A Two-Step Time of Arrival Estimation Algorithm for Impulse Radio Ultra Wideband Systems

TL;DR

This paper introduces a two-step TOA estimation algorithm for UWB systems that combines energy-based rough estimation with hypothesis testing for accurate first path detection, reducing complexity and time.

Contribution

A novel two-step TOA estimation method that uses low-rate correlation outputs and improves speed and accuracy over traditional correlation-based algorithms.

Findings

Accurate TOA estimation achieved with reduced computational complexity

Method outperforms conventional algorithms in simulation tests

Effective first path detection in multipath environments

Abstract

High time resolution of ultra wideband (UWB) signals facilitates very precise positioning capabilities based on time-of-arrival (TOA) measurements. Although the theoretical lower bound for TOA estimation can be achieved by the maximum likelihood principle, it is impractical due to the need for extremely high-rate sampling and the presence of large number of multipath components. On the other hand, the conventional correlation-based algorithm, which serially searches possible signal delays, takes a very long time to estimate the TOA of a received UWB signal. Moreover, the first signal path does not always have the strongest correlation output. Therefore, first path detection algorithms need to be considered. In this paper, a data-aided two-step TOA estimation algorithm is proposed. In order to speed up the estimation process, the first step estimates the rough TOA of the received signal based on received signal energy. Then, in the second step, the arrival time of the first signal path is estimated by considering a hypothesis testing approach. The proposed scheme uses low-rate correlation outputs, and is able to perform accurate TOA estimation in reasonable time intervals. The simulation results are presented to analyze the performance of the estimator.