X-Ray Vision With Only WiFi Power Measurements Using Rytov Wave Models

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. The authors 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, they 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. The 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 the authors to image more complex areas not possible before. Finally, they show the impact of robot positioning and antenna alignment errors on their see-through imaging framework.

• Record URL:
  • https://doi.org/10.1109/TVT.2015.2397446
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Depatla, S
  • Buckland, L
  • Mostofi, Y
• Publication Date: 2015-4

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1376-1387
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 64
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Autonomous vehicle guidance; Line of sight; Signal processing; Trajectory control; Wave motion; Wireless LANs; X rays
• Identifier Terms: IEEE 802.11 (Standard)
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment; I90: Vehicles;

Filing Info

• Accession Number: 01564544
• Record Type: Publication
• Files: TRIS
• Created Date: May 26 2015 4:12PM