Specifications

8
Types of measurements
Common spectrum analyzer measurements include frequency, power,
modulation, distortion, and noise. Understanding the spectral content of a
signal is important, especially in systems with limited bandwidth. Transmitted
power is another key measurement. Too little power may mean the signal
cannot reach its intended destination. Too much power may drain batteries
rapidly, create distortion, and cause excessively high operating temperatures.
Measuring the quality of the modulation is important for making sure a
system is working properly and that the information is being correctly
transmitted by the system. Tests such as modulation degree, sideband
amplitude, modulation quality, and occupied bandwidth are examples of
common analog modulation measurements. Digital modulation metrics
include error vector magnitude (EVM), IQ imbalance, phase error versus
time, and a variety of other measurements. For more information on these
measurements, see Application Note 150-15, Vector Signal Analysis Basics.
In communications, measuring distortion is critical for both the receiver
and transmitter. Excessive harmonic distortion at the output of a transmitter
can interfere with other communication bands. The pre-amplification stages
in a receiver must be free of intermodulation distortion to prevent signal
crosstalk. An example is the intermodulation of cable TV carriers as they
move down the trunk of the distribution system and distort other channels on
the same cable. Common distortion measurements include intermodulation,
harmonics, and spurious emissions.
Noise is often the signal you want to measure. Any active circuit or device
will generate excess noise. Tests such as noise figure and signal-to-noise ratio
(SNR) are important for characterizing the performance of a device and its
contribution to overall system performance.
Types of signal analyzers
While we shall concentrate on the swept-tuned, superheterodyne spectrum
analyzer in this note, there are several other signal analyzer architectures.
An important non-superheterodyne type is the Fourier analyzer, which
digitizes the time-domain signal and then uses digital signal processing (DSP)
techniques to perform a fast Fourier transform (FFT) and display the signal
in the frequency domain. One advantage of the FFT approach is its ability
to characterize single-shot phenomena. Another is that phase as well as
magnitude can be measured. However, Fourier analyzers do have some
limitations relative to the superheterodyne spectrum analyzer, particularly in
the areas of frequency range, sensitivity, and dynamic range. Fourier analyz-
ers are typically used in baseband signal analysis applications up to 40 MHz.
Vector signal analyzers (VSAs) also digitize the time domain signal like
Fourier analyzers, but extend the capabilities to the RF frequency range
using downconverters in front of the digitizer. For example, the Agilent 89600
Series VSA offers various models available up to 6 GHz. They offer fast,
high-resolution spectrum measurements, demodulation, and advanced
time-domain analysis. They are especially useful for characterizing complex
signals such as burst, transient or modulated signals used in communications,
video, broadcast, sonar, and ultrasound imaging applications.