Invariant methods for indexing and relative reconstruction of 3D models using 1D HRR and 2D SAR

Paul Max Payton; Eamon B. Barrett; Wolfgang Kober; John K. Thomas; Steven E. Johnson

doi:10.1117/12.323249

2 October 1998 Invariant methods for indexing and relative reconstruction of 3D models using 1D HRR and 2D SAR

Paul Max Payton, Eamon B. Barrett, Wolfgang Kober, John K. Thomas, Steven E. Johnson

Proceedings Volume 3454, Vision Geometry VII; (1998) https://doi.org/10.1117/12.323249
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

We describe a geometric model of high-resolution radar (HRR), where objects being imaged by the sensor are assumed to consists of a collection of isotropic scattering centers distributed in three dimensions. Three, four, five and six point pure HRR invariant quantities for non-coplanar reflecting centers are presented. New work showing invariants combining HRR and SAR measurements are then presented. All these techniques require matching corresponding features in multiple HRR and/or SAR views. These features are represented using analytic scattering models. Multiple features within the same HRR resolution cell can be individually detected and separated using interference-suppression filters. These features can then be individually tracked to maintain correspondence as the object poise changes. We validate our HRR/SAR invariants using the XPATCH simulation system. Finally, a view-based method for 3D model reconstruction is developed and demonstrated.

Citation Download Citation

Paul Max Payton, Eamon B. Barrett, Wolfgang Kober, John K. Thomas, and Steven E. Johnson "Invariant methods for indexing and relative reconstruction of 3D models using 1D HRR and 2D SAR", Proc. SPIE 3454, Vision Geometry VII, (2 October 1998); https://doi.org/10.1117/12.323249

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