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When using valid foreground and signal models, the uncertainties on extractedsignals in global 21-cm signal experiments depend principally on the overlapbetween signal and foreground models. In this paper, we investigate twostrategies for decreasing this overlap: (i) utilizing time dependence byfitting multiple drift-scan spectra simultaneously and (ii) measuring all fourStokes parameters instead of only the total power, Stokes I. Although measuringpolarization requires different instruments than are used in most existingexperiments, all existing experiments can utilize drift-scan measurementsmerely by averaging their data differently. In order to evaluate the increasein constraining power from using these two techniques, we define a method forconnecting Root-Mean-Square (RMS) uncertainties to probabilistic confidencelevels. Employing simulations, we find that fitting only one total powerspectrum leads to RMS uncertainties at the few K level, while fitting multipletime-binned, drift-scan spectra yields uncertainties at the $\lesssim 10$ mKlevel. This significant improvement only appears if the spectra are modeledwith one set of basis vectors, instead of using multiple sets of basis vectorsthat independently model each spectrum. Assuming that they are simulatedaccurately, measuring all four Stokes parameters also leads to loweruncertainties. These two strategies can be employed simultaneously and fittingmultiple time bins of all four Stokes parameters yields the best precisionmeasurements of the 21-cm signal, approaching the noise level in the data.

Global 21-cm signal extraction from foreground and instrumental effects III: Utilizing drift-scan time dependence and full Stokes measurements