A weather radar operation control method and system

Abstract

This invention relates to the field of weather radar operation control technology, and discloses a weather radar operation control method and system. By extracting incoming weather targets, establishing an impact channel for the event site, calculating arrival time and impact priority, and combining task observation benefits with task execution costs, more observation capabilities can be allocated to weather targets more likely to affect the event site when scanning resources are limited. Furthermore, by adopting an event-support-oriented improved wolf pack algorithm, candidate local observation and control tasks are optimized and solved, and the event support response time limit is embedded in the search and update process. This makes the weather radar operation control scheme more suitable for the use of large-scale outdoor event site support scenarios, continuously improving the event site support effect. It solves the problem that existing weather radar fixed-body scanning methods cannot form priority observation and control around large-scale outdoor event sites, resulting in insufficient early warning lead time for event sites.

Description

Technical Field

[0001] This invention relates to the field of weather radar operation control technology, and in particular to a weather radar operation control method and system. Background Technology

[0002] Weather radar typically employs a fixed-volume scanning method to perform regional weather monitoring tasks. This operational mode offers good stability and consistency in routine meteorological operations, meeting the needs of general regional precipitation monitoring, routine convection monitoring, and ordinary weather monitoring. However, in practical applications, weather radar does not always serve the needs of averaged and uniform regional observations. In certain specific application scenarios, the operational target of weather radar will be significantly biased towards a particular type of key protected object. For example, in the context of large-scale outdoor events such as concerts, outdoor sporting events, large-scale outdoor activities at scenic spots, and opening and closing ceremonies, the task of weather radar is no longer merely to observe the presence of weather echoes in the area, but rather to focus on whether there are rapidly approaching rainfall, strong winds, or severe convective weather targets in and around the event site, and whether such weather targets will enter the event site in a short period of time and directly affect personnel gathering, equipment safety, and event procedures.

[0003] Most existing weather radar operations are based on fixed-body scanning structures, with scanning resources relatively evenly distributed across the entire detection area. Even when it is known operationally that a particular event requires priority protection, the traditional approach typically involves on-duty personnel manually monitoring the event on a display terminal, or, in limited circumstances, performing localized supplementary scans based on experience. This approach has significant shortcomings. On one hand, the radar system itself does not automatically include the event as a protected target in its operational control, resulting in a significant amount of scanning resources being consumed in airspace unrelated to the event. On the other hand, although incoming weather targets that will affect the event may have been detected by the radar, the lack of priority analysis and control strategies centered around the event often makes it difficult to generate higher-frequency, more continuous, and more targeted localized observations. Especially when a rapidly approaching strong echo band or discrete convective cell appears upstream of the event, the traditional operational approach typically cannot automatically determine which weather targets are truly more important to the event, nor can it directly translate the need for advance warning of the event into radar operational control actions. This can lead to a situation where event support personnel, while aware of the presence of weather targets in the vicinity, struggle to obtain timely information on key changes around the event site, thus impacting support decisions such as canceling performances, evacuating personnel, protecting equipment, and conducting on-site emergency command.

[0004] Therefore, how to enable weather radar to prioritize the observation and control of upstream weather targets around the event site in the context of large-scale outdoor event security, and improve the advance warning of the event site under the constraints of scanning resources and equipment load, has become an urgent technical problem to be solved in the field of weather radar operation and control. Summary of the Invention

[0005] This invention provides a weather radar operation control method and system to at least solve the problem that existing weather radar fixed-body scanning methods cannot form priority observation and control around large outdoor event sites, thus resulting in insufficient advance warning for event sites.

[0006] To achieve the above objectives, the present invention provides a weather radar operation control method, the method comprising the following steps: Acquire the activity support zone configuration parameters, weather radar reflectivity data, weather radar radial velocity data, and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support zone configuration parameters; Based on the weather radar reflectivity data and the weather radar radial velocity data, incoming weather targets are extracted, and a weather target state vector corresponding to each incoming weather target is constructed. An incoming influence channel is established based on the activity protection target area and the weather target state vector, and the arrival time and influence priority of each incoming weather target on the activity protection target area are calculated. Local observation and control tasks are generated based on the impact priority of each incoming weather target, and the observation benefits and execution costs of each local observation and control task are established. Based on the local observation and control tasks, the optimal weather radar operation and control scheme is obtained by using the activity-support-oriented improved wolf pack algorithm. Based on the optimal weather radar operation control scheme, a weather radar operation control command sequence is generated. Based on the observation update results obtained after executing the weather radar operation control command sequence, the control performance is calculated and the control parameters for the next control cycle are corrected.

[0007] Optionally, the system acquires activity support zone configuration parameters, weather radar reflectivity data, weather radar radial velocity data, and radar execution status data, and generates an activity support target area and activity support response time limit based on the activity support zone configuration parameters. Specifically, this includes: Obtain the activity support zone configuration parameters, map the activity support zone configuration parameters to the weather radar polar coordinate space, and generate the activity support target zone; The configuration parameters of the event support area include at least the azimuth of the event site center, the distance from the event site center, the support radius of the event site, and the event support early warning time requirements; Generate event support response time limits based on event support early warning time requirements; The activity support target area, the activity support response time limit, the weather radar reflectivity data, the weather radar radial velocity data, and the radar execution status data are uniformly correlated to form the data input for subsequent incoming weather target extraction and local observation and control tasks.

[0008] Optionally, incoming weather targets are extracted based on the weather radar reflectivity data and the weather radar radial velocity data, and a weather target state vector corresponding to each incoming weather target is constructed, specifically including: Connectivity regions are extracted from weather radar reflectivity data within the current control cycle to form multiple incoming weather target areas; Calculate the peak reflectance and average reflectance of each incoming weather target area; Based on the difference in the target center azimuth between the current control cycle and the previous control cycle, and the average radial velocity of the current control cycle, calculate the motion index of the incoming weather target. The peak reflectivity, average reflectivity, target center azimuth, target center distance, target azimuth span, and motion indicators are combined to generate a weather target state vector.

[0009] Optionally, an incoming influence channel is established based on the activity support target area and the weather target state vector, and the arrival time and impact priority of each incoming weather target on the activity support target area are calculated, specifically including: Based on the center location of each incoming weather target and the center location of the event site, calculate the distance and azimuth overlap between the incoming weather targets and the event support target area; Based on the distance and the motion index, calculate the predicted time for each incoming weather target to reach the activity support target area; The impact priority is calculated based on peak reflectance, average reflectance, motion index, channel overlap, and the difference in response time for event support. Based on the aforementioned impact priority, high-priority incoming weather targets are identified, and the identification results are used as the data basis for the generation of local observation and control tasks.

