rfi mitigation and burst detection with a digital receiver

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RFI Mitigation and Burst Detection with a Digital Receiver RFI2004 July 16 - 18, 2004 Cedric Dumez-Viou 1,4 , Andrée Coffre 4 ,Pierre Colom 2 , Laurent Denis 4 , Alain Lecacheux 2 , Jean-Michel Martin 3 , Philippe Ravier 1 , Rodolphe Weber 1 , Philippe Zarka 2 1 LESI, Polytech'Orleans - Université d'Orléans 2 LESIA, Observatoire de Paris/CNRS 3 GEPI, Observatoire de Paris/CNRS 4 Station de Radioastronomie de Nançay 1

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RFI Mitigation and Burst Detectionwith a Digital Receiver

RFI2004July 16 - 18, 2004

Cedric Dumez-Viou1,4, Andrée Coffre4,Pierre Colom2,Laurent Denis4, Alain Lecacheux2, Jean-Michel Martin3,

Philippe Ravier1, Rodolphe Weber1, Philippe Zarka2

1 LESI, Polytech'Orleans - Université d'Orléans 2 LESIA, Observatoire de Paris/CNRS3 GEPI, Observatoire de Paris/CNRS4 Station de Radioastronomie de Nançay

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RSR: Radio Spectrum Reconquest

● High dynamic receiver ( > 70dB )

● Highly reconfigurable

● for multipurpose use2

RSR: Radio Spectrum Reconquest

● High dynamic receiver ( > 70dB )

● Highly reconfigurable

● for multipurpose use3

Current implementations

● Sigma detectors forTime-Frequency Blanking

● T-FDMA RFI mitigation● Wideband RFI mitigation

● Fine Structures

● Future works...4

Given constraints

● Implementation of basic methods to be used today.

● RFIs detection based on power estimation.

● Real-time algorithms.- Only a small part of the signal is available.- Limited data-flow.

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Blanking of T-FDMA modulation:principle

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Blanking of T-FDMA modulation:principle

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Blanking of T-FDMA modulation:principle

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Blanking of T-FDMA modulation:principle

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Original Data

Frequency

Time

Blanking of T-FDMA modulation:principle

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Original Data

Frequency

Time

Blanking of T-FDMA modulation:principle

Full Spectrum Blanking

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Original Data

Frequency

Time

Blanking of T-FDMA modulation:principle

Time-frequency

Block blanking

Full Spectrum Blanking

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Blanking of T-FDMA modulation:method

● T-FDMA are narrow band signals--> efficient mean and variance estimate

using median filtering or robust mean.

● Full spectrum blanking:- 20% loss of data.- Excellent rejection of RFI.

● Time-frequency Block blanking:- 2.5% loss of data.- Unequal equivalent time of integration.

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Blanking of T-FDMA modulation:IIIZw35 OH megamazer results

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Blanking of Wideband RFIs:principle

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Blanking of Wideband RFIs:principle

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Blanking of Wideband RFIs:principle

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● Lightnings, Radars, ...● Occupy the full band or most of it.– Median filtering not applicable.– Estimation of mean and variance compromised.

Blanking of Wideband RFIsmethod

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● Lightnings, Radars, ...● Occupy the full band or most of it.– Median filtering not applicable.– Estimation of mean and variance compromised.

Blanking of Wideband RFIsmethod

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● Lightnings, Radars, ...● Occupy the full band or most of it.– Median filtering not applicable.– Estimation of mean and variance compromised.

Blanking of Wideband RFIsmethod

● Lightnings, Radars, ...● Occupy the full band or most of it.– Median filtering not applicable.– Estimation of mean and variance compromised

● Wideband BUT not continuous in time.– Some spectrum are free of RFIs– Time averaging to find clean spectrum

Blanking of Wideband RFIsmethod

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Blanking of Wideband RFIsresults

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● Blanking simulation on real data.● Current results allow 10 minutes of

integration without signs of RFIs.● Further testes needed to evaluate RFI

rejection.

Blanking of Wideband RFIsresults

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Fines Structures:principle

● Solar and Jovian radio-emissions● Very brief « Chirps » (~100ms).

● High frequency and time resolutionrequired to understand the underlying physics

● High volume of data (50Go/h)--> Backup of interesting events only.

● Automatic recorder✔ Detection of RFI-like SOIs,✔ Corrupted by RFIs (frequency lines and wide-band signals),✔ With real-time constraints.

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Fines Structures: method

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Fines Structures: results

More advanced methods for the future...

● Encouraging results for real-time RFI mitigation.● Should work shortly for daily-use observation.● Classifier (SVM, neural networks, expert systems,...).

– Automatic determination of RFIs characteristics.– Selection of the appropriate parameters for blanking.

● Implementation of cyclostationary detector.– Highlight hidden periodicities of signals.– Present in telecommunications.– Absent in most natural signals.

www.obs-nancay.fr/rfi27

More advanced methods for the future...

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