Abstract:
Optical beam position on a detector array is an important parameter for optimal symbol detection in a free-space optical communication system; hence it is essential to ac...Show MoreMetadata
Abstract:
Optical beam position on a detector array is an important parameter for optimal symbol detection in a free-space optical communication system; hence it is essential to accurately estimate and track the beam position (which is unknown and may be varying in time). In this paper, we have attempted to solve the beam position tracking problem by setting it up as a state space variable filtering problem in the context of a dynamical system. We propose the following filtering methods for tracking the beam position: a Kalman filter and a particle filter that both use the maximum likelihood estimate of stationary beam position as a measurement in a linear dynamical model setting, and another particle filter which employs the received photon counts as observations for the nonlinear dynamical model. We compare the performance of these three filters in terms of mean-square error assuming that the beam position evolves in time according to a specified model. It is concluded from simulation results that the Kalman filter gives close to optimal performance for high to moderate photon rates for the Gauss-Markov evolution model. However, both the particle filtering algorithms outperform the Kalman filter for the uniformly distributed evolution noise scenario.
Published in: IEEE Transactions on Aerospace and Electronic Systems ( Volume: 54, Issue: 2, April 2018)