基于改进离散布谷鸟算法的干扰资源分配研究

李东生; 高杨; 雍爱霞

doi:10.11999/JEIT150726

基于改进离散布谷鸟算法的干扰资源分配研究

doi: 10.11999/JEIT150726

基金项目:

国家自然科学基金(61179036)

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- 被引次数: 0
出版历程
- 收稿日期: 2015-06-15
- 修回日期: 2015-11-27
- 刊出日期: 2016-04-19

Jamming Resource Allocation via Improved Discrete Cuckoo Search Algorithm

Funds:

The National Natural Science Foundation of China (61179036)

摘要

摘要: 该文对二次雷达机制的协同式敌我识别系统的干扰资源分配问题进行研究，将离散布谷鸟算法(Discrete Cuckoo Search, DCS)引入敌我识别系统的干扰资源分配问题。首先给出协同式敌我识别系统的干扰效果评估指标，建立干扰资源分配模型，将模型简化为一对一、多对少模型，使用DCS算法求解模型。针对Levy飞行后期出现搜索速度慢和精度低的问题，将遗传算法中的交叉与变异操作引入DCS算法得到改进的离散布谷鸟算法(Improved Discrete Cuckoo Search, DCS)，用以求解分配模型。仿真分析表明：所提干扰效果评估指标可以合理地评估干扰效果；IDCS算法比IDCS算法收敛更快、耗时更短；IDCS算法与做出相应改进的遗传算法(Improved Genetic Algorithm, IGA)相比具有更好的寻优能力。
- 协同式敌我识别 /
- 干扰资源 /
- 资源分配 /
- 改进离散布谷鸟算法
Abstract: Jamming resource distribution of cooperative identification friend or foe via secondary radar is researched by introducing Discrete Cuckoo Search (DCS) algorithm. The jamming effect evaluation rules and indexes are given, and the aim function and distribution model are given. According to the analysis, distribution models can be changed into one-to-one model and much-to-little model, which can be solved by DCS algorithm. Owing to the slow searching speed and low precision in the Levy flights later stage, the crossover and variation are introduced into DCS algorithm, which gets Improved Discrete Cuckoo Search (IDCS) algorithm. The simulation results show that the jamming effect judging index is effective, the IDCS algorithm has a faster convergence speed than the DCS algorithm, and it has a better searching optimization speed than Improved Genetic Algorithm (IGA).
- Cooperation identification friend or foe /
- Jamming resource /
- Resource distribution /
- Improved Discrete Cuckoo Search (IDCS) algorithm

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