Research on Fusion Method for Indoor Positioning System based on Sensors and WLAN Technology
In order to improve the quality of the RSS(Received Signal Strength)during the offline phase,a Mixture Gaussian Calibration Model(MGCM)is proposed by us,and a Time Latency Calibration Model(TLCM)is proposed to address the time latency effect during the online phase for a fast moving object.Firstly,MGCM is applied to the collected RSS data to precisely extract the less noised RSS.Then a feed forward neural network is trained to build a model between RSS and physical location.Finally,TLCM is applied during the online phase.The experimental results indicate that MGCM and TLCM reduce error compared to traditional positioning method respectively,which demonstrate the advantages of the proposed algorithms.
RSS Gaussian fingerprint latency calibration
Guang Yang
Beijing Engineering Research Center for IoT Software and Systems;School of Software Engineering,Beijing University of Technology Beijing,China
国际会议
重庆
英文
2689-2692
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）