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[Test & Measurement]
Avoid Large Amplitude Errors In Spectrum Analysis
Incorporation of a noise source in a line of modern spectrum analyzers aids tuning of the analyzers’ front-end preselector filter and improves amplitude accuracy for all input signals.

Joe Gorin  |  ED Online ID #14639 |  January 2007

Modern spectrum analyzers have improved dramatically in recent years in terms of low-frequency analog precision and a tremendous boost from digital-signal-processing (DSP) components, especially in the front-end intermediate-frequency (IF) filters. While spectrum analyzers can provide even better accuracy at RF, their accuracy at microwave frequencies has not generally been improving. Because of the demanding applications for modern spectrum analyzers, including analysis of signals with advanced wideband digital modulation formats, higher accuracy is difficult to realize with even the best spectrum-analyzer designs. Fortunately, a combination of careful hardware design and clever measurement algorithms has been incorporated in the new MXA signal-analyzer platform from Agilent Technologies (www.agilent.com) to help users maintain the best accuracy without requiring a specific kind of input signal or external test signal.

Microwave spectrum analyzers employ tunable preselector filters to improve performance by removing unwanted mixer images and responses to local-oscillator (LO) harmonics. Unfortunately, these preselectors have instabilities and must be retuned frequently, and proper preselector tuning traditionally has required a signal of nearCW statistical distribution at the frequency of interest. In the new MXA signal analyzers, an integral noise source is used as a tuning signal for the preselector filter, helping to ensure filter accuracy as part of an automatic routine in the instruments.

Modern spectrum analyzers operating to 26.5 GHz have a "low band" and a "high band" signal path, as shown in the simplified block diagram (Fig. 1). The low band typically operates to 3 GHz or higher. In the low band, the signal is frequency upconverted to a high IF near 4 GHz or more, then downconverted to a lower IF near 300 MHz. This double-conversion scheme can dramatically reduce mixer image responses.

"High-band" frequency ranges cannot practically be built with the same block diagram as low-band ranges because the first IF amplifier would have to work at a frequency where the amplifier noise and distortion would inevitably be unsatisfactorily high for operators. The alternative block diagram involves a single-conversion step to the IF shown in Fig. 1. In this block diagram, image responses in the first mixer are spaced by only twice the IF, or about 600 MHz. Such images are unacceptable in a general-purpose spectrum analyzer. Thus, the tunable preselector filter (a bandpass filter) is used to remove the images.

To achieve the rejection and tuning bandwidth required at microwave frequencies, the preselector filter is based on yttrium-iron-garnet (YIG) technology. The action of YIG spheres controlled within a precise magnetic field creates the filter passband resonances needed to remove unwanted images and responses from the spectrum analyzer's signal path.

YIG preselectors usually have a passband width of about 40 to 80 MHz that can be tuned across a wide range of microwave frequencies. When used at frequencies up to 26.5 GHz, the required quality factors (Qs) of the resonators are very high, resulting in sharp cutoff frequencies but also accompanied by amplitude and frequency instabilities.

Post-tuning drift is one form of instability in a YIG-tuned bandpass filter. The magnet used to tune the resonant frequency of the YIG spheres heats up or cools down as the selected frequency is changed. The temperature change of the magnet affects the dimensions of the magnet and the magnetic field strength, and thus the frequency of the filter tuning. Mechanical aging of the magnet/sphere structure works in the same way to cause further instabilities.

Also, the relationship between the tuning current and the filter center frequency is not perfectly modeled by any simple algebraic function. Therefore, even without tuning instabilities, there are tuning errors. The result is that frequency tuning errors lead to amplitude errors (Fig. 2).

Figure 2a shows a typical YIG filter response. The x-axis represents frequency, but because the frequency of a YIG filter is nearly proportional to tuning current, the x-axis can also be thought of as YIG filter tuning current. In this example, small tuning current errors map to amplitude errors proportional to the slope of the passband shape at the operating point. The design operating point is the midpoint between the –4-dB response points, because this design is highly robust regarding tuning errors.

A YIG filter can be adjusted by means of measurements with a modern spectrum analyzer. A user can adjust operating current directly, or execute a "preselector center" operation. Because the spectrum-analyzer amplitude response was factory calibrated under the condition of centering the preselector tuning, centering is the preferred operation. Note that peaking the preselector would result in poorer amplitude accuracy.

Figure 2b shows the importance of YIG filter centering. Point A shows the plot used for factory calibration of the YIG filter's frequency response. This point is on the response curve of a new analyzer at room temperature. Its horizontal location is at the midpoint between the –4 dB (relative to peak) response frequencies.

Point B is on a congruent curve, displaced vertically to indicate the expected total system response changes when the ambient temperature is changed. The influences of post-tuning drift and aging, in addition to ambient temperature changes, could result in the curve with point F on it. In this case, the amplitude error can be quite large. This error is indicated as length E, which is the difference between the response points B and F.


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