To date, the actual population of High Area-to-Mass Ratio (HAMR) objects in Deep Space is still un- quantified. These are objects having area-to-mass ratios (AMR's) in the range of around 0.1 m2/kg to 20 m2/kg and higher. Typical methods for population assessment using optical sensors either count number of detections per unit time, or employ a disparate sequence of methods to compute HAMR object trajectories, where these methods assume linearized dynamics and fixed-gate correlations. This paper provides results from a set of actual angles (line of sight) data on HAMR objects, where the initial orbit determination and follow-on data/track association is performed probabilistically and autonomously. Moreover, the data are not only used to infer trajectories but also simultaneously exploited for their information content relating to each detected object's albedo-area-to-mass ratio. The results show that the inferred HAMR orbital elements and area-to-mass ratio values (CrA/m), parametrically, can be derived autonomously and without a priori knowledge of the orbit and CrA/m states. This will aid in the correlation of large numbers of uncorrelated tracks.