Radar resource scheduling method based on stacked beams

Abstract

The invention discloses a radar resource scheduling method based on stacked beams, and the method comprises the steps: determining radar parameters, and an azimuth angle range and a pitch angle range which need to be scanned according to a plurality of target tasks; further determining the number of azimuth wave positions and the number of pitching wave positions; determining a plurality of pitching wave position piles corresponding to each azimuth dimension according to the number of the pitching wave positions and a preset number; based on the attribute information and the mapping relationship of each target task, aggregating a plurality of target tasks corresponding to the same azimuth dimension according to a pitching wave position pile to obtain a plurality of aggregated task packets corresponding to each azimuth dimension; and scheduling a target aggregation task packet from the plurality of aggregation task packets corresponding to each azimuth dimension, and carrying out parallel processing on a plurality of target tasks in the target aggregation task packet. According to the method, the searching and scanning time can be greatly shortened, and rapid discovery and response to high-speed and high-maneuvering targets and sudden threats are realized; the multi-task robustness of a radar system can be improved in a high-density target environment.

Description

A Radar Resource Scheduling Method Based on Stacked Beams Technical Field

[0001] This invention belongs to the field of radar data processing technology, specifically relating to a radar resource scheduling method based on stacked beams. Background Technology

[0002] With the evolution of aerospace technology and modern warfare, the battlefield environment has become increasingly complex, posing unprecedented challenges to the detection performance of radar systems. The emergence of advanced targets such as high-speed stealth fighters, ballistic missiles, and hypersonic cruise missiles requires radars to possess longer detection ranges, higher measurement accuracy, and faster response speeds. Active phased array radar, as the culmination of modern radar technology, achieves agile beam pointing by replacing mechanical scanning with electronic scanning, providing the physical basis for addressing these challenges. However, the ultimate performance of phased array radar depends on its resource management and beam positioning system. Beam positioning, which determines the strategy of when, how, and in which airspace the radar beam points, directly determines the radar's time utilization, multi-target processing capability, and overall mission effectiveness. Given fixed resources, an efficient beam positioning algorithm is key to unlocking the potential of phased array radar.

[0003] In the field of phased array radar, the traditional adaptive scheduling method divides the radar advance time into continuous time frames. Search tasks generate a fixed sequence of bit requests based on a preset airspace scan map. Other tasks generate bit requests for data updates based on target status and extrapolation predictions by the track manager. All task requests are placed in a dynamic task queue. Within each time frame, the scheduler first checks the task queue for high-priority tracking task requests. If so, the bit request corresponding to the tracking task is executed first. Only when there are no tracking tasks, or if there is remaining time after resources reserved for tracking tasks, are low-priority search tasks executed. Finally, the echo signal for that bit is generated and processed serially.

[0004] Existing technical solutions employ a "point-by-point scanning" approach, meaning the radar beam must sequentially access every independent position in the airspace. Completing full coverage of the scanned airspace requires a long frame time, resulting in slow updates to the overall airspace situational information acquired by the radar, making it unable to promptly capture dynamic changes in high-speed, highly maneuverable targets. Furthermore, existing technologies use simple fixed-priority scheduling, which severely compresses or even interrupts the search task when the number of targets to be tracked increases. This means that while the radar system can maintain tracking of detected targets, it loses the ability to detect new threats, making it highly susceptible to tactical blind spots in complex electromagnetic environments. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a radar resource scheduling method based on stacked beams.

[0006] The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a radar resource scheduling method based on stacked beams, comprising: determining radar parameters and the required azimuth and elevation angle ranges for scanning according to multiple target tasks; determining the number of azimuth and elevation beams according to the radar parameters, azimuth and elevation angle ranges; determining multiple elevation beam stacks corresponding to each azimuth dimension according to the number of elevation beams and a preset number; wherein each elevation beam has a mapping relationship with its corresponding elevation beam stack; based on the attribute information and mapping relationship of each target task, aggregating multiple target tasks corresponding to the same azimuth dimension according to the elevation beam stacks to obtain multiple aggregated task packages corresponding to each azimuth dimension; the attribute information of the target tasks includes azimuth and elevation angles; scheduling target aggregated task packages from the multiple aggregated task packages corresponding to each azimuth dimension, and performing parallel processing on multiple target tasks in the target aggregated task packages.

