Empirical Bayes Trajectory Estimation Based on Bearings from Moving Observer

The problem of estimating an object's initial distance and velocity components via noised bearings from a moving observer belongs to a class of linear models with stochastic regression matrix, at that, estimates has uncontrollable bias. Bayes combination of least squares and orthogonal regression aimed at the above bias reduction is considered in this paper.