ACTA AERONAUTICAET ASTRONAUTICA SINICA >
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)
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.
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 . DOI: 10.7527/S1000-6893.2013.0489
[1] Schleher D C. LPI radar: fact or fiction[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 21(5): 3-6.
[2] Gao J Y. Analysis of low probability of intercept (LPI) radar signals using the wigner distribution. Monterey: Naval Post Graduate School, 2002.
[3] Yang H B, Zhou J J, Wang F, et al. Characterization parameters of warplane RF stealth and analysis of its affecting factors[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(10): 2040-2045. (in Chinese) 杨红兵, 周建江, 汪飞, 等. 飞机射频隐身表征参量及其影响因素分析[J]. 航空学报, 2010, 31(10): 2040-2045.
[4] David L J. Introduction to RF stealth[M]. Raleigh: Science Technology Publishing Incorporation, 2004: 8-12.
[5] Zhang Z K, Wang F, Zhou J J, et al. Adaptive time resource scheduling for multiple target tracking[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(3): 522-530. (in Chinese) 张贞凯, 汪飞, 周建江, 等. 多目标跟踪中自适应时间资源调度[J]. 航空学报, 2011, 32(3): 522-530.
[6] Le N V, Scheers B. Performance of delay and add direct sequence spread spectrum modulation scheme with fast frequency hopping in frequency selective rayleigh channels//Military Communications Conference, 2011: 622-627.
[7] Scheers B, Le N V. Pseudo-random binary sequence selection for delay and add direct sequence spread spectrum modulation scheme[J]. IEEE Communications Letters, 2010, 14(11): 1002-1004.
[8] Mukumoto K, Nagata S, Wada T, et al. Proposal of go-back-i-symbol ARQ scheme and its performance evaluation in meteor burst communications[J]. IEEE Transactions on Communications, 2012, 60(8): 2336-2343.
[9] Komatsubara K, Mukumoto K, Wada T. Proposal of new decision feedback carrier synchronization method for meteor burst communications//2012 International Symposium on Information Theory and Its Applications (ISITA), 2012: 21-25.
[10] Hong T, Song M Z, Liu Y. Signal transmitted from switched antenna array with low interception probability for physical layer security[J]. Journal of Applied Sciences, 2011, 29(4): 368-373. (in Chinese) 洪涛, 宋茂忠, 刘渝. 切换天线发射的低截获率通信信号物理层安全传输[J]. 应用科学学报, 2011, 29(4): 368-373.
[11] Xiao Y S, Zhou J J, Huang L Z, et al. Study and design of spatial domain uncertainty of airborne radar RF stealth[J]. Modern Radar, 2012, 34(8): 11-15. (in Chinese) 肖永生, 周建江, 黄丽贞, 等. 机载雷达射频隐身的空域不确定性研究与设计[J]. 现代雷达, 2012, 34(8): 11-15.
[12] Chacon M, Esteve M. Design and implementation of a simulation platform for Link-16 networks using NS-2//Information Systems and Technologies, 2012: 1-6.
[13] McCabe L. Operator-in-the-loop experimentation: providing combat utility measures//Military Communications Conference, 2011: 2170-2175.
[14] Wang L Y, Xue W, Luo W Z. Model analysis of Link-16 based on global grid reference model//International Conference on Computer Science and Network Technology, 2011, 2: 910-913.
[15] Xu X B, Zheng K F, Li D, et al. New chaos-particle swarm optimization algorithm[J]. Journal of Communication, 2012, 33(1): 24-30. (in Chinese) 胥小波, 郑康锋, 李丹, 等. 新的混沌粒子群优化算法[J]. 通信学报, 2012, 33(1): 24-30.
[16] Meng H J, Zheng P, Wu R Y, et al. A hybrid particle swarm algorithm with embedded chaotic search//IEEE Conference on Cybernetics and Intelligent Systems, 2004, 1: 367-371.
[17] Zhang L, Zhu L D. Detection of meteor burst and its channel modeling simulation//2010 2nd International Conference on Signal Processing Systems, 2010, 3: 321-325.
[18] Liu Z B, Chen J S. An analysis of meteor burst communication[J]. Ship Electronic Engineering, 2006, 26(4): 125-128. (in Chinese) 刘志斌, 陈家松. 流星余迹猝发通信分析[J]. 舰船电子工程, 2006, 26(4): 125-128.
[19] Shannon C E. A mathematical theory of communication[J]. Bell System Technical Journal, 1948, 27(3-4): 379-423, 623-656.
[20] Jaynes E T. Information theory and statistical mechanics[J]. The Physical Review, 1957, 106(4): 620.
[21] Wang G B, Huang H Z, Zhang X L. Risk possibility number-a new model for risk evaluation and prioritization based on maximum entropy theory[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(9): 1683-1690. (in Chinese) 王贵宝, 黄洪钟, 张小玲. 风险可能数——一种基于最大信息熵理论的风险度量和风险排序新方法[J]. 航空学报, 2009, 30(9): 1683-1690.
[22] Rastrow A, Dredze M, Khudanpur S. Adapting n-gram maximum entropy language models with conditional entropy regularization//2011 IEEE Workshop on Automatic Speech Recognition and Understanding, 2011: 220-225.
[23] Kennedy J, Eberhart R. Particle swarm optimization//Proceedings of IEEE International Conference on Neural Networks, 1995, 4(2): 1942-1948.
[24] Modares H, Alfia A, Naghibi S M B, et al. Parameter estimation of bilinear systems based on an adaptive particle swarm optimization[J]. Engineering Applications of Artificial Intelligence, 2010, 23(7): 1105-1111.
[25] Karakuzu C. Parameter tuning of fuzzy sliding mode controller using particle swarm optimization[J]. International Journal of Innovative Computing, 2010, 6(10): 4755-4770.
/
〈 |
|
〉 |