[0010] Optionally, local observation and control tasks are generated based on the impact priority of each incoming weather target, and task observation benefits and task execution costs are established for each local observation and control task, specifically including: For each high-priority incoming weather target, generate local observation and control tasks, and determine the width of the local observation sector based on the impact priority and the target azimuth span; The recommended revisit period for local observation and control tasks is determined based on the impact priority; the task observation benefits are established based on the impact priority and the predicted arrival time; and the task execution costs are established based on the angle switching amount, task scanning time, and equipment load. The local observation sector width, the suggested revisit period, the task observation benefit, and the task execution cost are correlated to form a set of candidate local observation control tasks.

[0011] Optionally, based on the local observation and control tasks, an improved wolf pack algorithm guided by activity assurance is used to obtain the optimal weather radar operation and control scheme, specifically including: Each candidate local observation and control task is encoded into a control scheme vector; A fitness function is established based on the observation benefits, execution costs, coverage penalties, and overall time overrun penalties for each local observation and control task. Based on the fitness function, perform wolf pack individual search, alpha wolf selection and siege convergence processing, and output the optimal weather radar operation control scheme that satisfies the constraint of the remaining schedulable time of the volume scan.

[0012] Optionally, based on the fitness function, perform wolf pack individual search, alpha wolf selection, and encirclement convergence processing to output the optimal weather radar operation control scheme that satisfies the constraint of remaining schedulable time for volume scan, specifically including: The wolf search step size is determined based on the average impact priority of the selected tasks in the current wolf individual's plan; Based on the predicted arrival time and activity support response time limit of each local observation and control task, an activity support time limit guidance vector is generated; A joint approximation update is performed based on the current alpha wolf scheme and the activity guarantee time limit guidance vector; When the updated control scheme vector does not meet the overall time constraint, calculate the task benefit-cost ratio and remove local observation control tasks from low to high according to the task benefit-cost ratio until the overall time constraint is met. The optimal weather radar operation control scheme is output based on the wolf individual scheme that satisfies the overall time constraint.

[0013] Optionally, a weather radar operation control command sequence is generated based on the optimal weather radar operation control scheme, specifically including: The selected local observation and control task in the optimal weather radar operation and control scheme is decoded into weather radar operation and control commands; The execution priority value of weather radar operation control commands is calculated based on mission observation benefits and predicted arrival time; The weather radar operation control commands are arranged in descending order of execution priority, a weather radar operation control command sequence is generated, and output to the weather radar execution control terminal.

[0014] Optionally, based on the observation update results obtained after executing the weather radar operation control command sequence, the control performance is calculated and the control parameters for the next control cycle are corrected, specifically including: Based on the peak reflectivity, motion index and predicted arrival time obtained after executing the weather radar operation control command sequence, the observation update benefit of each local observation control task is calculated. Based on the observation update benefits and task execution costs of each local observation and control task, the control performance of the current control cycle is calculated. The priority weight and revisit cycle compression coefficient for the next control cycle are adjusted based on the control performance. The revised activity guarantee response time difference weight and revisit cycle compression coefficient are used as the control parameter inputs for the next control cycle.

[0015] Furthermore, to achieve the above objectives, the present invention also provides a weather radar operation control system, comprising: The target area generation module is used to acquire the activity support area configuration parameters, weather radar reflectivity data, weather radar radial velocity data and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support area configuration parameters; The target extraction module is used to extract incoming weather targets based on weather radar reflectivity data and weather radar radial velocity data, and to construct the weather target state vector corresponding to each incoming weather target. The priority calculation module is used to establish an incoming influence channel based on the activity protection target area and the weather target state vector, and to calculate the arrival time and influence priority of each incoming weather target on the activity protection target area. The task generation module is used to generate local observation and control tasks based on the impact priority of each incoming weather target, and to establish the task observation benefits and task execution costs for each local observation and control task. The optimization solution module is used to obtain the optimal weather radar operation control scheme based on each local observation and control task and by adopting an activity-support-oriented improved wolf pack algorithm. The feedback update module is used to generate a weather radar operation control command sequence based on the optimal weather radar operation control scheme, and to calculate the control performance and correct the control parameters for the next control cycle based on the observation update results obtained after executing the weather radar operation control command sequence.

[0016] The beneficial effects of this invention are as follows: It proposes a weather radar operation control method and system. By extracting incoming weather targets, establishing an impact channel for the event site, calculating arrival time and impact priority, and combining task observation benefits with task execution costs, it can allocate more observation capabilities to weather targets more likely to affect the event site when scanning resources are limited. Furthermore, by adopting an event support-oriented improved wolf pack algorithm, it optimizes the solution for candidate local observation and control tasks and embeds the event support response time limit into the search and update process, thereby making the weather radar operation control scheme more suitable for the use needs of large-scale outdoor event site support scenarios. By calculating observation update benefits and correcting control performance based on the execution results, this invention can also adaptively update the parameters for the next control cycle, thereby continuously improving the event site support effect. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the method of an embodiment of the present invention; Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] This invention provides a weather radar operation control method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the weather radar operation control method according to an embodiment of the present invention. The present invention provides a weather radar operation control method and system, primarily applied to large-scale outdoor event support scenarios. These scenarios may include, but are not limited to, open-air concerts, open-air sporting events, large-scale nighttime tours of scenic areas, opening ceremonies, closing ceremonies, and temporary large-scale gatherings. It should be noted that in such scenarios, the objective of weather radar operation control is no longer merely to perform an average scan of the entire detection area, but rather to focus on the event site as the key support target, implementing more targeted priority observation and control of upstream weather targets that may affect the event site, thereby improving the lead time for weather warnings and the efficiency of operational support at the event site.

[0020] In this embodiment of the invention, the weather radar operation control method includes the following steps.

[0021] Step S1: Obtain the activity support zone configuration parameters, weather radar reflectivity data, weather radar radial velocity data, and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support zone configuration parameters.

