  Active Radio Frequency Interference (RFI) mitigation becomes a necessity for
radio astronomy. The solution commonly applied by the community consists in
monitoring the statistics of the received signal, and flag out the detected
corrupted data. Subspace projection with array radio telescopes has been
suggested as an alternative to data excision to avoid important losses of data
and overcome its inherent ineffectiveness with continuous interference. Spatial
filtering relies on the estimation of the RFI spatial contribution, and the
projection of the subspace spanned by the RFI out of the observed data vector
space. To perform well, the dimensionality of the RFI subspace is constrained.
RFI subspace estimation techniques assume the source of RFI to be spatially
stationary over the sample covariance matrix evaluation. When the relative
movement between the telescope and the interferer becomes significant, the RFI
subspace gets smeared over the whole data vector space. The subspace projection
can then no longer be applied without affecting the source of interest
recovery. This paper addresses the effect of RFI subspace smearing on the
subspace projection approach, and suggests an alternative technique based on a
covariance matrix subtraction, improving the performance of spatial filtering
in the case of high subspace smearing.
