Phased array radar resource scheduling method for adaptively tracking time interval

Abstract

The invention discloses a time-interval phased array radar resource scheduling method and device, electronic equipment and a storage medium, and relates to the technical field of radar data processing and resource scheduling, and the method comprises the steps: determining an airspace region according to a radar monitoring range and a beam width, and defining a scheduling period and an airspace monitoring frame period of a radar event, a list of beam requests for radar events is initialized. And setting a group of standard tracking time interval lists, calculating state prediction covariance matrixes under different time intervals by using a Kalman filter, and adaptively adjusting to obtain an optimal tracking time interval. And arranging events in each beam request list into an execution list according to the priority of the radar events, and executing high-priority events according to the optimal time interval. And finally, updating a beam request list by removing processed requests and supplementing new requests, and dynamically adjusting and optimizing a scheduling plan according to an actual execution condition. According to the invention, the problems of unreasonable resource allocation and inflexible response in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of radar data processing and resource scheduling technology, and in particular to a method, apparatus, electronic device and storage medium for adaptive tracking time interval phased array radar resource scheduling. Background Technology

[0002] With the continuous advancement of radar technology, phased array radar has demonstrated powerful capabilities in target search and multi-target tracking due to its flexible beam pointing and customizable scanning modes.

[0003] However, phased array radar resources are limited, and it needs to balance routine searches of the monitored airspace with stable tracking of detected targets within a specified timeframe, posing a significant challenge to resource scheduling. Traditional phased array radar resource scheduling methods with adaptive tracking time intervals often employ fixed or empirical tracking time intervals, making it difficult to flexibly adjust them based on target dynamics and radar resource conditions. When target motion changes or radar load increases, fixed time intervals may lead to unreasonable resource allocation, affecting tracking performance and search efficiency.

[0004] Furthermore, traditional methods lack dynamic adjustment mechanisms, making it difficult to achieve optimal resource allocation in complex and ever-changing airspace environments. This not only limits the radar's ability to respond quickly to sudden targets but also affects the overall flexibility and efficiency of mission execution.

[0005] Therefore, there is an urgent need for a phased array radar resource scheduling method that can adaptively adjust the tracking time interval, optimize resource allocation, and improve the efficiency and flexibility of radar mission execution. Summary of the Invention

[0006] The embodiments of this invention provide a phased array radar resource scheduling method with adaptive tracking time intervals to solve the problems of unreasonable resource allocation in existing technologies, which affects tracking and search efficiency, and the lack of a dynamic priority adjustment mechanism, which limits radar response speed and mission execution flexibility. The technical solution is as follows:

[0007] According to one aspect of the present invention, a method for scheduling phased array radar resources with adaptive tracking time intervals is provided. The method includes: determining a spatial region based on the radar's monitoring range and beamwidth, defining a scheduling period for radar events and a spatial monitoring frame period, and initializing a beam request list for the radar events; the beam request list includes a tracking beam request list, a confirmation beam request list, a lost-track beam request list, and a search beam request list; setting a set of standard tracking time interval lists according to the scheduling period of the radar events; calculating the state prediction covariance matrix under different time intervals using a filter; and applying the state prediction covariance matrix to the... The optimal tracking time interval is obtained by adaptively adjusting the tracking time interval list; the priority order of the radar events is defined, and the events in each of the beam request lists are arranged into the execution event list of the current next cycle according to the priority order, and the radar events are executed according to the optimal tracking time interval; the radar events include tracking events, confirmation events, tracking failure events, and search events; after all the radar events are executed in the current scheduling cycle, the beam request lists are updated by removing processed requests and adding new requests, and the scheduling plan for the current next cycle is dynamically adjusted and optimized according to the actual execution situation and radar resource usage.

[0008] In one embodiment, the airspace region is determined based on the radar's monitoring range and beamwidth, and the scheduling cycle of radar events and the airspace monitoring frame cycle are defined. The initialization of the radar event beam request list is achieved through the following steps: calculating the required fully covered airspace region based on the radar's monitoring range parameters and beamwidth values; determining the radar event scheduling cycle and the airspace monitoring frame cycle; the radar event scheduling cycle refers to the duration of the radar event arrangement and execution cycle; the airspace monitoring frame cycle refers to the duration of a complete monitoring scan of the monitored airspace; initializing the radar event beam request list; the search beam request list records beam requests requiring search tasks; the tracking beam request list stores beam requests requiring target tracking; the confirmation beam request list records beam requests requiring target status confirmation; and the loss-of-track beam request list records beam requests for lost-track targets.

[0009] In one embodiment, setting a standard tracking time interval list based on the scheduling period of the radar event is achieved through the following steps: taking an integer multiple of the scheduling period of the radar event as each time interval option in the tracking time interval list, and arranging the time interval options in ascending order to obtain a standard tracking time interval list; the tracking time interval list includes multiple time interval options for radar tracking targets.

[0010] In one embodiment, the optimal tracking time interval is obtained by adaptively adjusting the tracking time interval list based on the state prediction covariance matrix using a filter to calculate the state prediction covariance matrix of the target under different time intervals. This is achieved through the following steps: using a Kalman filter, the state prediction covariance matrix of the target under different time intervals is calculated for each time interval option in the tracking time interval list; the state prediction covariance matrix is ​​used to reflect the degree of uncertainty in the target state prediction; using a linear function of the measurement noise covariance as a threshold, each state prediction covariance matrix is ​​compared with the threshold, and the maximum time interval not exceeding the set threshold is selected from the tracking time interval list as the optimal tracking time interval.

[0011] In one embodiment, the priority order of the radar events is defined, and events in each beam request list are arranged into the current next cycle execution event list according to the priority order. The execution of the radar events according to the optimal tracking time interval is achieved through the following steps: The priority order of the radar events is determined from high to low as tracking events, confirmation events, tracking failure events, and search events. Events in the beam request list of the tracking events that meet the optimal tracking time interval are arranged into the current next cycle execution event list. The beam request lists of the confirmation events and the tracking failure events are all placed into the current next cycle execution event list, and search events are added sequentially until the maximum number of beam requests for the current next cycle is reached. The highest priority tracking event is executed according to the priority order and the optimal tracking time interval. After execution, the processed request is removed from the corresponding event list, and new related requests are added to the beam request lists of the corresponding radar events.