[0022] In this embodiment of the invention, step S1 is used to first determine the business object served by the current control cycle before the weather radar operation control process begins, and to convert this business object from the activity support semantic level into a data object that the weather radar control system can directly use. It should be noted that traditional weather radar operation methods typically do not automatically change their scanning control logic simply because an outdoor activity is in progress. However, this invention first introduces the spatial location of the activity site, the protection range, and advance warning requirements into the control link, and then performs subsequent data processing and control optimization around the protected object. The purpose of this is to avoid the radar operation control remaining in a state where only the weather is known but the business priorities are unknown, and instead enables the weather radar to clearly know where the most important target area is in this control cycle.

[0023] In practical applications, the system first receives the activity support area configuration parameters. These parameters may include at least the azimuth of the activity site center, the distance from the activity site center, the activity site support radius, and the activity support early warning time requirement. It should be noted that these parameters can typically be input and confirmed before the activity begins by the business support platform, activity support terminal, or manual configuration interface, and can also be updated appropriately during the activity based on on-site management needs. This invention does not strictly limit the source of the activity support area configuration parameters, as long as they can form the spatial description of the activity site required for subsequent control processing.

[0024] Furthermore, in one executable implementation, the activity support zone configuration parameters can be mapped to the polar coordinate space of a weather radar to generate an activity support target zone. The activity support target zone can be represented as: ; in, Indicates the target area for the activity. Indicates the azimuth angle of the spatial location to be determined. This represents the distance to the spatial location to be determined. This represents the distance function in the polar coordinate space of the weather radar. Indicates the azimuth of the center of the event site. Indicates the distance from the center of the event venue. Indicates the radius of the event site security.

[0025] In this embodiment of the invention, the aforementioned activity support target area is used to clearly indicate the on-site support range prioritized by the weather radar within the current control cycle. It should be noted that the activity support target area in this invention is not merely a display area, but rather the core reference object for all subsequent weather target screening, incoming influence channel establishment, priority analysis, and local control task generation. In other words, whether a subsequent weather target is worth prioritizing observation is no longer determined solely by its own strength, but rather by its relationship with the activity support target area.

[0026] In this embodiment of the invention, after the activity support target area is generated, an activity support response time limit is further generated. The activity support response time limit is used to express that, from the perspective of weather radar control, an incoming weather target that is likely to enter the activity site within this time range should be considered a higher priority target. Furthermore, in one executable implementation, the activity support response time limit satisfies: ; in, Indicates the response time limit for event support. This indicates the required timeframe for event security warnings. This indicates the system's safety margin time.

[0027] It should be noted that the event support early warning time requirement is not necessarily equivalent to the actual response threshold in the radar control system. This is because, in actual on-site support operations, from identifying weather risks to triggering actions such as on-site broadcasts, temporary suspension of the performance, personnel guidance, equipment protection, and area containment, additional system processing time and execution redundancy time are often required. Therefore, this invention adds a system safety margin time to the event support early warning time requirement to form a more suitable event support response time limit for radar control. It should also be noted that the system safety margin time can be configured according to different event types, on-site scale, audience density, or emergency strategies; this invention does not impose any limitations on this.

[0028] In one specific implementation, it can be assumed that an open-air concert is currently being supported. The center of the event site is located in a direction slightly northeast of due north from the weather radar, corresponding to a center distance of several kilometers. The support radius for the event site is set to range from several hundred meters to several kilometers depending on the size of the venue, and the event support warning time requirement can be set to thirty minutes. Furthermore, to ensure sufficient time for event suspension and audience evacuation, a system safety margin of several minutes to more than ten minutes can be added, thereby generating a corresponding event support response time limit. Through the above method, this invention can transform the business semantics of concert site support into a data object that can be directly processed by subsequent algorithms and control modules.

[0029] Furthermore, it should be noted that the activity support target area is not limited to a strictly circular region in this invention. In a non-limiting embodiment, if the activity site is distributed in a strip along a road, river, or scenic area axis, it can also be represented by an equivalent polygonal region, an elliptical region, or a buffer extension region, as long as it can be formed through a unified coordinate mapping to create an activity support target area that can be directly used in subsequent steps.

[0030] Step S2: Extract incoming weather targets based on weather radar reflectivity data and weather radar radial velocity data, and construct the weather target state vector corresponding to each incoming weather target.

[0031] In this embodiment of the invention, step S2 is used to transform the raw weather radar observation results within the current control cycle from a large amount of discrete grid data into target objects that can be processed by the operational control system. It should be noted that in event support scenarios, the control system is not concerned with the changes in every pixel on the radar screen, but rather with identifying which weather targets are approaching the event site with a certain intensity, range, and motion characteristics. Therefore, in this step, the weather targets are first extracted and then organized into a unified state vector to reduce the complexity of subsequent control calculations and enhance operational relevance.

[0032] In practical applications, the system first performs connected component extraction on the weather radar reflectivity data within the current control cycle. This process is not limited to a specific segmentation method; it can employ threshold-based connected component extraction, or a combination of region growing, target clustering, or morphological merging, as long as it can extract echo regions that are spatially continuous and meteorologically consistent with the same incoming weather target. Through this process, multiple incoming weather target regions can be obtained from the original reflectivity field.

[0033] Furthermore, in one executable implementation, the peak reflectance and average reflectance of each incoming weather target area can be calculated separately to reflect the intensity characteristics of the weather target. The peak reflectance and average reflectance can be expressed as: ; ; in, This represents the peak reflectance of the i-th incoming weather target within the control period t. This represents the average reflectance of the i-th incoming weather target during the control period t. This represents the target area of ​​the i-th incoming weather event. This represents the reflectance value at sampling point p. This indicates the number of sampling points within the target area of ​​the incoming weather event.

[0034] In this embodiment of the invention, the peak reflectivity is used to reflect the strongest local structure in the incoming weather target, and the average reflectivity is used to reflect the overall average energy level of the incoming weather target. It is easy to understand that relying solely on peak reflectivity is easily affected by local strong echo spikes, while relying solely on average reflectivity may ignore local strong weather nuclei. Therefore, this invention retains both, so that subsequent priority calculations can take into account both overall and local hazards.

