal frequency corresponding to the high-speed search radar at the rth preset time point, represents the second target distance corresponding to the rth preset time point of the high-speed search radar after the search accuracy adjustment, Indicates the preset maximum value of ultra-fine radar loss. It represents the maximum loss of preset high-speed search radar, c represents the speed of light, and e represents a natural constant.

[0041] In this embodiment, the preset maximum value of the ultra-fine radar loss is represented by the maximum value of the ultra-fine radar loss in the historical time period in the database, and the preset maximum value of the 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. In this embodiment, (m / s).

[0042] It should be understood that the algorithm of this embodiment combines the channel signal related data analysis to obtain the channel signal evaluation value. The channel signal related data in the algorithm of this embodiment does not exist independently, but has mutual correlation. The increase of the first signal frequency and the second signal frequency 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 considered comprehensively. 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 be increased indefinitely, because the higher the signal frequency, the greater the possibility of absorption and scattering when propagating in the air. As the first target distance and the second target distance increase, the signals of the ultra-fine radar and the high-speed search radar will experience greater attenuation during the propagation process, resulting in a weakening of the signal strength. The parameters of the algorithm of this embodiment need to consider the impact on the results together.

[0043] Specifically, assuming that the hyperfine radar loss meets the value The range is 0.1-0.6, and the high-speed search radar loss meets the value The range is 0.1-0.6, as shown in Table 1, which is a statistical table of changes in channel signal evaluation values ​​provided in an embodiment of the present application: Table 1 Statistics of changes in channel signal evaluation values

[0044] As can be seen from the table above, as the ultra-fine radar loss meets the value The loss of the high-speed search radar is consistent with the value The channel signal evaluation value gradually increases, which means that the attenuation of the received signals of the ultra-fine radar and the high-speed search radar is gradually increasing, realizing the precise quantification of the accuracy of the high-speed search radar in searching for tornadoes, and thus realizing the improvement of the accuracy of the tornado detection collaborative tracking data.

[0045] Furthermore, the specific process of judging whether to perform collaborative tracking adjustment based on the evaluation value of the hyperfine radar site is as follows: A1, judging whether the evaluation value of the hyperfine radar site meets condition one. When the evaluation value of the hyperfine radar site meets condition one, no collaborative tracking adjustment is performed, otherwise A2 is executed; A2, performing pulse compression, when the evaluation value of the monitored hyperfine radar site meets condition one, the collaborative tracking adjustment is stopped, otherwise A3 is executed, pulse compression means suppressing the multipath effect by the pulse compression method; A3, performing phase coding modulation, when the evaluation value of the monitored hyperfine radar site meets condition one, the collaborative tracking adjustment is stopped, otherwise an alarm is sent, phase coding modulation means improving the distance resolution of the hyperfine radar by the phase coding method; condition one means that the hyperfine radar site evaluation value is not lower than the reference hyperfine radar evaluation threshold obtained from the database.

[0046] In this embodiment, the reference hyperfine radar evaluation threshold is represented by the average value of the hyperfine radar site evaluation values ​​in the historical time period in the database. This embodiment increases the time-width-bandwidth product of the radar signal by a linear frequency modulation pulse compression method to improve the distance resolution, thereby reducing the impact of multipath effects on the distance measurement accuracy. The pulse compression method can form a narrowband signal through matched filtering of a broadband signal, thereby improving the resolution of the radar system. Phase coding modulation is based on the principle of phase modulation and carries more information by changing the phase of the signal. Phase coding modulation can divide a wide pulse into many short sub-pulses and control the phases of these sub-pulses by coding. After being transmitted, these encoded sub-pulses will form complex reflection signals at the target. When these reflection signals are received and processed by the radar receiver, the original phase information can be restored through decoding technology, which can improve the distance resolution of the hyperfine radar and achieve the improvement of the accuracy of tornado detection and collaborative tracking data.

[0047] Furthermore, the specific process of judging whether to adjust the search accuracy based on the high-speed search radar site evaluation value is as follows: B1, judging whether the high-speed search radar site evaluation value meets condition two. When the high-speed search radar site evaluation value meets condition two, no search accuracy adjustment is performed, otherwise B2 is executed; B2, sending 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 two, the search accuracy adjustment is stopped, otherwise B3 is executed. The waveform of the high-speed search radar includes a linear frequency modulation signal, a phase coded signal, etc.; B3, performing coherent detection. When the monitored high-speed search radar site evaluation value meets condition two, the search accuracy adjustment is stopped, otherwise an alarm prompt is sent. Coherent detection means improving the detection capability of the high-speed search radar signal by a coherent detection method; Condition two 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.

[0048] In this embodiment, the reference high-speed search radar threshold is represented by the average value of the high-speed search radar site evaluation value 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 technology, thereby improving the signal-to-noise ratio and detection performance of the high-speed search radar signal, and realizing the improvement of the accuracy of the tornado detection and collaborative tracking data.

