68 research outputs found
Statistical Analysis of Geometric Algorithms in Vehicular Visible Light Positioning
Vehicular visible light positioning (VLP) methods find relative locations of
vehicles by estimating the positions of intensity-modulated head/tail lights of
one vehicle (target) with respect to another (ego). Estimation is done in two
steps: 1) relative bearing or range of the transmitter-receiver link is
measured over the received signal on the ego side, and 2) target position is
estimated based on those measurements using a geometric algorithm that
expresses position coordinates in terms of the bearing-range parameters. The
primary source of statistical error for these non-linear algorithms is the
channel noise on the received signals that contaminates parameter measurements
with varying levels of sensitivity. In this paper, we present two such
geometric vehicular VLP algorithms that were previously unexplored, compare
their performance with state-of-the-art algorithms over simulations, and
analyze theoretical performance of all algorithms against statistical channel
noise by deriving the respective Cramer-Rao lower bounds. The two newly
explored algorithms do not outperform existing state-of-the-art, but we present
them alongside the statistical analyses for the sake of completeness and to
motivate further research in vehicular VLP. Our main finding is that direct
bearing-based algorithms provide higher accuracy against noise for estimating
lateral position coordinates, and range-based algorithms provide higher
accuracy in the longitudinal axis due to the non-linearity of the respective
geometric algorithms.Comment: Technical report. 7 pages, 4 figure
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