Acquired analog signals can be manipulated and processed by either the analog or digital portions of a system, for example, through filtering, multiplexing, and gain control. The analog portions of a system can typically provide reasonably simple processing at fairly low cost, power, and overhead. Digital processing can provide far greater analysis power and can alter the nature of the analysis without changing hardware. Sampling theory, however, must be taken into account. This session covers the signal chain basics from signal to sensor to amplifier to converter to digital processor and back out again.
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
System Partitioning and Design - VE2013
1. Advanced Techniques of Higher Performance Signal Processing
Partitioning Data Acquisition
Systems
Dave Kress
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2
3. Today’s Agenda
The dilemmas of system architecture and partitioning
Analog vs. digital signal processing
The perils of sampling
Digital vs. digital
Where to put all the processing functions
Gain
Sampling
Filtering
Multiplexing
Special analog processing
Isolation
3
4. Analog to Electronic Signal Processing
SENSOR
(INPUT)
DIGITAL
PROCESSOR
AMP CONVERTER
ACTUATOR
(OUTPUT)
AMP CONVERTER
4
5. … in the Beginning …
There was a sensor, mechanical driver, stylus, recording medium,
playback stylus, and mechanical amplifier – it worked
5
7. Current Day Integrated Functions
Audio codecs
SoundMAX® computer audio
codecs
I/O ports
Mixed-signal front ends:
modems, communications, CCD
imaging, flat panel displays
Transmit and receive signal
processors
Direct conversion radio
Energy metering
Video encoders/decoders,
codecs
Touchscreen digitizers
Analog microcontrollers (high
performance ADCs, DACs, and
ARM µP core and flash memory)
Blackfin® DSPs with on-board
ADCs and DACs
Motion sensors with embedded
ADCs
7
8. The Dilemmas of Partitioning
Why Digitize at All?
Analog vs. Digital Processing
Filtering
Linearization
Detection
Multiplexing
Multiple amplifiers, filters, converters
Simultaneous sampling
Signal Control
Gain ranging vs. high resolution
Compression
Filtering
8
9. Analog and Digital Domains
Why Convert to Digital?
Analog signals are continuous and provide the entire signal
Digital signals capture only a portion of the signal
Why digitize?
Improved signal analysis potential
More robust storage
More accurate transmission
Higher order filters implemented with less cost
Development objective of sampled data systems is to minimize
effect of the sampling process
9
10. Analog vs. Digital Design
Analog Design Advantages
Simpler and quicker to implement
Lower power
Analog systems don’t crash and need reboot
Disadvantages
Difficult to change once in production – or at a customer
Limited scale
Digital Design Advantages
Changeable without hardware modification
More filtering capability and scale
Not sensitive to temperature
Disadvantages
Initial software design takes longer
More complex hardware
Requires ADC that determines the SNR
10
11. Digital vs. Digital Design
FPGA vs. DSP
FPGA Pros
Deliver higher performance through very high parallelism
Flexible I/O to support high-speed analog interfaces
Low fixed costs
Quick design turns for hardware changes
FPGA Cons
Higher power in redundant logic
Higher cost at volume
DSP Pros
Programming is simpler – many libraries and third-party support companies
Higher speed for straight processing
DSP Cons
Fixed hardware structure
Limited scale for parallel processing
11
12. The Costs of Digitizing Signals
You need to learn sampling theory
The input signal will be compromised – the goal is to determine
what’s acceptable
The input signal needs to be filtered
Signal reconstruction will require another data converter
12
13. Many Types of Sampled Data Systems
Analog-to-Digital Converters
Digital-to-Analog Converters
Sample-and-Hold Amplifiers
Peak Detectors
Comparators
Switched Cap Filters
Samples a Continuous Signal
Domain Conversion
Analog to digital
Digital to analog
Continuous time to discrete time
Continuous frequency to discrete
frequency
Sampling Rate
Continuous, discontinuous
13
14. Sampled Data System: Sampling
and Quantization
LPF
OR
BPF
N-BIT
ADC
DSP
N-BIT
DAC
LPF
OR
BPF
fa
fs fs
t
AMPLITUDE
QUANTIZATION DISCRETE
TIME SAMPLING
fa
1
fs
ts=
14
16. Practical Resolution Needs for Data Converters
Instrumentation Measurements
Sensor resolution/accuracy of 0.5% = 1/200
8 bits equivalent to 1/256 -- digitizing will lose information
10x sensor resolution = 1/2000 -- 12 bits is 1/4096
Allows discrimination of small changes
Can also be driven by display requirements
Dynamic Signal Measurements
Audio systems need better than 0.1% distortion at 5% of full scale
Equivalent to 1/20,000 -- 16 bits is 1/65,536
16
19. Baseband Antialiasing Filter Requirements
A
DR
fs
fa fs - fa
fs
2
STOPBAND ATTENUATION = DR
TRANSITION BAND: fa to fs - fa
CORNER FREQUENCY: fa
Antialias Filter Prevents
Aliasing
Contributes to Dynamic Range
Antialias Filter Objectives
Brick Wall (Steep/Deep Rolloff)
