Laser pointing systems for small targets are mainly confronted with two pointing errors, jitter and boresight,
arising due to atmospheric turbulence, mechanical vibrations and errors in optical alignment. Knowledge of these
parameters provides information about the quality of the pointing and tracking system. In the past, several
techniques have been investigated to estimate these parameters from returned laser signals. These include the
key ratio technique, the chi-squared method and the maximum likelihood (ML) estimation technique. These
techniques have been studied in the literature for Gaussian irradiance profiles. In particular, the ML estimation
technique has been found to provide excellent results. In this paper, we extend the ML estimation technique from
Gaussian profiles to near-Gaussian irradiance profiles. Our results show that the modified estimator performs
much better than a direct application of the original ML estimator.
Accurate laser beam pointing is critical for a variety of applications including free space laser communications. Several methods have been described in the literature to estimate pointing error parameters. One such estimator is the maximum likelihood estimator that can provide nearly optimal estimates of the pointing error parameters using the signal returned from a target. This paper summarizes the key findings of the maximum likelihood estimator and compares its performance using experimental results.