[0007] This invention provides a radar resource scheduling method based on stacked beams. By employing a parallel detection mechanism of elevation beam stacking, it overcomes the slow speed of traditional "point-by-point scanning," significantly shortening search and scanning time and increasing data refresh rate. This enables rapid detection and response to high-speed, highly maneuverable targets and sudden threats. Furthermore, it adopts a beam aggregation scheduling strategy that balances the resource demands of search and other tasks. This ensures that the radar system maintains stable and high-precision tracking in high-density target environments without significantly sacrificing its ability to search for and detect new targets, fundamentally improving the multi-task robustness of the radar system.

[0008] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0009] Figure 1 is a flowchart illustrating a radar resource scheduling method based on stacked beams according to an embodiment of the present invention; Figure 2 is a schematic diagram of the beam stack in the radar resource scheduling method based on stacked beams according to an embodiment of the present invention. Detailed Implementation

[0010] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0011] This invention provides a radar resource scheduling method based on stacked beams. Referring to Figures 1 and 2, the method includes the following steps: S10, determining radar parameters and the required azimuth and elevation angle ranges for scanning based on multiple target tasks.

[0012] For example, a dynamic task queue can be initialized, which includes multiple target tasks to be executed. The dynamic task queue Q is used to receive, store, and manage requests for target tasks from different sources. Target tasks may include search tasks, tracking tasks, etc. Different radar parameters and the required azimuth and elevation angle ranges for scanning are pre-set according to different target tasks.

[0013] Radar parameters include azimuth beamwidth, elevation beamwidth, operating wavelength, array antenna geometry (such as the number and spacing of elements), transmitted signal waveform and power, and receiver noise characteristics. Based on the target mission, the azimuth range to be monitored by the radar is defined. With pitch angle range .

[0014] S20. Determine the number of azimuth and elevation wave positions based on radar parameters, azimuth range, and elevation range.

[0015] For example, as shown in Figure 2, several adjacent discrete pitch positions are merged into a unified scheduling unit in the pitch dimension, thereby upgrading the basic unit of airspace management from a "point" to a "stack" and dividing the airspace into a fine grid.

[0016] Optionally, step S20 may specifically include: S201, calculating the number of azimuth beams based on the azimuth beamwidth and azimuth angle range.

[0017] Specifically, the number of azimuth wave positions is expressed as:

[0018] in, The number of azimuth wave positions is indicated by the azimuth range. , Indicates the azimuth beamwidth.

[0019] S202. Calculate the number of elevation beam positions based on the elevation beamwidth and elevation angle range.

[0020] Specifically, the number of elevation positions is expressed as:

[0021] in, This indicates the number of pitch positions, and the pitch angle range is expressed as... , This indicates the pitch beamwidth.

[0022] S30. Based on the number of elevation positions and the preset number, determine the multiple elevation position stacks corresponding to each azimuth dimension.

[0023] Each pitch position has a mapping relationship with its corresponding pitch position stack.

[0024] Optionally, step S30 specifically includes: according to the number of elevation positions corresponding to each azimuth dimension, dividing a preset number of adjacent elevation positions into a group to obtain multiple elevation position stacks corresponding to each azimuth dimension; constructing a position stack mapping table, the position stack mapping table including the mapping relationship between the elevation angle corresponding to each elevation position and the elevation position stack.

[0025] For example, here, the azimuth dimension corresponds to the azimuth wave position, and each azimuth dimension corresponds to... There are several elevation position groups, with each group consisting of a predetermined number of K positions. The total number of elevation position groups for each azimuth dimension is calculated as follows: .

[0026]

[0027] when When (% indicates remainder), that is, the number of pitch positions in the last pitch position stack will be less than K, the previous All piles are full, each pitch position pile contains K positions, and the last pitch position pile contains the remaining R positions. .

[0028] Establish a pitch position stack mapping table to define which pitch position stack each pitch position belongs to. Let a certain pitch position stack be... The pitch angle of a certain pitch wave position is The mapping relationship f between the pitch angle corresponding to the pitch position and the pitch position stack is:

[0029] S40. Based on the attribute information and mapping relationship of each target task, multiple target tasks corresponding to the same azimuth dimension are aggregated according to the elevation position stack to obtain multiple aggregated task packages corresponding to each azimuth dimension.

[0030] The target mission's attribute information includes azimuth and elevation angles.

