22 October 1993 Model-based superresolution CSO processing
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This is a description of a model-based maximum likelihood estimation technique for determining the position and intensities of closely spaced objects (CSO's) present in the focal plane of a forward-looking infrared (FLIR) sensor. The object model considered here is approximate point sources; we present a methodology to superresolve two point sources separated closer than the Rayleigh resolution criteria. The Cramer-Rao theoretical lower bound is derived in closed form; the variance of the proposed estimator will be compared to this bound to verify its superresolving capability. Simulation results are presented for medium and high signal-to-noise (Gaussian noise) ratios and source separations.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John T. Reagan, John T. Reagan, Theagenis J. Abatzoglou, Theagenis J. Abatzoglou, } "Model-based superresolution CSO processing", Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); doi: 10.1117/12.157809; https://doi.org/10.1117/12.157809


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