Transcript Backend electronics for radioastronomy

Backend electronics for
radioastronomy
G. Comoretto
Data processing of a
radioastronomic signal
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Receiver (front-end)
 Separates the two polarizations
 Amplifies the signal by ~108
 Limits the band to a few GHz
 Translates the sky frequency to a more manageable range
The resulting signal is then processed by a back end
Electric field E(t)
Power density S(f)
to backend
Data processing of a
radioastronomic signal
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Measure S as a function of time, frequency, polarization status,
baseline
 Total power
 Polarimetry
 Spectroscopy
 Interferometry
 Pulsar (search and timing)
Record the instantaneous field E(t) for further processing
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VLBI/ Remote interferometry
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Radio science
Composite of the above (e.g. spectropolarimetric
interferometry)
Signal conversion
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IF output may be too wide
 Difficulties of building wideband backends
 Necessity of having several spectral points across the IF
bandwidth (e.g. for Faraday rotation)
 Interest in a specific spectral region (e.g. line spectroscopy)
 Necessity to avoid contaminated portion of the IF band
Baseband converters (BBC): select a portion of the IF
bandwidth and convert it to frequencies near zero
Each BBC followed by a specific backend (total power,
polarimeter, spectrometer, VLBI channel....)
Total power
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Simplest observable: total integrated flux over the receiver
bandwidth
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Filter: selects the frequency band of interest
Square law detector: diode (simpler, wideband) or analog
multiplier (more accurate, expensive, band limited)
Integrator: sets integration time: time resolution vs. ADC
speed
ADC: converts to digital. Integrator & ADC are often
implemented as a voltage-to-frequency converter & counter
Total power
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Sensitivity:
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t = integration time
 Df = bandwidth or frequency resolution
 S = total (receiver dominated) noise
For modern receivers, 1/f gain noise dominant for t > 1-10 s
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need for accurate calibration & noise subtraction
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Added mark
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Correlating receiver
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On-the fly mapping
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Wobbling optics
Polarimetry
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Dual polarization receiver:
vertical/horizontal or left/right
Cross products give remaining
Stokes parameters
Instrumental polarization: 30dB
= 0.1%
Bandwidth limited by avaliable
analog multipliers
Need for coarse spectroscopic
resolution (Faraday rotation)
Spectroscopy
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Acousto-optic spectrometer:
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signal converted to acoustic waves in a crystal
diffraction pattern of a laser beam focussed on a CCD
amplitude of diffracted light proportional to S(f)
Large bandwidth, limited (1000 points) resolution
Rough, compact design
All parameters (band, resolution) determined by physical design
=> not adjustable
AOS Array for Herschel - HiFi
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LiNb cell with 4 acoustic channels
Instantaneous band: 4x1.1 GHz (4 – 8 GHz)
Resolution
: 1 MHz
Spectroscopy – Digital correlator
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Digital spectrometers:
Bandwidth determined by sampling frequency
 Max BW technologically limited, currently to few 100MHz
 Reducing sampling frequency decreases BW = > increased resolution
Autocorrelation spectrometers (XF)
 Compute autocorrelation function:
 Fourier transform to obtain S(f)
 Frequency resolution:
Signal quantized to few bits (typ. 2)
Complexity proportional to N. of spectral points
Spectroscopy – FFT spectrometer
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FFT spectrometers:
 Compute spectrum of finite segment of data
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Square to obtain power and integrate in time
Complexity proportional to log2(N) => N large
Requires multi-bit (typ. 16-18 bit) arithmetic
Easy to implement in modern, fast FPGA, with HW multipliers
Slower than correlator, but keeping pace
Polarimetric capabilities with almost no extra cost
Spectroscopy – FFT spectrometer
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Poly-phase structure: multiply (longer) data segment with
windowing function => very good control of filter shape
Very high dynamic range (106-109) => RFI control
Interferometry
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Visibility function: <E1(t)*E2(t+t)>
Computed at distant or remote location: need for physical
transport of the radio signal
 Directly connected interferometers
 Connected interferometers with digital samplers at the
antennas and digital data link
 E-VLBI: time-tagged data over fast commercial (IP) link
 Conventional VLBI: data recorded on magnetic media
Accurate phase and timing control
Interferometry
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Visibility computed on dedicated correlator or FFT processor
Conventional correlator scales as (number of antennas)2
FFT (FX) scales as N
Must compensate varying geometric delay:
 Varying sampler clock
 Memory based buffer, delay
by integer samples
 Phase correction in the
frequency domain
Due to frequency conversion,
varying delay causes
“fringe frequency” in the correlation
ALMA correlator (1 quadrant)
Digital vs. Analog Backend
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All backend functions can be performed on a digital signal
representation
Current programmable logic devices allow to implement
complex functions on a single chip
Digital system advantages:
 predictable performances – easy calibration
 high rejection of unwanted signals - RFI
 Better performances, filter shapes etc.
 Easy interface with digital equipments
Example of a general-purpose full digital backend
Digital vs. Software Backend
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Software backends (e.g. SW correlator) becoming possible
 e.g Blue Chip IBM supercomputer viable as LOFAR
correlator
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Most Radio Science processing done on software
Computing requirements scale as a power of the BW
Dedicated programmable logic still convenient
1 FPGA: 50-500 MegaOPS, ~16 FPGA/board
MarkIV correlator (in FX architecture): 1.7 TeraOPS
EVLA Correlator: 240 TeraOPS
Digital Backend: Examples
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ALMA Digital filterbank:
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2 GHz IF input
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32x62.5 MHz independently
tunable BBC
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General purpose board, can
be configured to implement
16 FFT spectropolarimeters
@ 125 MHz BW each
Digital Backend: Examples
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VLBI dBBC:
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1 GHz IF input
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250 MHz output bandwidth
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Directly interfaces with E-VLBI
BEE2 Berkeley system
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1 GHz IF input
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General purpose board, with library of predefined
components
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System design and validation using MATLAB