techniques for characterizing spurious signals spectrum analyzer dynamic range balancing distortion,...

Techniques for Characterizing Spurious Signals

Riadh Said

Product Manager

Microwave and Communications Division

Keysight Technologies

October 21, 2014

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Our Goals today

Review the sweep time equation to trade-off dynamic range for sweep speed.

Review the basics of applying good spur searching strategy.

Introduce new spectrum analysis technologies to accelerate spur searching for both R&D and manufacturing.

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What is a spur and why we care about them.

2. Introduce the sweep time equation for spectrum analysis.

3. Establishing your spur searching strategy.

4. Translate sweep time equation to real-life example

5. Techniques and technologies to manage your spur search time more effectively:

• New wideband, high dynamic range ADC & display signal processing

• New fast sweep capabilities vs. traditional sweep

• New stepped FFT approach with spur subtraction

• Noise subtraction & new pre-amps for best sensitivity

Agenda:

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Assumptions & Definitions

– Spectrum analyzer basics such RBW, TOI, and SHI

– “Noise” = Displayed average Noise level (DANL), sensitivity, noise

figure

– Distortion = Harmonics 2nd and 3rd order and their products

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What is a spur? Definition: spu·ri·ous, \ˈspyu̇r-ē-əs\ Adjective 1. not genuine, sincere, or authentic 2. of illegitimate birth 3. outwardly similar or corresponding to something without having its genuine qualities 4. of falsified or erroneously attributed origin 5. of a deceitful nature or quality

What you wanted.

Your Design

What you got.

Spurs & noise

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Where do spurs come from? …Many many places

• Mixers 2nd and 3rd order harmonics + their mixing products with LO and IF inputs…

• Multipliers ½ rate , ¾ rate harmonics or “sub-harmonics”

• Dividers Odd Harmonics

• Oscillators, LO, VCO’s, clocks Leakage

• PLL’s Frac-N-Loops spurs

• Amplifiers 2nd and 3rd order Harmonics

• DAC’s repetitive quantization errors…

• Poor filtering & isolation/coupling

• Incidental resonance from parasitic capacitance or inductance in circuit

• Vibration microphonic noise/spurs

• Power supply: line noise or switching harmonics, 50/60 Hz and their harmonics

• Glitch's or discontinuities in digital IF or baseband FPGA’s, ASIC’s etc…

• The mixing products of any of the above.

When a non-linear device is presented with two or more input frequencies the output will generator both the input frequencies

and the intermodulation distortion products of those input at the same time.

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http://www.markimicrowave.com/WepApps/Spur_Calculator.aspx

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Why do we care? …Link Budgets, Sensitivity, Range, Quality of Service

Satellite example: In channel Rx interference degrades sensitivity & range

Radar/EW example: False target /threat detection or inference

Cellular example: Out of channel Interference pollutes neighbors receiver and

degrades range & data rates. Regulatory requirements. (i.e. FCC)

Transmitter

Signal, f0 Return Signal, f1 (-85 dBm)

Spurious Signal

Very small received signal (-130 dBm)

Spurious Signal – Jam yourself

Small received signal (-50 dBm) Spurious Signal – Jam your neighbor

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Spectrum Analyzer Dynamic range Balancing Distortion, Noise & Test time

Spectrum Analyzer Dynamic range is limited by three factors:

1. Distortion performance of the input mixer 2nd & 3rd order products

2. Broadband noise floor of the system. Sensitivity/Displayed Average Noise level (DANL)

3. Phase noise of the local oscillator Narrow band measurements.

The above three factors must be optimized in combination with your DUT and measurement

uncertainties requirements.

Block diagram of a classic superheterodyne spectrum analyzer

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Spectrum Analyzer Dynamic range Distortion and Noise

• Increasing input attenuation reduces harmonic

distortion from spectrum analyzer. However this

also adds more IF gain which degrades noise

floor.

• To compensate for this you can reduce the RBW

and reduce the noise floor.

9 For more information see:

App Note 150: Spectrum analyzer basics

http://literature.cdn.keysight.com/litweb/pdf/5952-0292.pdf

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Spectrum Analyzer Dynamic range Uncertainties Budget for Noise + Distortion

Spectrum Analyzer Dynamic range must be optimized in combination with

your DUT requirements and measurement uncertainties you can tolerate.

