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Technology Polarimetric Imaging For Target And Threat Identification Technological and theoretical advancements have polarimetric imaging poised to serve on battlefields in target and threat identification applications. By Israel Vaughn M any attempts have been made to utilize polari- metric imaging and polarimetric measurements for target and threat identification (TTI) over the past 20 years. Polarimetric imaging is intrinsically promising to fill voids in current TTI schemes: The underly- ing phenomenology and imaging physics can yield improve- ments in target classification tasks that cannot be easily real- ized by other modalities, such as hyperspectral. The specific advantages of polarimetric imaging for a TTI context will be summarized here. We also will address some of the issues with polarimetric imaging, which include instrument complexity, computation- al limitations, lack of statistically robust polarimetric datasets, lack of generalization of contrast improvements from the lab to the field, and measurement bandwidth/speed limitations of polarimetric instruments. Advancements in the field of polarimetric instrumentation, made by our group and others, have reduced some of the risks of utilizing polarimetry for TTI. Although many of the insights about using polarimetric measurements for TTI or classification purposes began in the polarimetric SAR (synthetic aperture radar) community, we will focus here on imaging polarimetry in the optical wave- length regime. Figure 1 shows a schematic representative both of polariza- tion and of what we measure with polarimetric instruments. Specifically, we measure the time average of the polarization ellipse, corresponding to the red ellipse. Or, if we control the polarization properties of the source, we can infer how an object changes the polarization properties of the light, which is characterized by a four-by-four matrix denoted as the Mueller matrix. For polarimetric measurements, we specify four numbers representing the polarization information and call them the Stokes parameters, shown in Figure 2. In Figure 2 i , s 0 represents the total irradiance; s 1 represents the prevalence of horizontal linear polarization over verti- cal linear polarization; s 2 represents the prevalence of linear polarization oriented at 45˚ over linear polarization oriented at -45˚; and s 3 represents the prevalence of right circular polarization over left circular polarization. A Mueller matrix represents a linear transformation of these four Stokes param- eters, and therefore is a four-by-four matrix. Generally, there are two major types of optical polarimetric imaging: passive and active. Passive imaging measures the polarization of light reflected by objects illuminated with a source that we cannot control, such as the sun, measuring only Stokes parameters. In active imaging, we control the polarization properties of the source (Stokes parameters) illuminating our scene and measure the Mueller matrix of the object. The current state-of-the-art in the field attempts to use active imaging polarimeters for TTI tasks since the possible classification space is larger and more specific. Figure 3 shows a portable, state-of-the-art active polari- metric imager built by our lab — the Advanced Sensing Laboratory — for general remote sensing tasks. Electronic Military & Defense Annual Resource, 5th Edition 8 Figure 1: Electromagnetic radiation can be conceptualized as a wave traveling in some direction, with components in the planes perpendicular to that propa- gation direction. The plane components define the polarization. Figure 2: Stokes parameter and Mueller matrix definitions. The Mueller matrix can be a function of some vector, x, representing the modulation domain. Figure 3: Portable Mueller matrix remote sensing polarimeter.