Abstract
Device-free passive (DFP) localization techniques have received increasing attention for location-based services due to their ability to realize localization without holding any wireless device. Most of the existing DFP localization systems are based on the measurement of received signal strength (RSS) only. However, the localization accuracy is easily affected by the spatial and temporal variance of RSS due to multipath fading and noise, even in a static environment. In this paper, we propose a novel localization system for DFP localization using an array sensor, which uses an antenna array at a receiver and is mainly based on the signal eigenvector. We use a fingerprinting technique with multiclass support vector machines (SVMs) based on a combination of array signal features with spatial and temporal averaging. We evaluate the localization performance of our proposed system in different propagation environments, i.e., line-of-sight (LOS) and non-line-of-sight (NLOS). In addition, we analyze two types of receive antenna placement, i.e., centralized and distributed antennas. The experimental results show that the localization accuracy can be improved by the proposed system, particularly in the centralized antenna case. Moreover, they show that the proposed system can improve localization accuracy compared with the conventional RSS-only-based system.
Original language | English |
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Article number | 7029093 |
Pages (from-to) | 1354-1363 |
Number of pages | 10 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 64 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2015 Apr 1 |
Keywords
- Antenna array
- device-free localization
- machine learning
- support vector machine (SVM)
ASJC Scopus subject areas
- Automotive Engineering
- Aerospace Engineering
- Applied Mathematics
- Electrical and Electronic Engineering