Matlab -based Scope Automation and data

analysis SW29/05/2012

Presents by- Abed Mahmoud & Hasan Natoor

Supervisor– Avi Biran

Introduction Project’s Goals Flowchart of the functions Settings of Scope CW SNR simulator

Zero crossing algorithm (SNR) calculations Signal-to-Noise ratio

Clock signals jitter simulator * Jitter statistical analysis and histograms “Real-life” signals captured from scope RAM * CW signal analysis * Clock “rect” signal analysis Next stages

Agenda

Scope is utilized as a primary testing instrument for time domain signals. Its multichannel and coherent sampling capabilities makes it useful for a variety of applications in different and complex engineering disciplines. Automation of the scope is essential for an efficient utilization of the platform.MATLAB, in conjunction with its Instrumentation Control Toolbox , is an ideal SW platform to both control the instrument parameters and acquisition properties, as well as post-process the acquired data arrays.

Introduction

Remote control of platform settings Capture and import Data matrices from the

scope channels directly into Matlab On/off -line data processing Building a user-friendly GUI

Project’s Goals

Building a dedicated, GUI-assisted, interface scripts for an embedded device control and using the vendor-specified SCPI commands

Utilization of the Matlab Instrumentation Control Toolbox as the SW platform

Using Matlab signal-processing and display functions for on-line analysis the captured waveforms and provide graphical displays of the post-processed functions

Proposed methodology

Automation of Infiniuum settings and data acquisition, including built-in AGC.

Building a Matlab-based simulators for generation of noisy CW & Clock Signals and statistical analysis of SNR & Jitter parameters

Calculation SNR & Jitter on “real-life” captured signals.

Main accomplishment

Flowchart of the functions

Parameters definition:1)X,Y scaling2)Sampling rate3)Acquisition mode (ASCii-Byte-Word)4)Data processing type (CW/Clock)5)Active channels6)Length record

Scope set

AGC

Scope run:

1)Capture and import Data matrices from the scope channels, save traces 2)On-line data processing3)Display analysis data (SNR/Jitter)

AGC(optional)

Settings of Scope -example

Capturing the signal from scope screen and import captured data matrices

Activate AGC : If the amplitude of the signal significantly

smaller relatively to the full Y-span – decrease the Y-scale to match the signal p.t.p amplitude

If the amplitude of the signal higher than the full-span Y-scale - increase the Y-scale to match the signal p.t.p amplitude

AGC operation

Aimed to optimize the captured signal dynamic range & avoid

signal clipping

AGC-example

Reduce the Y-scale to

optimize the signal

dynamic range

1-bit resolutio

n dynamic

range

240-level dynamic

range

increase the Y-scale

to avoid signal

clipping

CW (sine or cosine) waveforms – calculations of Signal-to-Noise (SNR) ratio.

Signal processing simulator (a):

CW-SNR

Sin signal

Random noise

noised signal

+Zero

crossing

FFTSignal-Noise

ratio (out)

Signal-Noise ratio (in)

compare

For exact calculation of the CW signal spectral response characteristics, an integer number of cycles is essential. ZC algorithm is employed to allow this calculation:

Zero- Crossings(ZC) algorithm

Truncate the signal length so that the

signal is composed of an integer number of CW periods

Use FFT calculate the center frequency. Calculate energy of the signal at the center

frequency(a) Integrate the energy of the out-of-peak data

points to calculate the energy of noise(b)

Signal-Noise ratio (out)

SNR=a/b

plot vs. SNRin SNRout

Clock waveforms: calculations of Jitter parameters.

Signal-processing simulator (b):Clock Jitter

Sin signal with

Phase Noise

Rectangle signal

Calculate mean time period and

STD

eliminate bad data points

Compute time-span between

any two ZC points

Estimate the ZC points

Histogram display

Estimated time period calculated

by the main

frequency Fourier domain

Calculated Jitter parameters:

Average: 0.2 [usec]usec

CW signal analysis:

“Real life” acquired signals examples:

Clock “rect” signal analysis:

“Real life” acquired signals examples:

GUI. Advanced Jitter analysis. Automation of Tabor signal generator.

What’s next?