[0012] In one embodiment, the scheduling plan for the current next cycle is dynamically adjusted and optimized based on the actual execution and radar resource usage by updating each beam request list by removing processed requests and adding new requests. This is achieved through the following steps: adding the first beam request in the beam request list corresponding to the tracking event to the execution event list for the current next cycle and removing it from the tracking event list; conversely, extending it to the execution event list for the next cycle; adding the beam request corresponding to the confirmation event to the execution event list for the current next cycle and deleting it from the confirmation event list; transferring the beam request corresponding to the tracking failure event to the execution event list for the current next cycle and deleting it from the tracking failure event list; sequentially adding the beam requests corresponding to the search events to the execution event list for the current next cycle until the maximum number of beam requests allowed for the current next cycle is reached, and sequentially transferring the added beam requests from the head to the tail of the beam request list corresponding to the search events.

[0013] In one embodiment, the method further includes the following steps: when the search beam corresponding to the search event detects a point and the signal-to-noise ratio reaches the detection threshold, a 2 / 3 logic method is initiated to determine whether track initiation can be completed. If it can be completed, the search event is converted into a confirmation event. When the probability of the confirmation beam corresponding to the confirmation event detecting the target is greater than a set value, a target motion track is established, the Kalman filter parameters are initialized, and the confirmation event is converted into a tracking event. When the tracking beam corresponding to the tracking event fails to detect the target twice consecutively, the search range is expanded. If the target is detected again and track association is completed, the tracking event is converted into a tracking failure event, and the target track and Kalman filter parameters are updated.

[0014] According to one aspect of the present invention, a phased array radar resource scheduling device with adaptive tracking time interval is provided. The device includes: an initialization setting module, configured to determine an airspace region based on the radar's monitoring range and beamwidth, define a scheduling period for radar events and an airspace monitoring frame period, and initialize a beam request list for the radar events; the beam request list includes a tracking beam request list, a confirmation beam request list, a lost-track beam request list, and a search beam request list; and an interval adjustment module, configured to set a set of standard tracking time interval lists according to the scheduling period of the radar events, calculate the state prediction covariance matrix under different time intervals using a filter, and adjust the interval based on the state prediction covariance matrix. The tracking time interval list is adaptively adjusted to obtain the optimal tracking time interval; the resource scheduling module is used to define the priority order of the radar events, arrange the events in each of the beam request lists to the execution event list of the current next cycle according to the priority order, and execute the radar events according to the optimal tracking time interval; the radar events include tracking events, confirmation events, tracking failure events, and search events; the list optimization module is used to update each of the beam request lists by removing processed requests and adding new requests after all the radar events are executed in the current scheduling cycle, and dynamically adjust and optimize the scheduling plan of the current next cycle according to the actual execution situation and radar resource usage.

[0015] According to one aspect of the present invention, an electronic device includes at least one processor and at least one memory, wherein computer-readable instructions are stored in the memory; the computer-readable instructions are executed by one or more of the processors to cause the electronic device to implement the phased array radar resource scheduling method with adaptive tracking time interval as described above.

[0016] According to one aspect of the invention, a storage medium stores computer-readable instructions that are executed by one or more processors to implement the phased array radar resource scheduling method with adaptive tracking time intervals as described above.

[0017] The beneficial effects of the technical solution provided by this invention are:

[0018] In the above technical solution, this invention first determines the airspace region based on the radar monitoring range and beamwidth, defines the scheduling period of radar events and the airspace monitoring frame period, and initializes the beam request list for radar events. Next, a set of standard tracking time interval lists is set, and the state prediction covariance matrix under different time intervals is calculated using a Kalman filter, adaptively adjusting to obtain the optimal tracking time interval. Subsequently, according to the priority of radar events, events in each beam request list are arranged into the execution list, and high-priority events are executed according to the optimal time interval. Finally, the beam request list is updated by removing processed requests and adding new requests, dynamically adjusting and optimizing the scheduling plan based on the actual execution situation. This method achieves efficient utilization of radar resources, improves the stability and search efficiency of target tracking, and effectively solves the problems of unreasonable resource allocation and inflexible response in traditional methods. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a phased array radar resource scheduling method with adaptive tracking time interval according to an exemplary embodiment;

[0021] Figure 2 This is a schematic diagram of resource scheduling for each radar event beam request according to an exemplary embodiment;

[0022] Figure 3 This is a block diagram of a phased array radar resource scheduling device with adaptive tracking time interval, according to an exemplary embodiment.

[0023] Figure 4 This is a hardware structure diagram of an electronic device according to an exemplary embodiment;

[0024] Figure 5 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0025] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0026] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this disclosure means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0027] This invention provides a phased array radar resource scheduling method with adaptive tracking time intervals. By adaptively adjusting the tracking time interval and dynamically optimizing radar event scheduling, it achieves efficient utilization of phased array radar resources, improves target tracking stability and search efficiency, and effectively solves the problems of unreasonable resource allocation, slow response speed, and insufficient task execution flexibility in traditional methods. This adaptive tracking time interval phased array radar resource scheduling method is applicable to phased array radar resource scheduling devices with adaptive tracking time intervals, which can be electronic devices. The adaptive tracking time interval phased array radar resource scheduling method in this invention can be applied to various scenarios, such as adaptive tracking time interval phased array radar resource scheduling in enterprise operations.

[0028] Please see Figure 1 This invention provides a phased array radar resource scheduling method with adaptive tracking time interval, which is applicable to electronic devices.

[0029] In the following method embodiments, for ease of description, the execution subject of each step of the method is an electronic device, but this does not constitute a specific limitation.

[0030] like Figure 1 As shown, the method may include the following steps:

[0031] Step 110: Determine the airspace area based on the radar's monitoring range and beamwidth, define the radar event scheduling cycle and airspace monitoring frame cycle, and initialize the radar event beam request list.

[0032] In one possible implementation, the required airspace coverage is calculated based on the radar's monitoring range parameters and beamwidth values. The scheduling cycle of radar events and the airspace monitoring frame cycle are then determined, and the beam request list for radar events is initialized.

[0033] Among them, the radar event scheduling cycle refers to the period of time for radar event arrangement and execution; the airspace surveillance frame cycle refers to the period of time for a complete surveillance scan of the surveillance airspace; the beam request list includes the tracking beam request list, the confirmation beam request list, the lost-track beam request list, and the search beam request list, etc., none of which are limited here.

[0034] The search beam request list records beam requests that need to perform search tasks; the tracking beam request list stores beam requests that need to track targets; the confirmation beam request list records beam requests that need to confirm the status of targets; and the loss-of-track beam request list records beam requests that have lost track of targets.