Linear Passband
Linear Phase
19
20. A Key Partitioning Question—Where to Filter?
Analog Filtering
Hardware oriented—generally fixed design
Digital Filtering
Software oriented—offers more flexibility
20
21. Purposes of Filtering
Noise Reduction
Typically low-pass
Discrimination and Selection
RF detection – channel separation
Extracting small signals from noise
Signal Enhancement
Music
Filter Complexity Derives from the Requirement
21
22. Types of Filters
Types of Analog filters
Active
More common at lower frequencies
Passive
More common at higher frequencies
Types of Digital filters
IIR (infinite impulse response)
Based on analog filters
More computationally efficient
FIR (finite impulse response)
Can be linear phase
More computationally intensive
Can provide more power and flexibility
Digital filtering requires digitizing—which requires an analog anti-
aliasing filter before the analog-to-digital converter
22
23. Comparing Analog and Digital Filters
Analog
No computational limitations
to limit high frequency
operation
Subject to component drift
and accuracy
Simpler circuit
Unlimited dynamic range
Basically no latency
Digital
Computations must be
completed in sampling time—
limits real-time operation
Not subject to component
drift and accuracy
More complex circuit
Requires antialiasing filter,
ADC, DSP, DAC, and
reconstruction filter
Dynamic range limited by
converter resolution
Much higher latency (delay)
Some filter functions can only
be done digitally
23
26. Throughput Considerations for Digital Filters
A digital biquad is a second-order recursive linear filter containing
two poles and two zeros
Determine how many biquad sections (N) are required
to realize the desired frequency response
Multiply this by the number of instruction cycles per
biquad for the DSP and add overhead cycles
The result (plus overhead) is the minimum allowable
sampling period (1 / fs) for real-time operation
26
28. Sigma-delta ADC -- the multi-purpose part
Sigma-delta ADCs span the analog and digital world
Provide customized filtering and high-resolution data
conversion
The core of digital audio processing
28
29. 29
Sigma-Delta ADC - First-Order Modulator
∑ ∫ +
_
+VREF
–VREF
DIGITAL
FILTER
AND
DECIMATOR
+
_
CLOCK
Kfs
VIN
N-BITS
fs
fs
A
B
1-BIT DATA
STREAM1-BIT
DAC
LATCHED
COMPARATOR
(1-BIT ADC)
1-BIT,
Kfs
SIGMA-DELTA MODULATOR
INTEGRATOR
31. 31
Simplified Frequency Domain Linearized Model
of a Sigma-Delta Modulator
∑
ANALOG FILTER
H(f) = 1
f
∑
X Y
+
_
X – Y
1
f
( X – Y )
Q =
QUANTIZATION
NOISE
Y =
1
f
( X – Y ) + Q
REARRANGING, SOLVING FOR Y:
Y =
X
f + 1
+
Q f
f + 1
SIGNAL TERM NOISE TERM
Y
32. 32
Oversampling, Digital Filtering,
Noise Shaping, and Decimation
fs
2
fs
Kfs
2
Kfs
KfsKfs
2
fs
2
fs
2
DIGITAL FILTER
REMOVED NOISE
REMOVED NOISE
QUANTIZATION
NOISE = q / 12
q = 1 LSBADC
ADC
DIGITAL
FILTER
Σ∆
MOD
DIGITAL
FILTER
fs
Kfs
Kfs
DEC
fs
Nyquist
Operation
Oversampling
+ Digital Filter
+ Decimation
Oversampling
+ Noise Shaping
+ Digital Filter
+ Decimation
A
B
C
DEC
