[1]赵春晖,许云龙,黄辉,等.基于Schmidt正交单位化的稀疏化定位算法[J].哈尔滨工程大学学报,2014,(06):747-752.[doi:10.3969/j.issn.10067043.201305076]
 ZHAO Chunhui,XU Yunlong,HUANG Hui,et al.Sparse localization on the basis of Schmidt orthonormalization in wireless sensor networks[J].hebgcdxxb,2014,(06):747-752.[doi:10.3969/j.issn.10067043.201305076]
点击复制

基于Schmidt正交单位化的稀疏化定位算法(/HTML)
分享到:

《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2014年06期
页码:
747-752
栏目:
出版日期:
2014-06-25

文章信息/Info

Title:
Sparse localization on the basis of Schmidt orthonormalization in wireless sensor networks
文章编号:
10067043(2014)06074707
作者:
赵春晖许云龙黄辉崔冰
哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001
Author(s):
ZHAO Chunhui XU Yunlong HUANG HuiCUI Bing
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
关键词:
稀疏化定位节点定位压缩感知Schmidt正交单位化无线传感器网络移动信标
分类号:
TP393
DOI:
10.3969/j.issn.10067043.201305076
文献标志码:
A
摘要:
为了提高在一个移动信标节点下的无线传感器网络节点定位的精度,提出了一种稀疏化的无线传感器网络节点定位算法。该算法通过网格化感知区域把节点定位问题转化为稀疏信号重构问题,并提出了Schmidt正交单位化的预处理方法,对观测矩阵进行预处理,使其有效地满足了约束等距性条件。并针对稀疏定位模型中得到的稀疏信号是近似稀疏信号的问题,采用质心算法来优化算法的定位精度。实验结果表明,相比于MAP类算法,稀疏化的无线传感器网络节点定位算法的定位精度更优,同时所需要的信标节点的广播次数也更少。

参考文献/References:

[1]赵春晖, 许云龙. 能量约束贝叶斯压缩感知检测算法[J]. 通信学报, 2012, 33(10): 16.ZHAO Chunhui, XU Yunlong. Energy constraint Bayesian compressive sensing detection algorithm[J]. Journal on Communications, 2012, 33(10): 16. [2]WANG Xingbo, FU Minyue, ZHANG Huanshui. Target tracking in wireless sensor networks based on the combination of KF and MLE using distance measurements[J]. IEEE Transactions on Mobile Computing, 2012, 11(4): 567576. [3]SICHITIU M L, RAMADURAI V. Localization of wireless sensor networks with a mobile beacon[C] //IEEE International Conference on Mobile Adhoc and Sensor Systems. Raleigh,USA, 2004: 174183. [4]XIAO Bin, CHEN Hekang, ZHOU Shuigeng. Distributed localization using a moving beacon in wireless sensor networks[J]. IEEE Transactions on Parallel and Distributed Systems, 2008, 19(5): 587600. [5]SSU K F, OU C H, JIAU H C. Localization with mobile anchor points in wireless sensor networks[J]. IEEE Transactions on Vehicular Technology, 2005, 54(3): 11871197. [6]LEE S, KIM E, KIM C, et al. Localization with a mobile beacon based on geometric constraints in wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2009, 8(12): 58015805. [7]LIAO W H, LEE Y C, KEDIA S P. Mobile anchor positioning for wireless sensor networks[J]. IET Communications, 2011, 5(7): 914921. [8]CADES E. Compressive sampling[J]. International Congress of Mathematicians, 2006, 3: 14331452. [9]CADES E, PLAN Y. A probabilistic and RIP less theory of compressed sensing[J]. IEEE Transactions on Information Theory, 2011, 57(11): 72357254. [10]WANG Jun, URRIZA P, HAN Yuxing, et al. Weighted centroid localization algorithm: theoretical analysis and distributed implementation[J]. IEEE Transactions on Wireless Communications, 2011, 10(10): 34033413. [11]ALINE B, KOEN L. MonteCarlo Localization for mobile wireless sensor networks[J]. Ad Hoc Networks, 2006, 6(5): 718733. [12]BROCH J, MALTZ D A, JOHNSON D B, et al. A performance comparison of multihop wireless Ad hoc network routing protocols[C]//ACM International Conference on Mobile Computing Networking. Dallas,USA, 1998: 8597. [13]PATWARI N, ASH J N, KYPEROUNTAS S, et al. Locating the nodes: cooperative localization in wireless sensor networks[J]. IEEE Signal Processing Magazine, 2005, 22(4): 5469. [14]HE T, HUANG C, BLUM M B , et al. Rangefree localization schemes for large scale sensor network[J]. ACM Transactions on Embedded Computing System, 2005, 4(4): 877906.

备注/Memo

备注/Memo:
收稿日期:2013-05-30. 网络出版时间:2014-05-14 15:53:57. 基金项目:国家自然科学基金资助项目(61077079);黑龙江省自然科 学基金资助项目(ZD201216);哈尔滨市优秀学科带头人 基金资助项目(RC2013XK009003). 作者简介:赵春晖(1965-),男,教授,博士生导师. 通信作者:赵春晖,E-mail: zhaochunhui@ hrbeu.edu.cn.
更新日期/Last Update: 2014-09-01