摘要
针对RSSI受外界因素影响较大,测距和定位精度很难得到保证的问题,从方差级干扰与均值级干扰两个层面对RSSI进行修正.首先在RSSI采集阶段提出一种基于离差的高斯模型(D-Gaussian)对方差级干扰进行过滤,以提高RSSI信号的可用性;其次在测距阶段,引入一种EWMA动态窗口机制并将其命名为R-EWMA,对均值级干扰进行处理.实验结果表明,研究工作有效地缓解了在传统定位算法中硬件成本与定位精度之间的矛盾。
In respect of positioning,the RSSI is affected greatly by external factors,so it is hard to ensure the accuracy in either ranging or positioning.Due to the interference that is at both variance and mean levels,RSSI should be amended at the two levels.In the data acquisition stage of RSSI,a Gaussian model based on deviation (D-Gaussian) is developed to filter the interference at variance level so as to improve the availability of RSSI signal.Then,in the ranging stage,a dynamic window mechanism EWMA is introduced,i.e.,the R-EWMA,to deal with the interference at mean level.Experimental results showed that the contradiction between positioning accuracy and the hardware costs in conventional positioning algorithm is moderated efficiently,thus reducing basically the error of RSSI positioning algorithm via processing RSSI properly.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2010年第5期647-650,共4页
Journal of Northeastern University(Natural Science)
基金
教育部高等学校科技创新工程重大培育基金资助项目(708026)
关键词
无线传感器网络
节点定位
RSSI
抗干扰
离差的高斯模型
WSN(wireless sensor network)
node localization
RSSI(received signal strength indicator)
anti-interference
D-Gaussian model