Analysis and extraction of strongly frequency modulated signals have been a challenging problem for Adaptive
Data Analysis methods; e.g., Empirical Mode Decomposition (EMD) [13]. In fact, many of the Newtonian
dynamical systems, including conservative mechanical systems, are sources of signals with low to strong levels
of frequency modulation. Analysis of such signals is an important issue in system identification problems. In
this paper, we present a novel method to accurately extract Intrawave Signals. This method is a descendant of
Sparse Time-Frequency Representation (STFR) methods [8, 7]. We will present numerical examples to show the
performance of this new algorithm. Theoretical analysis of convergence of the algorithm is also presented as a
support for the method. We will show that the algorithm is stable to noise perturbation, as well.