|
|
基于改进粒子群优化的无线传感器网络定位算法
Localization method based on modified particle swarm optimization for wireless sensor networks
查看参考文献13篇
|
文摘
|
无线电干涉定位系统获取的干涉距离是4个传感器节点间距离的线性组合值。针对以两个节点间距离作为输入的传统定位算法无法直接利用上述干涉距离进行定位的问题,提出一种基于改进粒子群优化的定位方法。利用干涉距离的实验数据,分析比较了遗传算法和改进粒子群优化在无线传感器网络节点定位问题中的性能。结果表明,基于改进粒子群优化的定位方法的平均耗费时间远远小于基于遗传算法的定位方法,具有更高的优化效率. |
|
其他语种文摘
|
The interferometric range which the radio interferometric positioning system obtains is a linear combination of distances among four sensor nodes.For the problem that the traditional localization methods using range estimstes between a pair of nodes as input can not be applied directly in localization, a localization method based on modified particle swarm optimization(PSO) is proposed.Experimental data of the interferometric range are used to compare the performance of two localization methods based on genetic algorithm(GA) and modified PSO for wireless sensor networks.The results show that the localization method based on modified PSO takes less time and achieves higher optimizing efficiency. |
|
来源
|
控制与决策
,2012,27(1):156-160 【核心库】
|
|
关键词
|
无线传感器网络
;
干涉定位
;
粒子群优化
;
遗传算法
|
|
地址
|
1.
苏州市职业大学电子信息工程系, 苏州, 215104
2.
中国科学院沈阳自动化研究所, 沈阳, 110016
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1001-0920 |
|
学科
|
自动化技术、计算机技术 |
|
基金
|
国家自然科学基金项目
;
江苏省自然科学基金面上项目
;
苏州市职业大学创新团队基金项目
;
苏州市职业大学校青年基金项目
|
|
文献收藏号
|
CSCD:4421215
|
参考文献 共
13
共1页
|
|
1.
Liu Y H. Location, Localization, and Localizability.
J of Computer Science and Technology,2010,25(2):274-297
|
被引
29
次
|
|
|
|
|
2.
Amitangshu Pal. Localization algorithms in wireless sensor networks: Current approaches and future challenges.
J of Network Protocols and Algorithms,2010,2(1):45-74
|
被引
1
次
|
|
|
|
|
3.
Li F F. An effective self-adapting localization algorithm in wireless sensor networks.
J of Applied Mechanics and Materials,2011,58/60:1013-1017
|
被引
2
次
|
|
|
|
|
4.
Jian L R. Beyond triangle inequality:Sifting noisy and outlier distance measurements for localization.
Proc of IEEE INFOCOM 2010,2010:1-9
|
被引
2
次
|
|
|
|
|
5.
Kung H T. Localization with snap-inducing shaped residuals: Coping with errors in measurement.
Proc of MobiCom 2009,2009:333-344
|
被引
2
次
|
|
|
|
|
6.
Li Z. Robust statistical methods for securing wireless localization in sensor networks.
Proc of IPSN 2005,2005:91-98
|
被引
4
次
|
|
|
|
|
7.
Zhang Q X. A RSSI based localization algorithm for multiple mobile robots.
Proc of CMCE'10,2010:190-193
|
被引
1
次
|
|
|
|
|
8.
Maroti M. Radio interferometric geolocation.
Proc of SenSys'05,2005:1-12
|
被引
1
次
|
|
|
|
|
9.
Kusy B. Node-density independent localization.
Proc of IPSN'06,2006:441-448
|
被引
1
次
|
|
|
|
|
10.
黄艳. 传感器网络中无线电干涉定位系统的多径误差分析.
控制与决策,2009,24(2):231-235
|
被引
4
次
|
|
|
|
|
11.
Vasconcelos J A. Improvements in genetic algorithms.
IEEE Trans on Magnetics,2001,37(5):3414-3417
|
被引
18
次
|
|
|
|
|
12.
Clerc M. The particle swarm-explosion,stability, and convergence in multidimensional complex space.
IEEE Trans on Evolutionary Computation,2002,6(1):58-73
|
被引
809
次
|
|
|
|
|
13.
.
http://tinyos.cvs.sourceforge.net/tinyos/tinyos-1.x/contrib/vu/tools/java/isis/snest/localization/rips/footballFieldData.zip?view=log
|
被引
1
次
|
|
|
|
|
|
了解气象卫星更多信息，请访问