Increasing GPS precision at low cost has always been a challenge for the
manufacturers of the GPS receivers. This paper proposes the use of a Wiener
filter for increasing precision in substitution of traditional GPS/INS fusion
systems, which require expensive inertial systems. In this paper, we first
implement and compare three GPS signal processing schemes: a Kalman filter, a
neural network and a Wiener filter and compare them in terms of precision and
the processing time. To further reduce the processing time of Wiener filter, we
propose parallel and reduced-length implementations.