  When using valid foreground and signal models, the uncertainties on extracted
signals in global 21-cm signal experiments depend principally on the overlap
between signal and foreground models. In this paper, we investigate two
strategies for decreasing this overlap: (i) utilizing time dependence by
fitting multiple drift-scan spectra simultaneously and (ii) measuring all four
Stokes parameters instead of only the total power, Stokes I. Although measuring
polarization requires different instruments than are used in most existing
experiments, all existing experiments can utilize drift-scan measurements
merely by averaging their data differently. In order to evaluate the increase
in constraining power from using these two techniques, we define a method for
connecting Root-Mean-Square (RMS) uncertainties to probabilistic confidence
levels. Employing simulations, we find that fitting only one total power
spectrum leads to RMS uncertainties at the few K level, while fitting multiple
time-binned, drift-scan spectra yields uncertainties at the $\lesssim 10$ mK
level. This significant improvement only appears if the spectra are modeled
with one set of basis vectors, instead of using multiple sets of basis vectors
that independently model each spectrum. Assuming that they are simulated
accurately, measuring all four Stokes parameters also leads to lower
uncertainties. These two strategies can be employed simultaneously and fitting
multiple time bins of all four Stokes parameters yields the best precision
measurements of the 21-cm signal, approaching the noise level in the data.
