Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, in which typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate CFAR detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetic X-band radar assembled largely from COTS components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established MIMO radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering PCL, a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation.