Radio Frequency Interference spatial processing for modern radio telescopes

Abstract : Radio astronomy studies cosmic sources through their radio emissions. As passive users, astronomers have to deal with an increasingly corrupted radio spectrum. The research presented here focuses on man-made Radio Frequency Interference (RFI), and how astronomical observations can be performed in non-protected frequency bands. Traditional approaches consist in monitoring radio telescopes output data through statistical parameters. Once detected, the corrupted data is removed before further processing. Besides other technical advantages compared to single dish radio telescopes, antenna arrays provide spatial information about astronomical observations. The spatial diversity between cosmic sources-of-interest (CSOI) and RFI can be exploited to develop spatial RFI processing. After formulating a multidimensional radio astronomical data model, an interference subspace subtraction technique is introduced. This approach consists in subtracting RFI contributions from antenna array radio telescopes data. Orthogonal projection applied to astronomical observation vector spaces has already been considered by the past. The orthogonality between RFI and CSOI subspaces is required to recover the CSOI without bias. In order to avoid this latter requirement, an oblique projection approach is here proposed. The projection techniques are compared to classic beamforming techniques in term of interference rejection and CSOI recovering. Being usually unknown, the RFI subspace has to be estimated. Several techniques allowing this estimation, based on statistical properties of RFI and cosmic sources (whiteness and cyclostationarity), are also presented and compared. The different techniques have been applied to real astronomical data, provided by the European radio telescope LOFAR. A last section presents an RFI mitigation algorithm implemented on the demonstrator EMBRACE.
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  • HAL Id : tel-01069394, version 1


Grégory Hellbourg. Radio Frequency Interference spatial processing for modern radio telescopes. Other. Université d'Orléans, 2014. English. ⟨NNT : 2014ORLE2006⟩. ⟨tel-01069394⟩



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