基于最大条件熵的射频隐身数据链猝发通信模型

doi:10.7527/S1000-6893.2013.0489

Abstract

Abstract:

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.

Key words: stealth technology, maximum entropy, burst communication, datalink, hybrid chaotic particle swarm optimization algorithm

CLC Number:

YANG Yuxiao, ZHOU Jianjiang, CHEN Jun, MO Qiankun. Burst Communication Datalink Model for Radio Frequency Stealth Based on Conditional Maximum Entropy[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(5): 1385-1393.

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Burst Communication Datalink Model for Radio Frequency Stealth Based on Conditional Maximum Entropy

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