  The research interest on location-based services has increased during the
last years ever since 3D centimetre accuracy inside intelligent environments
could be confronted with. This work proposes an indoor local positioning system
based on LED lighting, transmitted from a set of beacons to a receiver.The
receiver is based on a quadrant photodiode angular diversity aperture (QADA)
plus an aperture placed over it.This configuration can be modelled as a
perspective camera, where the image position of the transmitters can be used to
recover the receiver's 3D pose. This process is known as the
perspective-n-point (PnP) problem, which is well known in computer vision and
photogrammetry. This work investigates the use of different state-of-the-art
PnP algorithms to localize the receiver in a large space based on four
co-planar transmitters and with a distance from transmitters to receiver of 3.4
m. Encoding techniques are used to permit the simultaneous emission of all the
transmitted signals and their processing in the receiver. In addition,
correlation techniques are used to determine the image points projected from
each emitter on the QADA. This work uses Monte Carlo simulations to
characterize the absolute errors for a grid of test points under noisy
measurements, as well as the robustness of the system when varying the 3D
location of one transmitter. The IPPE algorithm obtained the best performance
in this configuration. The proposal has also been experimentally evaluated in a
real setup. The estimation of the receiver's position at three points using the
IPPE algorithm achieves average absolute errors of 4.33cm, 3.51cm and 28.90cm
in the coordinates x, y and z, respectively. These positioning results are in
line with those obtained in previous work using triangulation techniques but
with the addition that the complete pose of the receiver is obtained in this
proposal.
