CN112130978A - Unmanned platform-borne multifunctional radar task comprehensive priority calculation method - Google Patents
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Abstract
The invention provides a comprehensive priority calculation method for an unmanned platform-borne multifunctional radar task, which provides a basis for the comprehensive priority calculation of the task by constructing a full life cycle task model; by introducing manual control factors, a comprehensive priority calculation formula containing 6 factors such as manual command marks, task type priorities, target threat degrees, task deadline times, task expected execution times, task delay times and the like is constructed, and a priority factor index function and a weight coefficient calculation method are provided. The invention realizes the unified scheduling of the system automatic initiation task and the manual control command (including the task).
Description
Technical Field
The invention belongs to the technical field of radars.
Background
The advantages of unmanned platforms such as unmanned ships, unmanned vehicles, unmanned planes, unmanned underwater vehicles and the like are highlighted since the century. And sensors such as radar, photoelectric and sonar are the basis for the unmanned platform to function. Phased array radars are widely studied and used for their flexible beam agility and thus multitasking capabilities. Modern phased array radars are developing towards the trend of multifunctional integration, software, intellectualization and networking. The radar function is developed from traditional distance measurement and positioning towards integration of multiple functions such as detection, investigation, communication, electromagnetic interference, fire control, guidance and the like; its physical form also develops towards multi/wideband, multi-aperture integrated systems, such as Dual Band radar suite (e.g. AMDR radar by thunder, KRONOS Dual Band radar by leinna).
The resource management of the multifunctional radar is very critical, and generally comprises the following links: working mode control, hardware resource dynamic reconstruction, work task aperture-oriented distribution, task scheduling and space wave position arrangement. The design of these functional links is closely related to the working environment, the working object and the working content.
The unmanned platform carries the multi-functional radar and generally supports the operation modes such as manual remote control/autonomous control. Therefore, the realization of autonomous switching of working modes, autonomous planning of tasks and adaptive scheduling of tasks is required. However, due to the characteristics of dangerousness, concealment, long-term performance and the like of the unmanned platform operation, and the characteristics of dynamic performance and complexity of the operation environment and the target object, the unmanned platform-mounted multifunctional radar faces the actual situations of frequent switching of working modes, need of manual intervention for adding and deleting tasks and the like, and even further relates to the problem of ethical offensiveness. This is not fully qualified for near-phase machine decisions.
In documents such as a phased array radar task comprehensive priority computing method (publication number: CN 103605870A), a wide beam frequency conversion time difference positioning system resource scheduling method (publication number: CN 103593244A), a rotary phased array radar multi-type task priority dynamic decision model (publication number CN109885394A) and the like, the task priority model for task scheduling considers the task type priority, the importance degree of tasks in the same type of tasks (usually represented by target threat degree), the expected task execution time, the task deadline, the task duration, the task delay time and other factors, but does not consider the manual intervention factor in a special period. Moreover, the existing task priorities are all used for task scheduling, and no task comprehensive priority model can be simultaneously applied to three links of work mode assistant decision, task planning and task scheduling.
Therefore, the existing task priority model cannot meet the requirements of the unmanned platform for realizing three functions of auxiliary decision of a working mode, task planning, task scheduling and the like of the multifunctional radar.
Disclosure of Invention
The invention provides a task comprehensive priority calculation method for an unmanned platform-mounted multifunctional radar, which aims to solve the problem that the unmanned platform-mounted multifunctional radar automatically initiates tasks and uniformly schedules manual control commands.
The technical scheme of the invention is as follows:
s1: analyzing and enumerating all possible task types and parameter types thereof according to the function of the unmanned platform-carried multifunctional radar, determining a unified full-life-cycle task model, and performing parameter assignment on each task;
s2: selecting a task comprehensive priority factor according to a task planning strategy and a resource scheduling strategy of the unmanned platform-borne multifunctional radar;
s3: calculating each priority index function according to the influence rule of each factor on the comprehensive priority;
s4: constructing a mathematical formula according to the mission and task scheduling strategies of the multifunctional radar, and calculating the weight coefficient of each priority factor;
s5: and substituting the weight coefficient and each priority index function into the task comprehensive priority expression to obtain the comprehensive priority of each task. Further, the full-life-cycle task model in step S1 includes the following parameter sets: task type, time parameter set, waveform parameter set, beam parameter set, target threat level, manually specified task flag.
