  In this paper, we propose a novel indoor localization scheme that exploits
ubiquitous visible lights, which are necessarily and densely deployed in almost
all indoor environments. We unveil two phenomena of lights available for
positioning: 1) the light strength varies according to different light sources,
which can be easily detected by light sensors embedded in COTS devices (e.g.,
smart-phone, smart-glass and smart-watch); 2) the light strength is stable in
different times of the day thus exploiting it can avoid frequent site-survey
and database maintenance. Hence, a user could locate oneself by differentiating
the light source of received light strength (RLS). However, different from
existing positioning systems that exploit special LEDs, ubiquitous visible
lights lack fingerprints that can uniquely identify the light source, which
results in an ambiguity problem that an RLS may correspond to multiple
positions. Moreover, RLS is not only determined by device's position, but also
seriously affected by its orientation, which causes great complexity in
site-survey. To address these challenges, we first propose and validate a
realistic light strength model that can attributes RLS to arbitrary positions
with heterogenous orientations. This model is further perfected by taking
account of the device diversity, influence of multiple light sources and
shading of obstacles. Then we design a localizing scheme that harness user's
mobility to generate spatial-related RLS to tackle the position-ambiguity
problem of a single RLS, which is robust against sunlight interference, shading
effect of human-body and unpredictable behaviours (e.g., put the device in
pocket) of user. Experiment results show that our scheme achieves mean accuracy
$1.93$m and $1.98$m in office ($720m^2$) and library scenario ($960m^2$)
respectively.