Uncertainty versus difference in

amplitude between two sinusoids

at the same frequency Error in displayed signal

amplitude due to noise

Example of uncertainty budget: Distortion Error budget: +/- 1 dB error = -18 dBc margin relative to DUT input

Noise Error budget: +/- 0.3 dB error = 5 dB margin relative to noise floor

Maximum total error: (+/- 1 dB) + (+/- 0.3 dB) = +/- 1.3 dB (excludes instrument uncertainty)

Distortion Error Noise Error

For more information see: App Note 150: Spectrum

analyzer basics and http://mwrf.com/author/bob-nelson 10



http://mwrf.com/author/bob-nelson




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The sweep time equation for spectrum analysis Balancing Dynamic Range & Test Time

RBW = Resolution Bandwidth Filter

ST = Sweep Time

k = the constant of proportionality ST = k (Span)

RBW2

The rise time of a filter (RBW) is inversely

proportional to its bandwidth, and if we

include a constant of proportionality, k,

then: Rise time = k/RBW

RBW has a squared

relationship with time.

Noise floor change* =

10 log (BW2/BW1)

Where

BW1 = starting resolution bandwidth

BW2 = ending resolution bandwidth * Peak-detectors do not accurately represent the noise floor.

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42 ms (300kHz RBW)

4.2 sec (30 kHz RBW)

100x delta in sweep time

with a 10x delta in RBW!

-10 dB

Note: The k value varies based on a number of conditions including filter shape for

RBW, VBW and detector types. Generally a value of 2 or 3 for Gaussian filters.

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Probability of Intercept for Swept Analysis

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Odds of detecting intermittent spurious signals

POI = (R+T)

(R+R’)

T = duration of the signal of interest

R = listening time at frequency

R’ = time not listening

R+R’ = revisit time

Note: Assumes signal can be discerned

R (approx) = (RBW+SBW)*ST

Span

RBW = Resolution BW

SBW = spectral width of the signal

ST = spectrum analyzer sweep time

Span = spectrum analyzer span Listening time of swept-LO spectrum analyzers can easily be

approximated as the amount of time that some portion of the

resolution–bandwidth filter overlaps some part of the signal energy.

The Term (R+R’) is the sum of the sweep time and the dead time

between sweeps. And it is also called the revisit time.

Perfect POI = 1

Range: zero to one

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Establishing your spur searching strategy maximize test efficiency

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Know where & what to look for:

• Start with DUT block diagram, modes of operation & know design issues.

• Establish required target levels (Balance schedule & search time)

• Establish the type of spurious signals (static, moving, harmonic, random, modulated)

Balance the needs in production vs. R&D:

• R&D and production teams should partner to focus on problem areas.

• Production target test levels ideally more relaxed if designed with margin.

• Focus on known product/component variation problems.

Determine uncertainty budget:

• Just enough margin to yield required results and minimize total test time.

• Remove tests that deliver 100% yield with high margins. Go to sampling.

• Apply appropriate measuring tools for max speed. (Swept, FFT, Real-time)

N LO

Baseband

/IF/ ASIC

3 2 1

Band Filters

LPF X2

In Band Out of Band

Don’t waste time

looking outside

filtered bands?

Don’t waste time

looking outside

filtered bands?

Focus on known

problems first.

Unexpected ASIC errors

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Real-life example The sweep time equation in action

Target non-harmonic spurs: >-100 dBm

Max signal input size = - 10 dBm

Target attenuation = 16 dB

Target measurement error budget ~ 2 to 3 dB

RBW = 3 kHz, (peak detector, with pre-amp)

Span = 10 MHz to 18 GHz

Sweep time = 2.4k sec or 40 minutes

300 different test modes of DUT

Total test time = 200 hours!

Repeat every time a new design change is made…

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Manage your spur search time more effectively

New Techniques and technologies

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Large spurs > -75 dBc

Medium spurs > -100 dBc

Small Spurs < - 100 dBc

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Large Spurs >-75 dBc

New wideband high dynamic range digitization

& Processing

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ADC

510 MHz BW

CLK

500 MHz

FPGA FPGA

ASIC

SDRAM

Page Agilent Confidential

July 2014

The Follow features available on Keysight X-Series Analyzer & new N9040B UXA Signal Analyzer

MHz, High Performance IF for spur searching

– See your spurs clearly with SFDR

of > -75dBc across 510MHz BW

– Monitor and capture highly elusive

spurs across the full analysis

bandwidth with real time signal

analysis

– Maximise dynamic range and

accuracy with excellent IF

frequency response of <0.7dB

New N9040B UXA Spectrum Analyzer

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For more information see application note:

Using Wider, Deeper Views of Elusive Signals to Characterize Complex

Systems and Environments 5992-0102EN

http://literature.cdn.keysight.com/litweb/pdf/5992-0102EN.pdf






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How to Capture the Intermittent Spurious Signal

– Questions about the signal of

interest

• What Frequency?

