Article,
Antenna Arrays
Proc. of the ION GNSS Conf., (1999)
Abstract
The reduction of the errors in the observables caused by the multipath
propagation and the interferences is addressed. Two different estimators
are derived by applying the maximum likelihood (ML) principle to
a signal model that assumes the reception of several refl ections
of the GNSS signal and that the spatial signatures of all the signals
are arbitrary and unstructured. The first estimator, which is a classical
result since the noise is modeled as spatially white, is an extension
of the well-known multipath estimating delay-lock-loop. The second
estimator is derived by assuming that the spatial correlation matrix
of the noise is unknown. This endows the estimator with interference
cancelation capability, of which the first estimator lacks. The second
method constitutes a new result and its performance is always equal
or better than that of the first one. Moreover, we propose an approximation
of the estimator for the correlated-noise case that provides the
same performance as the original criterion. This approximation may
allow the use of a computationally simple optimization algorithm
that was only applicable in the white-noise case.
