1. A Digital Pulse Processing System Dedicated to CdZnTe Detectors
G. Montémont, C. Moulin, J. Isard and L. Verger
CEA-LETI, Grenoble, France
Bi-parametric method
Digital implementation

2. Why bi-parametric processing ?
counts
Charge 3 2 1
cathode
anode g
* 3
* 2
* 1
Planar detector
counts
Charge 2 3 1
cathode
anode g
* 3
* 2
* 1
Capacitive Frisch grid detector
Transit time 1 2 3
Charge
Transit time 1 2 3
Charge
BP enables tailing compensation

3. Bi-parametric spectrum acquisition
g rays - e +
derivator
Current pulse
preamp
Charge pulse
Amplitude
Transit time
Energy
=800 ns
122 keV
Corrected spectrum

4. Adaptation to pulse shape → iterative processing
Why a digital approach ?
Noise optimality
→ custom digital filter
Adaptation to pulse shape
→ iterative processing
Multi-interaction processing
→ model based approach
Integration & real-time operation
→ FPGA & DSP technologies

5. Noise filtering: digital implementation
Experimental noise
Filter impulse response
Noise coloration has to be compensated
=sum of several gaussian responses
→ easy multirate implementation
Multi-rate interpolated FIR
Speed= 100 MSamples/s (12 bits)
Integrated in a 100k gates FPGA
Y. Neuvo, Dong C-Y, S.K. Mitra, « Interpolated Finite Impulse Response Filter »,
IEEE Trans. Acoust. Speech Signal Proc., Vol. 32, pp , 1984.

6. Adaptation to pulse shape
I(t)
X(t)
threshold T
Q(t)
Iterative threshold evaluation
FPGA → continuous filtering
DSP → iterative algorithm
1000 samples= 10 µs

7. Why threshold adaptation ?
Fixed threshold
Adapted threshold
Charge
Transit time
=800 ns
122 keV
Under-evaluation of time for low amplitudes
Charge
Transit time
122 keV
Time estimation independent of amplitude

8. Multiple interaction physics
Energy range= keV
Aim: reduce Compton background
Double interactions are more likely to depose the total gamma-ray energy.
Solution:
Identify double interactions

9. Multiple interaction signal
with 1 cm3 detector
Weighting potential
Model-based maximum likelihood iterative algorithm
1 µs
w/ matched filters for
beginning of pulse
end of pulse
Intensity

10. Multiple interaction spectrometry
with Cesium 137
Single pulses
Double pulses
Transit time
Transit time
Charge
Charge
Counts
Corrected spectrum
Counts
Corrected spectrum
Compton edge suppression

11. Conclusion Results Perspectives Quasi-optimum filter realization.
Adaptation to pulse amplitude & width.
Multiple pulses separation.
Compact & real-time implementation.
Perspectives
Use of pulses parameters for physical interpretation of multiple interactions.
Improvement of spectra by Compton background reduction.
64 mm x 34 mm digital BP board
137Cs + 133Ba