Agilent Technologies Agile or Elusive Signals Using Manual

© 2013 Agilent Technologies
Analyze Agile or Elusive Signals Using
Real-Time Measurement and Triggering
Ben Zarlingo, Agilent Technologies Inc.

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This Webcast
Agile & Elusive Signals
Discovering Signals vs. Troubleshooting, Optimizing
Two Case Studies
Dynamic signal environment-ISM band
Radar signal
Choosing & Using Techniques & Tools
Make the most of what you already know & own
Swept spectrum analyzers
Vector signal analyzers/VSA software
Oscilloscopes
Real time analyzers
Using Triggering to Enhance Measurement Effectiveness

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Case Study #1: 2.45 GHz ISM Band
100 MHz Wide
Spread Spectrum Techniques
Lightly Regulated, Signals Not Explicitly Coordinated
WLAN (typically dominant occupant), Bluetooth, Cordless Phones
•And 1 kW+ microwave ovens!
•And almost anything else!
Very Dynamic
•Content not known at any specific point in time
•May be very low occupancy
Lots of Collision Tolerance May Be Needed
Potential “Cliff Effect” at Some Degree of Crowding

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ISM Band View: Swept Spectrum Analysis
Band: 100 MHz
Span: 160 MHz
Dynamics X2 (swept RBW & changing signals) Confuse the View
Peak Hold Detects Signals but Frequency Overlap Obscures
Signals Typically Short Duty Cycle, Total Low Occupancy
POI is Approx. “Low” (useful concept even if not strictly applicable)
Single Sweep
(fast but retrace not as fast)
Peak Hold (short)
Peak Hold (long)

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ISM Band View: Real Time Analyzer
Density or
Histogram Display
Gap-Free Analysis
No Signals Missed
Density Display Shows Signals Inside Signals
Fast, Full Display Update Rate Shows Signal Dynamics
See Unexpected Behavior, Even If Infrequent
Individual Display Updates Combine Thousands of Spectra

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ISM Band View: Real Time Analyzer
Spectrogram Display
Top Trace is Latest or
Selected Spectrum
Same Spectral Data as
Density/Histogram
Individual Spectrogram Line
Represents Many Spectra
(typically thousands)
View into Dynamics, Timing
Acquisition Time Setting Affects Way Spectra are Combined to Form
Display Update
WLAN Signals Active Continuously?
What are Vertical Bars? A Multitone Signal?

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Spectrogram Display
Adjusting Acquisition Time
Shorter Acquisition Time
Determines Amount of Data
Processed for Spectrum or
Spectrogram Trace Update
Each Trace Update &
Spectrogram Line Represents
Fewer Spectra
More Trace Updates/Second, Finer Time Resolution
Spectrogram Covers Shorter Interval
Determines Time Scale of Spectrogram
Use Spectrogram Trace Buffer to Examine Signal Dynamics

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Characteristics of the Real Time Analyzer
Density View
Fast Display Updates, High Data Density
Easily Understand Signal or Event Frequency
Find Very Infrequent Events
Find Unexpected Events, Behavior
Limitations
•Combining traces combines behavior from different times
•Limited flexibility (RBW, span combinations)
•Limited frequency span
•Power spectrum only
•Markers only on combined spectrum or density at a point

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What is “Real Time” Analysis?
Understanding Real Time Analyzers and Real Time Analysis
General Definition of Real Time
•Measurement operations where all signal samples are used in calculating
measurement results of some kind (usually spectrum)
Real Time Bandwidth (RTBW)
•The widest analysis bandwidth where an analyzer can maintain real time
operation
•Duration of maintaining real time operation is not specified; it may
assumed to be short term or long term or unlimited
Current Usage for Signal Analyzers
•A spectrum or FFT analyzer having a signal processing path where most or
all samples, even at wide bandwidths, are used to create a spectral display
or to trigger signal measurement or acquisition (sometimes both)

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Real Time Operation
In Real Time Operation the Analyzer’s Processing (CALC) is
Fast Enough to Keep Up with All Data Samples
CALC Time Includes FFT or Power Spectrum, Averaging, Display
Updates, etc.
However some data
may still be “lost”

