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Active Radio Frequency Interference (RFI) mitigation becomes a necessity forradio astronomy. The solution commonly applied by the community consists inmonitoring the statistics of the received signal, and flag out the detectedcorrupted data. Subspace projection with array radio telescopes has beensuggested as an alternative to data excision to avoid important losses of dataand overcome its inherent ineffectiveness with continuous interference. Spatialfiltering relies on the estimation of the RFI spatial contribution, and theprojection of the subspace spanned by the RFI out of the observed data vectorspace. To perform well, the dimensionality of the RFI subspace is constrained.RFI subspace estimation techniques assume the source of RFI to be spatiallystationary over the sample covariance matrix evaluation. When the relativemovement between the telescope and the interferer becomes significant, the RFIsubspace gets smeared over the whole data vector space. The subspace projectioncan then no longer be applied without affecting the source of interestrecovery. This paper addresses the effect of RFI subspace smearing on thesubspace projection approach, and suggests an alternative technique based on acovariance matrix subtraction, improving the performance of spatial filteringin the case of high subspace smearing.

RFI subspace smearing and projection for array radio telescopes