Extending the Performance of the Cubic Phase Function Algorithm
This paper details an algorithm for estimating the parameters of cubic phase signals embedded in additive white Gaussian noise. The new algorithm is an extension of the cubic phase (CP) function algorithm, with the extension enabling performance at lower signal-to-noise ratios (SNRs). This improvement in the SNR performance is achieved by coherently integrating the CP function over a compact interval in the two-dimensional CP function space. The computation of the new algorithm is quite moderate, especially when compared to the maximum-likelihood (ML) technique. Above threshold, the algorithm's parameter estimates are asymptotically efficient. A threshold analysis of the algorithm is presented and is supported by simulation results. A method for extending the capability of this algorithm to process higher degree phase signals is also presented. Furthermore, the algorithm is applied to a real data signal.
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|Item Type:||Journal Article|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Power and Energy Systems Engineering (excl. Renewable Power) (090607)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||Copyright 2007 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||23 Jul 2008|
|Last Modified:||29 Feb 2012 23:35|
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