Vehicle Tracking Through the Exploitation of Remote Sensing and LWIR Polarization Science

Vehicle tracking is an integral component in layered sensing exploitation applications. The utilization of a combination of sensing modalities and processing techniques provides better insight about a situation than can be achieved with a single sensing modality. In this work, several robust features are explored for vehicle tracking using data captured in a remote sensing setting. Particularly, a video sequence is evaluated in the layered sensing framework. The target area is surveyed by two sensors operating across two different modalities: a LWIR polarized sensor and a LWIR sensor. We here extend our previous work ([1]) to experimental analysis on several feature sets including three classic features (Stokes images, DoLP, the Degree of Linear Polarization, and AoP, the Angle of Polarization) and two experimental features (ρ, an extension of the DoLP, and δ, the phase difference between two orthogonal projections of an observed electromagnetic wave).