[0035] Specifically, firstly, based on the radar's monitoring range and beamwidth, the required comprehensive airspace coverage is precisely calculated. This ensures that the radar can monitor the designated area without omissions. Simultaneously, the radar event scheduling cycle and airspace monitoring frame cycle are defined. The former determines the frequency of radar event scheduling and execution, while the latter refers to the duration of a complete scan of the monitored airspace. Subsequently, beam request lists are initialized, including search beam request lists, track beam request lists, confirm target status request lists, and lost-track beam request lists. These lists are used to record beam requests for performing search tasks, tracking targets, confirming target status, and for targets lost for various reasons, respectively.

[0036] In the above process, the embodiments of the present invention ensure the efficient utilization of radar resources by accurately calculating the surveillance airspace range and defining the scheduling cycle. Initializing various beam request lists provides basic data support for subsequent radar event scheduling, achieving comprehensive coverage and flexible scheduling of the surveillance airspace.

[0037] Step 120: Set a set of standard tracking time interval lists according to the scheduling cycle of radar events, use filters to calculate the state prediction covariance matrix under different time intervals, and adaptively adjust the tracking time interval list according to the state prediction covariance matrix to obtain the optimal tracking time interval.

[0038] In one possible implementation, the time length of an integer multiple of the radar event scheduling period is used as the various time interval options in the tracking time interval list, and the time interval options are arranged in ascending order to obtain a standard tracking time interval list.

[0039] The tracking time interval list includes multiple radar tracking target time interval options.

[0040] In one possible implementation, a Kalman filter is used to calculate the target's state prediction covariance matrix for each time interval option in the tracking time interval list. The linear function of the measurement noise covariance is used as a threshold, and each state prediction covariance matrix is ​​compared with the threshold. The maximum time interval not exceeding the set threshold is selected from the tracking time interval list as the optimal tracking time interval.

[0041] Among them, the state prediction covariance matrix is ​​used to reflect the degree of uncertainty in the prediction of the target state.

[0042] Specifically, a standard list of tracking time intervals is set according to the radar event scheduling cycle. These time interval options are integer multiples of the radar event scheduling cycle and are arranged in ascending order. Subsequently, a Kalman filter is used to calculate the target's state prediction covariance matrix at different time intervals, which reflects the degree of uncertainty in the target's state prediction. By comparing the linear function of the measurement noise covariance as a threshold with the state prediction covariance matrix, the maximum time interval not exceeding the set threshold is selected from the tracking time interval list as the optimal tracking time interval.

[0043] In the above process, this embodiment of the invention achieves adaptive adjustment of the tracking time interval through Kalman filter calculation and threshold comparison. It can dynamically select the optimal tracking time interval based on the uncertainty of the target state prediction, thereby improving the accuracy and stability of target tracking.

[0044] Step 130: Define the priority order of radar events, arrange the events in each beam request list into the current next cycle execution event list according to the priority order, and execute the radar events according to the optimal tracking time interval.

[0045] In one possible implementation, the priority order of radar events is determined from high to low as: tracking events, confirmation events, tracking failure events, and search events. Events in the beam request list of tracking events that meet the optimal tracking time interval are arranged into the execution event list for the next cycle. The beam request lists of confirmation events and tracking failure events are all added to the execution event list for the next cycle. Search events are added in sequence until the maximum number of beam requests for the next cycle is reached. The highest priority tracking events are executed according to the optimal tracking time interval in priority order. After execution, the processed requests are removed from the corresponding event lists, and new relevant requests are added to the beam request lists of the corresponding radar events.

[0046] Radar events include tracking events, confirmation events, loss of tracking events, and search events, etc., none of which are specified here.

[0047] Specifically, after determining the optimal tracking time interval, the priority order of radar events is defined. Based on this order, events in each beam request list are moved to the execution event list for the next cycle. Tracking events have the highest priority, followed by confirmation events, loss of tracking events, and search events. For tracking events, only those matching the optimal tracking time interval are added to the execution list; for confirmation and loss of tracking events, all are added to the execution list; search events are added sequentially until the maximum number of beam requests for the next cycle is reached.

[0048] In the above process, embodiments of the present invention define the priority order of radar events and arrange the events into an execution list according to this order, ensuring the timely processing of high-priority events. This method improves the radar's rapid response capability to sudden targets and optimizes the allocation of radar resources.

[0049] Step 140: After all radar events have been executed within the current scheduling cycle, update the request list for each beam by removing processed requests and adding new requests, and dynamically adjust and optimize the scheduling plan for the next cycle based on the actual execution and radar resource usage.

[0050] In one possible implementation, the first beam request in the beam request list corresponding to a tracking event is added to the current next cycle execution event list and removed from the tracking event list; conversely, the first beam request is carried over to the next cycle execution event list. The beam request corresponding to a confirmation event is added to the current next cycle execution event list and removed from the confirmation event list. The beam request corresponding to a lost tracking event is transferred to the current next cycle execution event list and removed from the lost tracking event list. The beam requests corresponding to search events are added to the current next cycle execution event list in sequence until the maximum number of beam requests allowed in the current next cycle is reached, and the added beam requests are sequentially transferred from the head to the tail of the beam request list corresponding to search events.

[0051] Specifically, the process determines whether the beam request corresponding to a tracking event should be executed immediately or postponed to the next cycle; beam requests corresponding to confirmation events and tracking failure events are added to the execution list and removed from the original list; beam requests corresponding to search events are added to the execution list sequentially until the maximum number of beam requests is reached, and the added search events are removed from the head of the list and added to the tail. Furthermore, when a search event detects a point and the signal-to-noise ratio reaches the detection threshold, track initiation is initiated; when the probability of a confirmed event detecting a target is greater than a set value, a target motion track is established and Kalman filter parameters are initialized; when a tracking event fails to detect a target twice consecutively, the search range is expanded and the track and filter parameters are updated after the target is detected again.

[0052] In the above process, the embodiments of the present invention ensure efficient utilization and flexible response of radar resources by dynamically adjusting and optimizing the scheduling plan. This method can adjust the scheduling strategy in a timely manner according to the actual execution situation and resource usage, thereby improving the adaptability and stability of the radar in complex environments.

[0053] In one possible implementation, when the search beam corresponding to a search event detects a point and the signal-to-noise ratio reaches the detection threshold, a 2 / 3 logic method is initiated to determine whether track initiation can be completed. If it can be completed, the search event is converted into a confirmation event. When the probability of the confirmation beam corresponding to the confirmation event detecting the target is greater than a set value, the target motion track is established, the Kalman filter parameters are initialized, and the confirmation event is converted into a tracking event. When the tracking beam corresponding to the tracking event fails to detect the target twice consecutively, the search range is expanded. If the target is detected again and track association is completed, the tracking event is converted into a tracking failure event, and the target track and Kalman filter parameters are updated.

[0054] Through the above process, this invention achieves efficient utilization and flexible scheduling of radar resources by initialization and area definition, adaptive adjustment of tracking time intervals, priority scheduling of radar events, and dynamic adjustment and optimization. It can dynamically adjust the tracking time interval based on the uncertainty of target state prediction, ensuring the accuracy and stability of target tracking. Simultaneously, by defining the priority order of radar events and dynamically adjusting the scheduling plan, it improves the radar's rapid response capability to sudden targets and its adaptability in complex environments. Overall, this scheme significantly improves the performance and efficiency of phased array radar.

[0055] In one exemplary embodiment, the process of requesting resource scheduling for each radar event beam is illustrated in the phased array radar resource scheduling method of the present invention with adaptive tracking time interval.

[0056] like Figure 2 As shown, specifically, it may include the following steps:

[0057] Step S1: Construct and initialize beam request.

[0058] Specifically, a search beam request list (search event list) corresponding to a search event is first constructed based on the surveillance airspace and beamwidth of the phased array radar. This list is filled in according to the order of radar search positions, and the number of beam requests it contains is equal to the number of airspace positions.

[0059] Furthermore, a tracking beam request list (tracking event list) corresponding to a tracking event, a confirmation beam request list (confirmation event list) corresponding to a confirmation event, and a tracking loss beam request list (tracking loss event list) corresponding to a tracking loss event are constructed, and all are initialized to empty lists in the initial state. These lists provide basic data support for subsequent radar event scheduling and resource allocation.

[0060] Step S2: The tracking time interval is adaptively adjusted.

[0061] Specifically, a typical tracking time interval list is set according to the scheduling cycle of radar events, and the elements in the list are arranged in ascending order from smallest to largest.

[0062] Furthermore, using the prediction part calculation method of the Kalman filter, the state of the target tracking filter is predicted at different time intervals, and the corresponding state prediction covariance matrix is ​​calculated. A linear function of the measurement noise covariance is set as the desired tracking threshold. By comparing the calculated state prediction covariance matrix with this threshold, the maximum time interval that meets the desired tracking threshold is selected from the list of tracking time intervals and determined as the appropriate tracking time interval. This achieves adaptive optimization of the tracking time interval, ensuring the accuracy and stability of target tracking.

[0063] Step S3, radar event priority scheduling.

[0064] Specifically, according to the established radar event priority order (tracking events have the highest priority, followed by confirmation events, loss of tracking events, and search events have the lowest priority), the events in each beam request list are sequentially arranged into the current next cycle execution event list.

[0065] The handling procedures for different radar events are as follows:

[0066] Trace event handling: For beam requests in the trace event list, it is necessary to determine whether the sequence number of the beam request in the list is 1. If it is 1, then the beam request in the trace event list that meets the set requirements is included. Figure 2 The beam requests corresponding to the orange numbers 1, 3, and 5 are added to the "Current Next Cycle Execution List" and removed from the trace event list; if it is not 1, the trace event is retained in the trace event list. Figure 2 The updated tracking time list is then checked, and the list number is decremented by 1. The beam request is then postponed to the next cycle for further evaluation.

[0067] Confirmation event handling: Directly process beam requests in the confirmation event list ( Figure 2 The beam requests corresponding to the green numbers 1, 2, and 3 are added to the "Current Next Cycle Execution List" and removed from the confirmation event list.

[0068] Loss of tracking event handling: Similarly, directly handle the beam request in the loss of tracking event list ( Figure 2 The beam requests corresponding to the blue numbers 1 and 2 are added to the "Current Next Cycle Execution List" and removed from the list of lost events.

[0069] Search event handling: Process beam requests from the search event list in sequence. Figure 2 The beam requests corresponding to the purple numbers 1, 2...k-1, k are added sequentially from front to back to the "Current Next Cycle Execution List" until the maximum number of beam requests allowed in each scheduling cycle is reached. Figure 2 (k in the context). For search events already added to the "Current Next Cycle Execution List", add them to the top of the search event list. Figure 2 The beam requests corresponding to the purple numbers 1, 2...k-1, k have been moved from the head to the tail of the search event list. Figure 2 The purple numbers 1, 2...k-2, k-1, k in the "Updated Search Event List" correspond to beam requests, thus ensuring the continuity of the search beam position.

[0070] Finally, after executing all radar events scheduled for the next cycle within the current scheduling period, the system enters the list update phase. This involves removing processed requests and adding new requests based on actual execution data to update the tracking beam request list, confirming beam request list, lost-track beam request list, and search beam request list. Simultaneously, based on actual execution and radar resource usage, the scheduling plan for the next cycle is dynamically adjusted and optimized to prepare for resource scheduling in the next cycle, thereby achieving continuous and efficient operation of phased array radar resource scheduling throughout the entire phased array adaptive tracking time interval.

[0071] Through the above process, the embodiments of the present invention achieve efficient allocation and utilization of phased array radar resources by reasonably constructing a beam request list, adaptively adjusting the tracking time interval, scheduling radar events according to priority, and dynamically updating the list, thereby effectively improving the performance and efficiency of the radar in target tracking, search and other tasks.

[0072] In one exemplary embodiment, a search beam request list L is constructed based on the monitored airspace and the beamwidth. search A tracking beam request list L is constructed based on the surveillance airspace frame period and the radar event scheduling period. track Confirm Beam Request List L confirm Loss of Beam Request List L lost Based on the radar event scheduling cycle and beam dwell time, construct the current and next cycle execution event list L. event A list of typical tracking time intervals L is set according to the radar event scheduling cycle. Tinterval Used to adaptively adjust the target tracking time interval; calculate the state prediction covariance matrix of the target tracking filter under different time intervals, and the maximum time interval that meets the expected threshold is the appropriate tracking time interval; arrange the beam request list of each event in order of priority to the current next cycle execution event list; update the beam request list of each radar event.

[0073] The process involves determining the airspace surveillance area of ​​the phased array radar based on the actual application scenario, specifically the azimuth and elevation angle ranges covered by the phased array radar beams. The azimuth and elevation beamwidths are determined based on the size of the phased array radar array. The phased array radar array coordinate system is then transformed to a sinusoidal space coordinate system, and the beam positions are arranged in sinusoidal space, with three options: array, interleaved, and low-loss. Next, the search beam positions in the sinusoidal space coordinate system are transformed back to the radar array coordinate system, resulting in a list of search beam positions covering the entire surveillance airspace. The number N of airspace beam position arrangements is recorded. beam .

[0074] Furthermore, set the tracking beam request list L trackConfirm Beam Request List L confirm Loss of Beam Request List L lost Initially empty, search beam request list L search The beams are filled in according to the order of radar search positions, and the number of beam requests included is equal to the number of airspace positions N. beam .

[0075] The transitions between the various radar events mentioned above and the execution of related operations include:

[0076] Search event to confirmation event: If a spot is detected in the search beam and the signal-to-noise ratio reaches the detection threshold, a confirmation beam needs to be arranged, and the 2 / 3 logic method is started to determine whether the track initiation can be completed.

[0077] Confirmation event to tracking event: If the target is detected in two or more of the three confirmation beam illuminations, a tracking beam needs to be arranged to establish the target's motion trajectory and initialize the Kalman filter parameters;

[0078] Tracking event turning into a tracking event: If the tracking beam fails to detect the target twice in a row, a tracking beam needs to be arranged to expand the beam coverage at the target's predicted location and search for the target again.

[0079] Loss of tracking event to tracking event: If the target is detected again in the prediction area and track association is successfully completed, a tracking beam needs to be arranged, the target motion track information needs to be updated, and the parameters of the Kalman filter need to be updated.

[0080] Furthermore, the radar event scheduling period T is determined based on the actual application scenario. s and the airspace monitoring frame period T scan Calculate the average number N of routine searches that need to be scheduled in each scheduling cycle. SRB ,Right now

[0081]

[0082] in, This indicates the rounding up operation.

[0083] Calculate the total number N of various beam requests. total :N total =N search +N track +N confirm +N lost .

[0084] Specifically, the priorities of various radar events are shown in Table 1 below.

[0085] Table 1 Priority of Radar Events

[0086] Radar incident Tracking events Confirmation event Loss of contact incident Search event Priority 1 2 3 4

[0087] Furthermore, a list of execution events for the current and next cycle is established to store the beam requests L corresponding to radar events within the current and next scheduling cycle. event It is initialized to empty.

[0088] The maximum number of beam requests in each scheduling cycle is N. max The calculation method is as follows

[0089] in, T represents rounding down. dwell The beam dwell time for each beam.

[0090] Furthermore, the event list for the next cycle is populated according to the priority of radar events, prioritizing target tracking. If the number of targets is too large, all radar resources are used for target tracking, abandoning the search function. The maximum number of targets that can be tracked is N. max That is, all beam requests within a scheduling cycle are used for tracking.

[0091] The remaining time in the next scheduling cycle will be used for routine search events, i.e.

[0092]

[0093] in, This refers to the actual routine search events scheduled for the next scheduling cycle, which is typically less than the average number N of routine searches that need to be scheduled in each scheduling cycle. SRB Because the above takes into account rounding up and down, if there is still time remaining in the next scheduling cycle, but it is less than the beam dwell time of one wave position, no radar events will be scheduled.

[0094] Furthermore, the time intervals between confirmation events, tracking loss events, and search events are fixed, all being the radar event scheduling period T. s This means that track initiation and re-tracking of lost targets need to be completed in the shortest possible time. For tracking events, an appropriate tracking time interval is selected based on the state covariance matrix of the target's tracking filter, as detailed below.

[0095] Step 1: Pre-define a list of typical tracking time intervals L Tinterval ={T1,T2,...,T n The elements are arranged in ascending order from smallest to largest, and the desired tracking threshold is set. Set the initial interval time. Where T is the interval time series. i =i·T s ,i=1,2,...,n.

[0096] Normally, a threshold is selected. It is a linear function of the noise covariance R. Where λ is adjustable according to the tracking accuracy.

[0097] Step 2: Calculate the prediction part of the Kalman filter to calculate different time intervals T. i Prediction error covariance P of maneuvering targets i (k|k-1). The calculation steps are as follows:

[0098] State prediction:

[0099] Prediction error covariance matrix: P i (k|k-1)=Φ i P i (k-1|k-1)Φ i T +Q;

[0100] Where, Φ i (k-1) is the state transition matrix, and Q is the prediction noise covariance matrix.

[0101] Step 3: Adjust the interval time T i Optimization is performed to select an interval time that meets the desired tracking threshold. The interval time of the previous sampling interval is used as the initial interval time, and it is determined whether the desired tracking threshold is met based on the following criteria:

[0102] like Then, the interval time is traversed to the right, and the largest interval time that satisfies the expected tracking threshold is found among the larger interval time times, which is used as the interval time for the next cycle.

[0103] like Then, the interval is iterated to the left until an interval that meets the expected tracking threshold is found, which is then used as the interval for the next cycle.

[0104] If none of the intervals that meet the expected tracking threshold are found after iterating through all the intervals, then the smallest interval in the interval group is selected as the interval for the next cycle.

[0105] Step 4: Select the interval time from Step 3 and perform the Kalman filtering algorithm to complete the subsequent filtering process. The main calculation process includes:

[0106] Calculate the Kalman gain: K(k) = P(k|k-1)H T [HP(k|k-1)H T +R] -1 ;

[0107] Update the state vector:

[0108] Calculate the filter state covariance matrix: P(k|k)=[IK(k)H(k)]P(k|k-1);

[0109] Where k is the sequence number corresponding to the current interval time, H is the observation matrix, and R is the measurement noise covariance matrix.

[0110] Furthermore, after calculating the optimal tracking time interval for all targets at the current moment, radar event scheduling begins, populating the list of events to be executed in the next cycle. The specific steps are as follows:

[0111] First, for beam requests in the tracking event list, determine and calculate the tracking time interval list L. Tinterval If i is 1, add the trace event to the current next cycle execution event list and delete it from the trace event list. Otherwise, keep the trace event in the trace event list and decrement i by 1, and carry it over to the next cycle for judgment on whether to process it.

[0112] Second, for beam requests in the confirmation event list, add them to the current next cycle execution event list and remove them from the confirmation event list.

[0113] Third, for beam requests in the list of events that have lost track of a beam, add them to the list of events to be executed in the next cycle, and remove them from the list of events that have lost track of a beam.

[0114] Fourth, for beam requests in the search event list, add them sequentially from the beginning to the execution event list for the next cycle, until the maximum number of beam requests N allowed per scheduling cycle is reached. max Furthermore, for search events added to the current next cycle execution event list, they need to be deleted from the head of the search event list and added to the tail of the list to ensure the continuity of the search wave position.

[0115] Through the above process, this embodiment of the invention first constructs multiple beam request lists based on the monitored airspace, and sets a tracking time interval list. The optimal interval is selected by calculating the covariance matrix using Kalman filtering. Events are arranged to the execution list according to priority, and the list is updated after execution. This completes the arrangement of the beam request list for the current and next cycle, as well as the updating of the beam request lists for each radar event, achieving reasonable allocation of radar resources and improving target tracking and search efficiency.

