摘要
为降低测距误差对定位精度的影响,提出了一种基于核局部保持映射(KLPP)的定位算法。该算法以节点间的传输时间向量为输入,借助能够体现网络拓扑结构局部信息的核局部保持映射进行建模。仿真结果表明:基于KLPP的定位算法与传统基于核函数主成分分析(KPCA)的定位算法相比,在解决TOA定位问题时具有较高的定位精度,在复杂环境下能更有效地降低测量误差对TOA定位精度的影响。
This paper aims at reducing the influence of ranging error on localization accuracy.A Wireless Sensor Network（WSN） localization algorithm was proposed,which was based on Kernel Locality Preserving Projection（KLPP）.The algorithm took transmission time vector between nodes as input,and a model was established by KLPP,which can reflect partial information network topology structure.The simulation results indicate that compared with Kernel Principle Component Analysis（KPCA）,the algorithm can achieve higher localization accuracy in Time of Arrival（TOA） localization and reduce the influence of ranging error on localization accuracy effectively in complex environment.
出处
《计算机应用》
CSCD
北大核心
2011年第10期2876-2879,共4页
journal of Computer Applications
基金
河北省自然科学基金资助项目(F2010001040)
关键词
无线传感网络
定位
到达时间
核局部保持映射
核主成分分析
Wireless Sensor Network（WSN）
localization
Time Of Arrival（TOA）
Kernel Locality Preserving Projection（KLPP）
Kernel Principle Component Analysis（KPCA）