fs
33. Data Acquisition Subsystem Configuration
Multiplexing
Multiple preamps
Multiple anti-alias filters
Multiple ADCs
Gain
Adjustable gain per channel
PGA vs. high resolution ADC
Simultaneous Sampling
Multiple signals correlated in time
Noise Reduction/Antialiasing Filter Placement
Special Analog Processing
Isolation
33
34. Data Acquisition Subsystem Configuration
Multiplexing
Multiplexing is done to reduce system cost by using fewer ADCs
ADC is fast enough to handle all channels in sequence
ADC errors are the same for all channels
Multiplexing issues
Settling time after switching channels
Multiplexer impedance may compromise signal
Final buffer amplifier may be needed
Multiplexer switching transients
Correlated sampling may require a faster solution
How close in time sampling needs to be done
Nyquist theory determines how often each signal needs to be sampled
Total signal throughput rate
Simultaneous sampling at lower rates
Simultaneous conversion at higher rates
34
35. Sample-and-Hold Function
Required for Digitizing AC Signals
ADC
ENCODER
TIMING
SAMPLING
CLOCK
SW
CONTROL
ANALOG
INPUT
SAMPLE
HOLD
SAMPLE
C
ENCODER CONVERTS
DURING HOLD TIME
SW
CONTROL
N
36. Input Frequency Limitations of
Non-Sampling ADC (Encoder)
N-BIT
SAR ADC ENCODER
CONVERSION TIME = 8µs
EXAMPLE:
dv = 1 LSB = q
dt = 8µs
N = 12, 2N = 4096
fmax = 9.7 Hz
v(t) =
2N
2
sin (2π f t )
dv
dt
2N
2
2π f cos (2π f t )=
dv
dt max
= 2(N–1) 2π f
dv
dt max
2(N–1) 2π q
fmax =
fs = 100 kSPS
ANALOG INPUT
N
dv
dt max
qπ 2N
fmax =
q
q
q
37. Simple ADC Multiplexing—AD7298
8 inputs plus temp sensor and single track/hold
37
TEMP
SENSOR
12-BIT
SUCCESSIVE
APPROXIMATION
ADC
INPUT
MUX
T/H
VDD GND
PD/RST
SCLK
DOUT
DIN
CS
VDRIVE
VIN7
VIN0
CONTROL
LOGIC
SEQUENCER
VREF
BUFREF
AD7298
08754-001
TSENSE_BUSY
38. Simultaneous Sampling—AD7606
8 Track/Hold Inputs Sampled Together
V1
V1GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V2
V2GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V3
V3GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V4
V4GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V5
V5GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V6
V6GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V7
V7GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
V8
V8GND
RFB1MΩ
1MΩ RFB
CLAMP
CLAMP
SECOND-
ORDER LPF
T/H
8:1
MUX
AGND
BUSY
FRSTDATA
CONVST A CONVST B RESET RANGE
CONTROL
INPUTS
CLK OSC
REFIN/REFOUT
REF SELECT
AGND
OS 2
OS 1
OS 0
DOUTA
DOUTB
RD/SCLK
CS
PAR/SER/BYTE SEL
VDRIVE
16-BIT
SAR
DIGITAL
FILTER
PARALLEL/
SERIAL
INTERFACE
2.5V
REF
REFCAPB REFCAPA
SERIAL
PARALLEL
REGCAP
2.5V
LDO
REGCAP
2.5V
LDO
AVCCAVCC
DB[15:0]
AD7606
08479-001
38
39. Full High Speed Dual Sampling—AD9643
2 Complete Sampling ADCs at 170 MHz
14
14
REFERENCE
SERIAL PORT
SCLK SDIO CSB CLK+ CLK– SYNC
1 TO 8
CLOCK
DIVIDER
AD9643
VIN+A D0±
D13±
DCO±
OR±
PDWN
OEB
VIN–A
VIN+B
VCM
VIN–B
NOTES
1. THE D0± TO D13± PINS REPRESENT BOTH THE CHANNEL A
AND CHANNEL B LVDS OUTPUT DATA.
AVDD AGND DRVDD
09636-001
.
.
.
.
.
