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A RANDOM ACCELERATION MODEL FOR FILTERING POLYNOMIAL-LIKE SIGNALS,
MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB
Random type models for filtering discrete time, polynomial-like signals from noise are discussed. The particular model analyzed is a second-degree polynomial with the acceleration second derivative considered to be a random process. The optimum filter corresponding to this model is derived. Results include curves of filter frequency response, estimate variance, and filter impulse response for various choices of the system parameters. Some of the factors that affect the choice of a model for polynomiallike signals are discussed. Author