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The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

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Page 1: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

The World Leader in High-Performance Signal Processing Solutions

Data Conversion Fundamentals

Analog-Digital Converters

Online Seminar

Fall 2002

Page 2: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

The World Leader in High-Performance Signal Processing SolutionsThe World Leader in High-Performance Signal Processing Solutions

Introduction to A/D Converters

Page 3: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

A/D Converter (ADC) Introduction

A/D Fundamentals Sampling Quantization

Factors Affecting A/D Converter Performance Static Performance Dynamic Performance

ADC Architectures SAR ADCs Pipelined ADCs Flash Type ADC Sigma-Delta ADCs

High Speed ADC Application Considerations

Page 4: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

The Measurement & Control Loop

MUXANALOGSIGNAL

PROCESSOR

A - DCONVERTER

D - ACONVERTER

ANALOGSIGNAL

PROCESSORMUX

MICROPROCESSOR

ORDSP

PROCESSOR

REFERENCE• Multiplier/Divider• Log Amplifier• rms-dc Converter• F-V/V-F Converter

• Operational Amp• Differential Amp• Instrumentation Amp• Isolation Amp

nbits

nbits

Page 5: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ADC SAMPLED ANDQUANTIZED WAVEFORM

DAC RECONSTRUCTEDWAVEFORM

ADC

DAC

DSP MemoryChannel

Analog Digital

timetime

An

alo

g

Dig

ita

l

Am

pli

tud

e

Valu

e

“REAL WORLD” SAMPLED DATA SYSTEMS CONSIST OF ADCs and DACs

Page 6: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ANALOGINPUT

DIGITALOUTPUT

RESOLUTIONN BITS

REFERENCEINPUT

Analog Input DIGITAL OUTPUT CODE = x (2N - 1) Reference Input

What is an Analog-Digital Converter?

Produces a Digital Output Corresponding to the Value of the Signal Applied to Its Input Relative to a Reference Voltage

Finite Number of Discrete Values : 2N Resulting in Quantization Uncertainty

Changes Continuous Time Signal into Discrete Time Sampled Representation

Sampling and Quantization Impose Fundamental yet Predictable Limitations

Page 7: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Sampling Process

Representing a continuous time domain signal at discrete and uniform time intervals

Determines maximum bandwidth of sampled (ADC) or reconstructed (DAC) signal (Nyquist Criteria)

Frequency Domain- “Aliasing” for an ADC and “Images” for a DAC

DISCRETETIME SAMPLING

AMPLITUDEQUANTIZATION

y(t)

y(n)

y(n+1)

n-1 n n+1 n+3 ts

t

Page 8: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Quantization Process

Quantization Process Representing an analog signal having infinite resolution with a digital

word having finite resolution Determines Maximum Achievable Dynamic Range Results in Quantization Error/Noise

100

11

10

01

00

Dig

ital

Analog0 1/4 1/2 3/4 1 = FS

1LSB

Any Analog Input in this Range Gives the Same

Digital Output Code

Page 9: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DIG

ITA

L O

UT

PU

T

1 LSB

ANALOG INPUT

1/8 2/8 3/8 4/8 5/8 6/8 7/8

001

010

011

100

101

110

111

Conversion Relationshipfor an Ideal A/D Converter

Page 10: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Quantization Noise

001

010

011

100

101

110

111

1/8 2/8 3/8 4/8 5/8 6/8 7/8 FS

NORMALIZED ANALOG INPUT

DIG

ITA

L O

UT

PU

T

quantization noise error

q = 1 LSB

Page 11: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

0 volts

+q/2

-q/2

Quantization Noise (con’t)

The RMS value of the quantization noise sawtooth is its peak value, q2, divided by 3, or q12

For Sine Wave Full Scale RMS Value is 2(N-1)/2 For Saw Tooth Quantization Error Signal RMS Value is q /12 Thus S/N is 1.225 x 2N Expressed in dB as 1.76 + 6.02N, where N is the resolution of the

A/D converter

Page 12: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

OUTPUT

FSIGNALFS/2 FS

RMS QUANTIZATION NOISE

HARMONICS OF FSIGNAL

(EXAGGERATED FOR CLARITY)

If the quantization noise is uncorrelated with the frequency of the AC input signal, the noise will be spread evenly over the Nyquist bandwidth of Fs/2.

If, however the input signal is locked to a sub-multiple of the sampling frequency, the quantization noise will no longer appear uniform, but as harmonics of the fundamental frequency

Quantization Noise (con’t)

Page 13: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ADC Resolution vs. Quantization Parameters

Resolution, Bits (n)

2n

LSB, mV (2.5V FS)

% Full Scale

ppm Full Scale

dB Full Scale

8 256 9.77 0.391 3906 -48.0

10 1024 2.44 0.098 977 -60.0

12 4096 0.610 0.024 244 -72.0

14 16,384 0.153 0.006 61 -84.0

16 65,536 0.038 0.0015 15 -96.0

18 262,164 0.0095 0.00038 3.8 -108.0

Page 14: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Analog Input Signal Definitions

Page 15: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Unipolar and Bipolar Converter Codes

0 0 0

FS - 1LSB FS - 1LSB FS - 1LSB

ALL"1"s 1 AND ALL "0"S

ALL"1"s

UNIPOLAR OFFSET BINARY 2’s COMPLEMENT

-FS -(FS - 1LSB)

Page 16: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Factors Affecting A/D Converter Performance- Offset And Gain for Unipolar Ranges

ACTUAL

OFFSET

ERROR

WITH GAIN ERROR:OFFSET ERROR = 0

ACTUAL

IDEAL IDEAL

ZERO ERROR

NO GAIN ERROR:ZERO ERROR = OFFSET ERROR

0 0

GAIN

Page 17: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ACTUAL

OFFSETERROR

WITH GAIN ERROR:OFFSET ERROR = 0ZERO ERROR RESULTSFROM GAIN ERROR

ACTUAL

IDEAL IDEAL

ZERO ERROR ZERO ERROR

NO GAIN ERROR:ZERO ERROR = OFFSET ERROR

0 0

Factors Affecting A/D Converter Performance- Offset And Gain for Bipolar Ranges

Page 18: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DC Specifications (Ideal)

Ideal ADC code transitions are exactly 1 LSB apart.

For an N-bit ADC, there are 2N codes. (1 LSB = FS/ 2N )

For this 3-bit ADC, 1 LSB = (1V/23 = 1/8th)

Each “step” is centered on an eighth of full scale

001

111

110

101

100

011

010

000

1/8 7/83/45/81/23/81/40

Analog Input

Dig

ital O

utpu

t 1 LS B

A D C T ransfer Function(Idea l)

Page 19: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DC Specifications (DNL)

Differential Non-Linearity (DNL) is the deviation of an actual code width from the ideal 1 LSB code width

Results in narrow or wider code widths than ideal and can result in missing codes

Results in additive noise/spurs beyond the effects of quantization 001

111

110

101

100

011

010

000

1/8 7/83/45 /81 /23 /81 /40

Analog Input

Dig

ital O

utpu

t

A D C T ransfer Function(D N L E rror)

+1/2 LSB

+1/2 LSB

-1/2 LSB

Page 20: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DC Specifications (DNL)

DNL error is measured in lsbs.

A given ADC will have a typical DNL pattern.

These patterns will also have an element of randomness to them.

Page 21: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DC Specifications (INL)

Integral Non-Linearity (INL) is the deviation of an actual code transition point from its ideal position on a straight line drawn between the end points of the transfer function.

INL is calculated after offset and gain errors are removed

Results in additive harmonics and spurs

001

111

110

101

100

011

010

000

1/8 7/83/45 /81 /23 /81 /40

Analog Input

Dig

ital O

utpu

t

A D C T ransfer Function(IN L E rror)

+1/2 LSB

+1 LSB

+1/2 LSB

Page 22: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DC Specifications (INL)

Some typical INL patterns

Bow indicates 2nd order nonlinearity

“S” indicates 3rd order nonlinearity

Page 23: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

QUANTIFYING ADC DYNAMIC (AC) PERFORMANCE

Harmonic Distortion

Worst Harmonic

Total Harmonic Distortion (THD)

Total Harmonic Distortion Plus Noise (THD + N)

Signal-to-Noise-and-Distortion Ratio (SINAD, or S/N +D)

Effective Number of Bits (ENOB)

Signal-to-Noise Ratio (SNR)

Analog Bandwidth (Full-Power, Small-Signal)

Spurious Free Dynamic Range (SFDR)

Two-Tone Intermodulation Distortion

Noise Power Ratio (NPR) or Multitone Power Ratio (MPR)

Page 24: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Dynamic Testing of A/D Converters