Further, the task comprehensive priority factor in step S2 includes: manual command flags, task type priority, target threat level, task deadline, task expected execution time, and task delay time.
Further, in step S3, priority factors of different dimensions are mapped to a dimensionless data space by using a sorting method, and a parameter value range is adjusted to a [0,1] interval by normalizing a maximum value, so as to obtain an index function value of each priority factor:
(1) artificial command mark index function f1(Comk)：
f1(Comk)＝Comk
(2) Task type priority index function f2(TskClak)：
Pre-designing a priority distribution table of all task types, wherein each task type has an original task priority value, and the larger the value is, the higher the priority is; normalizing the original task type priority of each task to the maximum value in the priority table to obtain a task type priority parameter value;
(3) target threat level index function f3(TagDisk)：
Arranging the threat degrees from small to large according to the result obtained by the threat degree calculation formula, wherein the obtained sequence number is the parameter value; the larger the value is, the larger the threat degree is;
(4) index function of cut-off time f4(DthTk)：
The M tasks are arranged from large to small according to the deadline to obtain a sequence, and the sequence number is larger as the time is closer; normalizing the obtained serial number relative to the maximum serial number value to obtain a deadline parameter; the larger the value is, the higher the priority is; tasks whose deadline is less than the minimum time of the current scheduling interval are discarded;
(5) expected execution time index function f5(ExpTk)：
Arranging the M tasks in a reverse order according to expected execution time, wherein the sequence number is larger when the time is closer; normalizing the obtained sequence number relative to the maximum sequence number value to obtain an arrival time parameter; the larger the value is, the higher the priority is;
(6) task delay time index function f5(DeLTk)：
The delay task is that the current time of the system exceeds the expected execution time of the task, but the deadline of the task is not exceeded; the delay time is equal to the current time minus the expected execution time; the tasks are arranged from small to large according to the delay time, and the longer the delay is, the larger the serial number is; normalizing the delay sequence number to the maximum sequence number value to obtain a delay parameter; the larger the delay parameter, the higher the priority.
Further, the mathematical formula of step S4 is:
further, the task comprehensive priority expression in step S5 is as follows:
Pk＝w1f1(Comk)+w2f2(TskClak)+w3f3(TagDisk)+w4f4(DthTk)+w5f5(ExpTk)+w6f6(DelTk)
wherein ComkAssigning a task designation to the person; TskClakIs task type priority; TagDiskTarget threat levels; DthTk: stopping the execution time of the task; ExpTkExpecting an execution time for the task; delt (DeLT)kA task delay time; f. of1，f2，f3，f4，f5，f6Sequentially providing index functions corresponding to a manual command mark, a task type, a target threat degree, a task deadline, a task expected execution time and a task delay time; omega1，ω2，ω3，ω4，ω5，ω6Weight coefficients corresponding to index function items of a manual command mark, a task type, a target threat degree, a task deadline time, a task expected execution time and a task delay time are sequentially set; pkThe integrated priority of the kth target, k is 1,2, …, and M is the total number of tasks.
The invention has the beneficial effects that: by providing a full-life-cycle task model and a task comprehensive priority calculation method, the problem of unified scheduling of automatically initiating tasks in the process of manually controlling commands and situational awareness of the multifunctional radar carried by the unmanned platform is solved. The method provides a manual intervention mechanism for the self-adaptive task scheduling of the multifunctional radar carried by the unmanned platform, and is beneficial to improving the working efficiency and safety of the multifunctional radar of the unmanned platform; a unified task priority computing method is provided for unmanned platform-borne multifunctional radar working mode decision, task planning and task scheduling, and system design is simplified.
Drawings
FIG. 1 is a task full lifecycle evolution process of the present invention;
FIG. 2 is a distribution network of task integration priorities to factors of the present invention;
FIG. 3 is a flow chart of a task synthesis priority calculation method of the present invention.
Detailed Description
The technical solution of the present invention is further explained with reference to the drawings and the embodiments.
The invention provides a task comprehensive priority calculation method of an unmanned platform-borne multifunctional radar, which comprises the following implementation processes:
s1: and analyzing and enumerating all possible task types and parameter types thereof according to the function of the unmanned platform-carried multifunctional radar, determining a unified full-life-cycle task model, and performing parameter assignment on each task.