[0035] In this embodiment of the invention, intensity features alone are insufficient to support priority observation and judgment in activity protection scenarios; therefore, motion features need to be further introduced. Specifically, the system maps the target center positions of the current control cycle to those identified as the same incoming weather target in the previous control cycle, and combines this with the average radial velocity within the current control cycle to form a motion index. Furthermore, in one executable implementation, it can take the following form: ; ; in, This represents the average radial velocity of the i-th incoming weather target during the control period t. This represents the radial velocity value at sampling point p. This represents the motion index of the i-th incoming weather target. This indicates the change in the target center's azimuth between the current control cycle and the previous control cycle. Indicates the weight of the orientation change term. This indicates the weight of the radial velocity term.

[0036] It should be noted that the motion index is not simply a velocity value, but a comprehensive measure reflecting whether the target is in a state of significant motion during the current control cycle. Both azimuth change and average radial velocity are used for characterization because relying solely on the periodic position difference is easily affected by changes in the target identification boundary; relying solely on the average radial velocity may not fully describe the actual movement trend of the target center relative to the activity site. Therefore, this invention constructs the motion index through a fusion approach, making it more suitable for subsequent control analysis.

[0037] Furthermore, in one executable implementation, peak reflectivity, average reflectivity, target center azimuth, target center distance, target azimuth span, and motion indicators can be combined to form a weather target state vector: ; in, This represents the state vector of the i-th incoming weather target. Indicates the center location of the target. Indicates the distance to the center of the target. Indicates the target's azimuth span.

[0038] In this embodiment of the invention, the weather target state vector will serve as the direct input for subsequent establishment of the incoming impact channel and calculation of impact priority. It should be noted that the purpose of forming the state vector here is not to increase the number of parameters, but to compress the truly meaningful features in the event support scenario into a unified data structure, allowing subsequent steps to continuously reuse the previously obtained data.

[0039] In one specific implementation, it can be assumed that within the current control cycle, multiple incoming weather target areas are extracted from the reflectivity field. One target is located relatively far upstream of the event site, while another is located laterally to the event site. By further calculating the peak reflectivity, average reflectivity, target center position, and motion indicators of both targets, it can be found that although their intensities may be similar, the former has a higher overall motion indicator in terms of azimuth variation and average radial velocity. This motion difference will continue to play a role in subsequent steps, thereby preventing the system from making judgments that do not meet the event support requirements based solely on target intensity.

[0040] Furthermore, it should be noted that in some embodiments, weather target extraction may further consider additional features such as target area, target principal axis direction, target development trend, or target echo compactness; however, these additional features are not essential for the existence of this invention. In the current embodiment of this invention, the technical objective of this invention can be achieved as long as a set of state vectors that can support subsequent priority calculation and control task generation can be formed using reflectivity and radial velocity.

[0041] Step S3: Establish an incoming impact channel based on the activity support target area and the weather target state vector, and calculate the arrival time and impact priority of each incoming weather target on the activity support target area.

[0042] In this embodiment of the invention, step S3 is used to analyze which incoming weather targets are truly worthy of priority scanning for the event site within the current control cycle. It should be noted that the mere presence of a weather target within the radar detection area does not necessarily imply that it will have the same impact on the event site. Only those weather targets that have a clear spatial relationship with the event site, are likely to enter the event site relatively quickly in time, and whose intensity and motion characteristics are sufficient to warrant attention in terms of security should receive higher priority in operational control. Therefore, this invention introduces the event site as a security reference object in this step to reassess the impact of weather targets on the event site from the perspective of event site impact.

[0043] In practical applications, the distance and azimuth overlap between the weather target and the event site's center can be calculated first, based on the spatial relationship between the center of the incoming weather target and the center of the event site. One executable implementation can take the following form: ; ; in, This represents the distance from the i-th incoming weather target to the center of the activity support target area. This represents the distance function in the polar coordinate space of the weather radar. Indicates the degree of overlap of channels in the directional direction. This represents the azimuth scale parameter.

[0044] In this embodiment of the invention, the distance is used to characterize how far the weather target is from the event site, and the azimuth channel overlap is used to characterize whether the weather target is located near the main direction of approach from the event site. It is easy to understand that some weather targets, although generally strong, may not pose a high immediate threat if their azimuth deviates significantly from the event site. By introducing azimuth channel overlap, this invention can spatially prioritize the identification of weather targets that are more likely to approach along the upstream direction of the event site.

[0045] Furthermore, in one executable implementation, the predicted time for the weather target to reach the activity support target area can be calculated based on the distance between the weather target and the activity support target area, as well as the motion indicators obtained in the previous step. ; in, This represents the predicted time when the i-th incoming weather target will arrive at the activity support target area. This represents a small constant to prevent the denominator from being zero.

[0046] It should be noted that the arrival time is not a complete result of a fine physical extrapolation of the meteorological process, but rather a rapid forecast for the operational control level. Its purpose is not to replace formal weather forecasts, but rather to quickly determine which weather target is closer to the activity site within the critical control interval during radar operational control. Therefore, this invention uses a combination of distance and motion indicators to characterize the arrival time, primarily serving subsequent control strategies.

[0047] In event support scenarios, simply knowing whether a weather target is close to the event site is insufficient; it is also necessary to determine whether it has entered the event support response timeframe. To this end, this invention further constructs an event support response timeframe difference and uses it, along with weather target intensity, motion characteristics, and channel relationships, to calculate impact priority. In one executable implementation, the following can be defined first: ; Further, we can determine the priority of impact: ; in, This indicates the difference in response time for event support. This indicates the priority of the impact of the i-th incoming weather target. This represents the normalized peak reflectance. This represents the normalized average reflectance. This represents the normalized motion index. This represents the normalized channel overlap. This represents the normalized difference in activity assurance response time. to This indicates the fusion weight.

[0048] In this embodiment of the invention, the impact priority is actually a comprehensive score built around the event site support requirements. It is easy to understand that if a weather target is strong, actively moving, its orientation more closely overlaps with the event site, and its arrival time falls within the event support response timeframe, its impact priority will significantly increase. Conversely, if a weather target has a strong echo but is far from the event site, moves slowly, or has a large orientation deviation, its impact priority will decrease accordingly. In this way, the invention substantially embeds event support requirements into the weather target selection logic, thereby providing a clear basis for the generation of subsequent local observation and control tasks.

[0049] In one specific implementation, it can be assumed that there are two incoming weather targets of similar intensity. One weather target is located directly upstream of the event site and its arrival time is significantly shorter than the event support response time limit. The other weather target, although having a slightly higher peak reflectivity, is located further away from the event site and has a longer arrival time. In the traditional approach that only considers intensity, the latter might be mistakenly considered to be more worthy of priority observation. However, in this invention, the former has a higher degree of overlap in azimuth channels and a larger difference in event support response time limits, thus its impact priority is higher, which is more in line with the event site support needs.

