  We propose an indoor localization algorithm for visible light systems by
considering effects of non-line-of-sight (NLOS) propagation. The proposed
algorithm, named database assisted nonlinear least squares (DA-NLS), utilizes
ideas from both the classical NLS algorithm and the fingerprinting algorithm to
achieve accurate and robust localization performance in NLOS environments. In
particular, a database is used to learn NLOS effects, and then an NLS algorithm
is employed to estimate the position. The performance of the proposed algorithm
is compared against that of the fingerprinting and NLS algorithms.
