Techniques for Characterizing Spurious Signals

Transcription

1 Techniques for Characterizing Spurious Signals October 21, 2014 Riadh Said Product Manager Microwave and Communications Division Keysight Technologies

2 Our Goals today Review the sweep time equation to tradeoff 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. Page 2

3 Agenda: 1. 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 Page 3

4 Assumptions & Definitions Spectrum analyzer basics such RBW, TOI, and SHI Noise = Displayed average Noise level (DANL), sensitivity, noise figure Distortion = Harmonics 2 nd and 3 rd order and their products Page 4

5 What is a spur? Definition: spu ri ous, \ˈspyu r-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 Your Design What you wanted. What you got. Spurs & noise Page 5

6 Where do spurs come from? Many many places Mixers 2 nd and 3 rd 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 2 nd and 3 rd 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. Page 6

7 Why do we care? Link Budgets, Sensitivity, Range, Quality of Service Radar/EW example: False target /threat detection or inference Transmitter Signal, f 0 Spurious Signal Return Signal, f 1 (-85 dbm) Satellite example: In channel Rx interference degrades sensitivity & range Spurious Signal Jam yourself Very small received signal (-130 dbm) Cellular example: Out of channel Interference pollutes neighbors receiver and degrades range & data rates. Regulatory requirements. (i.e. FCC) Spurious Signal Jam your neighbor Small received signal (-50 dbm) Page 7

8 Spectrum Analyzer Dynamic range Balancing Distortion, Noise & Test time Block diagram of a classic superheterodyne spectrum analyzer Spectrum Analyzer Dynamic range is limited by three factors: 1. Distortion performance of the input mixer 2 nd & 3 rd 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. Page 8

9 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. For more information see: App Note 150: Spectrum analyzer basics Page 9

10 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. 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 Uncertainty versus difference in amplitude between two sinusoids at the same frequency Error in displayed signal amplitude due to noise For more information see: App Note 150: Spectrum analyzer basics and Page 10

11 The sweep time equation for spectrum analysis Balancing Dynamic Range & Test Time ST = k (Span) RBW 2 RBW = Resolution Bandwidth Filter ST = Sweep Time k = the constant of proportionality 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. 100x delta in sweep time with a 10x delta in RBW! 42 ms (300kHz RBW) 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. -10 db 4.2 sec (30 khz RBW) 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. Page 11

12 Probability of Intercept for Swept Analysis Odds of detecting intermittent spurious signals Perfect POI = 1 Range: zero to one 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+S BW)*ST Span RBW = Resolution BW S BW = spectral width of the signal ST = spectrum analyzer sweep time Span = spectrum analyzer span 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. 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. Page 12

13 Establishing your spur searching strategy maximize test efficiency 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) Baseband /IF/ ASIC Unexpected ASIC errors LPF X2 Band Filters In Band Out of Band Don t waste time looking outside filtered bands? LO Don t waste time Focus on known looking outside problems first. filtered bands? N Page 13

14 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 Page 14

15 Manage your spur search time more effectively New Techniques and technologies Large spurs > -75 dbc Medium spurs > -100 dbc Small Spurs < dbc Page 15

16 Large Spurs >-75 dbc New wideband high dynamic range digitization & Processing 510 MHz BW 500 MHz SDRAM ADC CLK FPGA FPGA ASIC Page 16

17 The Follow features available on Keysight X-Series Analyzer & new N9040B UXA Signal Analyzer Page 17 Page Agilent Confidential July 2014

18 510 MHz, High Performance IF for spur searching New N9040B UXA Spectrum Analyzer 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 For more information see application note: Using Wider, Deeper Views of Elusive Signals to Characterize Complex Systems and Environments EN Page Page 18

19 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? Page 19

20 The Swept Analysis Mode A swept LO w/ an assigned RBW. Covers much wider span. Swept LO 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. Lost Information Lost Information Lost Information Freq Data (info) loss when LO is not there. Time Page 20

21 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. Parked LO Performs FFT for time- freqdomain conversion Captures both magnitude and phase information (vector info). Data is collected in bursts with data loss between acquisitions. Lost Information Analysis BW Freq Meas Time or FFT Window Length Meas Time or FFT Window Length Time Page 21

22 Real Time Spectrum Analysis A parked LO w/ a given IF BW Collects IQ data over an interval of time. Parked LO Data is corrected and FFT d in parallel Vector information is lost Advanced displays for large amounts of FFT s Acquisition or slice time Freq Acquisition or slice time Real-time BW Time Page 22

23 Real-Time Spectrum Analysis Hardware ADC (400 MSA/s, 14-bit) Real-time corrections and decimation Time Domain Processor Overlap Memory FFT Engine (292,968 FFT s/s) Power vs Time trace memory Spectrum trace memory Density trace memory Frequency Mask Trigger Display processor Page 23

24 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 Window size = FFT windowing in points Time record length = FFT bin size in points P = Overlap FFT processing points f s = sample rate 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. For more information see application note: Understanding and Applying Probability of Intercept in Real-time Spectrum Analysis EN Using Wider, Deeper Views of Elusive Signals to Characterize Complex Systems and Environments EN Page 24

25 Real-Time Spectrum Analysis Density Display Color coded for fast visualization & triggering Page 25

26 >-75 dbc Wider, cleaner analysis BW Quickly Analyze large spans for spurs with confidence Maximize the dynamic range for optimum headroom. 510 MHz Page

