With a Dirac's pulse you should get a continuous spectra.. 
One disadvantage of a continuous spectrum stimulus is that the detector cannot benefit from processing gain. IOW, as the detector bandwidth is reduced, the SNR does not increase accordingly, because with decreasing bandwidth, the detector captures less noise, but also less of a useful wide-band signal

OTOH, if useful signal is concentrated in a single frequency, the detector still captures the full power of the useful signal when the detector's bandwidth is reduced, but it captures less noise, therefore increasing SNR.
And the crest factor of a Dirac delta impulse is, of course, horrible (in fact, it is infinite). For a given peak-to-peak amplitude (which is limited by the ADC), the crest factor determines the power of the signal (high crest factor implies low power), and a low-power signal has a low SNR wrt. to a given noise power.
Try to generate random square noise and do N averagings of the spectra, what it does..
PRBS has at least a low crest factor. But its spectrum is still noisy, i.e. there will exist random frequencies in the spectrum with low stimulus power and therefore low SNR.
If you want to do vector averaging, you can only average the complex gain Vout(f) / Vin(f), which has the same expected value in each acquisition. But if you want to average multiple acquisitions of Vin(f) or Vout(f), you can only do power averaging, i.e. you don't get phase information.