PARALLEL
DDR LVDS
AND
DRIVERS
PIPELINE
14-BIT
ADC
PIPELINE
14-BIT
ADC
39
40. Positioning the Noise Reduction Filter to
Reduce the Effects of the Op Amp Noise
ADCs often have very high input bandwidths, usually greater than fs/2
Low distortion drive amplifiers typically have high bandwidths
Placing a simple LPF or BPF placed between the amp and the ADC is
an excellent noise reduction technique
Filter output impedance must be able to drive ADC
The output capacitor of the filter absorbs some of the ADC input
transient currents.
2.40
fFILTER
AMP
AMP
LPF
OR
BPF
LPF
OR
BPF
ADC
ADC
fFILTER
fs
fs
fCL
fCL
fADC
fADC
(A)
(B)
Amp noise integrated
over amp BW or ADC BW,
whichever is less
Amp noise integrated
over filter noise
bandwidth only
41. Where to Put the Gain?
Partitioning question about using PGA vs. high resolution ADC
PGA with wide-range gain steps can extend effective resolution of
ADC
Provides fine resolution
Not an exact solution unless gain ranges are perfectly matched
Nonlinearity induced between ranges
Not as popular with advent of higher resolution ADCs
Still useful in certain applications
41
42. ADC Multiplexing with Programmable Gain—
AD7194
16 inputs plus temp sensor and programmable gain amplifier
Accommodates sensors with widely varying signal levels
42
DVDD DGND REFIN1(+) REFIN1(–)
AIN1/P3
AIN2/P2
AIN3/P1/REFIN2(+)
AIN4/P0/REFIN2(–)
AINCOM
AD7194
SERIAL
INTERFACE
AND
CONTROL
LOGIC
REFERENCE
DETECT
TEMP
SENSOR
DOUT/RDY
DIN
SCLK
CS
MCLK1 MCLK2
CLOCK
CIRCUITRY
AVDD AGND
AIN5
AIN16
Σ-Δ
ADC
PGA
MUX
08566-001
AVDD
AGND
43. Special Analog Processing and Special Cases
Certain sensors require specialized analog processing to extract
precise measurements
Thermocouples—cold-junction compensation
Wide-dynamic-range photodiodes—signal compression
Linearization
Some sensors require precision tuning per unit—others can be
tuned together
Calibration and replacement issues
Digital options—store adjustment coefficients in software
Isolation
Analog or digital
Power isolation
43
44. Thermocouples
Thermocouples require cold-junction compensation
Traditionally done with specialized amplifiers with internal temperature sensors
Newer techniques use high-accuracy temperature sensors and A-D converters
to allow compensation at the processor
Thermocouple non-linearity is non-linear
Difficult to construct analog compensation
Digital systems use look-up tables
Detailed analysis in the Low-Level Signal Acquisition session
44
46. Log Amplifiers
Signal compression
Many applications must capture signals over a very wide dynamic range
Radio antennas capturing broadcast signals
Photomultipliers and photodiodes capture light signals over a very wide range
To process and use these signals, they need to be compressed to a much
smaller range
Logarithmic amplifiers
Log amplifiers compress signals over ranges of as much as 120db – a million
to one -- to a normal range of 1 to 10 volts
Accuracy is typically 0.1 to 0.5 dB -- 1 to 5%
Digital compression alternative
Programmable gain amplifier combined with high-resolution ADC
Can achieve range out to 120dB
Limited at very high frequencies
47. Log Amp Transfer Function
IDEAL
ACTUAL
SLOPE = VY
2VY
VY
IDEAL
ACTUAL
VYLOG (VIN/VX)
+
-
VIN=VX
VIN=10VX
VIN=100VX
INPUT ON
LOG SCALE
VOUT = VY log10
0
VIN
VX
IDEAL
ACTUAL
SLOPE = VY
2VY
VY
IDEAL
ACTUAL
VYLOG (VIN/VX)
+
-
VIN=VX
VIN=10VX VIN=100VX
INPUT ON
LOG SCALE
VOUT = VY log10
0
VIN
VX
49. AD8307 six-decade RF power
measurement
TO
ANTENNA
VP
604Ω
100kΩ
1/2W
NC
2kΩ
VR1
2kΩ
INT ±3dB
51pF
51pF
0.1µF
NC
OUTPUT
LEAD-
THROUGH
CAPACITORS,
1nF
1nF
NC = NO CONNECT
+5V
VOUT
AD8307
INP VPS ENB INT
INM COM OFS OUT
8 7 6 5
2 3 41
50Ω INPUT
FROM P.A.
