ANEKA INFO TEKNIK: SPECTRUM ANALYZER; Detector types

Detector types
With digital displays, we had to decide what value should be displayed for each display data point. No matter how many data points we use across the display, each point must represent what has occurred over some frequency range and, although we usually do not think in terms of time when dealing with a spectrum analyzer, over some time interval.

Figure 2-17. When digitizing an analog signal, what value should be displayed at each point?

It is as if the data for each interval is thrown into a bucket and we apply whatever math is necessary to extract the desired bit of information from our input signal. This datum is put into memory and written to the display. This provides great flexibility. Here we will discuss six different detector types.
In Figure 2-18, each bucket contains data from a span and time frame that is determined by these equations:

Frequency: bucket width = span/ ( trace points -1)
Time: bucket width = sweep time/ ( trace points -1)

The sampling rates are different for various instruments, but greater accuracy is obtained from decreasing the span and/or increasing the sweep time since the number of samples per bucket will increase in either case. Even in analyzers with digital IFs, sample rates and interpolation behaviors are designed to be the equivalent of continuous-time processing.

Figure 2-18. Each of the 101 trace points (buckets) covers a 1 MHz frequency span and a 0.1 millisecond time span

The bucket concept is important, as it will help us differentiate the six detector types:

Sample

Positive peak (also simply called peak)

Negative peak

Normal

Average

Quasi-peak

The first 3 detectors, sample, peak, and negative peak are easily understood and visually represented in Figure 2-19. Normal, average, and quasi-peak are more complex and will be discussed later.

Figure 2-19. Trace point saved in memory is based on detector type algorithm

Let's return to the question of how to display an analog system as faithfully as possible using digital techniques. Let's imagine the situation illustrated in Figure 2-17. We have a display that contains only noise and a single CW signal.

Sample detection

As a first method, let us simply select the data point as the instantaneous level at the center of each bucket (see Figure 2-19). This is the sample detection mode. To give the trace a continuous look, we design a system that draws vectors between the points. Comparing Figure 2-17 with 2-20, it appears that we get a fairly reasonable display. Of course, the more points there are in the trace, the better the replication of the analog signal will be. The number of available display points can vary for different analyzers. On ESA and PSA Series

spectrum analyzers, the number of display points for frequency domain traces can be set from a minimum of 101 points to a maximum of 8192 points. As shown in figure 2-21, more points do indeed get us closer to the analog signal.

Figure 2-20. Sample display mode using ten points to display the signal of Figure 2-17

Figure 2-21. More points produce a display closer to an analog display

While the sample detection mode does a good job of indicating the randomness of noise, it is not a good mode for analyzing sinusoidal signals. If we were to look at a 100 MHz comb on an Agilent ESA E4407B, we might set it to span from 0 to 26.5 GHz. Even with 1, 001 display points, each display point represents a span (bucket) of 26.5 MHz. This is far wider than the maximum 5 MHz resolution bandwidth.

As a result, the true amplitude of a comb tooth is shown only if its mixing product happens to fall at the center of the IF when the sample is taken. Figure 2-22a shows a 5 GHz span with a 1 MHz bandwidth using sample detection. The comb teeth should be relatively equal in amplitude as shown in Figure 2-22b (using peak detection). Therefore, sample detection does not catch all the signals, nor does it necessarily reflect the true peak values of the

displayed signals. When resolution bandwidth is narrower than the sample interval (i. e., the bucket width), the sample mode can give erroneous results.