Normal Detection Algorithm

The normal detection algorithm:

If the signal rises and falls within a bucket:
Even numbered buckets display the minimum (negative peak)
value in the bucket. The maximum is remembered.
Odd numbered buckets display the maximum (positive peak)
value determined by comparing the current bucket peak with
the previous (remembered) bucket peak.
If the signal only rises or only falls within a bucket, the peak
is displayed. See Figure 2-25.

This process may cause a maximum value to be displayed one data point too
far to the right, but the offset is usually only a small percentage of the span.
Some spectrum analyzers, such as the Agilent PSA Series, compensate for
this potential effect by moving the LO start and stop frequencies.

Another type of error is where two peaks are displayed when only one
actually exists. Figure 2-26 shows what might happen in such a case. The
outline of the two peaks is displayed using peak detection with a wider RBW.

So peak detection is best for locating CW signals well out of the noise. Sample
is best for looking at noise, and normal is best for viewing signals and noise.

Figure 2-25. Trace points selected by the normal detection algorithm

Figure 2-26. Normal detection shows two peaks when actually only one
peak exists