• How Often?

• How much Power?

• What is the Bandwidth?

• What Modulation?

• Where is the Noise Floor?

• What is the Phase Noise?

• Is there more than one signal?

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The Swept Analysis Mode

• A swept LO w/ an assigned RBW.

• Covers much wider span.

• Good for events that are stable in the freq domain.

• Magnitude ONLY, no phase information (scalar info).

• Captures only events that occur at right time and right frequency point.

• Data (info) loss when LO is “not there”.

Freq

Time

Lost Information

Lost Information

Lost Information

Swept LO

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IQ Analyzer (Basic) Mode – Complex Spectrum and Waveform Measurements

• A parked LO w/ a given IF BW

• Collects IQ data over an interval of time.

• Performs FFT for time- freq-domain conversion

• Captures both magnitude and phase information (vector info).

• Data is collected in bursts with data loss between acquisitions.

Freq

Meas Time

or

FFT

Window

Length

Meas Time

or

FFT

Window

Length

Lost Information

Time

Parked LO

Analysis BW

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Real–Time Spectrum Analysis

• A parked LO w/ a given IF BW

• Collects IQ data over an interval of time.

• Data is corrected and FFT’d in parallel

• Vector information is lost

• Advanced displays for large amounts of FFT’s

Freq

Time

Parked LO

Real-time BW

Acquisition or

slice time

Acquisition or

slice time

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Real-Time Spectrum Analysis Hardware

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ADC (400 MSA/s, 14-bit)

Real-time corrections and decimation

Overlap

Memory

FFT Engine (292,968 FFT’s/s)

Time Domain

Processor

Spectrum

trace memory

Density trace

memory

Frequency

Mask Trigger

Power vs Time

trace memory

Display processor

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Using Real-Time Spectrum Analysis

Benefits

– Gap free capture

– Supports wide bandwidths

– Real-Time capture of signals that are

present for only 2 ns with large S/N

ratio’s.

– For full amplitude accuracy UXA POI

expressed in time = 3.57 us

– Best at measuring the

shortest duration signals that

are infrequent or occur only

one time within 510 MHz

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POI express in time duration T is the minimum length of the

signal of interest if it is to be detected with 100-percent

probability and measured with the same amplitude accuracy as

that of a CW signal.


Understanding and Applying Probability of Intercept in Real-time Spectrum

Analysis 5991-4317EN



Window size = FFT windowing in points Time record length = FFT bin size in points P = Overlap FFT processing points

fs= sample rate

http://cp.literature.agilent.com/litweb/pdf/5991-4317EN.pdf












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Real-Time Spectrum Analysis – Density Display

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Color coded for fast visualization & triggering

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Wider, cleaner analysis BW Quickly Analyze large spans for spurs with confidence

510 MHz

Maximize the dynamic range for

optimum headroom.

>-7

5 d

Bc

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Minimize Measurement Uncertainty IF Frequency Response UXA N9040B

Page

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Minimize measurement

uncertainties across wide

instantaneous bandwidths

<0.7

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Stepped Density Method

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Using Real-time Dwell

Freq

Time




Capture of repetitive non CW signals over large bandwidths









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Stepped Density Method

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Using Real-time Dwell over full span

Full span of spectrum analyzer

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Medium to low Spurs (<-75 dBc)

New fast sweep vs. traditional sweep

30

ADC

CLK

500 MHz

FPGA FPGA

ASIC

SDRAM

Page Agilent Confidential

July 2014

The Follow features available on Keysight X-Series Analyzer & new N9040B UXA Signal Analyzer

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Traditional Sweep – non-continuous signals

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Limited by analog RBW rise time vs. accuracy needs

Freq

Time

RBW Signals

Sweep

Standard Analog Sweep

ST = k (Span)

RBW2

POI = (R+T)

(R+R’)

R = (RBW+SBW)*ST

Span

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Fast Sweep – non-continuous signals

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Compensated RBW rise time with improved accuracy

Freq

Time

UXA Fast Sweep

ST = k (Span)

RBW2

Modified

k value

For more information see :

5991-3739EN-Using Fast-Sweep Techniques to Accelerate Spur Searches

POI = (R+T)

(R+R’)

R = (RBW+SBW)*ST

Span









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Up to 50x faster vs. Traditional Sweep

Fast Sweep Traditional Sweep

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Full 26.5 GHz span Full 26.5 GHz span










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The Effects of Over-sweeping RBW filter limits the rise time of signal

Oversweeping produces errors in frequency, amplitude and bandwidth

• Low amplitude: The displayed amplitude of the spurious

and other signals is lower than the true value, and by an

amount larger than the analyzer specifications would

indicate.