[0031] For example, in the dynamic task queue, each target task is assigned basic attributes, as shown in Table 1. Each target task includes the following attribute information: Table 1 Dynamic Task Queue Attribute Structure

[0032] The scheduler collects tasks from the dynamic task queue Q that are in the same azimuth angle. Above, all target tasks that need to be executed. Let the list of tasks to be executed at a certain azimuth position be... ,but

[0033] Each target task Includes its mission type, priority, and specified pitch position. , Indicates the index of the target task.

[0034] Find each target task based on the wavelet stack mapping table. Specified pitch position The pitch wave potential stack Grouping all target missions according to their respective elevation wave positions allows us to obtain the azimuth wave positions. Above, several task groups based on elevation potential stacks. ,in .

[0035] if If the set is non-empty, then immediately create an aggregate task package for that task group. Aggregated task packages The coverage area is the entire pitch wave plateau. The corresponding pitch angle range corresponds to the task list, which is the task group. All target tasks.

[0036] For some high-priority independent target tasks in the dynamic task queue, since they cannot be aggregated with other target tasks in the current scheduling period, empty tasks are used to fill the task group corresponding to the pitch position stack to which the independent target task belongs, forming an aggregated task package for unified scheduling.

[0037] S50. Schedule the target aggregate task package from the multiple aggregate task packages corresponding to each azimuth dimension, and process the multiple target tasks in the target aggregate task package in parallel.

[0038] Optionally, step S50 may specifically include: S501, determining the priority of each aggregated task package based on the dynamic priority of multiple target tasks in each aggregated task package.

[0039] Optionally, the dynamic priority of the target task is represented as:

[0040] in, Indicate the target task Dynamic priority, Indicates the weighting factor for time urgency. For the target task Inherent basic priority, For the current radar system time, For the target task The last execution time.

[0041] For example, the scheduler performs dynamic priority evaluation on all target tasks in the dynamic task queue. This dynamic priority is determined by the target task's inherent base priority and a time urgency factor that increases over time, ensuring that the radar system can respond to critical threats while preventing any task from being shelved for an extended period.

[0042] In addition, methods for calculating dynamic priorities for aggregated task packages can also include prioritizing the aggregation of the elevation position stack with the most tracking tasks, or selecting the aggregation scheme with the lowest total resource consumption of the radar system based on the theoretical resource consumption under different aggregation methods.

[0043] Optionally, step S501 may specifically include: calculating the dynamic priority of each target task based on the basic priority of each target task in each aggregated task package; and determining the priority of each aggregated task package based on the dynamic priorities of multiple target tasks in each aggregated task package.

[0044] Optionally, the priority of the aggregated task package is represented as follows:

[0045] in, Indicates aggregated task package priority, Indicates aggregated task package The set of target tasks within, It is an aggregated task package A fusion function for the dynamic priorities of each target task within the task. Indicates the weighting factor for time urgency. This is the current radar system time. It is an aggregated task package The last execution time.

[0046] S502. Based on the priority of each aggregated task package, schedule the target aggregated task package with the highest current priority, and process multiple target tasks in the target aggregated task package in parallel.

[0047] For example, the scheduler selects the current aggregated task from all pending aggregated task packages based on the calculated priority of each aggregated task package. The highest-density target aggregation task package is used for scheduling. In high-density target scenarios, because the aggregation task package aggregates target tasks from several elevation positions according to position stacks, several radar tasks, including search and tracking, are scheduled within a dwell time, improving the radar's search efficiency across the entire airspace. Furthermore, since tracking events and other radar events are carried over to search events and scheduled and processed in units of position stacks, these other radar events will not encroach on the search event's time, effectively improving the search event's ability to discover new targets.

[0048] The receiver receives a target aggregation task packet, breaks it down, generates multiple echo signals at different elevation angles in parallel according to different parameters, and then performs dedicated signal processing according to different task types. The generated target information is filtered and predicted by data processing to generate new radar target tasks, which are stored in the dynamic task queue for the next cycle and then scheduled by the scheduler.

[0049] This embodiment provides a radar resource scheduling method based on stacked beams. Through the parallel detection mechanism of beam stacking, it overcomes the slow speed of traditional "point-by-point scanning," significantly shortening the search and scanning time and improving the data refresh rate. This enables rapid detection and response to high-speed, highly maneuverable targets and sudden threats. Furthermore, a beam aggregation scheduling strategy is designed to balance the resource demands of search and other tasks, ensuring that the system maintains stable and high-precision tracking in high-density target environments without significantly sacrificing its ability to search for and discover new targets, fundamentally improving the system's multi-task robustness.