[0050] Furthermore, it should be noted that the weights of the activity support response time limit, intensity, and sports items in the activity support response time limit difference are not fixed. Different weight configurations can be used for different activity types, different support levels, or different weather conditions, as long as the priority is still constructed based on the on-site support needs of the activity.

[0051] Step S4: Generate local observation and control tasks based on the impact priority of each incoming weather target, and establish the observation benefits and execution costs of each local observation and control task.

[0052] In this embodiment of the invention, step S4 is used to further transform the high-priority incoming weather targets obtained in the previous step into local observation and control tasks that can be directly invoked by the weather radar operation control. It should be noted that the influence priority only indicates which weather target is more worthy of priority service at the event site, but does not specify how the radar should be controlled to observe that target. Therefore, this step further constructs the observation sector width, suggested revisit period, task observation benefits, and task execution costs, transforming the weather target from an analytical object into a control task object that can be scheduled and optimized.

[0053] In practical applications, local observation and control tasks can be generated for incoming weather targets with an impact priority higher than a preset threshold. These tasks include at least the task center azimuth, the width of the local observation sector, the suggested revisit period, and the estimated scan time. Furthermore, in one executable implementation, the width of the local observation sector can be determined based on the impact priority and the target's azimuth span. ; in, This represents the width of the observation sector corresponding to the i-th local observation control task. Indicates the minimum sector width. Indicates the priority amplification factor. This represents the target span magnification factor.

[0054] As is easily understood, the width of a local observation sector is not a simple fixed value, but rather dynamically set based on the impact priority and scale of the incoming weather target. If the target has a high priority, it means that the radar is more worthy of investing additional observation resources, and the corresponding sector width can be appropriately increased to ensure that the target does not easily leave the observation range during its movement. If the target has a large azimuth span, a wider observation sector is also needed to avoid focusing only on the target center and missing changes at the target's edges. In this way, the local observation and control task can take into account both target priority and target spatial scale.

[0055] In this embodiment of the invention, to ensure that high-priority targets receive more frequent attention, a suggested revisit cycle is further generated based on the impact priority. In one executable implementation, it can take the following form: ; in, This represents the suggested revisit period for the i-th local observation and control task. Indicates the basic revisit period. This represents the compression factor of the priority on the revisit period.

[0056] In this embodiment of the invention, the suggested revisit period is used to express that for high-priority event support targets, the weather radar should re-observe them at shorter time intervals to update their intensity, movement, and arrival time changes more quickly. It should be noted that during large-scale outdoor event support, what is truly valuable is not merely whether a target is seen once, but whether it is continuously seen and updated in a timely manner as it approaches the event site. Therefore, this invention directly translates event support priority into scanning rhythm requirements through the suggested revisit period.

[0057] While generating control tasks, this invention further establishes task observation benefits and task execution costs. In one executable implementation, the task observation benefits can be expressed as: ; in, This represents the observation gain of the i-th local observation and control task. and This indicates the weight of the benefits. It should be noted that targets with higher priority and faster entry into the event venue have more direct value for event security, and therefore their observed benefits are higher.

[0058] On the other hand, in one executable implementation, the cost of task execution can be expressed as: ; ; in, Indicates the cost of task execution. Indicates the angle switching amount. Indicates the task scan time. Indicates equipment load index, This represents the normalized value of angular velocity. This represents the normalized value of the drive current. This represents the normalized value of the driving temperature. to and to This indicates the corresponding weight.

[0059] In this embodiment of the invention, the task execution cost is used to express the turning, time, and equipment load costs that the radar system needs to incur to execute the task. It should be noted that although on-site support for the event has a high priority, this does not mean that all high-priority tasks can be executed without constraints. If a task has high benefits but requires large angle switching and incurs high equipment load, the system still needs to weigh these factors during subsequent optimization. By simultaneously modeling observation benefits and execution costs, this invention provides a complete foundation for subsequent swarm intelligence optimization.

[0060] In one specific implementation, it can be assumed that there are three high-priority incoming weather targets located upstream of the event site in the main incoming direction, the secondary incoming direction, and the lateral region. Among these, the weather targets in the main incoming direction have the highest priority and the shortest arrival time, so the system allocates a wider observation sector and a shorter suggested revisit period to them. While targets in the lateral region have higher intensity, their arrival time is longer, resulting in relatively lower observation benefits. Simultaneously, if a target requires a significant turn to be scanned, its execution cost will increase accordingly. Through this method, the present invention enables the local observation and control task to possess both benefit and cost attributes, preparing for subsequent solutions to the optimal control scheme.

[0061] Step S5: Based on the local observation and control tasks, the optimal weather radar operation control scheme is obtained by using the activity-support-oriented improved wolf pack algorithm.

[0062] In this embodiment of the invention, step S5 is a crucial step in the entire weather radar operation control method. It should be noted that in the preceding steps, the system already knows which incoming weather targets are more important to the event site and has established local observation and control tasks for these targets. However, the scanning resources that a weather radar can allocate within a control cycle are limited, and there are also constraints on equipment load and remaining volume scan time. Therefore, it is not possible to simply execute all tasks simultaneously. Based on this, this invention introduces an activity-assurance-oriented improved wolf pack algorithm to solve for the optimal weather radar operation control scheme under multi-task and multi-constraint conditions.

[0063] In practical applications, candidate local observation control tasks can first be encoded as control scheme vectors. Each control scheme vector represents which tasks are selected and which are not selected in the current control cycle. Based on this, a fitness function is established to simultaneously express the task observation reward, task execution cost, non-coverage priority loss, and overall time limit penalty. In one executable implementation, the following fitness function can be used: ; The total time limit penalty can be represented as: ; in, The fitness value represents the control scheme vector. This indicates the selection status of the i-th local observation and control task. Indicates the gains from mission observation. Indicates the cost of task execution. Indicates the priority of the impact of incoming weather targets. This indicates the penalty for exceeding the overall time limit. This indicates the remaining schedulable time for the current body scan. to This represents the penalty coefficient.