• Bandwidth spreading: The effective RBW of the

measurement is significantly wider than the selected value.

• Frequency shift: The apparent center frequency of

spurious and other signals is higher than the true value, and

by an amount larger than the analyzer specifications would

indicate.

Leveraging real-time DSP during fast sweep, the phase response of the RBW filter is

adjusted based on the sweep rate to compensate for oversweeping effects. This maintains

the correct amplitude and bandwidth of the detected signal, even at very high sweep rates.

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F F T S W E E P S P E E D I M P R O V E M E N T Sweep Speed Improvement with IF CHIRP Processing

Area where Chirp IF

processing improves

speed

FFT Swept

With Chirp

Without Chirp

> 10 x Faster!

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Fast Sweep Repeatability

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Comparing fast sweep to traditional sweep, the lower values and shallower slope of the blue data points

(fast sweep) show that repeatability is improved and varies less with sweep time.

Holding sweep time constant while

using a narrower RBW to measure

CW signals reduces measurement

variance because the narrower

filter blocks more of the broadband

noise.











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Fast-sweep technology provides at least four important benefits:

1. Dramatically reduced sweep times for CW spur searches over wide spans and

narrow RBWs. (> 10x faster)

2. Improved measurement throughput while maintaining accuracy, frequency

selectivity and consistent bandwidth

3. Improved measurement repeatability at faster sweep rates

4. Simplified selection of RBW to get a desired combination of dynamic range and

repeatability, because repeatability depends almost entirely on dynamic range

rather than both dynamic range and sweep time.

Fast Sweep Benefits Summary

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Note: Installed base Keysight (Agilent) X-Series spectrum analyzers can be upgraded with fast sweep.

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Medium to Low Spurs (< -75 dBc)

Stepped FFT

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FFT- Based

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The following features available on the M9393A PXIe Performance Vector Signal Analyzer

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Stepped spectrum analysis

Benefits:

Fast “sweeps” and excellent dynamic

range with narrow RBW

Search for spurs, measure harmonics

or analyze multiple signals at once.

Trade-off

Solid state front end limits max

sensitivity, but can be balance with

narrower RBW’s and speed.

Method:

Multiple FFTs are concatenated to

create a span >the IF bandwidth

High speed LO and digitizer list mode

enables fast stepping across span

Software stitches together FFTs and

displays single trace result up to 27GHz

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High-speed stepped FFTs to analyze wide spans Single FFT up to max

analysis BW (160 MHz)

Span up to frequency range of analyzer (27 GHz)

Fastest stepped spectrum analysis requires wide

analysis bandwidth and fast frequency tuning

options, and powerful computer.

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Digital Image Rejection

42

Fast, accurate measurements without hardware pre-selector

Minimum detect

High & Low Side Mixing Smart Image rejection processing

Method:

1. Adjust LO making 2 acquisitions: high-side

mix then low-side mix

2. Use minimum detection algorithm to

determine real signals

3. Use additional techniques including max-

hold, IF dithering and using narrow RBW to

accurately measure even challenging signals For more information see application notes:

5991-4039EN - Achieving Excellent Spectrum Analysis Results Using

Innovative Noise, Image and Spur-Suppression Techniques











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Digital image rejection

Benefits:

Fast tuning speed

Excellent amplitude accuracy

Compact physical size

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Fast, accurate measurements without hardware pre-selector

2 GHz LFM

signal

AWG alias

product

AWG 12

GHz clock

Challenging test scenario: Measuring 2 GHz wide linear FM chirp

from arbitrary waveform generator centered at 2 GHz

Image-protect

For more information see application notes:












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Power Spectrum mode for high-speed stepped FFT analysis

– Measure spurs & harmonics across 27 GHz @ 10 kHz RBW in < 1

second

– Achieve > 300 GHz/sec sweep speeds

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Results

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Stitched FFT with Digital Image Rejection Summary

– Fastest tuning speed enabled by:

