Real-time RFI Mitigation for the Upgraded GMRT

Transcription

1 Real-time RFI Mitigation for the Upgraded GMRT Kaushal D. Buch Digital Backend Group, Giant Metrewave Radio Telescope, NCRA-TIFR, Pune, India

2 The (Upgraded) GMRT Giant Metrewave Radio Telescope(GMRT) Array consisting of thirty 45m diameter parabolic reflector antennas A highly sensitive radio receiver system for observing astrophysical phenomena at low radio frequencies Upgraded GMRT(uGMRT) Nearly seamless frequency coverage from 50 to 1450 MHz Instantaneous receiver bandwidth from 32 MHz to 400 MHz Increased bandwidth and receiver sensitivity to encounter increasing levels of manmade radio frequency interference(rfi) ugmrt MHz and L-band released for observations on shared-risk basis 2

3 Major Sources of RFI at GMRT Broadband RFI Sparking on power-lines Corona Discharge Automobile sparking 11 kv transformers around S-arm of GMRT array Narrowband RFI Communication transmitters Broadcast TV / Radio Satellites 3 Data Courtesy: Pravin Raybole, RFI Group, GMRT

4 RFI at GMRT RFI Broadband RFI is stronger at lower radio frequencies Broadband RFI Narrowband RFI Examples showing impulsive time and frequency domain RFI observed at the GMRT 4 RFI

5 Need for Real-time Excision Temporally impulsive RFI: Energy spreads post-fft hence excision is needed before FFT. Power-line RFI: Low duty cycle but high spectral occupancy RFI is correlated in closely spaced antennas Spectrally impulsive RFI: RFI excision useful for low time occupancy Best possible time resolution: reduction in loss of astronomical data due to flagging (trade-off) Leads to improvement in the receiver sensitivity 5

6 Location of Real-time Excision blocks FFT: Fast Fourier Transform MAC: Multiply & Accumulate IA: Incoherent Array PA: Phased Array RFI excision at multiple locations in the receiver chain (This talk will focus on real-time RFI for the ugmrt correlator) 6

7 GMRT Wideband Digital Backend (GWB) GWB: Reddy et al., JAI 2017 Real-time broadband RFI Mitigation is implemented on ROACH-1 FPGA board 7

8 Robust Detection using MAD RFI in astronomical data outliers make Gaussian distribution heavy-tailed (Fridman, 2008) Excision (Baan, 2001, 2010) assumes that RFI is much stronger than the astronomical signal Robust threshold using Median Absolute Deviation for RFI detection (Fridman,2008) σ MAD=1.4826(med( x(i) med(x) )) Impulsive RFI detection and filtering(buch et al., JAI, 2016) Excision(filtering) by replacing the RFI affected samples by constant value ornoiseorthreshold Robustthreshold: median ± n*σ MAD Implemented in temporal and spectral domains for the ugmrt (Buch et al., RFI- 2016, IEEE, 2016) 8

9 Broadband RFI Excision FFT: Fast Fourier Transform MAC: Multiply & Accumulate IA: Incoherent Array PA: Phased Array 9 Broadband RFI filtering is carried out in real-time on Nyquist-sampled digital timeseries (for each antenna) at 800 MHz

10 Estimation Detection -Filtering Filtering can be bypassed 10

11 MAD-based RFI Detection and Filtering Computation of real-time Median using the histogram method Non-linear filtering med(x+y) med(x) + med(y) Values outside the range of [median ± n*σ MAD ] are treated as RFI Available filtering options: 1. Clipping Replacement with 2. Constant value 3. Digital noise (Buch et al., JAI, 2014) 4. Median RFI Detection is followed by filtering 11