[0064] It should be noted that the fitness function described above does not simply pursue maximizing the number of selected tasks, nor does it simply pursue maximizing a single metric. Instead, it seeks a balance between activity support benefits, radar execution costs, losses of high-priority targets not covered in the activity area, and overall time constraints. Through this design, the present invention can avoid the algorithm biasing towards a single objective while ignoring overall executability.

[0065] To make the wolf pack search process more suitable for large-scale outdoor event security scenarios, this invention improves the traditional wolf pack algorithm based on specific scenarios. Specifically, in one executable implementation, the wolf search step size is determined based on the average impact priority of the selected tasks in the current wolf's plan: ; in, This represents the search step size of the q-th wolf in the k-th iteration. Indicates the maximum search step size. Indicates the minimum search step size. This indicates the average impact priority of the selected tasks in the current plan.

[0066] It's easy to understand that if a wolf's current plan already includes many high-priority activity support tasks, it means the plan is quite close to the activity support goal. In this case, the search step size should be reduced to enhance the local fine-grained search capability. Conversely, if its current plan still focuses on lower-priority tasks, it means there is a large deviation between it and the activity support requirements. In this case, maintaining a larger search step size is more conducive to expanding the search range. In this way, the present invention enables the search step size of the wolf pack algorithm to dynamically change according to the value of activity support.

[0067] Furthermore, in one executable implementation, the present invention also introduces an activity assurance time limit guidance vector to express which local observation and control tasks have entered the activity assurance response time limit range. The activity assurance time limit guidance vector can be expressed as: ; in: ; in, This represents the guiding vector for the activity guarantee time limit. This represents the time limit guide value for the i-th local observation and control task.

[0068] Based on this, in one executable implementation, the alpha wolf scheme and the activity guarantee time limit guidance vector can be jointly introduced into the wolf pack individual update process, forming the following update relationship: ; in, This represents the control scheme vector for the q-th wolf individual in the k-th iteration. This represents the alpha wolf strategy in the k-th iteration. and Indicates approximation weights, This represents the operation of projecting onto the feasible region. This represents the feasible region of the current control cycle.

[0069] In this embodiment of the invention, the wolf pack no longer simply follows the current globally optimal alpha wolf strategy, but is also guided by which tasks have entered the event support response time limit. In this way, the algorithm does not merely perform general task combination optimization, but explicitly converges towards a solution that better aligns with the urgency of event support. That is, the alpha wolf represents the currently best-performing solution, while the time limit guidance vector represents the set of tasks that should not be ignored from the perspective of event support; both participate in the update together.

[0070] In this embodiment of the invention, a feasibility repair mechanism is also introduced. Specifically, when the total scan time of the updated control scheme exceeds the remaining schedulable time for the current volume scan, the scheme needs to be pruned. It should be noted that this step ensures that, at the engineering implementation level, the output will not become an unexecutable theoretical solution. In one executable implementation, tasks can be prioritized for retention or deletion based on the task benefit-cost ratio. This benefit-cost ratio can be expressed as: ; in, This represents the task benefit-cost ratio of the i-th local observation and control task. Subsequently, tasks with lower benefit-cost ratios can be removed sequentially until the total task scan time satisfies the remaining schedulable time constraint for the current volume scan.

[0071] In one specific implementation, it can be assumed that there are several tasks in the candidate local observation and control task set. Some of these tasks, although having high priority, require large angle switching or long scanning time, making the overall scheme infeasible under the overall time constraint. In this case, an improved wolf pack algorithm guided by activity assurance is first used to obtain a better combination, and then a feasibility repair mechanism is used to eliminate the task with the lowest benefit-cost ratio. This yields the optimal weather radar operation and control scheme that satisfies both the activity assurance priority principle and the engineering execution constraints.

[0072] Furthermore, it should be noted that although this invention uses the wolf pack algorithm as the core swarm intelligence optimization algorithm, its improvement direction is not limited to a certain fixed parameter setting. As long as the algorithm retains the two core ideas of activity guarantee value orientation and activity guarantee time limit guidance, it can be considered as an extension of the technical concept of this invention.

[0073] Step S6: Generate a weather radar operation control command sequence based on the optimal weather radar operation control scheme, and calculate the control performance and correct the control parameters for the next control cycle based on the observation update results obtained after executing the weather radar operation control command sequence.

[0074] In this embodiment of the invention, step S6 is used to further transform the optimal control scheme obtained in the previous step into an executable operation control command for the weather radar, and after execution, form a feedback update for the next control cycle. It should be noted that this invention does not merely select a few tasks temporarily within a single control cycle, but rather aims to enable the weather radar to continuously optimize the control parameters for the next cycle based on the actual observation results of the previous cycle during the continuous support of large-scale outdoor events, thereby forming a continuous adaptive capability for event support scenarios.

[0075] In practical applications, the selected local observation and control tasks in the optimal weather radar operation and control scheme can be decoded into weather radar operation and control commands. These commands can be expressed using information such as the mission center azimuth, observation sector width, suggested revisit period, and mission scan time, and are directly output to the weather radar execution control terminal. Furthermore, the system can assign execution priority to each weather radar operation and control command based on the mission observation benefits and predicted arrival time, ensuring that tasks more urgent and valuable to the event site are executed first.

[0076] In this embodiment of the invention, after executing the sequence of weather radar operation control commands, the system recalculates the state changes of relevant weather targets based on the new observation results. These state changes are not limited to updates to reflectivity values, but also include changes in motion indicators and predicted arrival times. By comparing the key states of the same target before and after execution, it can be determined whether local priority observations have made the relevant weather targets at the event site clearer, more timely, and easier to judge.

[0077] Furthermore, in one feasible implementation, the observation update benefit for each local observation and control task can be calculated based on the updated peak reflectance, updated motion indicators, and updated predicted arrival times. It's important to note that the observation update benefit doesn't simply refer to the presence of new data, but rather whether the new data significantly improves the effectiveness of risk assessment at the event site. For example, if prioritizing observation reveals a significantly shortened arrival time for a target or a significantly enhanced motion indicator, it indicates that the prioritized observation action has high value for event support.

[0078] In practical applications, the gains from observation updates can be characterized by the weighted sum of the differences between the updated peak reflectance, motion index, and reciprocal of the predicted time of arrival and the original peak reflectance, motion index, and reciprocal of the predicted time of arrival.

