Tracking down interference in complex RF environments

May 03, 2013 //By Dave Murray
Tracking down interference in complex RF environments
Dave Murray of Agilent Technologies examines how the gapless capture RF recording technique can be used to track down interference in complex RF environments.

Radio frequency interference occurs in everything from commercial wireless networks and devices to military communications, radar and electronic warfare (EW) systems. Addressing this problem can be especially difficult since measuring interference is unpredictable. Additionally, the intermittent failure modes in typical signal analyzers make data capture particularly challenging. Consequently, when the root cause of a problem is not yet known, it can be difficult for engineers to set up a measurement that captures the failure.

Despite the challenge, the task of finding, identifying and analyzing interfering signals in a crowded spectrum—whether intentional or not—has become increasingly important in a wide array of applications. One RF recording technique that may prove particularly useful in addressing this problem is gapless capture. Using this technique, system engineers can now measure data continuously over long durations and ensure the capture of all RF events when they occur.

Understanding the measurement challenge

When characterizing system interference, system engineers have traditionally relied on a signal analyzer performing continuous long-duration recordings, as shown in Figure 1 . The main limitation to long-duration recording is that test equipment typically has limited on-board memory. Signals-of-interest enter the analyzer’s RF input and are processed by subsequent stages, resulting in the displayed waveform on the right of Figure 1 . Up to the blue vertical line, all signals-of-interest within the instrument’s capture bandwidth are processed in real-time, assuming a fixed local oscillator. However, once the samples fill the memory buffer or RAM, the instrument no longer looks at incoming digital samples. Instead, it must process previously recorded samples.


Figure 1: Shown here is a block diagram of a typical signal analyzer
Click on image to enlarge


The signal analyzer does not capture any samples while it post-processes previously captured data, effectively creating a gap in its continuous acquisition of data. If events occur while the previous event is being processed or if the new event lasts longer than the available memory, it

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