  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.
