28 April 2009 An algorithm for 3D target scatterer feature estimation from sparse SAR apertures
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We present an algorithm for extracting 3D canonical scattering features from complex targets observed over sparse 3D SAR apertures. The algorithm begins with complex phase history data and ends with a set of geometrical features describing the scene. The algorithm provides a pragmatic approach to initialization of a nonlinear feature estimation scheme, using regularization methods to deconvolve the point spread function and obtain sparse 3D images. Regions of high energy are detected in the sparse images, providing location initializations for scattering center estimates. A single canonical scattering feature, corresponding to a geometric shape primitive, is fit to each region via nonlinear optimization of fit error between the regularized data and parametric canonical scattering models. Results of the algorithm are presented using 3D scattering prediction data of a simple scene for both a densely-sampled and a sparsely-sampled SAR measurement aperture.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Julie Ann Jackson, Julie Ann Jackson, Randolph L. Moses, Randolph L. Moses, } "An algorithm for 3D target scatterer feature estimation from sparse SAR apertures", Proc. SPIE 7337, Algorithms for Synthetic Aperture Radar Imagery XVI, 73370H (28 April 2009); doi: 10.1117/12.820497; https://doi.org/10.1117/12.820497

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