• Very fast LO & all solid-state design

• List mode executes predefined set

of acquisitions from digitizer FPGA

• Takes advantage of latest processor

technology – M9037A or high-power

PC

– Outstanding speed to dynamic range to

see low-level signals quickly

– Leading to shorter test times & higher

throughput in design validation &

production

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Optimized for speed & compact form factor

Frequency tuning speed (nominal)

< 3.6 GHz 175 us

3.6 to 8.4 GHz 135 us

8.4 to 13.6 GHz 135 us

13.6 to 17.1 GHz 155 us

17.1 to 27 GHz 145 us

Meas. time:

1 second

1 GHz span

105 dB

dynamic range

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Low Spurs (< -100 dBc)

How to improve the noise floor

Pre-Amps Noise subtraction

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Noise Floor Extensions/Corrections

Benefit:

Accurately measure signals

close to the noise floor

Trade off:

Increases variability typically

requires more averaging when

near the noise floor and

therefore more time.

Method:

1. Measures internally generated noise (N)

2. Measures input signal and noise (S + N)

3. Subtract the two measurements for

corrected result: (S + N) – N = S

4. Use averaging/VBW filter to see effects of

noise correction

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Subtracting the noise floor of the spectrum analyzer

For more information see application notes:

5990-5340EN - Using Noise Floor Extension in the PXA Signal Analyzer



Feature available on both X-Series & M9393A

Real-time ASIC Software driven
















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USB Pre-Amps

Pre-calibrated plug & play operation

48

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U7227x USB Preamps

Model Frequency Range

U7227A 10 MHz to 4 GHz

U7227C 100 MHz to 26.5 GHz

U7227F 2 GHz to 50 GHz

– Noise Fig ~ 5dB

– Gain >17 dB (makes NF of SA

negligible).

– USB provides power to Preamp,

and reads gain, noise fig, and S-

parameter data from flash.

– UXA SA app can use preamp as

“remote front end”; correct absolute

amplitude vs frequency displayed.

U7227x USB Preamplifiers

X-series Analyzers + USB Preamplifiers provide: 2X improved noise figure beyond 10 GHz up to 50 GHz Improved measurement uncertainty up to 1/3 Lower DANL/noise floor improving to -171 dBm/Hz

– Pre-calibrated and ready to use with X-Series

49 Keysight USB Pre-amplifiers: 5991-4246EN:




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Summary

1. Start with a smart spur search strategy

2. Balance it with the Sweep time considerations

3. Leverage modern digital IF processing:

• Real-Time • Stepped Density Capture of repetitive non CW signals over large bandwidths

• Real-time Density Best at measuring the shortest duration signals that are infrequent or

occur only one time within 510 MHz

• Pre-Selected Fast sweep Best at measuring both small and large signals

with or without modulation at high speed.

• Stitched FFT with digital image & spur rejection Ideal for continuous

CW like spurs. Ideal for the fastest speeds when absolute noise floor can be

traded off.

• Noise Floor corrections – When you can trade-off speed for dynamic range.

4. USB Pre-Amps – Simplified calibrated setup to extend noise floor, improve

uncertainties, or increase sweep speed with wider RBW’s.

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Where to learn more/References

• Spectrum Analyzer Basics, App Note 150, 5952-0292:


• Using Wider, Deeper Views of Elusive Signals to Characterize Complex Systems and Environments:


• Using Fast-Sweep Techniques to Accelerate Spur Searches, 5991-3739EN:


• Achieving Excellent Spectrum Analysis Results Using Innovative Noise, Image and Spur-Suppression Techniques


• Understanding and Applying Probability of Intercept in Real-time Spectrum Analysis :


• Measuring Agile Signals and Dynamic Signal Environments: 5991-2119EN:


• Using Noise Floor Extension in the PXA Signal Analyzer:


• N9040B UXA X-Series Signal Analyzer: www.keysight.com/find/UXA

• M9393A PXIe Performance Vector Signal Analyzer: www.keysight.com/find/M9393A

• Keysight USB Pre-amplifiers: 5991-4246EN: http://literature.cdn.keysight.com/litweb/pdf/5991-4246EN.pdf

• Spur Calculator from Marki Microwave: http://www.markimicrowave.com/WepApps/Spur_Calculator.aspx

• Technical Expert Bob Nelson: http://mwrf.com/author/bob-nelson

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http://www.keysight.com/find/UXA

http://www.keysight.com/find/M9393A




















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Thank You!

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techniques for characterizing spurious signals spectrum analyzer dynamic range balancing distortion,...

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