Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Signal Processing for Nuclear Detectors, Bavarian Forest, 24 April 2009 Dipartimento di Fisica.

Slides:



Advertisements
Similar presentations
Physical Layer: Signals, Capacity, and Coding
Advertisements

DCSP-2: Fourier Transform I Jianfeng Feng Department of Computer Science Warwick Univ., UK
Noise Lecture 6.
1. INTRODUCTION In order to transmit digital information over * bandpass channels, we have to transfer the information to a carrier wave of.appropriate.
Digital Coding of Analog Signal Prepared By: Amit Degada Teaching Assistant Electronics Engineering Department, Sardar Vallabhbhai National Institute of.
University Of Vaasa Telecommunications Engineering Automation Seminar Signal Generator By Tibebu Sime 13 th December 2011.
Analog to Digital Converters (ADC) 2 ©Paul Godin Created April 2008.
Presented by- Md. Bashir Uddin Roll: Dept. of BME KUET, Khulna-9203.
So far We have introduced the Z transform
Spring 2007W. Rhett DavisNC State UniversityECE 747Slide 1 ECE 747 Digital Signal Processing Architecture SoC Lecture – Working with Analog-to-Digital.
Quantization Prof. Siripong Potisuk.
IMPLEMENTATION OF DSP RADIO RECEIVER Amaar Ahmad Syed.
Digital Data Transmission ECE 457 Spring Information Representation Communication systems convert information into a form suitable for transmission.
Electrical Noise Wang C. Ng.
Digital Voice Communication Link EE 413 – TEAM 2 April 21 st, 2005.
Pulse Modulation 1. Introduction In Continuous Modulation C.M. a parameter in the sinusoidal signal is proportional to m(t) In Pulse Modulation P.M. a.
Introduction to Adaptive Digital Filters Algorithms
Sub-Nyquist Reconstruction Final Presentation Winter 2010/2011 By: Yousef Badran Supervisors: Asaf Elron Ina Rivkin Technion Israel Institute of Technology.
ECE 590 Microwave Transmission for Telecommunications Noise and Distortion in Microwave Systems March 18, 25, 2004.
1 of 20 Z. Nikolova, V. Poulkov, G. Iliev, G. Stoyanov NARROWBAND INTERFERENCE CANCELLATION IN MULTIBAND OFDM SYSTEMS Dept. of Telecommunications Technical.
COMMUNICATION SYSTEM EEEB453 Chapter 5 (Part IV) DIGITAL TRANSMISSION.
Digital Signal Processing and Generation for a DC Current Transformer for Particle Accelerators Silvia Zorzetti.
DISP 2003 Lecture 6 – Part 2 Digital Filters 4 Coefficient quantization Zero input limit cycle How about using float? Philippe Baudrenghien, AB-RF.
Jessica Arbona & Christopher Brady Dr. In Soo Ahn & Dr. Yufeng Lu, Advisors.
Signals CY2G2/SE2A2 Information Theory and Signals Aims: To discuss further concepts in information theory and to introduce signal theory. Outcomes:
Unit-V DSP APPLICATIONS. UNIT V -SYLLABUS DSP APPLICATIONS Multirate signal processing: Decimation Interpolation Sampling rate conversion by a rational.
- 1 - YLD 10/2/99ESINSA Tools YLD 10/2/99ESINSA Filters Performances A filter should maintain the signal integrity. A signal does not exist alone.
Preliminary Design of FONT4 Digital ILC Feedback System Hamid Dabiri khah Queen Mary, University of London 30/05/2005.
