Why not using a simple matched filter? Or its general statistical counterpart called cross correlation. Given a known pattern x(t) and a noisy compound time series containing your pattern shifted in a,b,...,z like y(t) = x(t-a) + x(t-b) +...+ x(t-z) + n(t). The cross correlation function between x and y should give peaks in a,b, ...,z
