Massively broadband® RF channel sounding is severely constrained by the sampling rates required for analog to digital conversion. Analog compressed sensing (CS) techniques based on Xampling have demonstrated the ability to lower sampling rates far below the Nyquist rate. Here, we show attributes of the multipath channel sounding problem appear to be well suited to CS approaches for reducing measurement acquisition time while simultaneously estimating time delays, multipath amplitudes, and angles of arrival. This paper presents results of the fusion of CS with modern channel sounding. We show measured propagation data from 60 GHz field trials and note the channel sparsity in time and space. We then propose an architecture for the first massively broadband CS channel sounder based on the Xampling framework (which we call the Channel Sounding Xampler) to exploit the sparsity, and we use field measurements to explore tradeoffs between analog and digital signal processing to perform channel impulse response (CIR) parameter estimation in real time. We also offer conceptual approaches for the Channel Sounding Xampler designed to trade off analog and digital components with the goal of improving CIR acquisition at sub-THz frequencies.