[0049] Furthermore, the specific process of judging whether to perform radar signal interference adjustment based on the channel signal evaluation value is as follows: C1, judging whether the channel signal evaluation value meets condition three. When the channel signal evaluation value meets condition three, no radar signal interference adjustment is performed, otherwise C2 is executed; C2, sending a prompt to the preset personnel to amplify the RF signal. When the monitored channel signal evaluation value meets condition three, the radar signal interference adjustment is stopped, otherwise C3 is executed. RF signal amplification means reducing the loss of signal reflection through a low noise amplifier; C3, performing Doppler frequency shift compensation. When the monitored channel signal evaluation value meets condition three, the radar signal interference adjustment is stopped, otherwise an alarm prompt is sent. Doppler frequency shift compensation is used to enhance the receiving sensitivity of the signal through the Doppler effect and adaptive filtering; Condition three indicates that the channel signal evaluation value is not higher than the reference signal interference threshold obtained from the database.

[0050] In this embodiment, the reference signal interference threshold is represented by the average value of the channel signal evaluation value in the historical time period in the database. The low noise amplifier has the characteristics of high gain and low noise coefficient, which can amplify the signal more effectively and reduce the interference of noise. The low noise amplifier can minimize the introduction of noise while amplifying the signal. Doppler shift compensation is used to correct the signal frequency change caused by the Doppler effect. The adaptive filtering can dynamically adjust the parameters of the filter according to the characteristics of the input signal, further reduce the influence of noise and interference, and enhance the receiving sensitivity of the signal. Furthermore, the specific process of drawing the obstruction 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 is as follows: conduct a site clearance environment analysis, which means analyzing the site clearance environment through GIS (Geographic Information System) technology; draw the obstruction area map by combining 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, the obstruction area map includes a shielding angle map and an equal beam height map.

[0051] In this embodiment, if Figure 4As shown, it is a map of the obstruction area provided by the embodiment of the present application, wherein Figure (a) is a 1 km equal beam height map, and Figure (b) is a 3 km equal beam height map. Due to the obstruction of high-rise buildings and mountains, the key to radar deployment is site selection and layout. For example, a "4+1+1+N" layout of "quadrilateral + center + mobile + auxiliary" is adopted, that is, 4 fine radars at the four corners, 1 full airspace high-speed search radar in the center, 1 mobile tracking radar, several micro-manometers, observation cameras and other auxiliary equipment. GIS technology is used to analyze the site clearance environment, combined with 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 channel signal related data after radar signal interference adjustment. The obstruction area is obtained through the digital elevation model, and the equal beam height map is drawn, which realizes the visual display of the radar's detection capability in all directions, thereby realizing the improvement of the accuracy of the tornado detection collaborative tracking data.

[0052] To summarize, the embodiment of the present application determines whether to perform collaborative tracking adjustment through the obtained ultra-fine radar site evaluation value, then performs a high-speed search radar site evaluation based on the obtained high-speed search radar site related data and determines whether to adjust the search accuracy, then determines whether to perform radar signal interference adjustment based on the obtained channel signal evaluation value, and finally draws 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, thereby realizing dynamic adjustment of radar monitoring sites, and further realizing the improvement of the accuracy of tornado detection collaborative tracking data, effectively solving the problem of inaccurate tornado detection collaborative tracking data in the prior art.

[0053] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take 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.

[0054] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0057] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0058] 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 equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A tornado detection and collaborative tracking method, characterized in that: The following steps are involved: S1, performing a hyperfine radar site evaluation based on the acquired hyperfine radar site related data to obtain a hyperfine radar site evaluation value, and judging whether to perform a collaborative tracking adjustment based on the hyperfine radar site evaluation value, wherein the hyperfine radar site evaluation value is used to evaluate the accuracy of the hyperfine radar collaborative tracking of the tornado; S2, performing a high-speed search radar site evaluation based on the acquired high-speed search radar site related data to obtain a high-speed search radar site evaluation value, and judging whether to perform a search accuracy adjustment based on the high-speed search radar site evaluation value, wherein 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, evaluating the radar receiving channel signal according to the ultra-fine radar site evaluation value after the coordinated tracking adjustment, the high-speed search radar site evaluation value after the search accuracy adjustment, and the channel signal related data to obtain a channel signal evaluation value, and judging whether to perform radar signal interference adjustment based on the channel signal evaluation value, wherein the channel signal evaluation value is used to evaluate the attenuation of the receiving signal strength of the ultra-fine radar and the high-speed search radar; S4, draws a blocked 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.

2. The tornado detection and collaborative tracking method according to claim 1, characterized in that: 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 the second target distance and scanning angular velocity; The channel signal related data includes a first signal frequency and a 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 a high-speed search radar.

