A computationally efficient technique for estimating the parameters of polynomial-phase signals from noisy observations

Many real-world applications are characterized by the presence of polynomial phase signals embedded in noise. These applications include radar, sonar, telemetry, communications, and power systems. In a significant number of these applications, it is highly desirable to be able to accurately estimate the polynomial phase signal parameters. This correspondence presents a computationally efficient method for estimating any or all of the parameters of polynomial-phase signals in white Gaussian noise and provides a first-order statistical analysis of the technique. Simulations are also presented to support the theoretical analysis.