1µW TO
1kW
22Ω
50. Oversampled SAR ADC with PGA
Achieving Greater Than 125 dB
Dynamic Range (CN0260)
Dynamic gain ranging
Faster than high-resolution sigma delta
Sampling rate up to 2.5MSPS
50
51. Oversampled SAR ADC with PGA Achieving
Greater Than 125 dB Dynamic Range
(CN0260)
51
52. Where to Put the Isolation?
Isolation is used to galvanically separate systems
Safety in patient monitoring
High-voltage systems
Remove high common-mode noise
Most commonly done at the digital level
ADC converter signal to digital
Transmitted across digital isolators
Providing power to isolated circuits needed
High-voltage amplifiers suitable in some motor control or power
control systems
More detail in the Data and Power Isolation session
52
55. Novel Analog-to-Analog Isolator Using an
Isolated Sigma-Delta Modulator, Isolated
DC-to-DC Converter, and Active Filter (CN0185)
55
56. Reverse Partitioning
Smarter peripheral devices sensing local conditions
Make local decisions to off-load main processor
Reduce programming load
Automatic gain control
Power control
56
57. Reverse Partitioning—AD5755
Quad 16-bit DAC for 4–20 mA industrial signaling
Dynamic power control for thermal management
On-chip diagnostics
57
AD5755
AVSS
–15V AGND
AVDD
+15V
AVCC
5.0V
DVDD
DGND
LDAC
CLEAR
SCLK
SDIN
SYNC
SDO
FAULT
DC-TO-DC
CONVERTER
POWER
CONTROL
INPUT
SHIFT
REGISTER
AND
CONTROL
STATUS
REGISTER
POWER-ON
RESET
REFERENCE
BUFFERS
DAC
REG A
INPUT
REG A
VREF
WATCHDOG
TIMER
(SPI ACTIVITY)
ALERT
REFOUT
REFIN
AD1
AD0
DAC A
1616
SWA VBOOST_A
GAIN REG A
OFFSET REG A
R1
R2 R3
RSET_A
VOUT_A
IOUT_B, IOUT_C, IOUT_D
RSET_B, RSET_C, RSET_D
+VSENSE_B, +VSENSE_C, +VSENSE_D
VOUT_B, VOUT_C, VOUT_D
IOUT_A
+VSENSE_A
–VSENSE_A
DAC CHANNEL B
DAC CHANNEL A
DAC CHANNEL C
DAC CHANNEL D
SWB, SWC, SWD
VBOOST_B, VBOOST_C, VBOOST_D
7.4V TO 29.5V
REG
VSEN1 VSEN2
+
07304-001
VOUT
RANGE
SCALING
30kΩ
58. Flexible 4-Channel Analog Front End for Wide
Dynamic Range Signal Conditioning (CN0251)
This circuit has it all
Multiplexing front-end
Multiplexer buffer
Instrumentation amplifier for CMRR
Anti-alias filter
Funnel amplifier to fit ADC range
Internal programmable gain amplifier
Gain ranges trimmed and matched
Sigma-delta ADC provides noise shaping
58
60. Tweet it out! @ADI_News #ADIDC13
What We Covered
The dilemmas of system architecture and partitioning
Analog vs. digital signal processing
The perils of sampling
Digital vs. digital
Where to put all the processing functions
Gain
Sampling
Filtering
Multiplexing
Special analog processing
Isolation
60
61. Tweet it out! @ADI_News #ADIDC13
Visit the Flexible 4-Channel Analog Front End
for Wide Dynamic Range Signal Conditioning
(CN0251) in the Exhibition Room
This flexible signal conditioning
circuit is for processing signals
of wide dynamic range, varying
from several mV p-p to 20 V p-p.
The circuit provides the
necessary conditioning and
level shifting and achieves the
dynamic range using the internal
programmable gain amplifier
(PGA) of the high resolution
analog-to-digital converter
(ADC).
61
Image of demo/board
This demo board is available for purchase:
www.analog.com/DC13-hardware
62. Tweet it out! @ADI_News #ADIDC13
FMComms1 Demo @ Exhibition Hall
New partitioning concepts for radio
Ubuntu Linux on ZC702
FMComms1 on FMC
HDMI Display and USB
Keyboard/Mouse
Full Transmit and Receive
62
Image of demo/board
This demo board is available for purchase:
www.analog.com/DC13hardware