Name
Abstract | ||
|---|---|---|
This paper presents a new method for imaging, localizing, and tracking motion behind walls in real time. The method takes advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network. Using a multipath channel model, we show that the signal strength on a wireless link is largely dependent on the power contained in multipath components that travel through space containing moving objects. A statistical model relating variance to spatial locations of movement is presented and used as a framework for the estimation of a motion image. From the motion image, the Kalman filter is applied to recursively track the coordinates of a moving target. Experimental results for a 34-node through-wall imaging and tracking system over a 780 square foot area are presented. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TMC.2010.175 | IEEE Trans. Mob. Comput. |
Keywords | Field | DocType |
signal strength measurement,multipath channel model,34-node through-wall imaging,motion-induced variance,signal strength,motion tracking,variance-based radio tomography networks,statistical model,multipath component,new method,wireless link,see-through walls,motion image,reactive power,kalman filters,kalman filter,tomography,real time,radar imaging,sensors,object tracking,tracking,tracking system,wireless network,wireless networks | Multipath propagation,Computer vision,Wireless network,Radar imaging,Computer science,Tracking system,Kalman filter,Video tracking,Statistical model,Artificial intelligence,Match moving | Journal |
Volume | Issue | ISSN |
10 | 5 | 1536-1233 |
Citations | PageRank | References |
78 | 3.83 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joey Wilson | 1 | 469 | 24.16 |
| Neal Patwari | 2 | 3805 | 241.58 |