Interference and Multipath Resilient ToA Estimation

TL;DR

This paper introduces a computationally-efficient ToA estimation algorithm that robustly handles multipath and interference by combining adaptive spatial filtering and autodifferentiation, outperforming traditional methods.

Contribution

The paper proposes a novel ToA estimation method leveraging multiple antennas, adaptive filtering, and autodifferentiation, eliminating the need for model-order estimation and improving robustness.

Findings

Significant performance gains over correlation-based methods

Effective in multipath-rich indoor environments

Low computational complexity

Abstract

We present a computationally-efficient algorithm for time-of-arrival (ToA) estimation that is robust under multipath propagation and strong interference. Our algorithm leverages multiple receive antennas to combine adaptive spatial filtering with autodifferentiation in order to super-resolve the tap of the first-arriving path at low computational complexity and without requiring model-order estimation. We use simulations with ray-traced indoor propagation channels to demonstrate significant performance improvements over conventional correlation-based ToA estimation methods and subspace techniques such as JADE.