[0079] In this embodiment of the invention, after obtaining the observation update benefits of each local observation and control task, the control performance of the current control cycle is further calculated based on the observation update benefits and the corresponding task execution costs. The control performance is used to comprehensively evaluate whether the control behavior in this cycle has achieved a higher level of activity assurance awareness through more reasonable scanning resources. It is easy to understand that high control performance does not mean that the system scans more in this cycle, but rather that the system has obtained more valuable activity assurance information with more reasonable resource allocation.

[0080] In practical applications, control performance can be characterized by the ratio of the sum of observation update benefits of all executed local observation control tasks to the sum of task execution costs of all executed local observation control tasks.

[0081] In one feasible implementation, several control parameters for the next cycle can be modified based on the control performance of the current control cycle. Preferably, the weight of the activity assurance response time difference and the revisit cycle compression coefficient can be modified. The former determines the importance of the factor affecting the priority of entering the assurance time limit range in the next cycle, while the latter determines the recommended revisit cycle length for high-priority targets. In this way, if the results of the current cycle indicate that the activity assurance time limit item contributes significantly to the actual effect, its weight can be further increased in the next cycle; if the current cycle shows that the revisit of high-priority targets is still not timely enough, the revisit cycle compression can be further strengthened.

[0082] In practical applications, the weighting of the activity assurance response time difference is the same as the weighting of the activity assurance response time difference when calculating the impact priority in the preceding steps. The revisit cycle compression factor is the compression factor of the revisit cycle due to the priority of the preceding steps. The weighting of the difference in response time for event security The correction can be made through calculation. The compression factor for the revisit cycle is determined by summing the product of the control performance (minus the performance reference value) for the current control cycle and the first preset correction step size. The correction can be made through calculation. The value is determined by the sum of the product of the performance reference value minus the control performance of the current control cycle and the second preset correction step size.

[0083] In one specific implementation, it can be assumed that after one control cycle, the system finds that, after priority scanning, the predicted arrival time of weather targets in the upstream main incoming direction of an event site is significantly shortened and the intensity growth trend is clearer, while the execution cost of the task has not increased significantly. In this case, the performance of the current control cycle is high. In this situation, the weight of the event support response time difference can be appropriately increased in the next cycle, allowing the system to further strengthen the targets that will soon affect the site in the new priority calculation. Conversely, if no significant effective updates are obtained after priority observation in the current cycle, or if the execution cost is too high, the system can appropriately reduce the relevant weights or adjust the revisit compression coefficient in the next cycle to avoid ineffective resource allocation.

[0084] Furthermore, it should be noted that the feedback correction in step S6 is not limited to correcting only two parameters. In other non-limiting embodiments, parameters such as the minimum observation sector width, priority threshold, task benefit weight, or equipment load penalty weight can also be further corrected, as long as the updates still revolve around the data link and activity assurance scenario logic established by this invention.

[0085] In a complete implementation process, the system receives configuration parameters for the event support area before the event begins, forming the event support target area and event support response time limit. Then, within each control cycle, it extracts incoming weather targets, constructs weather target state vectors, and calculates the target's distance to the event site, arrival time, and impact priority. Based on high-priority targets, it generates local observation and control tasks and obtains the optimal weather radar operation control scheme through an improved wolf pack algorithm guided by event support. Next, the scheme is converted into an operation control command sequence and issued for execution. Finally, based on the updated observation results after execution, the control performance is calculated, and the control parameters for the next cycle are adjusted. Through this continuous processing, the present invention enables weather radar operation control to shift from traditional regional average scanning to priority observation control for large-scale outdoor event support, thereby effectively improving the lead time for weather warnings and the targeted nature of support at the event site.

[0086] Reference Figure 2 , Figure 2 This is a schematic diagram of the weather radar operation control system according to an embodiment of the present invention.

[0087] like Figure 2 As shown, the weather radar operation control system proposed in this embodiment of the invention includes: The target area generation module 10 is used to acquire the activity support area configuration parameters, weather radar reflectivity data, weather radar radial velocity data and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support area configuration parameters. The target extraction module 20 is used to extract incoming weather targets based on weather radar reflectivity data and weather radar radial velocity data, and to construct the weather target state vector corresponding to each incoming weather target. The priority calculation module 30 is used to establish an incoming influence channel based on the activity protection target area and the weather target state vector, and to calculate the arrival time and influence priority of each incoming weather target on the activity protection target area. The task generation module 40 is used to generate local observation and control tasks based on the impact priority of each incoming weather target, and to establish the task observation benefits and task execution costs for each local observation and control task. The optimization solution module 50 is used to solve for the optimal weather radar operation control scheme based on each local observation and control task and using the activity-support-oriented improved wolf pack algorithm. The feedback update module 60 is used to generate a weather radar operation control command sequence based on the optimal weather radar operation control scheme, and to calculate the control performance and correct the control parameters for the next control cycle based on the observation update results obtained after executing the weather radar operation control command sequence.

[0088] Other embodiments or specific implementations of the weather radar operation control system of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0089] It is understood that in the description of this specification, references to terms such as "one embodiment," "another embodiment," "other embodiments," or "first embodiment to Nth embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0090] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0091] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A weather radar operation control method, characterized in that, The method includes the following steps: Acquire the activity support zone configuration parameters, weather radar reflectivity data, weather radar radial velocity data, and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support zone configuration parameters; Based on the weather radar reflectivity data and the weather radar radial velocity data, incoming weather targets are extracted, and a weather target state vector corresponding to each incoming weather target is constructed. An incoming influence channel is established based on the activity protection target area and the weather target state vector, and the arrival time and influence priority of each incoming weather target on the activity protection target area are calculated. Local observation and control tasks are generated based on the impact priority of each incoming weather target, and the observation benefits and execution costs of each local observation and control task are established. Based on the local observation and control tasks, the optimal weather radar operation and control scheme is obtained by using the activity-support-oriented improved wolf pack algorithm. Based on the optimal weather radar operation control scheme, a weather radar operation control command sequence is generated. Based on the observation update results obtained after executing the weather radar operation control command sequence, the control performance is calculated and the control parameters for the next control cycle are corrected.

