Average detection
Although modern digital modulation schemes have noise-like characteristics, sample detection does not always provide us with the information we need. For instance, when taking a channel power measurement on a W-CDMA signal, integration of the rms values is required. This measurement involves summing power across a range of analyzer frequency buckets. Sample detection does not provide this.
While spectrum analyzers typically collect amplitude data many times in each bucket, sample detection keeps only one of those values and throws away the rest. On the other hand, an averaging detector uses all the data values collected within the time (and frequency) interval of a bucket. Once we have digitized the data, and knowing the circumstances under which
they were digitized, we can manipulate the data in a variety of ways to achieve the desired results.
Some spectrum analyzers refer to the averaging detector as an rms detector when it averages power (based on the root mean square of voltage). Agilent PSA and ESA Series analyzers have an average detector that can average the power, voltage, or log of the signal by including a separate control to select the averaging type:
Power (rms) averaging averages rms levels, by taking the square root of the sum of the squares of the voltage data measured during the bucket interval, divided by the characteristic input impedance of the spectrum analyzer, normally 50 ohms. Power averaging calculates the true average power, and is best for measuring the power of complex signals.
Voltage averaging averages the linear voltage data of the envelope signal measured during the bucket interval. It is often used in EMI testing for measuring narrowband signals (this will be discussed further in the next section). Voltage averaging is also useful for observing rise and fall behavior of AM or pulse-modulated signals such as radar and TDMA transmitters.
Log-power (video) averaging averages the logarithmic amplitude values (dB) of the envelope signal measured during the bucket interval. Log power averaging is best for observing sinusoidal signals, especially those near noise. 11
Thus, using the average detector with the averaging type set to power provides true average power based upon rms voltage, while the average detector with the averaging type set to voltage acts as a general-purpose average detector. The average detector with the averaging type set to log has no other equivalent. Average detection is an improvement over using sample detection for the determination of power. Sample detection requires multiple sweeps to collect enough data points to give us accurate average power information. Average detection changes channel power measurements from being a summation over a range of buckets into integration over the time interval representing a range of frequencies in a swept analyzer. In a fast Fourier transfer (FFT) analyzer 12 , the summation used for channel power measurements changes from being a summation over display buckets to being a summation over FFT bins. In both swept and FFT cases, the integration captures all the power
information available, rather than just that which is sampled by the sample detector. As a result, the average detector has a lower variance result for the same measurement time. In swept analysis, it also allows the convenience of reducing variance simply by extending the sweep time.
11. See Chapter 5, Sensitivity and Noise.
12. Refer to Chapter 3 for more information on the FFT analyzers. They perform math computations on many buckets simultaneously, which improves the measurement speed.
EMI detectors: average and quasi-peak detection
An important application of average detection is for characterizing devices for electromagnetic interference (EMI). In this case, voltage averaging, as described in the previous section, is used for measurement of narrowband signals that might be masked by the presence of broadband impulsive noise. The average detection used in EMI instruments takes an envelope-detected signal and passes it through a low-pass filter with a bandwidth much less than the RBW. The filter integrates (averages) the higher frequency components
such as noise. To perform this type of detection in an older spectrum analyzer that doesn't have a built-in voltage averaging detector function, set the analyzer in linear mode and select a video filter with a cut-off frequency below the lowest PRF of the measured signal.
Quasi-peak detectors (QPD) are also used in EMI testing. QPD is a weighted form of peak detection. The measured value of the QPD drops as the repetition rat of the measured signal decreases. Thus, an impulsive signal with a given peak amplitude and a 10 Hz pulse repetition rate will have a lower quasi-peak value than a signal with the same peak amplitude but having a 1 kHz repetition rate. This signal weighting is accomplished by circuitry with specific charge, discharge, and display time constants defined by CISPR 13 .
QPD is a way of measuring and quantifying the annoyance factor of a signal. Imagine listening to a radio station suffering from int rference. If you hear an occasional pop caused by noise once very f w seconds, you can still listen to the program without too much trouble. How ver, if that same amplitude pop occurs 60 times per second, it becomes extremely annoying, making the radio program intolerable to listen to.
Averaging processes
There are several processes in a spectrum analyzer that smooth the variations in the envelope-detected amplitude. The first method, average detection, was discussed previously. Two other methods, video filtering and trace averaging, are discussed next. 14
13. CISPR, the International Special Committee on Radio Interference, was established in 1934 by a group of international organizations to address radio interference. CISPR is a non-governmental group composed of National Committees of the International Electrotechnical Commission (IEC), as well as numerous international organizations. CISPR's recommended standards generally form the basis for statutory EMC requirements adopted by governmental regulatory agencies around the world.
14. A fourth method, called a noise marker, is discussed in Chapter 5, Sensitivity and Noise.
A more detailed discussion can be found in Application Note 1303, Spectrum Analyzer
Measurements and Noise, literature number 5966-4008E.
Video filtering
Discerning signals close to the noise is not just a problem when performing EMC tests. Spectrum analyzers display signals plus their own internal noise, as shown in Figure 2-27. To reduce the effect of noise on the displayed signal amplitude, we often smooth or average the display, as shown in Figure 2-28. Spectrum analyzers include a variable video filter for this purpose. The video filter is a low-pass filter that comes after the envelope detector and
determines the bandwidth of the video signal that will later be digitized to yield amplitude data. The cutoff frequency of the video filter can be reduced to the point where it becomes smaller than the bandwidth of the selected resolution bandwidth (IF) filter. When this occurs, the video system can no longer follow the more rapid variations of the envelope of the signal(s) passing through the IF chain. The result is an averaging or smoothing of the displayed signal.
Figure 2-27. Spectrum analyzers display signal plus noise
Figure 2-28. Display of figure 2-27 after full smoothing
The effect is most noticeable in measuring noise, particularly when a wide resolution bandwidth is used. As we reduce the video bandwidth, the peak-to-peak variations of the noise are reduced. As Figure 2-29 shows, the degree of reduction (degree of averaging or moothing) is a function of the ratio of the video to resolution bandwidths. At ratios of 0.01 or less, the smoothing is very good. At higher ratios, the smoothing is not so good. The video filter does not affect any part of the trace that is already smooth (for example, a sinusoid displayed well out of the noise) .
Figure 2-29. Smoothing effect of VBW-to-RBW ratios of 3: 1, 1: 10, and 1: 100
If we set the analyzer to positive peak detection mode, we notice two things: First, if VBW > RBW, then changing the resolution bandwidth does not make much difference in the peak-to-peak fluctuations of the noise. Second, if VBW < RBW, then changing the video bandwidth seems to affect the noise level. The fluctuations do not change much because the analyzer is displaying only the peak values of the noise. However, the noise level appears to change
with video bandwidth because the averaging (smoothing) changes, thereby changing the peak values of the smoothed noise envelope. See Figure 2-30a. When we select average detection, we see the average noise level remains constant. See Figure 2-30b.
Because the video filter has its own response time, the sweep time increases approximately inversely with video bandwidth when the VBW is less than the resolution bandwidth. The sweep time can therefore be described by this equation:
The analyzer sets the sweep time automatically to account for video bandwidth as well as span and resolution bandwidth.
Figure 2-30a. Positive peak detection mode; reducing video bandwidth lowers peak noise but not average noise
Figure 2-30b. Average detection mode; noise level remains constant, regardless of VBW-to-RBW ratios ( 3: 1, 1: 10, and 1: 100)
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