Can you use clustering to pick out signals in noisy data?
Have you looked at DBSCAN? It is a density-based spatial clustering of data with noise that can define non-linear clusters (unlike k-means).

It doesn't require knowing the number of clusters. However, it does require two parameters (minimum cluster size and neighborhood size) that measure density. But you may be able to estimate them in your particular domain.