The radar task is a series of time-bounded radar event sequences, the mathematical model of which is a set of characteristic parameters.
In terms of task categories, each function may contain multiple task types. The search dwell of each wave position is regarded as a search task; probe beams for different types/distances of objects at the same spatial wave position are considered different tasks.
In the task processing process, the following stages are included: initiating a task, analyzing the task and completing parameters, accepting or rejecting the task, distributing the task facing to equipment, scheduling the task at the equipment level and executing the task. The task form aspect comprises the following steps: original task request, updated task request, task to be allocated, task to be scheduled, executable task/deferred task/deleted task. The invention refers to the whole task form set evolved in the task processing process as the whole life cycle of the task.
The task parameters related to the task full life cycle are summarized into four main categories:
1) the task characteristic parameters mainly comprise task types and comprehensive priorities;
2) the characteristic parameters of the operation object mainly comprise target threat degree;
3) radar system control parameters including task type, time parameter, pulse waveform parameter, and beam parameter;
4) the manual control parameters mainly comprise manual control marks.
A certain unmanned platform multifunctional radar is supposed to have the functions of air and sea detection, investigation, electromagnetic interference, communication and the like, and three working modes of warning, investigation and synthesis exist.
These functions are decomposed to obtain all task types and task parameter categories, and task type priorities are designed according to the importance of the tasks, see table 1.
TABLE 1 task types, Critical task parameters and priority Allocation Table
In the design phase, a full lifecycle task model is generated. When the resource management software or the resource scheduling software is implemented in a programming mode, the model corresponds to a structure body of one class. The full lifecycle task model contains the following parameter sets: task type, time parameter set, waveform parameter set, beam parameter set, target threat level, manually specified task flag:
Ri＝{P,Class,Th,T,Sig,Beam,Com}
the meaning of each parameter is as follows:
p: and calculating the comprehensive priority of the tasks in real time. The method can be used for working mode decision, task planning and task scheduling processes.
Class: the type of task. When the system is designed, a task type priority comparison table is designed in advance according to the operation requirement and the operation process rule. And according to the real-time task type, a table can be looked up to obtain the task type priority.
Th: target threat level. The threat degree of the target is generally the result of comprehensive evaluation of situation information such as attack intention, attack capability, shortest time for reaching the multifunctional radio frequency system, included angle and the like of the target.
T: the time parameter set comprises task arrival time Tavi, task expected line time Texp, task duration Tcon, task deadline Tdelay, task delay time Tdelay and actual task execution time Treal.
sig: and the pulse waveform parameter set comprises a transmitting or receiving frequency f, a pulse repetition period PRI and a pulse width tau.
Beam: beam parameter sets including beam pointing (azimuth, elevation), beam dwell time Δ t of the task request. During system design, the operation airspace is divided in advance according to the operation environment, the object characteristics and the operation requirements. According to the azimuth and the pitching information of the real-time task request, the corresponding waveform parameters and the corresponding regional priority can be obtained by looking up the table.
Com: the task flag is manually specified. When the system receives a manual control command or specifies a task, it should be preferentially executed. A Com value of 1 represents a manual control command or a designated task, otherwise, 0.
Assuming that the radar enters a stable communication state and captures 3 batches of targets when working in an alert working mode at a certain moment, the radar automatically initiates 3 air-sea active tracking tasks, 60 air-sea searching tasks and 1 communication task. Meanwhile, the radar receives a manual control command through a communication channel, and the tracking residence time and the tracking data rate of the target 1 are required to be improved, because the target is judged to frequently appear recently by a commander and is possibly higher in threat than the threat of automatic calculation of software. And the manual control command is sent to radar data processing software through system control software, the radar data processing software updates the tracking task parameters of the target with the batch number of 3, and submits the task request to resource management software.
The radar resource management software firstly carries out task analysis on an initiated original task request, establishes a task structural body according to a full life cycle model, extracts original task parameters and assigns the original task parameters to parameters corresponding to the structural body, and then supplements parameters such as delay time, manual control command marks and the like. The method is ready for subsequent links such as task planning (resource pre-estimation and task deletion), task scheduling and the like.