[0116] In one application scenario, the adaptive tracking time interval phased array radar resource scheduling method proposed in this embodiment of the invention is used to perform adaptive tracking and resource scheduling for an airport radar monitoring system. Specifically, this may include the following steps:

[0117] The first step is initialization and parameter settings.

[0118] Specifically, firstly, based on the actual range and requirements of the airport airspace, the azimuth (0° to 360°) and elevation (-10° to +20°) angular ranges that the phased array radar needs to monitor are determined. Based on the radar array size and performance parameters, the beamwidths in the azimuth and elevation directions are set (e.g., 1° azimuth, 2° elevation). The beam positions are arranged in a sinusoidal spatial coordinate system, selecting an array-type arrangement to optimize beam coverage. The search beam positions in sinusoidal space are then transformed to the radar array coordinate system, generating a list of search beam positions covering the entire monitored airspace, and the number of beam positions in the airspace is recorded (e.g., 1000 beam positions).

[0119] Furthermore, based on radar performance and actual needs, the radar event scheduling cycle is set to 1 second and the airspace surveillance frame cycle to 10 seconds, ensuring both timely response to target dynamics and effective utilization of radar resources.

[0120] The second step is to construct the beam request list.

[0121] Specifically, a beam search request list containing 1000 beam requests is constructed according to the order of radar beam searches. Each request records a unique beam ID, α and β angles in sinusoidal space, beam off-axis and rotation angles in the antenna array coordinate system, beam azimuth and elevation angles in the radar station coordinate system, and the corresponding beam control code (used to control the phase shift of each TR element in the phased array radar). The tracking request list, confirmation request list, and lost-track beam request list are initially empty and are gradually filled as the radar operates.

[0122] The third step is to adaptively adjust the tracking time interval.

[0123] Specifically, based on the radar event scheduling cycle, a typical list of tracking time intervals is set, such as [0.5, 1, 1.5, 2, 2.5] seconds, with elements arranged in ascending order to provide diverse tracking options. For each tracked target, a Kalman filter is used to predict its state (including position, velocity, etc.) at the next moment, and the state prediction covariance matrix under different tracking time intervals is calculated. This step is crucial for adaptively adjusting the tracking time interval.

[0124] Furthermore, a linear function of the measurement noise covariance is used as the desired tracking threshold, which can be adjusted according to the tracking accuracy requirements. The list of tracking time intervals is iterated through, and the largest time interval that satisfies the desired tracking threshold is selected as the appropriate tracking time interval. For example, for a certain target, if the calculated state prediction covariance matrix at a 1.5-second time interval is less than the threshold, then 1.5 seconds is selected as the tracking time interval for that target.

[0125] The fourth step is radar event priority scheduling.

[0126] Specifically, based on the radar event scheduling cycle (1 second) and the airspace surveillance frame cycle (10 seconds), the average number of routine searches that need to be scheduled in each scheduling cycle is calculated to be 10. Assuming that the beam dwell time of each beam is 0.1 seconds, the maximum number of beam requests in each scheduling cycle is 10 (1 second / 0.1 seconds = 10, rounded down).

[0127] Furthermore, the beam requests in the tracking event list are checked. If the tracking time interval condition is met (e.g., the beam request is first in the list), it is added to the execution event list for the next cycle and removed from the tracking event list. If the condition is not met, it is retained and carried over to the next cycle, while the count is decremented by 1.

[0128] Furthermore, if a point is detected in the search beam and the signal-to-noise ratio reaches the detection threshold, a confirmation beam is arranged, and the 2 / 3 logic method is initiated to determine the start of the track. The confirmation event is added to the current next cycle execution event list and then removed from the confirmation event list. If the tracking beam fails to detect the target twice consecutively, a tracking loss beam is arranged, and the beam coverage is expanded at the target's predicted location to re-search for the target. The tracking loss event is added to the current next cycle execution event list and then removed from the tracking loss event list.

[0129] Furthermore, beam requests from the search event list are added sequentially to the execution event list for the next cycle until the maximum number of beam requests (10) is reached. For added search events, they are deleted from the head of the search event list and added to the tail to ensure the continuity of search beams.

[0130] Furthermore, if there is remaining time in the current scheduling cycle (less than the beam dwell time for one beam position), no further radar events will be scheduled to avoid resource waste and ensure efficient system operation. After all radar events have been executed in the current scheduling cycle, the beam request list for each radar event is updated, processed requests are removed, and new requests are added based on the actual execution status. The execution results of the current cycle are fed back to the tracking filter to adjust the target state estimation, providing an accurate basis for resource scheduling in the next scheduling cycle.

[0131] Through the above process, the airport radar monitoring system significantly improves the search efficiency for new targets within the airspace while ensuring stable tracking of already detected targets. Simultaneously, the adaptive tracking time interval adjustment mechanism effectively enhances radar resource utilization, reduces system energy consumption, and extends equipment lifespan. It also enhances the system's flexibility and robustness, enabling it to better cope with complex and ever-changing airspace environments.

[0132] The following are embodiments of the apparatus of the present invention, which can be used to execute the phased array radar resource scheduling method with adaptive tracking time interval involved in the present invention. For details not disclosed in the embodiments of the apparatus of the present invention, please refer to the method embodiments of the phased array radar resource scheduling method with adaptive tracking time interval involved in the present invention.

[0133] Please see Figure 3 This invention provides a phased array radar resource scheduling device 800 with adaptive tracking time interval.

[0134] The phased array radar resource scheduling device 800 with adaptive tracking time interval includes, but is not limited to: initialization setting module 810, interval adjustment module 830, resource scheduling module 850 and list optimization module 870.

[0135] The initialization setting module 810 is used to determine the airspace area based on the radar's monitoring range and beamwidth, define the radar event scheduling cycle and airspace monitoring frame cycle, and initialize the radar event beam request list; the beam request list includes a tracking beam request list, a confirmation beam request list, a lost-track beam request list, and a search beam request list.

[0136] The interval adjustment module 830 is used to set a set of standard tracking time interval lists according to the scheduling cycle of radar events, use filters to calculate the state prediction covariance matrix under different time intervals, and adaptively adjust the tracking time interval list according to the state prediction covariance matrix to obtain the optimal tracking time interval.

[0137] The resource scheduling module 850 is used to define the priority order of radar events, arrange the events in each beam request list to the current next cycle execution event list according to the priority order, and execute radar events according to the optimal tracking time interval; radar events include tracking events, confirmation events, tracking loss events, and search events.

[0138] The list optimization module 870 is used to update the request list of each beam by removing processed requests and adding new requests after all radar events have been executed in the current scheduling cycle. It dynamically adjusts and optimizes the scheduling plan for the next cycle based on the actual execution and radar resource usage.

