An Indoor Positioning Algorithm with Reduction of Dynamic Noises in WLAN Environments
Date Issued
2007
Date
2007
Author(s)
Liu, Fu-Hsiang
DOI
en-US
Abstract
Positioning in wireless is growing rapidly in commercial interest and public safety for context aware applications. The essential challenge in location positioning technology is the severe fluctuation of the receive signal strength (RSS) even for a fixed location. In this article, our work is to develop a novel localization algorithm which would extract the robust feature from received signal strength (RSS). And the algorithm is less sensitive to time varying noise effect. There are two steps for our approach. The first step is to transform the dynamic multipath into an additive random variable in the logarithmic spectrum domain and thus can be averaged out the proposed method. Then, we apply the PCA technique to replace the elements by principal components (PCs) which are generated through a transformation such that the retained information can be maximized. Therefore, the transformed information would be less sensitive to time varying indoor environment. To our knowledge, this work is to enhance the robustness to multipath fading condition, which is common in the indoor environment. This approach is not only simple and easy to be implemented but also required neither new hardware nor extra sensor network installation.
In order to evaluate the performance of our algorithm, we collect realistic RSS in an indoor WLAN environment. The results show that the positioning accuracy is significantly improved. The numerical results show that mean and variance of estimated error are reduced by 52.8% and 74.9% on the average. Moreover, the experimental results also show that fewer training samples and access points are required to build the positioning models.
Subjects
室內無線定位
多重路徑干擾
可加性
PCA
context aware
RSS
multipath
positioning
Type
thesis