LOW PHASE

JITTER

SINEWAVE SOURCE

A/D CONVERTER

ON

EVALUATION BOARD

BANDPASS

FILTER

LOW PHASE

JITTER

SAMPLING

CLOCK SOURCE

FFT

ANALYZER

POWER

SUPPLIES

A Fast Fourier Transform (FFT) Analyzer is used to measure dynamic performance

Page 25: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

time

amp

litu

de

f1

3f1

2f1

frequency

amp

litu

de

f1 2f1 3f1

...to this

Fast Fourier Transform converts

this…

Page 26: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

An M-Point FFT

The Effective Noise Floor of an M-Point FFT Is Less Than The RMS Value

of the Quantization Noise

SNR = 6.02N + 1.76 dB

RMS Quantization Noise Level

FFT Floor = 10 log 10 (M 2)

0 dB

18 dB, M = 128

21 dB, M = 256

24 dB, M = 512

27 dB, M = 1024

30 dB, M = 2048

33 dB, M = 4096

Bin Spacing = F = FS M

Page 27: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Actual FFT Plot for AD7484, 14-Bit SAR ADC Sampling at 3MHz

-140

-120

-100

-80

-60

-40

-20

0

0 200 400 600 800 1000 1200 1400

Frequency (kHz)

dB

fIN = 1.013MHz

SNR = 77.7dBSNR+D = 77.6dBTHD = -95.5dB

Page 28: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

2 Signals that are Mixed Together Produce Sum and Difference

Frequency Components

Nyquist Theory Stipulates that the Signal Frequency, FSIGNAL must

be < to ½ FSAMPLING to Prevent a Condition Known As “Aliasing”, in

which the Difference Component Appears Within the Signal

Bandwidth of Interest

Nyquist Bandwidth & Aliasing

Page 29: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

The Signal Frequency Is < 1/2 the Sampling Frequency and So the Sum

and Difference Components Fall Outside (Beyond) the Signal Passband

1 MHz 4 MHz

fsampling fsampling + fsignalfsampling - fsignal

signalpassband

3 MHz 5 MHz

fsignal

The Nyquist Bandwidth & Aliasing(FSIGNAL < ½ FSAMPLING)

Page 30: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

The Signal Frequency Is > 1/2 (approx 2/3) the Sampling Frequency. An

“Alias” or False Image is Thus Created that Falls Within the Passband of

Interest.

The Nyquist Bandwidth & Aliasing(FSIGNAL > ½ FSAMPLING)

fsampling- fsignal fsignal fsampling fsampling + fsignal

2.5 MHz1.5 MHz1 MHz“Alias”0.5 MHz

Page 31: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

SINAD (Signal-to-Noise-and-Distortion Ratio) The ratio of the rms signal amplitude to the

mean value of the root-sum-squares (RSS) of all other spectral components, including harmonics, but excluding dc

ENOB (Effective Number of Bits)

SNR (Signal-to-Noise Ratio, or Signal-to-Noise Ratio Without Harmonics) The ratio of the rms signal amplitude to the

mean value of the root-sum-squares (RSS) of all other spectral components, excluding the first five harmonics and dc

SINAD, ENOB, and SNR

02.6

76.1 dBSINADENOB

Page 32: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ADC LARGE SIGNAL (OR FULL POWER) BANDWIDTH

Full-power bandwidth is defined as the input frequency where the fundamental in an FFT of the output, rolls off to its 3 dB point

ADC’s SHA generally determines the FPBW FPBW often limited by slew rate of the internal circuitry. May not be compatible with the converter’s maximum

operating rate Ideally fFPBW >> fs / 2

Many High Speed Converters have fFPBW < fs / 2

Use as a “prerequisite” specification for comparing ADC’s IF undersampling capabilities. But need to consider distortion as well.

