High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10169)


In subspace-based methods for mulditimensional harmonic retrieval, the modes can be estimated either from eigenvalues or eigenvectors. The purpose of this study is to find out which way is the best. We compare the state-of-the art methods N-D ESPRIT and IMDF, propose a modification of IMDF based on least-squares criterion, and derive expressions of the first-order perturbations for these methods. The theoretical expressions are confirmed by the computer experiments.


Frequency estimation Multidimensional harmonic retrieval Multilevel Hankel matrix N-D ESPRIT IMDF Perturbation analysis 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.GIPSA-lab, CNRS and Univ. Grenoble AlpesGrenobleFrance

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