CN108958918B - Multifunctional radar resource self-adaptive management method based on performance evaluation optimization - Google Patents

Multifunctional radar resource self-adaptive management method based on performance evaluation optimization Download PDF

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CN108958918B
CN108958918B CN201810764765.0A CN201810764765A CN108958918B CN 108958918 B CN108958918 B CN 108958918B CN 201810764765 A CN201810764765 A CN 201810764765A CN 108958918 B CN108958918 B CN 108958918B
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CN108958918A (en
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侯泽欣
吴少鹏
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724th Research Institute of CSIC
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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    • G06F9/4806—Task transfer initiation or dispatching
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    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

The invention belongs to the technical field of multifunctional radars, and particularly relates to a system resource self-adaptive scheduling management method of a multifunctional phased array radar. The invention provides a multifunctional radar resource self-adaptive management method based on performance evaluation optimization by evaluating each scheduling performance and calculating and analyzing the use state of system resources, realizes dynamic self-adaptive calculation of the comprehensive priority of a multifunctional radar task by using a scheduling performance evaluation result and the use state of the current system resources, reasonably arranges task scheduling execution, solves resource conflicts of system aperture, time, energy, frequency and the like, and realizes the self-adaptive management of the system resources.

Description

Multifunctional radar resource self-adaptive management method based on performance evaluation optimization
Technical Field
The invention belongs to the technical field of multifunctional radars, and mainly relates to a system resource self-adaptive scheduling management technology for a multifunctional phased array radar.
Background
The multifunctional radar adopts a phased array system, and realizes multiple functions such as integration by utilizing flexible beam forming capability, various working waveforms and multi-target processing capability. However, as a complex multifunctional sensor device, the multifunctional radar is limited by resources such as aperture, time, energy, frequency, signal processing unit, etc., and the mission and function, environmental situation and target characteristics of various multifunctional radar systems are different, and the multifunctional composition and system resource availability status are also different, so that it is the key point of current technical research to research dynamic real-time multifunctional radar resource self-adaptive management method, effectively adapt to the environmental situation and target characteristics of the immense change, and exert the use performance of the multifunctional radar system to the maximum extent. The resource self-adaptive management method is capable of adapting to dynamic and time-varying working environments and relative priorities of different working modes, and balancing resources such as time, energy and the like required by various radar task requests in real time; a scheduling method for scheduling an optimal sequence of scheduled tasks for each scheduling interval. The primary problem of multifunctional radar resource management is the calculation of the comprehensive priority value of a radar task. At present, most of the existing multifunctional radar system resource self-adaptive management methods adopt a fixed parameter calculation mode to realize task comprehensive priority calculation, but the resource management calculation result revision and the self-adaptive resource matching adjustment based on the current performance evaluation are not carried out according to the real-time environment and target situation, the detection task demand and the possible dynamic change of equipment resources, so that the dynamic real-time effective scheduling of radar resources is difficult to realize.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a multifunctional radar resource self-adaptive management method based on performance evaluation optimization, which is used for performing self-adaptive calculation on the task comprehensive priority of a multifunctional radar, realizing the self-adaptive optimization management of the multifunctional radar task system resources and reasonably distributing various resources of the system.
The technical solution for realizing the purpose of the invention is as follows: by designing a multifunctional radar resource self-adaptive management method based on performance evaluation optimization in the current state, dynamic self-adaptive calculation of comprehensive priorities of multifunctional radar tasks is realized by using a scheduling performance evaluation result and the current system resource use state, task scheduling execution is reasonably arranged, resource conflicts of system apertures, time, energy, frequency and the like are solved, and self-adaptive management of system resources is realized.
The invention has the beneficial effects that: the method can adaptively adjust and calculate the comprehensive priority value of the multifunctional radar task according to the use state of the current system resource and the scheduling performance evaluation result, and reasonably arrange the task scheduling execution sequence, so that the system resource is effectively managed. The method is mainly applied to resource scheduling management of a multifunctional radar system, and has important significance for the technical development and technological progress of modern national defense equipment.
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FIG. 1 is a flow chart of a multifunctional radar resource self-adaptive management method based on performance evaluation optimization.
FIG. 2 evaluates optimized adaptive integrated priority computation based on scheduling performance.
Detailed Description
The implementation process and the flow of the multifunctional radar resource self-adaptive management method based on performance evaluation optimization are shown in the attached figure 1, and are specifically described as the following processes:
step1, initializing, checking the current system resource state, emptying an execution task queue and a deletion task queue, and inquiring a radar application task queue;
step2, taking out the tasks with the expected execution time in the application task queue in the scheduling interval, and calculating the comprehensive priority value of each application task according to a self-adaptive comprehensive priority calculation method based on scheduling performance evaluation optimization to obtain a radar to-be-executed task queue of the scheduling interval;
step3, sequentially taking out the task with the highest comprehensive priority value from the queue to be executed, judging whether the residence time of the task meets the remaining time less than the scheduling interval, if so, determining the executable time range of the task according to the expected execution time and the time window of the task, allocating the actual execution time of the task, and sending the task into the execution task queue if the system resources required by the task are available; when the remaining time of the scheduling interval is not met or the system resource conflict required by the task is met, the Step4 is carried out;
step4, judging whether the latest executable time of the task is satisfied to be executed in the next scheduling interval, if so, sending the task into a delayed task queue, otherwise, sending the task into a deleted task queue;
step5 repeats Step3 and Step4 until the dispatching of the task queue to be executed in the dispatching interval is completed;
step6 scheduling performance evaluation, calculating the system resource use state and scheduling performance evaluation result in the scheduling interval, and feeding back the system resource use state and scheduling performance evaluation result in the scheduling interval to the comprehensive priority calculation method in Step2 to complete the self-adaptive optimization adjustment of the comprehensive priority calculation method;
and Step7, adding the tasks in the delayed task queue into the application task queue, and repeating the steps 2-6 to continue the scheduling management of the next scheduling interval.
The invention discloses a self-adaptive comprehensive priority computing method based on scheduling performance evaluation optimization in Step2, wherein a comprehensive priority computing structure diagram is shown in the attached figure 2, and the method comprises the following concrete implementation steps:
step1 extracting characteristic parameter values xi of taski(ξ1,ξ2,…,ξm)；
Step2 according to the system resource using state and scheduling performance evaluation result rjSelf-adaptive adjustment of weight coefficient magnitude omega of characteristic parameters of each taski＝fi(r1,r2,…,rn) (ii) a Rights systemThe calculation formula of the number is composed of a characteristic parameter xiiAnd system resource and scheduling performance evaluation result rnCorrelation of (2)
Figure GDA0003251641340000021
Determining, as shown in the following formula, that the relevant mapping table is shown in table 1;
Figure GDA0003251641340000031
table 1 mapping table for correlation between task characteristic parameters and system resource usage status and scheduling performance
r1(SSR) r2(HVR) r3(ATSR) r4(TUR) r5(AUR) ……
ξ1(P) c11 c12 c13 c14 c15
ξ2(Td) c21 c22 c23 c24 c25
ξ3(An) c31 c32 c33 c34 c35
…… …… ……
Step3 calculates the comprehensive priority of task by the characteristic parameter values and weight coefficients of the taskValue Ps(ii) a The calculation formula is shown in the following formula.
Figure GDA0003251641340000032
In the formula, xiiValue, ω, representing the ith characteristic parameter of the taskiRepresenting the magnitude of the weight coefficient of the ith characteristic parameter of the task, m representing m task characteristic parameters, rjA value representing the jth system resource use state and scheduling performance evaluation feedback result, cijAnd (3) representing the correlation between the ith characteristic parameter of the task and the jth system resource and scheduling performance evaluation feedback result, wherein n represents the use state of n system resources and the scheduling performance evaluation feedback result.
For example, as shown in table 1, three task characteristic parameters are selected for comprehensive priority calculation, and the task working mode priority P and the residence time TdAnd pore size requirement An. The system resource usage state and Scheduling performance evaluation result includes five items, namely a task Scheduling Success Rate (SSR), a high cost Rate (HVR), an Average Time migration Rate (ATSR), a Time Utilization Rate (TUR), and an Aperture Utilization Rate (AUR), and the weight coefficients of each feature parameter are respectively:
Figure GDA0003251641340000033
the comprehensive priority value of the task is as follows:
Figure GDA0003251641340000034

