The problem of estimating the mass properties of a spacecraft while tracking a 6-DOF reference is addressed using dual quaternions. Dual quaternions provide a position and attitude (pose) representation, which has proven to be advantageous over other, more conventional, parameterizations. An adaptive controller for 6-DOF tracking is proposed using concepts from the concurrent learning framework. The latter is a recently proposed methodology to incorporate current and recorded system data from measurements into the update of an adaptive controller's parameters. Asymptotic convergence of the parameters is ensured through an easily verifiable rank condition of the matrix formed from a finite set of collected data, contrary to the rather stringent, but more common requirement of persistency of excitation. Simulation results for the tracking of a non-persistently exciting, 6-DOF reference are provided and compared to the baseline adaptive controller.