[0139] It should be noted that the adaptive tracking time interval phased array radar resource scheduling provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the adaptive tracking time interval phased array radar resource scheduling device will be divided into different functional modules to complete all or part of the functions described above.

[0140] Furthermore, the adaptive tracking time interval phased array radar resource scheduling device and the adaptive tracking time interval phased array radar resource scheduling method provided in the above embodiments belong to the same concept. The specific way each module performs its operation has been described in detail in the method embodiments, and will not be repeated here.

[0141] Figure 4 A schematic diagram of the structure of an electronic device according to an exemplary embodiment is shown.

[0142] It should be noted that this electronic device is merely an example adapted to the present invention and should not be construed as providing any limitation on the scope of use of the present invention. Furthermore, this electronic device should not be interpreted as requiring or depending on having... Figure 4 One or more components of the exemplary electronic device 2000 shown.

[0143] The hardware structure of electronic devices 2000 can vary significantly due to differences in configuration or performance, such as... Figure 4 As shown, the electronic device 2000 includes: a power supply 210, an interface 230, at least one memory 250, and at least one central processing unit (CPU) 270.

[0144] Specifically, power supply 210 is used to provide operating voltage for various hardware devices on electronic device 2000.

[0145] Interface 230 includes at least one wired or wireless network interface 231 for interacting with external devices. Of course, in other examples adapted to this invention, interface 230 may further include at least one serial-to-parallel conversion interface 233, at least one input / output interface 235, and at least one USB interface 237, etc. Figure 4 As shown, this does not constitute a specific limitation.

[0146] The memory 250 serves as a carrier for resource storage and can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it include the operating system 251, application programs 253, and data 255, etc., and the storage method can be temporary storage or permanent storage.

[0147] The operating system 251 is used to manage and control the various hardware devices and application programs 253 on the electronic device 2000, so as to enable the central processing unit 270 to perform calculations and processing on the massive data 255 in the memory 250. It can be Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0148] Application 253 is a computer-readable instruction based on operating system 251 that performs at least one specific task, and may include at least one module ( Figure 4 (Not shown), each module may contain computer-readable instructions for electronic device 2000. For example, the phased array radar resource scheduling device with adaptive tracking time interval can be regarded as application program 253 deployed on electronic device 2000.

[0149] Data 255 may be signal information, etc., and is stored in memory 250.

[0150] The central processing unit 270 may include one or more processors and is configured to communicate with the memory 250 via at least one communication bus to read computer-readable instructions stored in the memory 250, thereby performing operations and processing on massive amounts of data 255 stored in the memory 250. For example, a phased array radar resource scheduling method with adaptive tracking time intervals can be implemented by the central processing unit 270 reading a series of computer-readable instructions stored in the memory 250.

[0151] Furthermore, the present invention can also be implemented through hardware circuits or a combination of hardware circuits and software. Therefore, the implementation of the present invention is not limited to any specific hardware circuit, software, or combination thereof.

[0152] Please see Figure 5 This invention provides an electronic device 4000, which may include: a desktop computer, a laptop computer, a server, etc., with sensor recognition capabilities.

[0153] exist Figure 5 In this context, the electronic device 4000 includes at least one processor 4001 and at least one memory 4003.

[0154] The data interaction between the processor 4001 and the memory 4003 can be achieved through at least one communication bus 4002. This communication bus 4002 may include a path for transmitting data between the processor 4001 and the memory 4003. The communication bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0155] Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0156] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0157] The memory 4003 may be a ROM (Read-Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or it may be an EEPROM (Electrically Erasable Programmable Read-Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program instructions or code in the form of instructions or data structures and accessible by the electronic device 4000, but not limited thereto.

[0158] The memory 4003 stores computer-readable instructions, and the processor 4001 can read the computer-readable instructions stored in the memory 4003 through the communication bus 4002.

[0159] The computer-readable instructions are executed by one or more processors 4001 to implement the phased array radar resource scheduling method with adaptive tracking time interval in the above embodiments.

[0160] Furthermore, this embodiment of the invention provides a storage medium storing computer-readable instructions, which are executed by one or more processors to implement the phased array radar resource scheduling method with adaptive tracking time interval as described above.

[0161] This invention provides a computer program product, which includes computer-readable instructions stored in a storage medium. One or more processors of an electronic device read the computer-readable instructions from the storage medium, load and execute the computer-readable instructions, thereby enabling the electronic device to implement the phased array radar resource scheduling method with adaptive tracking time interval as described above.

[0162] Compared with related technologies, the beneficial effects of the present invention are:

[0163] 1. This invention can significantly improve radar resource utilization; by adaptively adjusting the tracking time interval, radar resources are dynamically allocated according to the target status, avoiding resource waste or target loss caused by fixed time intervals, and ensuring optimal balance between tracking and search tasks.

[0164] 2. This invention has stronger target tracking stability; by calculating the state prediction covariance matrix of the target tracking filter at different time intervals, the maximum time interval not exceeding a set threshold is selected as the appropriate tracking time interval, thereby achieving stable tracking without losing the target.

[0165] 3. This invention can shorten the airspace search time; by reserving more phased array resources for search tasks, it accelerates the search speed of the monitored airspace while ensuring target tracking, improves the radar's ability to detect new targets, and enhances the timeliness of airspace monitoring.

[0166] 4. This invention offers greater flexibility and adaptability; by setting a list of typical tracking time intervals and dynamically adjusting them according to actual application scenarios, the radar system can flexibly respond to different target characteristics and airspace environments, thereby improving the system's adaptability and robustness.

[0167] 5. This invention can reduce system energy consumption; by optimizing radar resource allocation and avoiding unnecessary long-term tracking or frequent searching, it reduces the energy consumption of the radar system, extends the service life of the equipment, and conforms to the design concept of green energy saving.

[0168] 6. This invention improves multi-target processing capabilities; through a priority scheduling mechanism, it ensures that when there are many targets, high-priority targets are prioritized for tracking, while search tasks are rationally arranged, effectively improving the radar system's processing capabilities in multi-target environments.

[0169] 7. This invention enhances the real-time performance and accuracy of the system; by calculating the target state prediction and covariance matrix in real time and dynamically adjusting the tracking time interval, the radar system can respond to target changes more quickly, improving the real-time performance and accuracy of tracking and searching.

