The Hybrid HMM for RSS-based Localization in Wireless Sensor Networks
We propose a method of RSS-base localization in WSN (Wireless Sensor Network),called Hybrid HMM,to improve the stability of node localization based on RSS (Received Signal Strength).This model utilizes HMM (Hidden Markov Model) to take into account the time factor when receiving the RSS sequence,and converts the action of ranging into an operation of classification.For the received RSS used for localization,our Hybrid HMM will compare it with the preset RSS threshold value,and put the result into one of two categories for subsequent processing:If the received value is higher than the threshold value,the distance value will be drawn from the signal propagation model.If lower,the information will be obtained from a trained HMM.Experimental results show that the Hybrid HMM method can greatly improve the localization accuracy.
Wireless Sensor Network Localization Received signal strength Hidden Markov Model
Zang yanhong Wang Jinsong Ling Lin Lu Peizhong
Southwest Inst.of Electron & Telecom.Techn Shanghai,China
国际会议
杭州
英文
2212-2217
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）