Page 33: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Successive Approximation ADC

“Recursive” One-Bit Sub-Ranging Architecture

ANALOGINPUT

STARTCONVERT

COMPARATOR EOC ORDRDY

SHA +

-

DAC

SAR*

*SUCCESSIVE APPROXIMATION

REGISTER

DIGITALOUTPUT

Page 34: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Successive Approximation ADC

+FS

-FS

A nalogInput

P eriod 1

M S B

B it 4

B it 3

B it 2

P eriod 3P eriod 2P eriod 1P eriod 4P eriod 3P eriod 2

A nalogInput

In terna l s igna ls fo r a 4-b it successive approxim ation A D C

test a t 1

test a t 1

test a t 1

test a t 1

test a t 1

test a t 1

test a t 10

00

0

0

0

0

00

0

0

01

0

1

0

11

1

00

C onversion com ple te (1011),start on next conversion

Page 35: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

How a Successive Approximation A/D Converter Works

Rising/Falling Edge of Convert Start Pulse Resets Logic

Falling/Rising Edge Begins Conversion Process

Bit Comparisons Made on Each Clock Edge

Conversion Time Equals Number of Comparisons

(Resolution) Times Clock Period

The Accuracy of Conversion Depends on the DAC Linearity

and Comparator Noise

Page 36: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

EXAMPLE : ANALOG INPUT = 6.428V, REFERENCE = 10.000V

MSB5.000V

2SB2.500V

3SB1.250V

LSB0.625V

VIN > 5.000V VIN > 6.875VVIN > 6.250VVIN > 7.500V

YES

1

NO

0

YES

1

NO

0

How Successive Approximation Works

Page 37: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Advantages to SAR A/D converters

•Low Power (12-bit/1.5 MSPS ADC: 1.7 mW)

•Higher resolutions (16-bit/1 MSPS)

•Small Die Area and Low Cost

•No pipeline delay

Tradeoffs to SAR A/D converters

•Lower sampling rates

Typical Applications

•Instrumentation

•Industrial control

•Data acquisition

Successive Approximation ADC

Page 38: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Pipelined Sub-ranging ADC

Conversion divided into discrete stages thus causing pipeline delay1st Stage ADC is 6-bit

FLASH2nd Stage ADC is 7-bit

FlashTotal resolution is 12

bits (one bit used for error correction)

ANALOGINPUT

7

12

SHA1

6-BITADC

7-BITADC

GAIN

6

+

-

ERROR CORRECTION LOGIC

6-BITDAC

SHA2

SHA3

OUTPUT REGISTER

12

BUFFER

REGISTER

6

Page 39: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

+FS

-FS

A nalogInput

In terna l s igna ls fo r a p ipe lined A D C

First conversion (101) Zoom in and performsecond conversion (011)

Pipelined Sub-ranging ADC

+FS

-FS

A nalogInput

In terna l s igna ls fo r a p ipe lined A D C

First conversion (101)

Page 40: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Pipelined Sub-ranging ADC

Advantages to Pipelined Sub-ranging A/D converters

•Higher resolutions at high-speeds (14-bits/105 MSPS)

•Digitize wideband inputs

•Tradeoffs to pipelined sub-ranging A/D converters

•Higher power dissipation

•Larger die size

Typical Applications

•Communications

•Medical imaging

•Radar

Page 41: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Flash or Parallel ADC

2N-1 comparators form the digitizer array, where N is the ADC resolution

Analog input is applied to one side of the comparator array, a 1 lsb reference ladder voltage is applied to the other inputs.

The comparator array is clocked simultaneously and decides in parallel.

Output logic converts from thermometer code to binary

ANALOGINPUT

DIGITALOUTPUT

N

R

R

R

R

R

R

0.5R

1.5R+VREF

STROBE

PRIORITYENCODER

ANDLATCH

Page 42: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Flash or Parallel ADC

Advantages to Flash A/D converters

•Fastest conversion times (up to 1 GSPS)

•Low data latency

Tradeoffs to Flash A/D converters

•Higher power consumption

•High capacitive input is difficult to drive

Typical Applications

•Video digitization

•High-speed data acquisition

Page 43: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

FIRST-ORDER SIGMA-DELTA ADC

+

_

+VREF

–VREF

DIGITALFILTER

ANDDECIMATOR

+

_

CLOCK

Kfs

VINN-BITS

fs

fs

A

B

1-BIT DATASTREAM1-BIT

DAC

LATCHEDCOMPARATOR(1-BIT ADC)