S2: selecting a task comprehensive priority factor according to a task planning strategy and a resource scheduling strategy of the unmanned platform-carried multifunctional radar, wherein the task comprehensive priority factor specifically comprises an artificial command mark ComkTask type priority TskClakTarget threat level TagDiskExpected execution time of task ExpTkTask deadline DthTkTask delay time DelTkAnd the like.
S3: and mapping the priority factors of different dimensions to a dimensionless data space by adopting a sorting method, and regulating the parameter value range to a [0,1] interval by normalizing the maximum value, thereby obtaining the index function value of each priority factor.
It is assumed that the original values of the task integrated priority factor of the current task are shown in table 2. For ease of understanding, the times in the table below are time differences relative to the current system clock.
TABLE 2 task Integrated priority factor value for current task
S4: the following constraint condition expressions are designed according to the task mission and task scheduling principle of the multifunctional radar, and coefficients of the weight factors are calculated through a trial value method.
The values of the weight coefficients of the factors obtained by the test values are as follows:
s5: and substituting the weight coefficient and the value of each parameter into a task comprehensive priority calculation expression to obtain the comprehensive priority of each task. In the software programming implementation, the comprehensive priority calculation function is constructed according to the following model.
Pk＝w1f1(Comk)+w2f2(TskClak)+w3f3(TagDisk)+w4f4(DthTk)+w5f5(ExpTk)+w6f6(DelTk)
The radar resource management software calculates the comprehensive priority of each task according to the task comprehensive priority calculation expression provided by the invention, and then sorts the comprehensive priority of each task according to the size as follows:
P3＞P1＞P2＞P4＞P5-65
if the manual control factor is not considered, the model is calculated according to the following typical conventional task comprehensive priority, and the weight coefficients are the same
Pk＝w2f2(TskClak)+w3f3(TagDisk)+w4f4(DthTk)+w5f5(ExpTk)+w6f6(DelTk)
And calculating the comprehensive priority of each task, wherein the obtained results have the following relation:
P1＞P3＞P2＞P4＞P5-65
therefore, the invention can improve the task execution priority of manual intervention, realize the control of radar control personnel on the working mode decision, task planning and task scheduling process of the unmanned platform-borne multifunctional radar, make up the defects that the judgment of the algorithm and the rule on the complex environment and the target situation is not accurate enough or the situation related to the offence and defense ethics is difficult to deal with, and fully ensure the efficiency and the safety of the unmanned platform-borne multifunctional radar working process.
Claims (6)
1. A comprehensive priority calculation method for unmanned platform-borne multifunctional radar tasks is characterized by comprising the following steps:
s1: analyzing and enumerating all possible task types and parameter types thereof according to the function of the unmanned platform-carried multifunctional radar, determining a unified full-life-cycle task model, and performing parameter assignment on each task;
s2: selecting a task comprehensive priority factor according to a task planning strategy and a resource scheduling strategy of the unmanned platform-borne multifunctional radar;
s3: calculating each priority index function according to the influence rule of each factor on the comprehensive priority;
s4: constructing a mathematical formula according to the mission and task scheduling strategies of the multifunctional radar, and calculating the weight coefficient of each priority factor;
s5: and substituting the weight coefficient and each priority index function into the task comprehensive priority expression to obtain the comprehensive priority of each task.
2. The unmanned platform-based multifunctional radar task comprehensive priority calculation method according to claim 1, characterized in that: the full lifecycle task model in step S1 includes the following parameter sets: task type, time parameter set, waveform parameter set, beam parameter set, target threat level, manually specified task flag.
3. The unmanned platform-based multifunctional radar task comprehensive priority calculation method according to claim 1, characterized in that: the task integrated priority factor in step S2 includes: manual command flags, task type priority, target threat level, task deadline, task expected execution time, and task delay time.
