Recently with the advancement of solid state lighting and the application thereof
to Visible Light Communications (VLC), the concept of Visible Light Positioning
(VLP) has been targeted as a very attractive indoor positioning system (IPS) due to
its ubiquity, directionality, spatial reuse, and relatively high modulation bandwidth.
IPSs, in general, have 4 major components (1) a modulation, (2) a multiple access
scheme, (3) a channel measurement, and (4) a positioning algorithm. A number of
VLP approaches have been proposed in the literature and primarily focus on a fixed
combination of these elements and moreover evaluate the quality of the contribution
often by accuracy or precision alone.
In this dissertation, we provide a novel two-phase indoor positioning algorithmic
framework that is able to increase robustness when subject to insufficient anchor luminaries
and also incorporate any combination of the four major IPS components.
The first phase provides robust and timely albeit less accurate positioning proximity
estimates without requiring more than a single luminary anchor using time division
access to On Off Keying (OOK) modulated signals while the second phase provides a
more accurate, conventional, positioning estimate approach using a novel geometric
constrained triangulation algorithm based on angle of arrival (AoA) measurements.
However, this approach is still an application of a specific combination of IPS components.
To achieve a broader impact, the framework is employed on a collection
of IPS component combinations ranging from (1) pulsed modulations to multicarrier
modulations, (2) time, frequency, and code division multiple access, (3) received signal
strength (RSS), time of flight (ToF), and AoA, as well as (4) trilateration and
triangulation positioning algorithms.
Results illustrate full room positioning coverage ranging with median accuracies
ranging from 3.09 cm to 12.07 cm at 50% duty cycle illumination levels. The framework
further allows for duty cycle variation to include dimming modulations and results
range from 3.62 cm to 13.15 cm at 20% duty cycle while 2.06 cm to 8.44 cm at a
78% duty cycle. Testbed results reinforce this frameworks applicability. Lastly, a
novel latency constrained optimization algorithm can be overlaid on the two phase
framework to decide when to simply use the coarse estimate or when to expend more
computational resources on a potentially more accurate fine estimate.
The creation of the two phase framework enables robust, illumination, latency
sensitive positioning with the ability to be applied within a vast array of system
deployment constraints.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/30715 |
| Date | 03 July 2018 |
| Creators | Prince, Gregary Barton |
| Contributors | Little, Thomas D.C. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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