Digital detector signal processor: preliminary study

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Digital detector signal processor preliminary
study

• Claudio Mulatero, INFN To
• Future DAQ

GSI, Darmstadt 10-11 October 2005
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SIGNAL PROCESSING
HIT DETECTION
NOISE REDUCTION
CLUSTERING
SHAPE ANALYSIS
MOVING AVERAGE
OPTIMAL FILTER
BASELINE
POLE/ZERO COMPENSATION
RECTANGULARIMPULSE RESPONSE
FIR/IIR
FEATURESEXTRACTION
TRAPEZOIDAL IMPULSE RESPONSE
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Baseline shift
Pulses amplitude is measured relative to a true
zero baseline, presence of baseline shift can
modify the measure.
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Ballistic Deficit
Limited shaping time constants cause a loss in
the measurement of the pulses amplitude.
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Pileup
For a complete charge collection with a train of
pulses preamplifiers provide a long decay time.
With high rate of interaction these pulses will
tend to overlap one another. Ideal solution is to
shape the pulses with a time limited width.
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Pole/Zero Compensation
t
T (lt t)
T (gt t)
If the time width of the signal (T) is smaller
than time constant of the pre-amplifier (t), the
signal can be considered impulsive.
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Transfer function of the residual pole-zero
couple tz compensator time constant tp
pre-amplifier time constant (to be canceled)
Antialiasing Filter
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Accuracy of such compensator strongly affects the
baseline stability.
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Noise reduction
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Analysis assumption
Signal Amplitude (or -) the cumulative effect
of all NOISE STEPS
Fixed measurement time
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STEP NOISE INDEX
DELTA NOISE INDEX
Moving average impulse response
FIR/IIR impulse response
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DSP
Example of acquisition chain.
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Moving average filter
To obtain the area under the detector pulse it
can be used a trasversal filter with rectangular
weighting function (Moving Integrator).
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The output is obtained by integrating the input
over a fixed interval of time.
t output evaluation time T Integration Time
Width of Input Pulse
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Pulse Integration
Moving Average in the discrete case the integral
can be approximated with the sum
k number of the samples corresponding to the
integration time window
Pile-up Effects
In this processor the pulse amplitude
corresponding to event B will be correctly
measured if the time interval between events A
and B satisfing the conditions
TAB gt Tp T1 (Tp impulse pulse duration) TBC gt
T1 T (T processor integration time)
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• 0. -gt RESET
• DATA -gt INPUT REGISTER
• DATA PIPELINE OUT
• (A-B) OUT
• 2.S(A-B) OUT
• if (PEAKevent and PEAK1)
• SCALED S(A-B)-gtFIFO_IN
• end if
• if (FIFO_notempty)
• FIFO OUT

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Trapezoidal Filter

• Important constraints
• Minimum noise
• Introduction of flat-top in the impulse response
• Finite time duration.
• With digital techniques it is possible to create
  optimum filter for various shape just changing
  the parameters of digital filter.

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Time limited response
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Example with two coincident poles
G. Ripamonti et al. / Nucl. Instr. And Meth. In
Phys. Re. A 340 (1994)
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Two real and distinct poles s11/t, s21/?
Three coincident poles s11/t, s21/?
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Flat-top

• Shaper can be developed imposing constraints on
  overall processor response u(t)
• To maximize flating of the top
• To be time-limited

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• Tail cancellation
• Number of samples for a given pulse and hence the
  speed of ADC increase with the polar
  singularities of F(s)
• WF flat-top accuracy depend on ADC speed and ? of
  F(s)

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Bilinear z-transform (BZT)
Digital filter
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