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Passive millimeter wave (PMMW) imaging systems have many important applications, both military and commercial. However, due to the longer wavelength, resolution is limited when compared with shorter wavelength imaging systems of comparable aperture size. One approach to this problem is super resolution. Over sampling in the focal plane supports super resolution techniques that utilize maximum likelihood and constrained least squares methods, while preserving the field of view. In order to test super resolution algorithms with real image data, a versatile PMMW test bed constructed for the Air Force Smart Tactical Autonomous Guidance (STAG) program was utilized to obtain 16x over sampled images of three test targets. First, a Gunn diode oscillator (GDO) source was imaged in order to accurately measure the point spread function (PSF) of the imaging system. A special source pattern was then imaged to measure the system's response to differently oriented step functions, and to determine the system time constant. An M48 tank was then imaged as an example of a real world military target. In each case the experimental images were obtained by mechanically scanning a single TRF receiver module in a two-dimensional raster pattern in the focal plane of a 94 GHz, f/i, two element, refractive, telecentric imaging system. Imagery was obtained at horizontal scan velocities ranging from 1.27 cmlsec to 12.7 cmlsec with 1270 or 1 344 samples per horizontal scan line, and a horizontal sample spacing of 0. 1 mm. For comparison, Nyquist sampling was achieved with a 64x84 image size and 1 .6 mm sample spacing. In order to achieve the large amount of over sampling, and be able to handle the resulting large quantities of image data, hardware and software modifications had to be made to the existing STAG test bed. These changes will be reported along with the sampling details and results for all three targets. Keywords: Passive Millimeter Waves, Millimeter Wave Imaging, Radiometry, Smart Tactical Autonomous Guidance, Super resolution, Over Sampling, Image Enhancement, Nyquist Sampling
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