ESPRIT-estimation of signal parameters via rotational invariance techniques

1989/07/01 by R. Roy, T. Kailath · 7,111 citations
Computer Science · Earth and Planetary Sciences · Mathematics · #Algorithm #Artificial intelligence #Blind Source Separation Techniques #Capon #Computer science #Context (archaeology) #Direction of arrival #Direction-of-Arrival Estimation Techniques #Estimation theory #Geography #Image (mathematics) #Least-squares function approximation #Linear subspace #Mathematics #Noise (video) #Pure mathematics #Rotational invariance #SIGNAL (programming language) #Statistics #Telecommunications #Underwater Acoustics Research

paper · doi:10.1109/29.32276

published in IEEE Transactions on Acoustics Speech and Signal Processing 37(7), 984-995 (Institute of Electrical and Electronics Engineers)

openalex publication_date 1989/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. The technique, when applicable, manifests significant performance and computational advantages over previous algorithms such as MEM, Capon's MLM, and MUSIC.>

Citations

• The Differentiation of Pseudo-Inverses and Nonlinear Least Squares Problems Whose Variables Separate
• Detection of signals by information theoretic criteria

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