OPTIMAL EIGENVALUE DECOMPOSITION BASED FREQUENCY ESTIMATION ALGORITHM FOR COMPLEX SINUSOIDAL SIGNALS

Muhammad Zubair, Sajid Ahmed, Seifallah Jardak, Mohamed-Slim Alouini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The estimation performance of subspace based algorithms depends on the selection of dominant eigenvalues, which is challenging. In this paper, by exploiting the circular transformation, an optimal dominant eigenvalue selection subspace based frequency estimation algorithm is proposed. The proposed algorithm restricts the contribution of signal into fixed number of dominant eigenvalues. The performance of the proposed algorithm is compared with Multiple Signal Classification (MUSIC) and Karhunen-Loeve-transform (KLT) algorithms. The analytical and simulation results show that proposed algorithm outperforms the MUSIC and KLT algorithms.
Original languageEnglish (US)
Title of host publication2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1119-1123
Number of pages5
ISBN (Print)9781728112954
DOIs
StatePublished - Mar 18 2019

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