Amplitude accuracy is a key barometer of spectrum-analyzer performance. Simply put, amplitude accuracy instills confidence in a measurement. In an extreme case, poor amplitude accuracy can lead to shipping a component that did not meet a customer’s requirements, and failing a production-line component that performed properly. Understanding how spectrum-analyzer amplitude accuracy is determined and the factors that affect it can help guide the selection process when it is time to choose an RF/microwave spectrum analyzer.

A swept-tuned superheterodyne spectrum analyzer (Fig. 1) mixes input signals with a local oscillator (LO) with signal amplification, filtering, and detection performed at intermediate frequencies (IFs). The preselector filter (sometimes a lowpass filter) prevents high-frequency signals from reaching the mixer and mixing with the LO. The reference level shown on the spectrum analyzer's display is adjusted by the level of gain in the IF amplifier. This amplifier adjusts the vertical position of signals on the screen without affecting the signal level at the input attenuator. The horizontal scale is in frequency; vertical scale is calibrated amplitude, either linear (in volts) or logarithmic (in dB).

Spectrum-analyzer amplitude accuracy is specified in terms of absolute and relative accuracy. Absolute amplitude is the actual power level of a signal, in units of dBm. Relative amplitude, in dB, is the difference between two signal levels, using one as a reference for the other. An example of a relative measurement is a check of harmonic signal level, where the amplitude of the harmonic is measured relative to the amplitude of the fundamental frequency signal. Both absolute and relative amplitude measurement accuracy is improved in a spectrum analyzer by measuring a calibration source with precisely known amplitude and frequency.

In a spectrum analyzer, the front-end signal-processing components are sources of amplitude errors, including the amplifiers, filters, mixers, and LO. In some designs, improved components can reduce the measurement uncertainties associated with some of these components. The PSA Series of high-performance spectrum analyzers

(Fig. 2) from Agilent Technologies, for example, incorporates a full set of digital IF filters to minimize the amplitude variations inherent to analog IF filters. But simply improving some of the components in the signal-processing chain does not eliminate all of the error sources; better understanding how the various components in the spectrum-analyzer block diagram interact makes it possible to minimize amplitude errors and optimize amplitude measurement accuracy.

Why is amplitude measurement accuracy important? For an absolute measurement, for example, some communications standards require the use of modulated carrier signals not to exceed established power levels. For relative measurements, excessive harmonic and spurious signal levels from one communication system can cause interference with other systems. Amplifiers designed for these systems must be tested to determine that they meet linearity requirements and do not contribute to higher levels of harmonics and spurious signals. Filters for these systems must likewise be tested for passband and rejection performance.

The way that a spectrum analyzer's components work together contributes to different sources of error. Although not a complete list, Table 1 summarizes many major sources of amplitude measurement accuracy in a spectrum analyzer. Most manufacturers publish specifications for both absolute and relative measurement uncertainties. Since relative uncertainties affect the accuracy of both relative and absolute measurements, they will be the main focus of this White Paper.

One of the major factors of amplitude measurement uncertainty is the analyzer's frequency response or flatness. This is the relative amplitude uncertainty as a function of frequency over a specified frequency range. It is a function of input attenuator flatness, mixer conversion loss, LO amplitude variations, and input-signal filtering. Frequency-response uncertainty is usually specified for both absolute and relative measurements. The relative uncertainty describes the largest possible amplitude uncertainty over a frequency range relative to the midpoint of that band. It tends to be lower than the absolute specification for the same band. But to obtain the frequency-response uncertainty for relative amplitude measurements within a band, the relative frequency response specification must be doubled to reflect the peak-to-peak frequency response, which is often greater than the absolute frequency-response specification.

The preselector filter, usually a YIG-tuned filter, also contributes to the analyzer's frequency response. The filter must be precisely tuned and aligned in frequency to avoid additional frequency-response variations, and limited to the sweep rate of the LO plus whatever tuning delays and tuning compensation are needed for the YIG filter to keep it aligned in frequency relative to the LO. The front end of a spectrum analyzer usually also employs a lowpass filter to eliminate higher-frequency content from signals falling below the lower limit of the YIG preselector filter (typically about 2 GHz). Although this filter also contributes to the overall frequency response of the analyzer,it tends to suffer less amplitude error than the YIG filter.

Because a spectrum analyzer relies on mixing input signals with harmonics from the LO, the instrument operates in a variety of different frequency bands. Each of these bands has a specified frequency response, and amplitude measurement uncertainties result when switching between bands. A 26.5-GHz (E4440A) PSA spectrum analyzer, for example, operates in five internal mixing bands: 3 Hz to 3 GHz, 2.85 to 6.6 GHz, 6.2 to 13.2 GHz, 12.8 to 19.2 GHz, and 18.7 to 26.5 GHz. Whenever a measured frequency span crosses two or more of these internal mixing bands, and band switching occurs, some amplitude measurement uncertainty will result. When comparing signals in different bands, the frequency response is the sum of the responses of the two bands, along with any band-switching uncertainty. If band-switching uncertainty is not specified, the absolute frequency response relative to the calibration source (instead of the relative frequency-response uncertainty) can be used for each band (Table 1).

Scale fidelity is another source of amplitude measurement uncertainty in a spectrum analyzer. It applies when a signal at one vertical position in measured with respect to a second signal at a different vertical position. Scale fidelity depends upon the detector's linearity, the linearity of the analyzer's analog-to-digital-converter (ADC) circuitry, and the capabilities of the logarithmic/linear and vertical amplifiers to transform different signal voltages into their appropriate relative power (log) or voltage (linear) levels on the display. For most logarithmic amplifiers, log linearity degrades at decreasing signal levels.

For logarithmic (in dB) spectrum-analyzer measurements, scale fidelity is better for small amplitude differences between signals. It can be a few tenths of a dB for signals that are close in amplitude to 2 dB for signals with large differences in amplitude. A typical scale fidelity specification is ±0.4 dB/4 dB to a maximum of ±1.0 dB. The ±0.4 dB/4 dB specification is applied when the two signals are close in amplitude; the cumulative specification applies to signals having larger differences in amplitude.