[0050] It should be noted that the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention.

[0051] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature 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, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0052] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings and the disclosure in carrying out the claimed invention. In the description of the invention, the word "comprising" does not exclude other components or steps, "a" or "an" does not exclude a plurality, and "a plurality" means two or more, unless otherwise explicitly specified. Furthermore, while different embodiments may describe certain measures, this does not mean that these measures cannot be combined to produce good results.

[0053] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A radar resource scheduling method based on stacked beams, characterized in that, include: Based on multiple target tasks, radar parameters and the required azimuth and elevation angle ranges for scanning are determined. Based on the radar parameters, the azimuth and elevation angle ranges, the number of azimuth and elevation prepositions is determined. Based on the number of elevation prepositions and a preset number, multiple elevation preposition stacks corresponding to each azimuth dimension are determined. Each elevation preposition has a mapping relationship with its corresponding elevation preposition stack. Based on the attribute information of each target task and the mapping relationship, multiple target tasks corresponding to the same azimuth dimension are aggregated according to the elevation preposition stacks to obtain multiple aggregated task packages corresponding to each azimuth dimension. The attribute information of the target tasks includes azimuth and elevation angles. Target aggregated task packages are scheduled from the multiple aggregated task packages corresponding to each azimuth dimension, and multiple target tasks in the target aggregated task packages are processed in parallel.

2. The radar resource scheduling method based on stacked beams according to claim 1, characterized in that, The attribute information of the target task also includes dynamic priority. The parallel processing of multiple target tasks in each aggregated task package includes: determining the priority of each aggregated task package according to the dynamic priority of multiple target tasks in each aggregated task package; scheduling the target aggregated task package with the highest current priority according to the priority of each aggregated task package, and processing multiple target tasks in the target aggregated task package in parallel.

3. The radar resource scheduling method based on stacked beams according to claim 2, characterized in that, The attribute information of the target task also includes a basic priority. The step of determining the priority of each aggregated task package based on the dynamic priorities of multiple target tasks in each aggregated task package includes: calculating the dynamic priority of each target task based on the basic priority of each target task in each aggregated task package; and determining the priority of each aggregated task package based on the dynamic priorities of multiple target tasks in each aggregated task package.

4. The radar resource scheduling method based on stacked beams according to claim 3, characterized in that, The dynamic priority of the target task is represented as follows: in, Indicate the target task Dynamic priority, Indicates the weighting factor for time urgency. For the target task Inherent basic priority, For the current radar system time, For the target task The last execution time.

5. The radar resource scheduling method based on stacked beams according to claim 4, characterized in that, The priority of the aggregated task package is represented as follows: in, Indicates aggregated task package priority, Indicates aggregated task package The set of target tasks within, It is an aggregated task package A fusion function for the dynamic priorities of each target task within the task. Indicates the weighting factor for time urgency. This is the current radar system time. It is an aggregated task package The last execution time.

6. The radar resource scheduling method based on stacked beams according to claim 1, characterized in that, The radar parameters include azimuth beamwidth and elevation beamwidth. Determining the number of azimuth and elevation beamwidths based on the radar parameters, the azimuth range, and the elevation range includes: calculating the number of azimuth beamwidths based on the azimuth beamwidth and the azimuth range; and calculating the number of elevation beamwidths based on the elevation beamwidth and the elevation range.

7. The radar resource scheduling method based on stacked beams according to claim 6, characterized in that, The number of azimuth wave positions is expressed as: in, The number of azimuth wave positions is indicated by the azimuth range. ， The azimuth beamwidth is represented by: The number of elevation beam positions is represented as: in, This indicates the number of pitch positions, and the pitch angle range is expressed as... ， This indicates the pitch beamwidth.

8. The radar resource scheduling method based on stacked beams according to claim 1, characterized in that, The step of determining multiple pitch position stacks corresponding to each azimuth dimension based on the number of pitch positions and a preset number includes: grouping a preset number of adjacent pitch positions into a group based on the number of pitch positions corresponding to each azimuth dimension to obtain multiple pitch position stacks corresponding to each azimuth dimension; constructing a position stack mapping table, wherein the position stack mapping table includes the mapping relationship between the pitch angle corresponding to each pitch position and the pitch position stack.

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