2. The weather radar operation control method as described in claim 1, characterized in that, Acquire activity support zone configuration parameters, weather radar reflectivity data, weather radar radial velocity data, and radar execution status data, and generate activity support target area and activity support response time limit based on the activity support zone configuration parameters, specifically including: Obtain the activity support zone configuration parameters, map the activity support zone configuration parameters to the weather radar polar coordinate space, and generate the activity support target zone; The configuration parameters of the event support area include at least the azimuth of the event site center, the distance from the event site center, the support radius of the event site, and the event support early warning time requirements; Generate event support response time limits based on event support early warning time requirements; The activity support target area, the activity support response time limit, the weather radar reflectivity data, the weather radar radial velocity data, and the radar execution status data are uniformly correlated to form the data input for subsequent incoming weather target extraction and local observation and control tasks.

3. The weather radar operation control method as described in claim 1, characterized in that, Based on the weather radar reflectivity data and the weather radar radial velocity data, incoming weather targets are extracted, and a weather target state vector corresponding to each incoming weather target is constructed, specifically including: Connectivity regions are extracted from weather radar reflectivity data within the current control cycle to form multiple incoming weather target areas; Calculate the peak reflectance and average reflectance of each incoming weather target area; Based on the difference in the target center azimuth between the current control cycle and the previous control cycle, and the average radial velocity of the current control cycle, calculate the motion index of the incoming weather target. The peak reflectivity, average reflectivity, target center azimuth, target center distance, target azimuth span, and motion indicators are combined to generate a weather target state vector.

4. The weather radar operation control method as described in claim 1, characterized in that, An incoming weather impact channel is established based on the activity support target area and the weather target state vector, and the arrival time and impact priority of each incoming weather target on the activity support target area are calculated, specifically including: Based on the center location of each incoming weather target and the center location of the event site, calculate the distance and azimuth overlap between the incoming weather targets and the event support target area; Based on the distance and the motion index, calculate the predicted time for each incoming weather target to reach the activity support target area; The impact priority is calculated based on peak reflectance, average reflectance, motion index, channel overlap, and the difference in response time for event support. Based on the aforementioned impact priority, high-priority incoming weather targets are identified, and the identification results are used as the data basis for the generation of local observation and control tasks.

5. The weather radar operation control method as described in claim 1, characterized in that, Local observation and control tasks are generated based on the impact priority of each incoming weather target, and the observation benefits and execution costs of each local observation and control task are established, specifically including: For each high-priority incoming weather target, generate local observation and control tasks, and determine the width of the local observation sector based on the impact priority and the target azimuth span; The recommended revisit period for local observation and control tasks is determined based on the impact priority; the task observation benefits are established based on the impact priority and the predicted arrival time; and the task execution cost is established based on the angle switching amount, task scanning time, and equipment load. The local observation sector width, the suggested revisit period, the task observation benefit, and the task execution cost are correlated to form a set of candidate local observation control tasks.

6. The weather radar operation control method as described in claim 1, characterized in that, Based on the local observation and control tasks, an improved wolf pack algorithm guided by activity assurance is used to solve for the optimal weather radar operation and control scheme, which includes: Each candidate local observation and control task is encoded into a control scheme vector; A fitness function is established based on the observation benefits, execution costs, coverage penalties, and overall time overrun penalties for each local observation and control task. Based on the fitness function, perform wolf pack individual search, alpha wolf selection and siege convergence processing, and output the optimal weather radar operation control scheme that satisfies the constraint of the remaining schedulable time of the volume scan.

7. The weather radar operation control method as described in claim 6, characterized in that, Based on the fitness function, the wolf pack individual search, alpha wolf selection, and encirclement convergence processing are performed, outputting the optimal weather radar operation control scheme that satisfies the constraint of the remaining schedulable time of the volume scan, specifically including: The wolf search step size is determined based on the average impact priority of the selected tasks in the current wolf individual's plan; Based on the predicted arrival time and activity support response time limit of each local observation and control task, an activity support time limit guidance vector is generated; A joint approximation update is performed based on the current alpha wolf scheme and the activity guarantee time limit guidance vector; When the updated control scheme vector does not meet the overall time constraint, calculate the task benefit-cost ratio and remove local observation control tasks from low to high according to the task benefit-cost ratio until the overall time constraint is met. The optimal weather radar operation control scheme is output based on the wolf individual scheme that satisfies the overall time constraint.

8. The weather radar operation control method as described in claim 1, characterized in that, Based on the optimal weather radar operation control scheme, a weather radar operation control command sequence is generated, specifically including: The selected local observation and control task in the optimal weather radar operation and control scheme is decoded into weather radar operation and control commands; The execution priority value of weather radar operation control commands is calculated based on mission observation benefits and predicted arrival time; The weather radar operation control commands are arranged in descending order of execution priority, a weather radar operation control command sequence is generated, and output to the weather radar execution control terminal.

9. The weather radar operation control method as described in claim 1, characterized in that, Based on the observation update results obtained after executing the weather radar operation control command sequence, the control performance is calculated and the control parameters for the next control cycle are corrected, specifically including: Based on the peak reflectivity, motion index and predicted arrival time obtained after executing the weather radar operation control command sequence, the observation update benefit of each local observation control task is calculated. Based on the observation update benefits and task execution costs of each local observation and control task, the control performance of the current control cycle is calculated. The priority weight and revisit cycle compression coefficient for the next control cycle are adjusted based on the control performance. The revised activity guarantee response time difference weight and revisit cycle compression coefficient are used as the control parameter inputs for the next control cycle.

10. A weather radar operation control system, characterized in that, The system includes: The target area generation module is used to acquire the activity support area configuration parameters, weather radar reflectivity data, weather radar radial velocity data and radar execution status data, and generate the activity support target area and activity support response time limit based on the activity support area configuration parameters; The target extraction module is used to extract incoming weather targets based on weather radar reflectivity data and weather radar radial velocity data, and to construct the weather target state vector corresponding to each incoming weather target. The priority calculation module is used to establish an incoming influence channel based on the activity protection target area and the weather target state vector, and to calculate the arrival time and influence priority of each incoming weather target on the activity protection target area. The task generation module is used to generate local observation and control tasks based on the impact priority of each incoming weather target, and to establish the task observation benefits and task execution costs for each local observation and control task. The optimization solution module is used to obtain the optimal weather radar operation control scheme based on each local observation and control task and by adopting an activity-support-oriented improved wolf pack algorithm. The feedback update module is used to generate a weather radar operation control command sequence based on the optimal weather radar operation control scheme, and to calculate the control performance and correct the control parameters for the next control cycle based on the observation update results obtained after executing the weather radar operation control command sequence.

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