Summary: | In this dissertation, a visible light-based IPS using commonly used LED lamps and
smartphone camera is investigated and implemented in Android phone. An ID extracting
algorithm called frequency-label based on 2ASK-modulation [47] is designed to facilitate
the extraction of ID frames from captured pictures by leveraging the rolling shutter effect
of CMOS camera. In the procedure of position estimation by solving nonlinear equation
sets, an optimized algorithm based on non-iterative SVD-based method [47] is deployed
to obtain the close-form least square solution to position matrix and rotation matrix. Also,
optimization of an image sensor-based indoor visible light positioning (VLP) system [47]
by improving the positioning algorithm is discussed. We implement the algorithms on an
Android phone by JAVA programming with the basic idea of state machine to control
functional modules (capturing, image-processing and calculation).
Real-time experiments are carried out to verify the performance of the proposed indoor
positioning system. Results show that 3-D positioning errors are 6 cm on average, in the
experiment space of 2×2×2 m3. The results reveal that the introduced SVD-based noniterative
algorithm is more time-saving than the conventional algorithm (approximately
50-80 times). Meanwhile the positioning error and performance of the optimized VLP
system are investigated experimentally. This dissertation achieves smartphone-based
real-time indoor 3D positioning of high robustness with centimeter-level accuracy and 2
Hz positioning rate.
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