RFI mitigation techniques in radio astronomy

Radio frequency interference (RFI) is an important problem for a radio astronomy system (RAS) due to the very weak radio astronomical signals. Rapid expansions of active wireless systems (AWSs), as well as more demands for spectrum access by both AWS and RAS will result in scenarios with strong RFI. This will cause RAS's low-noise amplifier (LNA) to operate in a nonlinear region and impose a more challenging nonlinear RFI issue. We address this issue for RAS with the antenna array. We develop a new signal model at the output of RAS array processing when the LNA at each RAS receiver behaves nonlinearly. We show that the two existing methods to address RFI in RAS array systems fail to deal with the nonlinear RFI. Next, we propose two modified methods to address the nonlinear RFI. Analysis of the squared error of the RAS signal correlation estimate is also presented. The numerical results show the severe effects of nonlinear RFI and the capability of the proposed methods to keep the squared error almost as low as that of a linear system.

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“…In next equations (22) to 26, we eliminate the sampling indices for convenience. Define r y,nl as the (n, l) entry of the matrix R y .…”

Section: A New Signal Model For Array Ras With Nonlinear Lnasmentioning

confidence: 99%

“…Now, to obtain an expression for (22), we first have to obtain the instantaneous terms in (22) and then apply the expectation operator. By generalizing (16) and 17for the nth and the lth receivers, we obtain…”

Section: A New Signal Model For Array Ras With Nonlinear Lnasmentioning

confidence: 99%

RFI Cancellation for an Array Radio Astronomy System With Receiver Nonlinearity

Abdelgelil

Minn

2019

IEEE Access

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“…The inclusion of the CR in the dual GT enables the design of a GT that responds to the requirement of improving the angular resolution. Being suitable for designing solutions that enhance interference mitigation and angular resolution, the CR can be used to design technical solutions that enhance terrestrial radio astronomy observations [30]. However, the use of the CR in this aspect requires further consideration.…”

Section: Optimising Terrestrial Radio Astronomy Observationsmentioning

confidence: 99%

Intelligent Cognitive Radio Models for Enhancing Future Radio Astronomy Observations

Periola

Falowo

2016

Advances in Astronomy

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Radio astronomy organisations desire to optimise the terrestrial radio astronomy observations by mitigating against interference and enhancing angular resolution. Ground telescopes (GTs) experience interference from intersatellite links (ISLs). Astronomy source radio signals received by GTs are analysed at the high performance computing (HPC) infrastructure. Furthermore, observation limitation conditions prevent GTs from conducting radio astronomy observations all the time, thereby causing low HPC utilisation. This paper proposes mechanisms that protect GTs from ISL interference without permanent prevention of ISL data transmission and enhance angular resolution. The ISL transmits data by taking advantage of similarities in the sequence of observed astronomy sources to increase ISL connection duration. In addition, the paper proposes a mechanism that enhances angular resolution by using reconfigurable earth stations. Furthermore, the paper presents the opportunistic computing scheme (OCS) to enhance HPC utilisation. OCS enables the underutilised HPC to be used to train learning algorithms of a cognitive base station. The performances of the three mechanisms are evaluated. Simulations show that the proposed mechanisms protect GTs from ISL interference, enhance angular resolution, and improve HPC utilisation.

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“…RFI mitigation strategies and motivation for NGSO-SCRAS: Even though some efforts have been made to mitigate the RFI from active wireless services (including satellite communication) to the ground RAS, e.g., beam forming/subspace or spatial filtering [15]- [24], auxiliary antenna based RFI removal [25]- [29], cognitive radio based approaches [30], [31], and time-division spectrum sharing [32]- [34], blanking and excision [35]- [38], unfortunately, their applicability to the large-scale NGSO systems is very limited. As large-scale NGSO systems plan to cover most of the Earth surface, radio observatories on Earth cannot hide from NGSO satellites' potential RFI.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Algorithm for Radio Astronomy Observation Data Transport in an Integrated NGSO Satellite Communication and Radio Astronomy System

Mohamed

Minn

2021

IEEE Open J. Commun. Soc.

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An integrated non-geostationary orbit (NGSO) satellite communication and radio astronomy system (SCRAS), was recently proposed in [1] as a new coexistence paradigm. In SCRAS, the transportation of the radio astronomical observation (RAO) data from the space to the ground stations is an important problem, for which [1] proposed a linear programming optimization based algorithm. However, the computational complexity of this algorithm is quite high which is exacerbated by the need to re-compute the algorithm frequently due to the time-varying characteristics of the observing satellites, the Earth stations, and the RAO region. In this paper, to address this high complexity issue, we develop a low-complexity RAO data transport algorithm. In addition to the static resource constraint scenario considered in the existing work, we introduce a dynamic resource constraint scenario to exploit the knowledge of the satellite communication system (SCS) traffic statistics. We also present a modified version of the algorithm in [1] for the dynamic resource constraint scenario. In addition to the number of inter-satellite link (ISL) hops as the RAO data transport cost metric, we also evaluate the metric of the sum of the squared ISL hop distances which reflects the transmission energy cost. Furthermore, computational complexity analysis and data transport costs of the algorithms are presented. Our results show that the proposed algorithm yields several orders of computational complexity saving over the existing method while incurring a modest increase in the data transport cost. Our proposed dynamic resource constraint scenario provides plausible reduction of the RAO data transport cost.

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RFI mitigation techniques in radio astronomy

Cited by 30 publications

References 6 publications

RFI Cancellation for an Array Radio Astronomy System With Receiver Nonlinearity

RFI Cancellation for an Array Radio Astronomy System With Receiver Nonlinearity

Intelligent Cognitive Radio Models for Enhancing Future Radio Astronomy Observations

Low-Complexity Algorithm for Radio Astronomy Observation Data Transport in an Integrated NGSO Satellite Communication and Radio Astronomy System

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