  We use an Autoregressive (AR) approach combined with a Maximum Entropy Method
(MEM) to estimate radial surface currents from coastal High-Frequency Radar
(HFR) complex voltage time series. The performances of this combined AR-MEM
model are investigated with synthetic HFR data and compared with the classical
Doppler spectrum approach. It is shown that AR-MEM drastically improves the
quality and the rate of success of the surface current estimation for short
integration time. To confirm these numerical results, the same analysis is
conducted with an experimental data set acquired with a 16.3 MHz HFR in Toulon.
It is found that the AR-MEM technique is able to provide high-quality and
high-coverage maps of surface currents even with very short integration time
(about 1 minute) where the classical spectral approach can only fulfill the
quality tests on a sparse coverage. Further useful application of the technique
is found in the tracking of surface current at high-temporal resolution. Rapid
variations of the surface current at the time scale of the minute are unveiled
and shown consistent with a $f^{-5/3}$ decay of turbulent spectra.
