一种无线传感器网络中的混沌信号重构算法

黄锦旺; 李广明; 冯久超; 晋建秀

doi:10.7498/aps.63.140502

摘要

将无线传感器网络节点观测区域中的一个混沌信号发送到融合中心，进行信号重构. 由于节点的通信带宽受限，信号传输之前需要进行量化，给信号带来量化噪声，使得信号重构工作变得更为棘手. 本文提出用平方根容积卡尔曼滤波器对融合中心收集的信号进行重构. 首先估计观测信号的概率密度函数，使用最优量化器量化观测信号，在有限的量化比特数下，取得最优的信号量化性能. 平方根容积卡尔曼滤波器相对无先导卡尔曼算法具有较少的求容积分点，因此具有计算量小的优点，同时迭代过程采用传递误差矩阵的平方根矩阵，保证迭代过程的稳定性和提高数据估计精度. 仿真结果表明，该算法能够有效和快速地重构观测信号，并且比基于无先导卡尔曼滤波的算法更快.

关键词:

Abstract

A chaotic signal in an observation area of network nodes is sent to a fusion center for reconstruction. As the communication bandwidth is limited, the signal must be quantified before sending to the fusion center, which will add quantization noise to the observed signal, which makes the signal reconstruction more difficult. A chaotic signal reconstruction algorithm is proposed in this paper based on square-root cubature Kalman filter. Firstly the probability density function of the observed signal is estimated, and then the optimal quantizer is used to quantify the observed signal. Under the limited budget of quantization bits, the best performance can be achieved. Compared with the unscented Kalman filter counterpart, our algorithm has fewer cubature points and has the merit of small computation load; meanwhile, it uses the square root of error variance for iteration, this will be more stable and accurate when iterating for parameter estimation. Simulation results show that the algorithm can reconstruct the observed signal quickly and effectively, with consuming less computation time and being more accurate than the one based on unscented Kalman filter.

Keywords:

作者及机构信息

1.
华南理工大学电子与信息学院, 广州 510641;

2.
东莞理工学院计算机学院, 东莞 523808

基金项目: 国家自然科学基金（批准号：60872123，61101014）、广东省高等学校高层次人才项目基金（批准号：N9101070）和中央高校基本科研基金（批准号：2012ZM0025）资助的课题.

Authors and contacts

1.
School of Electronic and Information engineering, South China University of Technology, Guangzhou 510641, China;

2.
School of Computer Science, Dongguan University Of Technology, Dongguan 523808, China

Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 60872123, 61101014), the Fund for Higher-level Talent in Guangdong Province, China (Grant No. N9101070), and the Fundamental Research Funds for the Central Universities, China (Grant No. 2012ZM0025).

参考文献

[1]	Zhang C, Fei S M, Zhou X P 2012 Chin. Phys. B 21 120101
[2]	Qi H, Wang F B, Deng H 2013 Acta Phys. Sin. 62 104301 (in Chinese) [祁浩, 王福豹, 邓宏 2013 62 104301]
[3]	Liu H R, Yin W X, Han T, Dong M R 2014 Acta Phys. Sin. 63 040509 (in Chinese) [刘浩然, 尹文晓, 韩涛, 董明如 2014 63 040509]
[4]	Liu X L, Li Z, Hu Y S 2013 Acta Phys. Sin. 62 070201 (in Chinese) [刘向丽, 李赞, 胡易俗 2013 62 070201]
[5]	de Senneville B D, Roujol S, Hey S, Moonen C, Ries M 2013 IEEE Trans. Medical Imaging 32 711
[6]	Feng J C 2012 Chaotic Signal and Information Process (Beijing: Tsinghua University Press) p101 (in Chinese) [冯久超 2012 混沌信号与信息处理 (北京: 清华大学出版社)第101页]
[7]	Feng J C, Tse C K, Lau F C M 2003 IEEE Trans. Circuits and Systems-I 50 954
[8]	Ribeiro A, Giannakis G B, Roumeliotis S 2006 IEEE Trans. Signal Process. 54 4782
[9]	Chen H B, Feng J C 2010 J. Southwest Univ. (Natural Science Edition) 32 124 (in Chinese) [陈宏滨, 冯久超 2010 西南大学学报 (自然科学版) 32 124]
[10]	Roseveare N, Natarajan B 2012 IEEE Trans. Aerosp. Electron. Syst. 48 3494
[11]	Chandra K P B, Gu D W, Postlethwaite I 2013 IEEE Sensors J. 13 750
[12]	Wang S Y, Feng J C 2012 Acta Phys. Sin. 61 170508 (in Chinese) [王世元, 冯久超 2012 61 170508]
[13]	Zhou J, Liu Y A, Wu F, Zhang H G, Zu Y X 2011 Acta Phys. Sin. 60 090504 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 60 090504]
[14]	Walpole R E, Myers R H, Myers S L, Ye K 2012 Probability & Statistics for Engineers & Scientists (9th Ed.) (Boston: Pearson Education Inc.) pp84-86
[15]	Maaref A, Aissa S 2009 IEEE Trans. Commun. 57 214
[16]	Shi J, Yang D S, Shi S G 2011 Acta Phys. Sin. 60 064301 (in Chinese) [时洁, 杨德森, 时胜国 2011 60 064301]
[17]	Yu X, Wang H Q, Yang E H 2010 IEEE Trans. Inform. Theory 56 5796
[18]	Bianchi P, Jakubowicz J 2013 IEEE Trans. Signal Process. 61 3119
[19]	Cui S, Xiao J J, Goldsmith A J, Luo Z Q, Poor H V 2007 IEEE Trans. Signal Process. 55 4683
[20]	Chen H B, Feng J C, Fang Y 2008 Chin.Phys.Lett. 25 405
[21]	Yu S M, Yu Z D 2008 Acta Phys. Sin. 57 6859 (in Chinese) [禹思敏, 禹之鼎 2008 57 6859]
[22]	Gao G R, Liu Y P, Pan Q 2012 Acta Phys. Sin. 61 139701 (in Chinese) [高国荣, 刘艳萍, 潘琼 2012 61 139701]

