To investigate the structure of neutron-rich nuclei, we are developing a silicon tracker and a liquid hydrogen target which together form the STRASSE detection system. This system will allow to perform missing mass spectroscopy of radioactive nuclei from quasi-free scattering. PFAD is the demonstrator of the STRASSE detector, consisting of one third of the STRASSE tracker. It establishes a baseline for the performance capabilities and ensures the working principle of the future STRASSE tracker. During this thesis, experimental data acquired with PFAD will be used to develop and benchmark different optimization algorithms, which will then be compared to a neural-network alignment trained on simulations. This will lead to the best achievable alignment and position resolution. The work of this thesis will lay the groundwork for STRASSE.