Link to Document

Identifying frequency stability problems within a phase-locked loop (PLL) design can be greatly simplified when using an automated method. When an oscilloscope detects the period of a waveform cycle, this value can be directly inverted to compute the instantaneous frequency of the specific waveform cycle. Using all-instance measurements, instead of considering only the value of one cycle within the acquired waveform, the series of instantaneous frequencies of each cycle within an acquired input waveform can be computed as an array. With a tolerance band applied to instantaneous frequencies, the array of continuous instantaneous frequencies can be scanned by the oscilloscope to detect anomalous frequency content on a per-cycle basis. The waveform-scanning technique incorporates this new approach and can report frequency anomalies graphically and numerically to identify all switching cycles that are outside of frequency stability margins requirements.

Article Tools

• 

As shown in Figure 1, the output of a 66 MHz PLL has been acquired, with 1,319 measurements of instantaneous frequency on this single acquisition shown in the distribution of measurement parameter P1. The scanning filter limit is set to detect any frequencies greater than 66.7 MHz. Triggering action of the resultant scan of frequency is set to stop the acquisition when the frequency stability margin is exceeded. The oscilloscope has displayed a red box encompassing each waveform cycle in the upper grid that violates the defined scan tolerance band, and 16 cycles from the PLL output have met this criteria. Each frequency anomaly is listed in a tabular index in the upper-left edge of the display, and these correspond to the red areas highlighted in the PLL output waveform trace. Clicking on any of the index numbers will highlight that specific frequency violation in bright yellow. In addition, the Z1 zoom trace corresponds to the selected frequency anomaly.

The PLL has lost its lock, and in the lower grid the frequency deviation that has taken place can be seen (as well as an amplitude distortion on the subsequent cycle) as this is starting to occur.

Figure 2 shows the dynamic response of a 10 MHz PLL. The red waveform is a mathematical track waveform that has plotted frequency as a function of time. Overlaid onto the acquired blue PLL waveform, the track shows frequency characteristics of the phase-locked loop in the time domain. Because the Y-axis is frequency, we can apply measurement parameters of top and base to the track to obtain the starting frequency, ending frequency, and frequency difference that occurred during the 2,000-cycle waveform acquisition. In addition, because the track is displaying frequency (and not voltage) as a function of time, the transition time required for the PLL to switch frequencies from 9.92 MHz to 10.07 MHz can be measured using a rise time para-meter, which in this case, revealed a switching time of 3.7 microseconds. The amplitude parameter, when applied to the frequency track, shows a 151 kHz frequency difference between the starting and ending frequencies of the PLL transition. In addition to quantitative analysis using measurement parameters, the overall shape can be used to visually characterize the PLL dynamic response.

Waveform scanning is now able to monitor the rise time of the track (which in the frequency-vs.-time domain is the PLL transition time) to ensure that the PLL transitions between frequencies within the required time window. This technique can be applied to continuously acquired input waveforms for monitoring and compliance testing.

Waveform scanning makes debugging a PLL fast and efficient. Automatic scans can monitor for PLL transition time, drifts in frequency, duty cycle distortion, runts, non-monotonic edges, intermittent events, and many other phenomena. When operating on a deep acquisition record with a large number of events, the tool quickly locates and identifies anomalies. When operating on multiple acquisitions, the tool continuously scans and executes actions based on user-defined criteria. When a PLL design challenge is described in terms of a timing measurement, then waveform-scanning techniques rapidly find anomalous conditions. Measurement filtering methods are available to further narrow the search criteria. The ability to view histogrammed and overlaid measurement and data values provides further analysis of the anomalies identified by the scan. These techniques can also be adapted for monitoring and troubleshooting virtually any PLL timing behavior and identify anomalies as they occur.

ABOUT THE AUTHOR

Mike Hertz is a field applications engineer with LeCroy Corp. in Michigan. Before joining LeCroy, he was an applications engineer with Agilent Technologies. He has three U.S. patents pending in the area of oscilloscope measurement design. Hertz received a BSEE from Iowa State University and an MSEE from the University of Arizona.