施引文献

[1]	Zhang C, Fei S M, Zhou X P 2012 Chin. Phys. B 21 120101
[2]	Qi H, Wang F B, Deng H 2013 Acta Phys. Sin. 62 104301 (in Chinese) [祁浩, 王福豹, 邓宏 2013 62 104301]
[3]	Liu H R, Yin W X, Han T, Dong M R 2014 Acta Phys. Sin. 63 040509 (in Chinese) [刘浩然, 尹文晓, 韩涛, 董明如 2014 63 040509]
[4]	Liu X L, Li Z, Hu Y S 2013 Acta Phys. Sin. 62 070201 (in Chinese) [刘向丽, 李赞, 胡易俗 2013 62 070201]
[5]	de Senneville B D, Roujol S, Hey S, Moonen C, Ries M 2013 IEEE Trans. Medical Imaging 32 711
[6]	Feng J C 2012 Chaotic Signal and Information Process (Beijing: Tsinghua University Press) p101 (in Chinese) [冯久超 2012 混沌信号与信息处理 (北京: 清华大学出版社)第101页]
[7]	Feng J C, Tse C K, Lau F C M 2003 IEEE Trans. Circuits and Systems-I 50 954
[8]	Ribeiro A, Giannakis G B, Roumeliotis S 2006 IEEE Trans. Signal Process. 54 4782
[9]	Chen H B, Feng J C 2010 J. Southwest Univ. (Natural Science Edition) 32 124 (in Chinese) [陈宏滨, 冯久超 2010 西南大学学报 (自然科学版) 32 124]
[10]	Roseveare N, Natarajan B 2012 IEEE Trans. Aerosp. Electron. Syst. 48 3494
[11]	Chandra K P B, Gu D W, Postlethwaite I 2013 IEEE Sensors J. 13 750
[12]	Wang S Y, Feng J C 2012 Acta Phys. Sin. 61 170508 (in Chinese) [王世元, 冯久超 2012 61 170508]
[13]	Zhou J, Liu Y A, Wu F, Zhang H G, Zu Y X 2011 Acta Phys. Sin. 60 090504 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 60 090504]
[14]	Walpole R E, Myers R H, Myers S L, Ye K 2012 Probability & Statistics for Engineers & Scientists (9th Ed.) (Boston: Pearson Education Inc.) pp84-86
[15]	Maaref A, Aissa S 2009 IEEE Trans. Commun. 57 214
[16]	Shi J, Yang D S, Shi S G 2011 Acta Phys. Sin. 60 064301 (in Chinese) [时洁, 杨德森, 时胜国 2011 60 064301]
[17]	Yu X, Wang H Q, Yang E H 2010 IEEE Trans. Inform. Theory 56 5796
[18]	Bianchi P, Jakubowicz J 2013 IEEE Trans. Signal Process. 61 3119
[19]	Cui S, Xiao J J, Goldsmith A J, Luo Z Q, Poor H V 2007 IEEE Trans. Signal Process. 55 4683
[20]	Chen H B, Feng J C, Fang Y 2008 Chin.Phys.Lett. 25 405
[21]	Yu S M, Yu Z D 2008 Acta Phys. Sin. 57 6859 (in Chinese) [禹思敏, 禹之鼎 2008 57 6859]
[22]	Gao G R, Liu Y P, Pan Q 2012 Acta Phys. Sin. 61 139701 (in Chinese) [高国荣, 刘艳萍, 潘琼 2012 61 139701]

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