For NI VSAs and VSTs, the resolution bandwidth (RBW) determines the fast-Fourier transform (FFT) bin size, or the smallest frequency that can be resolved.

The following graphs represent the same signal with varying RBW.



The smaller RBW, on the right, has much finer resolution which allows the sidebands to be visible. Finer resolution requires a longer acquisition time. When acquisition time is a factor and the display needs to be updated rapidly or when the modulation bandwidth is wide, you can use a larger RBW. RBW and acquisition time are inversely proportional.

The following table shows the advantages and disadvantages of both larger and smaller RBWs:

Characteristic Larger RBW Smaller RBW
FFT size Smaller Larger
Number of samples Fewer More
Measurement speed Faster Slower
Ability to resolve tones Often unable to resolve two closely spaced tones in a spectrum Tones are easily resolved

In FFT-based (digital) spectrum analyzers and vector signal analyzers, RBW is inversely proportional to the number of samples acquired. By taking more samples in the time domain, or making the acquisition time longer while keeping the sampling rate the same, the RBW is lowered. The result is more bins in the same span and improved frequency resolution.

The FFT process is equivalent to passing a time-domain signal through a bank of bandpass filters with center frequencies corresponding to the frequencies of the FFT bins. For wide sweeps, a wide RBW is required to shorten acquisition times. For narrow sweeps, a narrow filter improves frequency resolution.

Carefully consider which FFT window type to use. As an example, a Flat Top window minimizes amplitude measurement error and is recommended for amplitude measurements even though it has non-optimal selectivity.