Common remote-sensing techniques of analyzing received radio frequency (RF) signals, such as amplitude envelope detection and frequency Doppler shift, may work fine when the transmitted RF signal is precisely known and available. But, some remote-sensing applications may not permit such control over the RF transmission. Another technique, RF polarization, offers satisfactory results in some of those situations-when multipath and/or bandwidth-delay spread can be kept low. However, a new technique leveraging the polarization mode dispersion (PMD) inherent in most RF channels promises better results (accuracy, precision, and sensitivity) for most remote-sensing applications. The PMD technique adds a frequency-subband dimension to the analysis that the other methods overlook. This paper will present the data analysis techniques for several methods of RF signal processing aimed at the general remote-sensing application of vibrometry (the measurement of vibrations). Using model simulations calibrated to laboratory results, the PMD-based approach is shown to out-perform more common techniques by one or more orders of magnitude for typical indoor environments. Such performance gains (up to 30 dB on average) could allow for the successful detection of a vibrator or target within an RF field simply by adopting these PMD-based data analysis techniques on the received RF signals.