4. The unmanned platform-based multifunctional radar task comprehensive priority calculation method according to claim 1, characterized in that: in step S3, priority factors of different dimensions are mapped to a dimensionless data space by using a sorting method, and a parameter value range is adjusted to a [0,1] interval by normalizing a maximum value, so as to obtain an index function value of each priority factor:
(1) artificial command mark index function f1(Comk)：
f1(Comk)＝Comk
(2) Task type priority index function f2(TskClak)：
Pre-designing a priority distribution table of all task types, wherein each task type has an original task priority value, and the larger the value is, the higher the priority is; normalizing the original task type priority of each task to the maximum value in the priority table to obtain a task type priority parameter value;
(3) target threat level index function f3(TagDisk)：
Obtaining an original threat degree value according to a threat degree calculation formula, wherein the larger the value is, the higher the threat degree is; normalizing the original threat degree value of each task to the maximum threat degree value in the tasks participating in the sequencing to obtain threat degree index function values of a plurality of tasks;
(4) index function of cut-off time f4(DthTk)：
The M tasks are arranged from large to small according to the deadline to obtain a sequence, and the sequence number is larger as the time is closer; normalizing the obtained serial number relative to the maximum serial number value to obtain a deadline parameter; the larger the value is, the higher the priority is; tasks whose deadline is less than the minimum time of the current scheduling interval are discarded;
(5) expected execution time index function f5(ExpTk)：
Arranging the M tasks in a reverse order according to expected execution time, wherein the sequence number is larger when the time is closer; normalizing the obtained sequence number relative to the maximum sequence number value to obtain an arrival time parameter; the larger the value is, the higher the priority is;
(6) task delay time index function f5(DeLTk)：
The delayed task refers to a task of which the current time of the system is greater than the expected execution time and is less than the deadline; the delay time is equal to the current time minus the expected execution time; the tasks are arranged from small to large according to the delay time, and the longer the delay is, the larger the serial number is; normalizing the delay sequence number to the maximum sequence number value to obtain a delay parameter; the larger the delay parameter, the higher the priority.
5. The unmanned platform-based multifunctional radar task comprehensive priority calculation method according to claim 1, characterized in that: the mathematical formula of step S4 is:
6. the unmanned platform-based multifunctional radar task comprehensive priority calculation method according to claim 1, characterized in that: the task comprehensive priority expression in step S5 is as follows:
Pk＝w1f1(Comk)+w2f2(TskClak)+w3f3(TagDisk)+w4f4(DthTk)+w5f5(ExpTk)+w6f6(DelTk)
wherein ComkAssigning a task designation to the person; TskClakIs task type priority; TagDiskTarget threat levels; DthTkEnding the execution time for the task; ExpTkExpecting an execution time for the task; delt (DeLT)kA task delay time; f. of1，f2，f3，f4，f5，f6Sequentially providing index functions corresponding to a manual command mark, a task type, a target threat degree, a task deadline, a task expected execution time and a task delay time; omega1，ω2，ω3，ω4，ω5，ω6Weight coefficients corresponding to index function items of a manual command mark, a task type, a target threat degree, a task deadline time, a task expected execution time and a task delay time are sequentially set; pkThe integrated priority of the kth target, k is 1,2, …, and M is the total number of tasks.
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| CN115856870A (en) * | 2023-02-15 | 2023-03-28 | 南京理工大学 | Variable data rate phased array radar self-adaptive searching and tracking method |
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| CN104899468A (en) * | 2015-06-25 | 2015-09-09 | 中国船舶重工集团公司第七二四研究所 | Multi-parameter geometric model based radar task comprehensive-priority computing method |
| WO2017167025A1 (en) * | 2016-03-28 | 2017-10-05 | 中兴通讯股份有限公司 | Method and device for realizing task scheduling, and computer storage medium |
| CN108734343A (en) * | 2018-05-02 | 2018-11-02 | 电子科技大学 | A kind of phased array beam dwell schedule method based on scheduling benefits and genetic algorithm |
| CN109946687A (en) * | 2019-01-11 | 2019-06-28 | 中国船舶重工集团公司第七二四研究所 | A kind of comprehensive radio frequency system working method decision-making technique of unmanned platform |
| CN111381949A (en) * | 2020-02-14 | 2020-07-07 | 中国人民解放军空军预警学院 | Backtracking strategy-based multifunctional phased array radar task scheduling method |
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| CN114860397A (en) * | 2022-04-14 | 2022-08-05 | 深圳清华大学研究院 | Task scheduling method, device and equipment |
| CN115856870A (en) * | 2023-02-15 | 2023-03-28 | 南京理工大学 | Variable data rate phased array radar self-adaptive searching and tracking method |
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