Compressive Time Delay Estimation Using Interpolation

TL;DR

This paper introduces a novel compressive sensing method with interpolation for accurate time delay estimation at lower sampling rates, enhancing precision and efficiency.

Contribution

It proposes an Interpolating Band-Excluded Orthogonal Matching Pursuit algorithm that improves estimation accuracy and reduces sampling frequency requirements.

Findings

Interpolation enhances estimation precision.

Compressive sensing achieves a favorable tradeoff between sampling rate and accuracy.

The method maintains performance at lower sampling frequencies.

Abstract

Time delay estimation has long been an active area of research. In this work, we show that compressive sensing with interpolation may be used to achieve good estimation precision while lowering the sampling frequency. We propose an Interpolating Band-Excluded Orthogonal Matching Pursuit algorithm that uses one of two interpolation functions to estimate the time delay parameter. The numerical results show that interpolation improves estimation precision and that compressive sensing provides an elegant tradeoff that may lower the required sampling frequency while still attaining a desired estimation performance.