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Indoor Localization
Table of Contents
- 2015 Winlab Summer Internship
- LTE Unlicensed (LTE-U)
- Introduction
- Objectives
- Theory
- Analyzing Tools
- Experiment 1: Transmit and Receive LTE Signal
- Experiment 2: The Waterfall Plot
- Experiment 3: eNB and UE GUI
- Experiment 4: Varying Bandwidths
- Experiment 5: Working with TDD or FDD
- Experiment 6: TDD with Varying Bandwidths
- Experiment 7: TDD Waterfall Plot
- Poster
- Members
- Materials
- Resources
- LTE Unlicensed (LTE-U)
- Body Sensor Networks
- Dynamic Video Encoding
Introduction
The use of GPS services is growing just as fast as the development and accessibility of mobile devices. A GPS device, which used to be a significant investment, is now included in every smartphone that emerges on the market. These services have assisted many as they navigate themselves from place to place outdoors.
Although GPS is well-defined outdoors, localization indoors is still an active research problem. GPS signals indoors tend to be weaker; even if they are usable, the accuracy associated with GPS signals is not up to par. Large errors (on the order of meters) associated with GPS generally do not affect the user's ability to navigate to buildings, parks, landmarks, etc. Errors on the order of meters indoors, however, could mean that somebody is in a different room or different building altogether. A fine-grained service, down to the centimeter, is needed to localize indoors.
Motivation
An effective, low-cost, easy-to-implement solution to the indoor localization problem will have immediate impacts on everyday life, especially commercial retail. Based on movements of people in a store, retailers could determine where to place their best-selling items. They could place products effectively to accommodate shoppers and increase profits. In addition to commercial applications, indoor localization could help emergency responders efficiently respond to calls indoors, or help the elderly navigate inside a large building. Once the technology is fully developed, there are plenty of applications.
Team
Rahul Hingorani, University of Michigan Vineet Shenoy, Rutgers University
Attachments (30)
- Rahul.png (16.1 KB ) - added by 10 years ago.
- Vineet.png (85.9 KB ) - added by 10 years ago.
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- Localization Week 2.pdf (218.2 KB ) - added by 10 years ago.
- Localization Week 3.pdf (2.7 MB ) - added by 10 years ago.
- Week 4 Localization.pdf (1.8 MB ) - added by 9 years ago.
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Orbit lab photo
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orbit_banner.png
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Orbit banner
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gridLocations.png
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Grid Location of Transmitter and Receiver
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Noise.png
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Orbit Noise
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Signal.png
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Orbit Signal
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