DocumentCode :
740741
Title :
X-Ray Vision With Only WiFi Power Measurements Using Rytov Wave Models
Author :
Depatla, Saandeep ; Buckland, Lucas ; Mostofi, Yasamin
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Volume :
64
Issue :
4
fYear :
2015
fDate :
4/1/2015 12:00:00 AM
Firstpage :
1376
Lastpage :
1387
Abstract :
In this paper, unmanned vehicles are tasked with seeing a completely unknown area behind thick walls based on only wireless power measurements using wireless local area network (WLAN) cards. We show that a proper modeling of wave propagation that considers scattering and other propagation phenomena can result in a considerable improvement in see-through imaging. More specifically, we develop a theoretical and experimental framework for this problem based on Rytov wave models and integrate it with sparse signal processing and robotic path planning. Our experimental results show high-resolution imaging of three different areas, validating the proposed framework. Moreover, they show considerable performance improvement over the state of the art that only considers the line-of-sight (LOS) path, allowing us to image more complex areas not possible before. Finally, we show the impact of robot positioning and antenna alignment errors on our see-through imaging framework.
Keywords :
X-ray imaging; antennas; computerised instrumentation; control engineering computing; image resolution; path planning; position control; power measurement; radiotelemetry; wireless LAN; LOS; Rytov wave model; WLAN card; WiFi power measurement; X-ray vision; antenna alignment error; high-resolution imaging; line-of-sight; robotic path planning; scattering phenomena; see-through imaging framework; sparse signal processing; unmanned vehicle; wave propagation; wireless local area network; wireless power measurement; Approximation methods; IEEE 802.11 Standards; Imaging; Mathematical model; Robot kinematics; Robot sensing systems; Inverse scattering; radio-frequency (RF) imaging; robot sensing systems; see-through wall imaging; x-ray vision;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2015.2397446
Filename :
7029099
Link To Document :
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