Instructor: Evgeniy Kuksin Preformed by: Ziv Landesberg Duration: 1 semester.
Digital Control Systems Digital Control Design via Continuous Design Emulación F,P&W Chapters 6 & 7.2.
Quiz 1 Review. Analog Synthesis Overview Sound is created by controlling electrical current within synthesizer, and amplifying result. Basic components:
EE445S Real-Time Digital Signal Processing Lab Spring 2014 Lecture 16 Quadrature Amplitude Modulation (QAM) Receiver Prof. Brian L. Evans Dept. of Electrical.
A complete DIY numerical shaper… … from scratch! instrumentation examples1 What do we need? The signal digitized at the output of a Charge Sensing Preamp.
Floyd, Digital Fundamentals, 10 th ed Digital Fundamentals Tenth Edition Floyd © 2008 Pearson Education Chapter 1.
IT-101 Section 001 Lecture #9 Introduction to Information Technology.
Electronic Noise Noise phenomena Device noise models
ASIC Activities for the PANDA GSI Peter Wieczorek.
Outline Transmitters (Chapters 3 and 4, Source Coding and Modulation) (week 1 and 2) Receivers (Chapter 5) (week 3 and 4) Received Signal Synchronization.
Impulse Response Measurement and Equalization Digital Signal Processing LPP Erasmus Program Aveiro 2012 Digital Signal Processing LPP Erasmus Program Aveiro.
1 st semester 1436 / Modulation Continuous wave (CW) modulation AM Angle modulation FM PM Pulse Modulation Analog Pulse Modulation PAMPPMPDM Digital.
Performance of Digital Communications System
Instructor: Evgeniy Kuksin Preformed by: Ziv Landesberg Duration: 1 semester.
Update on works with SiPMs at Pisa Matteo Morrocchi.
Noise in Communication Systems
Real-time Digital Signal Processing Digital Filters.
Lifecycle from Sound to Digital to Sound. Characteristics of Sound Amplitude Wavelength (w) Frequency ( ) Timbre Hearing: [20Hz – 20KHz] Speech: [200Hz.
MADEIRA Valencia report V. Stankova, C. Lacasta, V. Linhart Ljubljana meeting February 2009.
MECH 373 Instrumentation and Measurements
High Energy Physics experiments.
CLUster TIMing Electronics Part II
Jinfan Chang Experimental Physics Center , IHEP Feb 18 , 2011
A Digital Pulse Processing System Dedicated to CdZnTe Detectors
Analog to digital conversion
CluTim Algorithm for Drift Chambers Readout Electronics
A Comparison of Filtering Structures for FPGA Implementation
S-D analog to digital conversion
Electronics for Physicists
Sampling rate conversion by a rational factor
Calorimeter Upgrade Meeting
ECET 350 Competitive Success/snaptutorial.com
ECET 350 Education for Service/tutorialrank.com
Σ-D Analog to Digital Converter for CMOS Image Sensors Nonu Singh (RIT, MicroE Co-Op) Background After fabricating an imaging sensor it needs to be characterized.
Digital Control Systems Waseem Gulsher
لجنة الهندسة الكهربائية
Chapter 3: PCM Noise and Companding
Digital Control Systems Waseem Gulsher
Data Acquisition (DAQ)
Electronics for Physicists
Presented by Mohsen Shakiba
♪ Embedded System Design: Synthesizing Music Using Programmable Logic
Presentation transcript:

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Signal Processing for Nuclear Detectors, Bavarian Forest, 24 April 2009 Dipartimento di Fisica Generale M.P. Bussa, L. Ferrero, A. Grasso, M. Greco, M. Maggiora, Diego ALBERTO

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Outline Introduction Simulated Transmission Chain Simulated WGN Noise SNR and Peak Distortion Simulation Filtering Results Towards FPGA Our Real Transmission Chain Future works

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto The detector detector 1

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Detector The signal generated by the passage of a ionizing particle appeares as a voltage or current pulse This pulse amplitude is proportional to the energy released by the particle inside the detector “Baseline Shift”, “Pulse Pile-Up”, “Ballistic Deficit”, “Noise” During the signal analysis we must pay attention to all those phenomena that can modify time and amplitude measures: Introduction 2

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Simulated Transmission Chain IIR / FIR Noise Filter Simulated Signal i(t) Preamp / Integrator Analog Shaper / Antialias filter PZ comp White Gaussian Noise + ADC sampler quantizer 3

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Noise Causes of noise in an electronic acquisition chain: Thermal noise Thermal noise: is generated by the thermal agitation of the charge carriers inside an electrical conductor and depends on the bandwidth, a larger bandwidth implies a larger noise. Shot noise Shot noise: consists of random fluctuations caused by the fact that the current is carried on by discrete charges that pass through a potential barrier. Flicker noise Flicker noise: low frequency noise, typical on electronic devices, it depends on the generation and recombination processes on the material surface. 4

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Simulation: WGN We started to represent all these kind of noises as an additive White Gaussian Noise (WGN) to the input signal Our aim is the reduction of this noise using digital filters We are now studing other more realistic kinds of noise as the pink one Time [ns] Amplitude Standard vs Adaptive 5

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto SNR and Peak Distortion The Signal to Noise Ratio (SNR) is the ratio between the Signal Power and the Noise Power, usually expressed in dB. In general the power of a digital signal x[n] of N samples is evaluated as: desired filtered With Peak Distortion we intend the relative difference between the desired peak value and the filtered one, it is expressed in percentage Es: Butt. III LP → PD = 8.24 % 6

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Simulation: Standard Butterw III ord. Butterworth III ord. Transfer Function: Infinite Impulse Response ( IIR ) SNR: 5.76 dB PD: 8.24% 7

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto The update coefficients equation Simulation: Adaptive Least Mean Square LMS Adaptive FIR Filter - + best results µ = 0.18 SNR: 6.57 dB PD: 0.06% 8

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Simulation: Butterw vs LMS filtering This analysis has been published on Nuclear Instruments and Methods sect. A 594 (2008), pp DOI information: /j.nima

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Our aim is the implementation of these algorithms on a Xilinx Virtex 4 ML402 FPGA We decided to pass through Simulink and System Generator simulations Towards FPGA 10

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 12 bits 10 bits for the binary point System Generator and ISE (Butt. III LP) FIR section correctly implemented with the HW JTag Cosimulation This retroaction chain could not be automatically implemented with the HW JTag Cos 11

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto VHDL 12 For this reason we started to study VHDL We used Xilinx ISE tool We described in VHDL language some different standard filter structure With ChipeScope we could get the signal filtered by our ML402 Virtex 4 FPGA

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto FPGA elaboration Translating the filter structures into VHDL code written by ourselves we obtained good results with standard filters  # utilized Flip-Flop 315 / ̴ 1%  # 4 inputs LUT 346 / ̴ 1%  # occupied slices 333 / ̴ 2%  max frequency MHz 13

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Analog Chain Qδ(t) Detector i(t) Preamp/ Integr Analog Shaper PZ comp QQQ ADCIIRvsFIR Noise Filter sampler quantizer Digital Chain Q Transmission Chain 14

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Transmission Chain  PC  Xilinx Virtex 4 ML402 FPGA  our analog board  LeCroy 6100A programmable pulse generator Our real transmission chain is composed of a: 15

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Future Works 16 To cope with the implementation of LMS algorithms on FPGA Take into account faster algorithms (as the sign LMS ) To study different and more realistic kinds of noise

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto Thank you for the Attention !!

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 20 Simulink Schematics: Butterworth III LP Sys. Gen. Butterworth

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 21 Direct Form II Butt. III LP Butterworth III ord. Transfer Function: Infinite Impulse Response ( IIR )

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 22 System Generator and ISE The filter structure has been synthesized with System Generator (only the Netlist) We had:  to learn VHDL language and Xilinx ISE Tool  to write and manage PIN location, alimentations, filter connections The VHDL code has been included in an ISE project Input ROM Filter Output RAM FPGA Board

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 23 Model Sim code simulation Output Ram

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 24 Simulations comparison Simulating the filtering with Matlab and Model Sim we obtained: Considered the quantization there is a very good matching

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 25 ADC DAC P/Z comp Preampl An. Shaper ADC Filter Test Board Schematics

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 26 PANDA Test Board ORCAD layout Our board

Bavarian Forest, Bavarian Forest, 24 April 2009 D. Alberto 27 First results Input Analog Shaper Output (seen after our DAC, it passed in the FPGA ) Digital Shaper Output Higher Noise in Digital Shaper Output ??