Illumination Waveform Design For Non-Gaussian Multi-Hypothesis Target Classification In Cognitive Radar

RANDRIANANDRASANA Marie Emile, RANDRIAMITANTSOA Paul Auguste, RANDRIAMITANTSOA Andry Auguste

Abstract


The cognitive radar system is generalized to deal effectively with arbitrary non-Gaussian distributed target responses via two key contributions: (1) an important statistical expected value operation that is usually evaluated in closed form is evaluated numerically using an ensemble averaging operation, and (2) a powerful new statistical sampling algorithm and a kernel density estimator are applied to draw complex target samples from target distributions specified by both a desired power spectral density and an arbitrary desired probability density function. Simulations using non-Gaussian targets demonstrate very effective algorithm performance. As expected, this performance gain is realized at the expense of increased computational complexity


Keywords


Cognitive Radar, Non-Gaussian, target classification

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DOI: http://dx.doi.org/10.52155/ijpsat.v31.2.4174

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