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15 October 1993 Choice of an entropy-like function for range-Doppler processing
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Motion compensation of range-Doppler target signatures results in focused target imagery. Recently, an iterative approach based on a logarithmic entropy measure has been proposed for the motion compensation of signatures collected in the frequency domain. The effectiveness of this approach can be significantly improved by using an entropy-like function which is maximally resistant to noise and consistent with statistical boundaries. For purposes of analysis, the entropy-like function is written in terms of an information gain function (Delta) I. Several expressions for (Delta) I are tested to verify the accuracy of radial-motion parameter estimation. The effectiveness of these expressions is determined by the number of iterations required to find the minimum entropy measure, within an acceptable tolerance level for a given signal-to-noise ratio. Results show that the exponential information gain (Delta) I equals exp(1-I) yields an optimally convex entropy measure surface over a prescribed motion- parameter solution space. The surface minimum in this solution space has coordinates which are interpreted as the optimum motion-parameter estimates that can be obtained for the purpose of image focusing.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Benjamin C. Flores, Alberto Ugarte, and Vladik Kreinovich "Choice of an entropy-like function for range-Doppler processing", Proc. SPIE 1960, Automatic Object Recognition III, (15 October 1993);

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