[0170] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0171] The above description is only a partial embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for resource scheduling of phased array radar with adaptive tracking time interval, characterized in that, The method includes: The airspace area is determined based on the radar's monitoring range and beamwidth, and the scheduling period and airspace monitoring frame period of radar events are defined. The beam request list of the radar events is initialized. The beam request list includes a tracking beam request list, a confirmation beam request list, a lost-track beam request list, and a search beam request list. A set of standard tracking time interval lists is set according to the scheduling cycle of the radar events. The state prediction covariance matrix under different time intervals is calculated using a filter. The tracking time interval list is adaptively adjusted according to the state prediction covariance matrix to obtain the optimal tracking time interval. Define the priority order of the radar events, arrange the events in each of the beam request lists into the current next cycle execution event list according to the priority order, and execute the radar events according to the optimal tracking time interval; the radar events include tracking events, confirmation events, tracking loss events, and search events; After all radar events are executed within the current scheduling cycle, the beam request list is updated by removing processed requests and adding new requests. The scheduling plan for the next cycle is dynamically adjusted and optimized based on the actual execution and radar resource usage.

2. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The process of determining the airspace region based on the radar's monitoring range and beamwidth, defining the radar event scheduling period and airspace monitoring frame period, and initializing the radar event beam request list includes: Based on the radar's monitoring range parameters and beamwidth values, the required comprehensive monitoring airspace range is calculated, and the radar event scheduling cycle and airspace monitoring frame cycle are determined. The radar event scheduling cycle refers to the duration of the radar event arrangement and execution cycle; the airspace monitoring frame cycle refers to the duration of the complete monitoring scan of the monitored airspace. The radar event beam request list is initialized; the search beam request list is used to record beam requests that need to perform search tasks; the tracking beam request list is used to store beam requests that need to track targets; the confirmation beam request list is used to record beam requests that need to confirm the status of targets; and the loss-of-track beam request list is used to record beam requests that have lost tracking of targets.

3. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The step of setting a standard tracking time interval list based on the scheduling cycle of the radar events includes: The time intervals are selected as integer multiples of the scheduling period of the radar event as the time interval options in the tracking time interval list, and the time interval options are arranged in ascending order to obtain a standard tracking time interval list; the tracking time interval list includes multiple radar tracking target time interval options.

4. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The process of using a filter to calculate the state prediction covariance matrix at different time intervals, and adaptively adjusting the tracking time interval list based on the state prediction covariance matrix to obtain the optimal tracking time interval includes: A Kalman filter is used to calculate the target's state prediction covariance matrix for each of the time interval options in the tracking time interval list; the state prediction covariance matrix is ​​used to reflect the degree of uncertainty in the target's state prediction. Using a linear function of the measurement noise covariance as a threshold, the state prediction covariance matrix is ​​compared with the threshold, and the maximum time interval not exceeding the set threshold is selected from the tracking time interval list as the optimal tracking time interval.

5. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The definition of the priority order of the radar events, the arrangement of events in each of the beam request lists into the current next cycle execution event list according to the priority order, and the execution of the radar events according to the optimal tracking time interval include: The priority order of the radar events is determined from high to low as tracking events, confirmation events, loss of tracking events, and search events. Events in the beam request list of the tracking events that meet the optimal tracking time interval are arranged to be executed in the next cycle's event list. Add all the beam request lists of the confirmed events and the beam request lists of the lost events to the current next cycle execution event list, and add the search events in order until the maximum number of beam requests for the current next cycle is reached. The highest priority tracking event is executed according to the priority order and the optimal tracking time interval. After execution, the processed request is removed from the corresponding event list, and the new related request is added to the beam request list of the corresponding radar event.

6. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The process of updating each beam request list by removing processed requests and adding new requests, and dynamically adjusting and optimizing the scheduling plan for the next cycle based on actual execution and radar resource usage, includes: The first beam request in the beam request list corresponding to the tracked event is added to the current next cycle execution event list and removed from the tracked event list; otherwise, it is carried over to the next cycle execution event list. Add the beam request corresponding to the confirmation event to the current next cycle execution event list and delete it from the confirmation event list. Transfer the beam request corresponding to the tracking failure event to the current next cycle execution event list and delete it from the tracking failure event list. The beam requests corresponding to the search events are added to the execution event list of the next cycle in sequence until the maximum number of beam requests allowed in the next cycle is reached. The added beam requests are then moved from the head to the tail of the beam request list corresponding to the search events.

7. The phased array radar resource scheduling method with adaptive tracking time interval as described in claim 1, characterized in that, The method further includes: When the search beam corresponding to the search event detects a spot and the signal-to-noise ratio reaches the detection threshold, the 2 / 3 logic method is activated to determine whether the track initiation can be completed. If it can be completed, the search event is converted into a confirmation event. When the probability of the confirmation beam corresponding to the confirmation event detecting the target is greater than a set value, a target motion track is established, the Kalman filter parameters are initialized, and the confirmation event is converted into a tracking event; If the tracking beam corresponding to the tracking event fails to detect the target twice consecutively, the search range is expanded. If the target is detected again and track association is completed, the tracking event is converted into a tracking failure event, and the target track and Kalman filter parameters are updated.

8. A phased array radar resource scheduling device with adaptive tracking time interval, characterized in that, The device includes: The initialization setting module is used to determine the airspace area based on the radar's monitoring range and beamwidth, define the scheduling period of radar events and the airspace monitoring frame period, and initialize the beam request list of the radar events; the beam request list includes a tracking beam request list, a confirmation beam request list, a lost-track beam request list and a search beam request list. The interval adjustment module is used to set a set of standard tracking time interval lists according to the scheduling cycle of the radar event, use a filter to calculate the state prediction covariance matrix under different time intervals, and adaptively adjust the tracking time interval list according to the state prediction covariance matrix to obtain the optimal tracking time interval. The resource scheduling module is used to define the priority order of the radar events, arrange the events in each of the beam request lists into the current next cycle execution event list according to the priority order, and execute the radar events according to the optimal tracking time interval; the radar events include tracking events, confirmation events, tracking loss events, and search events; The list optimization module is used to update the beam request list by removing processed requests and adding new requests after all radar events have been executed in the current scheduling cycle, and to dynamically adjust and optimize the scheduling plan for the next cycle based on the actual execution and radar resource usage.

9. An electronic device, characterized in that, include: At least one processor and at least one memory, wherein, The memory stores computer-readable instructions; The computer-readable instructions are executed by one or more of the processors, causing the electronic device to implement the phased array radar resource scheduling method with adaptive tracking time interval as described in any one of claims 1 to 7.

10. A storage medium having computer-readable instructions stored thereon, characterized in that, The computer-readable instructions are executed by one or more processors to implement the phased array radar resource scheduling method with adaptive tracking time interval as described in any one of claims 1 to 7.

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