农业机械学报2018，Vol.49Issue(4)：241-248,8.DOI:10.6041/j.issn.1000-1298.2018.04.027
基于核自适应滤波的无线传感网络定位算法研究
Wireless Sensor Network Location Algorithms Based on Kernel Adaptive Filtering
摘要
Abstract
For the change of dynamic indoor environment and the effect of time-varying received signal strength on positioning accuracy,a class of indoor positioning algorithms for agricultural wireless sensor networks using kernel adaptive filtering was proposed,which included quantized kernel least mean square (QKLMS) as well as fixed-budget kernel recursive least-squares (FB-KRLS) algorithm.The QKLMS algorithm used a simple vector quantization approach as an alternative of sparsification to curb the growth of the radial basis function structure in kernel adaptive filtering.The FB-KRLS algorithm was an online kernel method by fixed memory budget,which was capable of recursively learning nonlinear mapping and tracking change over time.In contrast to a previous sliding-window based technique,the presented algorithm did not prune the oldest data point in every time instant but it was aimed to prune the least significant data point,thus suppressing the growth of kernel matrix.The kernel adaptive filtering algorithms achieved the indoor positioning for WSNs by building the non-linear mapping relations between the RSS fingerprint information and the physical location.The employed algorithms were applied to different indoor positioning instances in the simulation and physical environments for WSNs,under the same circumstances,compared with other kernel-based learning methods and extreme learning machine (ELM) etc.In the simulation experiment,the average localization error of the two algorithms was respectively 0.746 m and 0.443 m under three scenarios,and the average localization error of the two algorithms in the physical experiments was respectively 0.547 m and 0.282 m under two scenarios.Experimental results showed that the proposed adaptive filtering algorithms can improve the positioning accuracy,and its online learning ability made the proposed two localization algorithms all adaptable to the dynamic changes of the environments.关键词
核自适应滤波/量化核最小均方算法/核递推最小二乘算法/无线传感网络/室内定位Key words
kernel adaptive filtering/quantized kernel least mean square algorithm/kernel recursive least square algorithm/wireless sensor networks/indoor positioning分类
信息技术与安全科学引用本文复制引用
李军,赵畅..基于核自适应滤波的无线传感网络定位算法研究[J].农业机械学报,2018,49(4):241-248,8.基金项目
国家自然科学基金项目(51467008)和兰州交通大学优秀科研团队项目(201701) （51467008）
