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A Hybrid CPF-HAF Estimation of Polynomial-Phase Signals: Detailed Statistical Analysis

2012; Institute of Electrical and Electronics Engineers; Volume: 60; Issue: 10 Linguagem: Inglês

10.1109/tsp.2012.2205570

1941-0476

Igor Djurović, Marko Simeunović, Slobodan Djukanović, Pu Wang,

Structural Health Monitoring Techniques

In this paper, we consider parameter estimation of high-order polynomial-phase signals (PPSs). We propose an approach that combines the cubic phase function (CPF) and the high-order ambiguity function (HAF), and is referred to as the hybrid CPF-HAF method. In the proposed method, the phase differentiation is first applied on the observed PPS to produce a cubic phase signal, whose parameters are, in turn, estimated by the CPF. The performance analysis, carried out in the paper, considers up to the tenth-order PPSs, and is supported by numerical examples revealing that the proposed approach outperforms the HAF in terms of the accuracy and signal-to-noise-ratio threshold. Extensions to multicomponent and multidimensional PPSs are also considered, all supported by numerical examples. Specifically, when multicomponent PPSs are considered, the product version of the CPF-HAF outperforms the product HAF (PHAF) that fails to estimate parameters of components whose PPS order exceeds three.