27 Minimize Measurement Uncertainty IF Frequency Response UXA N9040B <0.7 Minimize measurement uncertainties across wide instantaneous bandwidths Page Page 27

28 Stepped Density Method Using Real-time Dwell Capture of repetitive non CW signals over large bandwidths Freq Time For more information see application note: Using Wider, Deeper Views of Elusive Signals to Characterize Complex Systems and Environments EN Page 28

29 Stepped Density Method Using Real-time Dwell over full span Full span of spectrum analyzer Page 29

30 Medium to low Spurs (<-75 dbc) New fast sweep vs. traditional sweep 500 MHz SDRAM ADC CLK FPGA FPGA ASIC Page 30

31 The Follow features available on Keysight X-Series Analyzer & new N9040B UXA Signal Analyzer Page 31 Agilent Confidential July 2014

32 Traditional Sweep non-continuous signals Limited by analog RBW rise time vs. accuracy needs Standard Analog Sweep Freq RBW Signals Sweep ST = POI = k (Span) RBW 2 (R+T) (R+R ) R = (RBW+S BW)*ST Span Time Page 32

33 Fast Sweep non-continuous signals Compensated RBW rise time with improved accuracy Modified k value UXA Fast Sweep Freq ST = k (Span) RBW 2 POI = (R+T) (R+R ) R = (RBW+S BW)*ST Span Time For more information see : EN-Using Fast-Sweep Techniques to Accelerate Spur Searches Page 33

34 Up to 50x faster vs. Traditional Sweep Fast Sweep Traditional Sweep Full 26.5 GHz span Full 26.5 GHz span For more information see : EN-Using Fast-Sweep Techniques to Accelerate Spur Searches Page 34 34

35 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 specifica- tions 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. For more information see : EN-Using Fast-Sweep Techniques to Accelerate Spur Searches Page 35

36 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 > 10 x Faster! Without Chirp Area where Chirp IF processing improves speed With Chirp FFT Swept Page Page 36

37 Fast Sweep Repeatability 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. 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. For more information see : EN-Using Fast-Sweep Techniques to Accelerate Spur Searches Page 37 37

38 Fast Sweep Benefits Summary 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. Note: Installed base Keysight (Agilent) X-Series spectrum analyzers can be upgraded with fast sweep. Page 38 38

39 Medium to Low Spurs (< -75 dbc) Stepped FFT FFT- Based Page 39

40 The following features available on the M9393A PXIe Performance Vector Signal Analyzer Page 40

41 Stepped spectrum analysis High-speed stepped FFTs to analyze wide spans 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. Single FFT up to max analysis BW (160 MHz) 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 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. Page 41

42 Digital Image Rejection Fast, accurate measurements without hardware pre-selector High & Low Side Mixing Smart Image rejection processing Minimum detect Method: For more information see application notes: EN - Achieving Excellent Spectrum Analysis Results Using Innovative Noise, Image and Spur-Suppression Techniques 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 maxhold, IF dithering and using narrow RBW to accurately measure even challenging signals Page 42

43 Digital image rejection Fast, accurate measurements without hardware pre-selector Benefits: Fast tuning speed Excellent amplitude accuracy Compact physical size 2 GHz LFM signal AWG 12 GHz clock AWG alias product 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: EN - Achieving Excellent Spectrum Analysis Results Using Innovative Noise, Image and Spur-Suppression Techniques Page 43

44 Power Spectrum mode for high-speed stepped FFT analysis Results Measure spurs & harmonics across khz RBW in < 1 second Achieve > 300 GHz/sec sweep speeds Page 44

45 Stitched FFT with Digital Image Rejection Summary 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 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 105 db dynamic range 1 GHz span Meas. time: 1 second Outstanding speed to dynamic range to see low-level signals quickly Leading to shorter test times & higher throughput in design validation & production Page 45

46 Low Spurs (< -100 dbc) How to improve the noise floor Pre-Amps Noise subtraction Page 46

47 Noise Floor Extensions/Corrections Subtracting the noise floor of the spectrum analyzer 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 Feature available on both X-Series & M9393A Software driven Real-time ASIC For more information see application notes: EN - Using Noise Floor Extension in the PXA Signal Analyzer EN - Achieving Excellent Spectrum Analysis Results Using Innovative Noise, Image and Spur-Suppression Techniques Page 47

48 USB Pre-Amps Pre-calibrated plug & play operation Page 48

49 U7227x USB Preamplifiers Pre-calibrated and ready to use with X-Series U7227x USB Preamps 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. Model U7227A U7227C U7227F Frequency Range 10 MHz to 4 GHz 100 MHz to 26.5 GHz 2 GHz to 50 GHz 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 Keysight USB Pre-amplifiers: EN: Page 49

50 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. Page 50

51 Where to learn more/references Spectrum Analyzer Basics, App Note 150, : Using Wider, Deeper Views of Elusive Signals to Characterize Complex Systems and Environments: Using Fast-Sweep Techniques to Accelerate Spur Searches, EN: 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: EN: Using Noise Floor Extension in the PXA Signal Analyzer: N9040B UXA X-Series Signal Analyzer: M9393A PXIe Performance Vector Signal Analyzer: Keysight USB Pre-amplifiers: EN: Spur Calculator from Marki Microwave: Technical Expert Bob Nelson: Page 51

52 Thank You! Page 52