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If Processing is Faster than Sampling, Perform Additional FFTs With
Partially-New Time Records as Samples Come In
Avoid Loss of Data Due to Windowing
Accurate Amplitude Measurements of Short Duration Signals
Overlap Processing
Overlap 0%
Overlap 50% Processor Idle
Window
Function

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Probability of Intercept (POI)
Treated Informally Here
•Finding signals important to you, expected or unexpected
•Reasonable effort and time to discovery
•Signals found can be measured as necessary
• Knowledge of signals may be “perfect” or simply adequate
A More Rigorous Treatment in MicroApp From Richard Overdorf
• “Understanding Probability of Intercept for Intermittent Signals“
IMS 2013 MicroApp presentation
Agilent Aerospace/Defense Symposium presentation (2013)
Evaluate These Techniques Against Your Requirements

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Frequency Mask Trigger (FMT)
Trigger Based on
In-Band Power
(scalar) Spectrum
Spectral Mask
Eval, High/Low
Limits, Logic
Trigger Generated
from High Speed
FFT Engine
Trigger Not
Time-Aligned
Trigger Timing Resolution: May Be 1/FFT Period
Trigger a Single Spectrum Measurement or Time Capture (VSA), etc.

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Vector Signal Analysis: The Logical Extension
and Complement to a Real Time Analyzer
Superheterodyne Downconversion to All-Digital IF
•Adaptable to swept
spectrum analysis and
real time analyzer
•Full vector data
preserved
Capture
Memory
Measurements
•Short/Long Data Block
•Vector, Demodulation

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VSA Spectrum of ISM Band Signals: 1 kpoint vs. 100 kpoints
Much More
Informative
Higher POI

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Improving POI with FFT Analyzers:
Several Steps for Dramatic Improvement
Use Much Longer Time Records (25,000 points or more)
•Time record length goes up faster than FFT speed goes down
Narrow Frequency Span to the Minimum Needed
•Time record is longer (in time) for given number of points
Use IF Magnitude Trigger, Pre/Post Delays, Holdoff
•Avoid measuring when no signal present in span
Use Persistence or Density/History Displays
•Typically persistence, to make peaks last long enough to be noticed
Peak Hold
Result: POI Dramatically Improved, Though may not be Near 100%

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Triggering in VSAs and Real Time Analyzers
IF Magnitude & Frequency Mask Triggers
Triggered Individual Measurements or Signal Captures
•Sqrt (I2+ Q2) of each
sample, is easier &
faster (VSAs)
•FFT power Spectrum
is slower but more
selective (RTSAs)
•VSA architecture can
do both
Capture
Memory
Measurements
•Short/Long Data Block
•Vector, Demodulation
IF Mag or
Freq Mask Trig

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Flexible Triggering
to Initiate Capture
IF Magnitude Trigger
Frequency Mask Trigger
Pre/Post-Trigger Delay
Adjustable
•Power Level
•Delay
•Holdoff time, type
Other Types
•Channel
•External/TTL
•Periodic Magnitude
Freq. Mask

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VSA Attributes for Detailed, Flexible Analysis
The Next Steps After Finding a Signal
Detailed Signal Analysis, Including Vector, Demodulation
Time Capture, Playback
Connection to Many Signal Analzyer Front-Ends
•Signal analyzers
•Oscilloscopes
•Digitizers
Multi-Channel Analysis, Including Channel Time Alignment
•Including multi-channel capture & analysis
•Beam-forming, MIMO, space-time coding
Multi-Band Analysis, Multi-Measurements
Excellent Complement to Single-Channel RTSA

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Agilent 89600B VSA Signal Capture:
Just Press the Red Button
Use Existing Center, Span
(Wider is ok)
Press Record
Then Press Play
Adjust Capture if
Desired
•Length (seconds, samples,
time records) or use default
•Input Range
•Frequency Center, Span
Better, Faster Insights from Measuring
Same Signal with Different Settings