Generalized Matrix-Pencil Approach to Estimation of Complex Exponentials with Gapped Data

TL;DR

This paper introduces a generalized matrix-pencil method for estimating complex exponential components from gapped, segmented data, achieving super-resolution and efficient parameter estimation in signal processing applications.

Contribution

The proposed approach extends the matrix-pencil method to handle segmented data and distributed array configurations, offering improved super-resolution estimation capabilities.

Findings

Effective estimation of complex exponentials from gapped data

Super-resolution performance demonstrated

Applicable to distributed array signal processing

Abstract

A generalized matrix-pencil approach is proposed for the estimation of complex exponential components with segmented signal samples, which is very efficient and provides super-resolution estimations. It is applicable to the signals sampled segmentally with the same sampling frequency and direction of arrival (DOA) estimation with distributed arrays within which array elements are placed uniformly with the same inter-element spacing.