3. The tornado detection and collaborative tracking method according to claim 2, characterized in that: The specific process of performing the ultra-fine radar site evaluation based on the acquired ultra-fine radar site related data to obtain the ultra-fine radar site evaluation value is as follows: Obtaining a super-fine radar obstruction angle compliance value by calculating the obstacle height, the obstacle distance and a reference super-fine radar detection first weight obtained from a database; Obtaining a super-fine radar sight range compliance value by calculating the first target distance, the target height and a second weight of a reference super-fine radar detection obtained from a database; The radar shielding compliance value is obtained by performing a ratio operation between the preset radar shielding maximum value obtained from the database and the ultra-fine radar shielding angle compliance value; The radar sight range compliance value is obtained by performing a ratio operation between the ultra-fine radar sight range compliance value and the preset radar sight range maximum value obtained from the database; The radar obstruction compliance value and the radar line of sight compliance value are combined to obtain the ultra-fine radar site assessment value.

4. The tornado detection and collaborative tracking method according to claim 2, characterized in that: The specific process of performing high-speed search radar site evaluation based on the acquired high-speed search radar site related data to obtain the high-speed search radar site evaluation value is as follows: The initial radar pitch angle is obtained by calculating the target height and the second target distance; The radar pitch compliance value is obtained by performing a ratio operation between the initial radar pitch angle and the preset radar pitch maximum value obtained from the database; The scanning angular velocity compliance value is obtained by performing a ratio operation between the scanning angular velocity and the preset scanning angular velocity maximum value obtained from the database; The radar pitch coincidence value and the scanning angular velocity coincidence value are combined to obtain the high-speed search radar site evaluation value.

5. The tornado detection and collaborative tracking method according to claim 2, characterized in that: The specific process of obtaining the channel signal evaluation value is as follows: The channel signal evaluation value is obtained by combining the ultra-fine radar loss coincidence value and the high-speed search radar loss coincidence value; The hyperfine radar loss compliance value is represented by the result of a ratio calculation between the initial hyperfine radar loss value and the preset hyperfine radar loss maximum value obtained from the database; The initial hyperfine radar loss value is obtained by calculating 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 a ratio calculation between the initial high-speed search radar loss value and the preset high-speed search radar loss maximum value obtained from the database; The initial high-speed search radar loss value is obtained by calculating the second signal frequency, the second target distance and the speed of light obtained from the database.

6. The tornado detection and collaborative tracking method according to claim 3, characterized in that: The specific process of determining whether to perform collaborative tracking adjustment based on the ultra-fine radar site evaluation value is as follows: A1, judging whether the evaluation value of the ultra-fine radar site meets condition 1. If the evaluation value of the ultra-fine radar site meets condition 1, no coordinated tracking adjustment is performed. Otherwise, A2 is executed. A2, pulse compression is performed. When the evaluation value of the monitored ultra-fine radar site meets condition 1, the coordinated tracking adjustment is stopped. Otherwise, A3 is executed; A3, phase coding modulation is performed. When the evaluation value of the monitored ultra-fine radar site meets condition 1, the coordinated tracking adjustment is stopped. Otherwise, an alarm prompt is sent; The condition one indicates that the hyperfine radar site evaluation value is not lower than a reference hyperfine radar evaluation threshold obtained from a database.

7. The tornado detection and collaborative tracking method according to claim 6, characterized in that: The limiting expression of the ultra-fine radar site evaluation value is as follows: ； In the formula, represents the hyperfine radar site evaluation value at the rth preset time point, , r represents the number of the preset time point, m represents the total number of preset time points, It represents the super-fine radar shielding angle compliance value corresponding to the super-fine radar at the rth preset time point, It represents the hyperfine radar sight range compliance value corresponding to the hyperfine radar at the rth preset time point, Indicates the preset radar shielding maximum value. It represents the preset maximum value of radar sight range, and e represents a natural constant.

8. The tornado detection and collaborative tracking method according to claim 4, characterized in that: The specific process of judging whether to adjust the search accuracy based on the high-speed search radar site evaluation value is as follows: B1, judging 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 B2 is executed; B2, sending 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 adjusting the search accuracy. Otherwise, execute B3; B3, perform coherent detection. When the evaluation value of the monitored high-speed search radar site meets condition 2, stop adjusting the search accuracy. Otherwise, send an alarm prompt. The second condition indicates that the high-speed search radar site evaluation value is not lower than the reference high-speed search radar threshold obtained from the database.

9. The tornado detection and collaborative tracking method according to claim 5, characterized in that: The specific process of judging 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 three. When the channel signal evaluation value meets condition three, no radar signal interference adjustment is performed. Otherwise, C2 is executed; C2, send a prompt to the preset personnel to amplify the RF signal. When the monitored channel signal evaluation value meets condition three, stop the radar signal interference adjustment, otherwise execute C3; C3, perform Doppler frequency shift compensation. When the monitored channel signal evaluation value meets condition three, stop radar signal interference adjustment. Otherwise, send an alarm prompt. The condition three indicates that the channel signal evaluation value is not higher than the reference signal interference threshold obtained from the database.

10. The tornado detection and collaborative tracking method according to claim 1, characterized in that: The specific process of drawing the obstruction 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 is as follows: Conduct site clearance environment analysis; The blocked area map is drawn by combining 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.

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