12 Real-time Implementation MAD = med( x(i) med(x) ) Resource utilization: (8-bit input) 16k window MAD: 20% slices 4k window MoM: 18% slices 12 Uses the histogram method for median computation explores parallelism on FPGA Windowsizeis2T R /T S )sampleswheret R isthe(worstcase)durationofrfiandt S is the sampling interval Long-lasting RFI: Hold MAD values from consecutive windows in a memory buffer and compute the median(m)i.e.medianofmad(mom)values(m m ) M m =M(MAD 1,MAD 2,...,MAD n ) Buch et al., RFI-2016, IEEE,

13 Real-time RFI Filtering: Features Filter one or both the polarizations First Median (External input) Includes option to bypass the filter 13 Two main parameters threshold value (N) and filtering options

14 RFI Count Broadband RFI filter counts the RFI samples in a given time period along with the total number of samples 64-bit counters Two control signals reset and hold Manual hold : Asynchronous mode, Automatic hold: Synchronous mode Flagging fraction = No. of RFI samples / Total samples Timestamp along with the count for each antenna Takes about half a minute to read data from all the 16 ROACH boards Works even if the filtering is OFF (bypass mode) 14

15 Test Procedure a. RFI emulator (controlled testing) b. Antenna signals c. System-level tests Outputs: raw voltage (1.25 ns), beam mode (1.31 ms) and correlator mode (671 ms) Simultaneous comparison between unfiltered and filtered data (different threshold and replacement options), beam and correlator outputs Improvement characterized by the mean/rmsratio Preliminary tests carried out for imaging radio sources with and without broadband RFI excision 15

16 Simultaneous Testing Unfiltered and Filtered Digital copy of one antenna fed to two or four inputs for simultaneous comparison 16

17 Test Results Raw voltage Comparison between MAD and MoM on unfiltered and filtered raw voltage Pulse input provided through RFI emulator, on-period 32μs total-period 240μs 17

18 Test Results MAD vsmom 18 Total samples in 30 min. duration = Samples flagged as RFI = (MAD)(0.43%) and (MoM)(0.44%)

19 Test Results MAD vsmom I (db) = 10log(M F /M U ) M F, M U : running mean/rms for filtered, unfiltered beam output 19

20 Test Results Beam and Correlator 20 Simultaneous recording of beam mode (1.3 ms) and correlator mode (671 ms) with different thresholds replacement by zeros.

21 First Image Unfiltered RMS: 2.26 mjy Image Courtesy: Dharam Vir Lal Filtered RMS: 1.29 mjy MHz, ugmrt, 16 antennas, Pol.-1 (left, without filter) & Pol.-2 (right, with broadband RFI filter), a factor of two (approx.) improvement in noise RMS 21

22 Spectral Domain RFI Filtering FFT: Fast Fourier Transform MAC: Multiply & Accumulate IA: Incoherent Array PA: Phased Array Real-time Narrowband RFI filtering is carried out at 0.671s integration on multi-core CPUs 22

23 Narrowband RFI Excision Two approaches to Spectral domain MAD filtering 1. MAD-based filtering of each channel over time(mfat) and 2. MAD-based filtering across the spectral channels(mfac) Estimation and filtering across channel is more suitable for real time applications with additional correction required for across the band gain variations. Current system: Normalization of spectral power is followed by MFAC 23

24 Narrowband RFI ugmrt ( MHz) 24

25 Summary Broadband RFI filtering is available for the ugmrt user community Long-term tests and imaging experiments show improvement in the performance of the system Narrowband real-time RFI excision will be released soon! Fine-tuning of broadband and narrowband RFI filtering techniques is in progress 25

26 Acknowledgements Current members Kishor Naik Sanjay Kudale Ajithkumar B. Yashwant Gupta Imaging tests and data analysis DharamVir Lal Ruta Kale Sanjay Kudale Ishwara Chandra C.H. Viral Parekh (RRI) Past members Swapnil Nalawade Shruti Bhatporia Short-term Engineering Interns GMRT groups GMRT Backend Team Control Room and Operations 26

27 Thank You! For queries, suggestions or comments, 27