Parameter estimation of polynomial phase signal based on low-complexity LSU-EKF algorithm in entire identifiable region

Fast implementation of parameter estimation for polynomial phase signal (PPS) is considered in this paper. A method which combines the least squares unwrapping (LSU) estimator and the extended Kalman filter (EKF) is proposed. A small number of initial samples are used to estimate the PPS's parameters and then these coarse estimates are used to initial the EKF. The proposed LSU-EKF estimator greatly reduces the computation complexity of the LSU estimator and can work in entire identifiable region which inherits from the LSU estimator. Meanwhile, in the EKF stage its output is in point-by-point wise which is useful in real applications.

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