Outline progress in RFI mitigation (methods inventory) system design & RFI mitigation: what and where

1. System design & RFI mitigation DS4T3 (OPAR, ASTRON, INAF-IRA, UORL, CSIRO) Outline • progress in RFI mitigation (methods inventory) • system design & RFI mitigation: what and where 2nd SKADS Workshop 10-11 October 2007

2. System design & RFI mitigation DS4T3 (OPAR, ASTRON, INAF-IRA, UORL, CSIRO) Deliverable Achieved 1 RFI mitigation methods inventory fall 2007 2 Influence on data quality Y3Q4 3 Impact of moving interference sources fall 2007 4 Cost effect. and tech. Requirements SKA site Y3Q4 5 Demonstrations with EMBRACE, BEST … Y4Q4 6 RFI mitigation strategies for the SKA Y4Q4 phased-arrays 2nd SKADS Workshop 10-11 October 2007

3. RFI Mitigation Methods InventoryReport, June 2007 • Introduction • Spectral selectivity • Temporal selectivity • Spatial Selectivity • Multi-dimensional techniques • Implications for SKA and conclusions 2nd SKADS Workshop 10-11 October 2007

4. Spectral selectivity polyphase filterbank ALMA memo 447 (J. Bunton) for cascaded PFB 2nd SKADS Workshop 10-11 October 2007

5. Spectral selectivitynarrow band RFI elimination 2nd SKADS Workshop 10-11 October 2007

6. Temporal selectivityBlanking • Detection theory based on hypothesis testing 2nd SKADS Workshop 10-11 October 2007

7. Temporal selectivityBlanking • Single-antenna detection: Pfa and PD are known Pfa = Qc2(2g) PD = Qc2(2g / (1+INR)) • Multiple-antenna (p) detection (spatial-temporal) : matched spatial detector: compare the received energy from the interferer to the noise test : data covariance matrix, combined with known interferer direction Pfa : same PD = Qc2(2g / (1+p.INR)) residual after blanking : INRresa 1 / p.N1/2 N: number of samples 2nd SKADS Workshop 10-11 October 2007

8. Spatial selectivityFiltering • Algorithms are based on modifications of data covariance matrix by a spatial filter, such that: Pkak = 0 (ak direction of interferer) Pk applied to covariance matrix: interferer energy nulled • when ak is unknown ? => find eigenvalues and eigenvectors • a correction (matrix) has to be applied to the filtered covariance matrix • Constraint: astronomical signal power << interferer power • residual after blanking : 2nd SKADS Workshop 10-11 October 2007

9. Multi-dimensional techniquesCyclostationarity cyclostationary process : statistics are periodic with time Random binary signal: temporal view covariance : time origin as random covariance : time origin as constant 2nd SKADS Workshop 10-11 October 2007

10. system design & RFI mitigationASTRON/ISPO SSSM SKA monitoring results 2005/2006 virtual site, i.e. median of maxima of curves from the four sites visited : South Africa, China, Australia, Argentina Cf. SKA monitoring protocol 2003 S.Ellingson et al (SKA memo) • Number of ADC bits: • 3 to 7 effective bits • depending on f, BW, site • if nonlinearities for short timescales are allowed: only 3 to 5 bits are needed 2nd SKADS Workshop 10-11 October 2007

11. system design & RFI mitigationdata transportbottleneck • From RFI & data coding perspective: • use large subband bandwidth from stations to central site • break bands into more subbands / isolate bands with strong RFI • apply (fixed) spatial nulls at station level (“cheap”) • apply parametric techniques (more expensive; specific to coding scheme) 2nd SKADS Workshop 10-11 October 2007

12. system design & RFI mitigation effectiveness • Bottom line: one can mitigate RFI down to the level that it can be detected • So: delay RFI mitigation to the last stages in the datastream where data compression reduces the RFI mitigation SP load (beamforming, post correlation integration), unless… • for dynamic range reasons • - linearity requirements of LNAs after BF (PAF) • - reduce number of bits (data transport reduction / digital stages PAF/AA) • RFI is strongly spatially distributed • - then local spatial filter makes more sense, • at stations or between several stations • RFI spectral bandwith does not match channel bandwidth • - all methods • RFI temporal characteristics • - excision of s bursts close to antenna; drawback: loss of gain information 2nd SKADS Workshop 10-11 October 2007

13. system design & RFI mitigation effectiveness • Stacking of methods is not usefull unless … • ...different domains are combined, e.g. • RFI source subtraction, sidelobe cancelling and spatial filtering in arrays are all spatial methods – in general not much use combining them • parametric methods (Glonass/DVB suppr., Ellingson et al) and spatial filtering 2nd SKADS Workshop 10-11 October 2007

14. system design & spatial filtering • DOA, subspace techniques: order Nant3 • Rank-one subspace techniques, single source DOA: order Nant2 • If direction known, and apply to beamformer or correlator: cheap! • DOA and subspace estimation usually is expensive • especially if it needs to be done at a high update rate • Applying fixed filters,known fixed directions • Most fixed transmitters: easily ~20 dB supp. • If propagation modifies spatial structure: • add closely spaced nulls / increase subspace to be removed • Very cheap method if combined with beamformer of correlator • Applying on-line varying filters, moving interferers • Both for fixed and moving transmitters: good suppression • Filter distorts uvw data as well, but can be restored under certain conditions • Expensive method (online matrix operations) • Drawback: affects the beamshape => hampers on-line calibration, “smoothness criterium” 2nd SKADS Workshop 10-11 October 2007

15. Signal path Method Pro’s Con’s Antenna beam- formers (e.g. PAF) varying spatial filtering, including sidelobe canceller reduce strong RFI enables the use of less ADC bits / lessens LNA req. fluctuating beam may impair calibration fixed spatial filtering reduce strong RFI enables the use of less ADC bits / lessens LNA req. difficult; needs careful calibration [excision] - lower SP load at output station beamformers Station beamformers fixed spatial filter very cheap; reduce data transport rate to central site more complex operation; connection wit cenral systems varying spatial filters, sidelobe canceller somewhat better suppression than fixed; tracking possibilities may be costly; changing sidelobes may impair calibration excision (assuming no subband filtering is done yet) low SP load unless booking is done on excised samples; fast transients bookkeeping very costly; impairing gain estimate otherwise parametric techniques (assuming wide bands) can be used in combination with other methods may be costly Pre-correlation Interstation sidelobe cancelling/ spatial filtering, moving sources may be applicable at shorter timescales than at location of correlator output influences UVW data points; may impair calibration Correlation excision can be done at short timescales and short bandwidths; common practice - Post processing Spatial filtering, parametric techniques, … very flexible; can be added when necessary; relatively cheap may be complex; may be time consuming Applicability in SKA 2nd SKADS Workshop 10-11 October 2007