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Air target autonomous distribution method and system

A technology of aerial target and allocation method, applied in the field of aerial target autonomous allocation method and system

Pending Publication Date: 2022-01-11
中国兵器装备集团自动化研究所有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is: the current air target allocation method cannot satisfy the real-time performance and benefit index optimization at the same time. Time iterative operation to find the optimal solution, easy to fall into the local optimal problem, while satisfying the optimal benefit index

Method used

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  • Air target autonomous distribution method and system
  • Air target autonomous distribution method and system
  • Air target autonomous distribution method and system

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Experimental program
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Embodiment 1

[0055] This embodiment provides a method for autonomous allocation of air targets, which combines the optimal solution method based on the optimal solution of the benefit index and the reasoning method of the expert system based on rules, and is divided into two parts: the creation of the expert system for autonomous allocation of air targets and the solution of the allocation scheme. In the stage, the particle swarm optimization algorithm is used to generate the training data set of target allocation, which is used to train and generate the air target autonomous allocation expert system constructed by the stack of adaptive neuro-fuzzy reasoning systems. In the application process, the expert system is firstly used to calculate the initial allocation plan, and then The initial distribution scheme is used to determine the initial position distribution of the particle swarm, and then the distribution scheme is solved by the particle swarm optimization algorithm. The method specif...

Embodiment 2

[0087] According to the air target autonomous allocation method provided in the above-mentioned embodiment 1, this embodiment is to further illustrate the effectiveness of the method of the present invention, with 5 air targets entering the defensive positions of 8 weapon units, assuming that the upper bound of the threat degree of the target is v up =0.9, the lower bound of the threat degree of the target is v down = 0.5, the upper bound of the damage probability of the weapon unit to the target is p up = 0.7, the lower bound of the damage probability of the weapon unit to the target is p down = 0.3.

[0088] Create 1,000,000 training data sets Tr according to the method described in step 1 in Example 1 in with Tr out ,Tr in with Tr out Part of the data in is as follows:

[0089]

[0090] Create the air target allocation expert system Ex according to the method described in step 2, Ex consists of 8 subsystems Ex i (i=1,2,...8), each subsystem is composed of 11 adapt...

Embodiment 3

[0104] A system for assigning aerial targets autonomously, comprising: an expert system creation module, which is used to create an expert system for autonomous assignment of aerial targets; a training set creation module, which is used to create a training set required for training the expert system; an expert system training module, It is used to use the training set to train the expert system; the particle swarm calculation module is used to perform data calculation according to the particle swarm optimization algorithm, and obtain the distribution plan; the output module is used to output the particle swarm calculation module. Air Target Allocation Scheme.

[0105] Wherein, the training set creation module includes: input data training subset creation unit, output data training subset creation unit;

[0106] The input data training subset creation unit is used to create and store input data samples for air target assignment;

[0107] The unit for creating the training sub...

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Abstract

The invention discloses an air target autonomous distribution method and system, and the method comprises the following steps: 1, creating an air target autonomous allocation expert system and a training set needed by the expert system, and where the training set comprises an input data training subset and an output data training subset; 2, training the expert system by using a training set; 3, acquiring an initial allocation scheme by using the trained expert system and the received target threat degree and damage probability data; 4, initializing the initial position of the particle swarm by using an initial distribution scheme; and step 5, according to the initial position of the particle swarm, iteratively updating the distribution scheme by using a particle swarm optimization algorithm until the number of iterations reaches a preset upper limit, and obtaining an air target distribution scheme. According to the invention, the problems that a large amount of time is needed for iterative operation to search for an optimal solution and local optimum is likely to happen due to particle swarm random initialization can be effectively solved, and compared with a single rule-based expert system reasoning method, an allocation scheme meeting the optimal benefit index can be provided.

Description

technical field [0001] The present invention relates to the technical field of air target prevention and control, in particular to a method and system for autonomous allocation of air targets. Background technique [0002] With the rapid development of low-cost precision guidance technology, intelligence, and unmanned technology, the air strike weapons faced by air defense operations are diversified and high-speed. In the case of rapid changes in the situation and increasingly complex battlefield environments, the air targets should be allocated reasonably. To the weapon unit is the key to further improving the probability of target interception and combat effectiveness. [0003] The current air target allocation methods can be roughly divided into two categories, one is the optimal solution method based on the optimal solution of the benefit index, and the other is the rule-based expert system reasoning method. Among them, the optimal solution method based on the optimal s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/00G06N5/04
CPCG06N3/006G06N5/048G06F18/214
Inventor 王长城陈大鹏陈力斯黄佳乐樊鹏陶俊瞳李文才曾刊
Owner 中国兵器装备集团自动化研究所有限公司
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