1-BIT,

Kfs

SIGMA-DELTA MODULATOR

INTEGRATOR

Page 44: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

OVERSAMPLING, DIGITAL FILTERING, NOISE SHAPING, AND DECIMATION

fs

2

fs

QUANTIZATIONNOISE = q / 12 q = 1 LSBADC

fs NyquistOperation

A

KfsKfs

2

fs

2

REMOVED NOISE

MODDIGITALFILTER

Kfs

DEC

fs

Oversampling+ Noise Shaping+ Digital Filter+ DecimationC

Kfs

2

Kfsfs

2

DIGITAL FILTER

REMOVED NOISEADCDIGITALFILTER

Kfs

Oversampling+ Digital Filter+ DecimationB

DEC

fs

Page 45: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

DEFINITION OF "NOISE-FREE" CODE RESOLUTION

EFFECTIVERESOLUTION

= log2

FULLSCALE RANGERMS NOISE BITS

P-P NOISE = 6.6 × RMS NOISE

NOISE-FREECODE RESOLUTION = log2

FULLSCALE RANGEP-P NOISE BITS

= EFFECTIVE RESOLUTION – 2.72 BITS

NOISE-FREECODE RESOLUTION

= log2FULLSCALE RANGE

6.6 × RMS NOISEBITS

0.4uVrms

20mV

16.5bits

Page 46: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

SIGMA-DELTA ADCs

Advantages to Sigma-Delta A/D converters

•High resolutions and accuracy (24-bits)

•Excellent DNL and INL performance

•Noise shaping capability

Tradeoffs in Sigma-Delta A/D converters

•Limited input bandwidth

•Slower sampling rates

Typical Applications

•Precision data acquisition and measurement

•Medical instrumentation

Page 47: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

High Speed ADC Time Domain Specifications Considerations

Aperture Jitter and Delay

ADC Pipeline Delay

Duty Cycle Sensitivity

DNL Effects

Page 48: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

EFFECTS OF APERTURE AND SAMPLING CLOCK JITTERJitter:

Most systems assume the signal is sampled uniformly Clock noise leads to non-uniform sampling (i.e. jitter)

Jitter leads to SNR degradation for high frequency inputs:

LSBpja VVTf 2

Page 49: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

SNR DUE TO APERTURE AND SAMPLING CLOCK JITTER

SNR(dB)

ENOB

FULLSCALE SINEWAVE INPUT FREQUENCY (MHz)

100

80

60

40

20

0

16

14

12

10

8

6

4

1 3 10 30 100

SNR = 20log101

2ftj

Page 50: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

SAMPLINGCLOCK

ANALOG INPUTSINEWAVE

ZERO CROSSING

+FS

-FS

0V

+te-te

te

Typically not an issue in frequency domain applications May vary slightly among devices of same product due to

variations in SHA bandwidth and CLK prop. delays

EFFECTIVE APERTURE DELAY TIME

Page 51: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ANALOGINPUT

SAMPLINGCLOCK

OUTPUTDATA

DATA N - 3 DATA N - 2 DATA N - 1 DATA N

N N + 1 N + 2 N + 3

Many High Speed ADC’s, such as subranging types, use pipeline architectures to: Reduce chip size, and power consumption Allows multiple samples to be converted simultaneously in ADC Results in fixed delay between Sampled Input and corresponding

digital output.

ADC LATENCY OR PIPELINE DELAY

Page 52: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

ADC DUTY CYCLE SENSITIVITY

High Speed ADCs are often sensitive to duty cycle of the CLK input CLK oscillators are usually

specified as 40/60 or 45/55 Digital Specifications of

datasheet provide a minimum CLK HIGH/LOW period (nsec) to achieve rated performance.

Some datasheets show SNR/THD graphs as a function of duty cycle

Note, ADC also has minimum specified sample rate

Page 53: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Ideal ADC code transitions are exactly 1 LSB apart. DNL is the deviation from this value.

Results in additive noise/spurs beyond the effects of quantization Limits ultimate achievable SNR and low level signal SFDR performance

Predictable for a given device once error transfer function is known. DNL error pattern varies among devices of a given product

Dynamic correction techniques include adding “dither” or element shuffling

DNL ERRORS LIMIT IDEAL NOISE AND SPUR FLOOR PERFORMANCE

Page 54: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Example : AD9433 SFDR

SFDRENABLED

DISABLED

Page 55: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Example : AD9433 SFDR

SFDR

ENABLED

DISABLED

Encode = 105MspsAin = 70MHz, -0.5dBFs

Page 56: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Example of Data Sheet Specifications for AD9430 ADC

Page 57: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

Example of Data Sheet Specifications for AD7476 ADC

Page 58: The World Leader in High-Performance Signal Processing Solutions Data Conversion Fundamentals Analog-Digital Converters Online Seminar Fall 2002

For complete information

on the World’s most extensive line of

A/D converters visit

WWW.ANALOG.COM