Claims (1)

1. a multifunctional radar resource self-adaptive management method based on performance evaluation optimization is characterized by comprising the following steps:
step1, initializing, checking the current system resource state, emptying an execution task queue and a deletion task queue, and inquiring a radar application task queue;
step2, taking out the tasks with the expected execution time in the application task queue in the scheduling interval, and calculating the comprehensive priority value of each application task according to a self-adaptive comprehensive priority calculation method based on scheduling performance evaluation optimization to obtain the radar to-be-executed task queue of the scheduling interval, wherein the calculation formula of the comprehensive priority is as follows:
Figure FDA0003251641330000011
in the formula, xiiValue, ω, representing the ith characteristic parameter of the taskiRepresenting the magnitude of the weight coefficient of the ith characteristic parameter of the task, m representing m task characteristic parameters, rjA value representing the jth system resource use state and scheduling performance evaluation feedback result, cijThe correlation between the ith characteristic parameter of the task and the jth system resource and scheduling performance evaluation feedback result is represented, and n represents the use state of n total system resources and the scheduling performance evaluation feedback result;
step3, sequentially taking out the task with the highest comprehensive priority from the queue to be executed, judging whether the residence time of the task meets the remaining time less than the scheduling interval, if so, distributing the actual execution time of the task according to the executable time range of the task, and the task meets the system resource constraint, and sending the task into the execution task queue; when the remaining time of the scheduling interval is not met or the task allocable execution time conflicts with other scheduled task time, the operation goes to Step 4;
step4, judging whether the latest executable time of the task is satisfied to be executed in the next scheduling interval, if so, sending the task into a delayed task queue, otherwise, sending the task into a deleted task queue;
step5 repeats Step3 and Step4 until the dispatching of the task queue to be executed in the dispatching interval is completed;
step6 scheduling performance evaluation, calculating the system resource use state and scheduling performance evaluation result in the scheduling interval, and feeding back the system resource use state and scheduling performance evaluation result in the scheduling interval to the comprehensive priority calculation method in Step2 to complete the self-adaptive adjustment of the comprehensive priority calculation method;
and Step7, adding the tasks in the delayed task queue into the application task queue, and repeating the steps 2-6 to continue the scheduling management of the next scheduling interval.
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CN111381949B (en) * 2020-02-14 2023-07-07 中国人民解放军空军预警学院 Multifunctional phased array radar task scheduling method based on backtracking strategy
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