New method for parameter estimation of polynomial phase signals

In this correspondence, a linear transform called polynomial to Hermite polynomial transform (PHPT) is proposed, and the PHPT-based method for parameter estimation of polynomial phase signals (PPS) embedded in additive white Gaussian noise is addressed. The first advantage is the low computational complexity. If the number of samples is N, the computational complexity is O(3N log₂N) regardless of the order or the component number of PPS. The second advantage is that there is no non-linear operation in PHPT algorithm; therefore there is no cross-term interference in between the various components. In addition, the proposed method can well process the PPS with unknown order phase. Simulations illustrate that the proposed algorithm is more effective as compared with the existing ones.