IT Forum presents "Harnessing nature to make wireless positioning practical and accurate"

Harnessing nature to make wireless positioning practical and accurate
Friday, March 15, 2019 - 1:15pm
Packard 202
Manikanta Kotaru (Stanford)
Abstract / Description: 

Positioning has been the Holy Grail of wireless sensing research with a wide range of applications from tracking virtual reality devices to in-body implants. However, despite two decades of active research, a widely deployable system with high accuracy has always been elusive. Wireless signals reflected from objects in the environment interfere with and distort the signal from the intended target device, corrupting the position estimates. In order to fight this 'multipath' phenomenon, previous approaches built specialized wireless devices with huge antenna arrays or large bandwidths making them impractical for ubiquitous deployment. In this talk, I will introduce a new technique called 'Synthetic Aperture Radio' that harnesses, rather than fighting, the multipath that naturally occurs in the environment and exploits the device motion that naturally occurs in these applications. By applying this technique, I have demonstrated the first real-time and centimeter-level accurate positioning system using standard, off-the-shelf WiFi radios. Building on synthetic aperture radio technique, I have developed practical positioning systems for indoor navigation, tracking virtual reality accessories and resource constrained devices like endoscopic capsules. Looking forward, these techniques lay a foundation for utilizing ubiquitous wireless devices for developing important machine vision applications in various domains like medical sensing, physical security and autonomous vehicles.


Manikanta Kotaru is a Ph.D. candidate in Electrical Engineering at Stanford University. His research focuses on building widely-accessible computational sensing systems with applications in robotics, virtual reality, Internet of Things and medical sensing. His research bridges RF sensing and machine vision, and brings theory and systems together. His work has appeared in premier conferences in both communications and computer vision such as SIGCOMM and CVPR. He is a recipient of Stanford Graduate Fellowship. Website