TThis paper presents a new approach to scattering center extraction based on a scattering model derived from the geometrical theory of diffraction (GTD). For stepped frequency measurements at high frequencies, the model is better matched to the physical scattering process than the damped exponential model and conventional Fourier analysis. In addition to determining downrange distance, energy, and polarization, the GTD-based model extracts frequency dependent scattering information, allowing partial identification of scattering center geometry. We derive expressions for the Cram&-Rao bound of this model; using these expressions, we analyze the behavior of the new model as a function of scatterer separation, bandwidth, number of data points, and noise level. Additionally, a maximum likelihood algorithm is developed for estimation of the model parameters. We present estimation results using data measured on a compact range to validate the proposed modeling procedure.

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A method for characterizing radar target signatures with Autoregressive Moving Average (ARMA) models is developed. A parameterization of the model that corresponds directly to the geometric properties of the target is chosen, and an efficient algorithm for estimating these parameters is presented. Procedures for minimizing the effects of unmodeled dynamics are also developed. Experiments on radar measurements obtained from a compact range are presented to test the effectiveness of the ARMA modeling procedure.

A new approach to scattering center extraction is developed based on a model derived from the Geometric Theory of Diffraction (GTD). For stepped frequency measurements at high frequencies, this model is better matched to the physical scattering process than the Prony or discrete Fourier transform modeling methods. In addition, the GTDbased model extracts more information about the scattering centers, allowing partial identification of scattering center geometry in addition to determining energy and downrange distance. We derive expressions for the Cramer-Rao bound of this model; using these expressions we analyze the behavior of the new model as a function of scatterer separation, bandwidth, number of data points, and noise level. We compare these results with those for the Prony model. Additionally, a Maximum Likelihood algorithm for the model is developed. Estimation results using data measured on a compact range are presented to validate the proposed modeling procedure.Recently, the Prony model has been used to model radar scattering 3,4,8 The Prony model has been shown O-8194-1538-3/94/$6.QO SPIEVo!. 2234/67 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/21/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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