When ancient samples are sequenced, one of the first questions asked is how those samples relate to modern populations and to each other. Commonly, this is assessed using methods such as Structure or Admixture, which model individuals as mixtures of latent "ancestry components". If an ancient individual is found to not carry similar ancestry components to a modern individual, that sample is considered to be not directly related to the modern individual. However, the model used by Structure fails to account for the difference in genetic drift in ancient and modern populations and hence can cause misleading inferences about the relationships of ancient samples to modern populations. As a first step toward remedying this, I developed a novel method that can estimate the relationship of an arbitrarily large sample of ancient individuals to a modern reference population. I do this using a diffusion theory approach, and integrate over the uncertainty in genotypes that results from low coverage ancient sequences. Although the approach can only estimate the relationships of a single population at a time, I use an ad hoc clustering method that can group individuals into populations and refine estimates of how those populations are related to the modern reference panel. I might show some application to human ancient DNA data from Europe.