Harnessing multipath to enable centimeter-level positioning using wireless channel state information from compact antenna arrays
- Positioning is a fundamental primitive that enables several important applications. A ubiquitous outdoor positioning system like GPS has transformed the way one navigates outdoors. An accurate and ubiquitous indoor positioning system will similarly transform several applications from indoor navigation to virtual reality. This dissertation shows that centimeters-level accurate wireless positioning system can be achieved using ubiquitous wireless communication infrastructure. Developing such a positioning system is very attractive as it enables ubiquitous deployment of positioning applications and has been an active area of research for more than two decades. However, achieving high accuracy demanded specialized devices with huge antenna arrays, which are undesirable, and this dissertation shows that they are no longer necessary by demonstrating high accuracy using commodity, off-the-shelf wireless communication chips with compact antenna arrays using wireless signal information that is already made available by these chips. This dissertation presents the design and implementation of three systems that progressively advanced the state-of-the-art in wireless positioning systems using ubiquitous wireless communication infrastructure. All the systems use wireless channel information called Channel State Information (CSI) exposed by commodity wireless communication chips as input and do not require any hardware or firmware changes. First system, SpotFi, uses wireless channel obtained from different frequencies of transmission, that are transmitted anyways for wireless communication, along with the wireless channel obtained at different antennas. SpotFi demonstrated the first decimeters-level accurate positioning system using commodity wireless communication chips with just three antennas. The second system, WiCapture, in addition, uses signals from multiple transmissions at different times as the wireless device naturally moves. The system uses a novel technique to overcome the clock-induced signal distortion across multiple transmissions between the transmitter and receiver by exploiting the reflectors that are naturally present in the environment. This is a very surprising insight as reflectors in the environment are traditionally viewed as undesired distorters of the wireless signal propagated from the transmitter to the receiver. WiCapture demonstrated the first positioning system that can accurately recreate the trajectory performed by a device with sub-centimeter level accuracy and recover the position of the wireless device with centimeters-level accuracy using ubiquitous wireless communication infrastructure. The third system, DeepCapture, uses novel deep learning-based algorithms to mine wireless channel information across multiple transmissions, antennas and frequencies together to extract accurate positioning of a wireless device in real time. The system tracks a wireless device with centimeters-level accuracy using a single stationary wireless communication radio and extracts position updates at a rate of atleast 142 Hz. DeepCapture has been used to enable and demonstrate interesting applications like an end-to-end virtual reality application which uses wireless devices as hand controllers. All these systems overcome the limitations of commodity wireless communication chips by harnessing the reflectors that are naturally present in the environment, harnessing the motion that is naturally happening on the device and harnessing multiple frequencies of transmission that are used for communication, and hence achieve high accuracy while retaining the practical advantages like ease of deployment offered by systems based on ubiquitous wireless communication infrastructure.
|Type of resource
|electronic resource; remote; computer; online resource
|1 online resource.
|Degree committee member
|Degree committee member
|Stanford University, Department of Electrical Engineering.
|Statement of responsibility
|Submitted to the Department of Electrical Engineering.
|Thesis Ph.D. Stanford University 2019.
- © 2019 by Manikanta Kotaru
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...