A key aspect of the search for Earth-like exoplanets with direct imaging is determining if the exoplanet is in the habitable zone. Future direct imaging mission concepts such as HabEx and LUVOIR require an efficient cadence of observations. Previous work shows that a minimum of three epochs, spanning more than half a period, can determine orbital parameters to 10% for a single, circular orbit. Multi-planet systems may require a different number and cadence of observations. We begin to address the multi-planet minimum observation approach by considering only the astrometric data of exoplanet candidate objects in high contrast images. Existing multi-planet trajectory matching libraries such as “Orbits For The Impatient” (OFTI) currently require users to specify which point sources belong to which planet and assumes that the user has already matched true- positive detections to planets. Additionally, planet matching needs to be considered when assessing the impact of observation scheduling on trajectory estimation accuracy. To address this need for fitting orbits to multiple objects with limited knowledge, we present an approach using a Monte Carlo study of different observation schedules and planetary systems in which we have developed an algorithm to automatically match observations to planets, and then check the accuracy of the matches. With a large number of cases, we can constrain the number of observations and the spacing necessary to “deconfuse” the detections. We present preliminary planet matching success rates for different observing schedules and planetary system parameters. We use these results to assess the scope of the confusion problem and discuss potential mitigation strategies.