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DOCUMENT CONTROL DATA -R&D(Securlrv clausiflcatin of title, body of abstract ad Indexing annotation must b entaed when the overall report I# Claeifled)

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ESPRIT processing appears to be the best of the known spectral-analysis techniques. It provides the highest resolution and has no spectral splatter. By applying matrix eigenstructure analysis, it gives a direct answer to the direct question "What frequencies, real or complex, are present in the data and what are their amplitudes?" Conventional Fourier techniques, as well as some of the other higher-resolution methods, answer the less direct question "What amplitudes, applied to a set of regularly-spaced real frequencies, best represent the data?" Then comes the problem of interpreting the amplitudes.These attributes of ESPRIT, in the two-dimensional version described here, make it a natural for radar signal processing, where it answers the need for high-resolution imaging, free of sidelobes in range and Doppler, and for high-fidelity target feature extraction. For example, the uncertainty in the scatterering-center locations in an ESPRIT image extracted from high-quality static-range radar data collected over a bandwidth of 1 GHz is just a few millimeters; for conventional Fourier processing of the same data the uncertainty is many centimeters. The signature of the base edge of a perfectly conducting cone extracted from static-range data by ESPRIT agrees accurately with the signature predicted by edgediffraction theory.This report starts with a mathematical model for the radar data, describes a technique for "resampling" the data to achieve a more perfect fit with the ESPRIT data model, summarizes the twodimensional ESPRIT algorithm itself, and presents examples of its performance. The appendix covers the details of this least-mean-square version of ESPRIT, including an enhancement that allows the scatterers to be tracked individually. The algorithm properly distinguishes between target locations having one coordinate in common, and it automatically associates correctly in pairs each entry in the list of ranges with the corresponding entry in the list of range rates. 1The Fourier and ESPRIT X-band radar images of an aluminum round-nosed cone target at nose-on aspect derived from measured static-range data of 1 GHz bandwidth. The target's rotation axis and the radar's magnetic-field polarization on transmit and receive were vertical (HH polarization); the target's body-axis of symmetry and the radar line of sight were horizontal. 2 2 The complex diffraction coefficient of the base edge extracted by ESPRIT processing, from the same measured static-range HH-polarization data used for Figure 1, compared with the coefficient predicted by the geometric theory of diffraction. 3 3 ESPRIT X-band images from different aspects and 360-composite images, both in B&W and, to include amplitude information, in false color. The images were extracted from the same measured static-range X-band HH-polarization radar data used for the previous figures. 9 4 Narrow-angle imaging with ESPRIT, including zoom views showing the smaller location uncertainty that greater signal-to-noise ratio provides. 11 5 360° trajectories of t...