Abstract
We consider fine parameter estimation of polynomial-phase signals (PPSs) using the cubic phase function (CPF). The CPF outperforms the high-order ambiguity function (HAF) both in the estimation accuracy and performance threshold. However, since the CPF cannot be calculated using the FFT, it is characterized by higher complexity than the HAF. The fine estimation is usually done through the time-consuming oversampling. In this paper, we propose three methods for the fine estimation of the PSS parameters from the CPF. The methods are based on the dichotomous search, Newton-Raphson (NR) method and secant method, iterative maximization methods. All the three methods significantly reduce the calculation complexity with respect to the oversampling or maximum-likelihood (ML) approach.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.