基于最大条件熵的射频隐身数据链猝发通信模型
收稿日期: 2013-07-22
修回日期: 2013-12-11
网络出版日期: 2013-12-14
基金资助
国家自然科学基金（61371170）；航空科学基金（20130152002）；中央高校基本科研业务费专项资金；江苏省普通高校研究生科研创新计划（CXZZ11_0212）
Burst Communication Datalink Model for Radio Frequency Stealth Based on Conditional Maximum Entropy
Received date: 2013-07-22
Revised date: 2013-12-11
Online published: 2013-12-14
Supported by
National Natural Science Foundation of China (61371170); Aeronautical Science Foundation of China (20130152002);The Fundamental Research Funds for the Central Universities; Funding of Jiangsu Innovation Program for Graduate Education (CXZZ11_0212)
为提高数据链的低被截获性能，以数据链发射时刻的不确定性为对象，提出了一种基于最大条件熵的射频隐身数据链猝发通信模型。该模型以先验数据为训练样本空间，以拉格朗日乘子为优化粒子，将最大条件熵的对偶规划问题作为目标，利用混合混沌粒子群优化（HCPSO）算法进行优化计算，最终确定最大条件熵概率分布模型。与单阈值方法（STM）和双阈值方法（DTM）的对比仿真结果表明：利用最大熵方法（MEM）自适应生成的发射规划，不仅具有最大的发射时刻条件熵，射频隐身性能最好，而且MEM的通信总时间、通信占空比也最大，对环境约束特征的适应性最好，因此，MEM具有最优的综合性能。
关键词： 隐身技术; 最大熵; 猝发通信; 数据链; 混合混沌粒子群优化算法
杨宇晓 , 周建江 , 陈军 , 莫乾坤 . 基于最大条件熵的射频隐身数据链猝发通信模型[J]. 航空学报, 2014 , 35(5) : 1385 -1393 . DOI: 10.7527/S1000-6893.2013.0489
In order to improve the low intercept performance of a datalink, a burst communication datalink model based on conditional maximum entropy is proposed in this paper. In this model, the prior datas are used as the training sample space, and lagrange multipliers are selected as optimized variables. Hybrid chaotic particle swarm optimization (HCPSO) algorithm is used for the optimization of the model, and the HCPSO takes the dual programming of the conditional maximum entropy as its objective function, and ultimately determines the conditional maximum entropy probability distribution model. Compared with the single threshold method (STM) and double threshold method (DTM), the simulation results show that the proposed maximum entropy method (MEM) can not only effectively increase the uncertainty of the transmitting moment, but also ensures longer effective communication time and better environment adaptability. Therefore, MEM demonstrates better comprehensive performance than both STM and DTM.
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