Synthetic Aperture Radar (SAR) creates a 2-D (azimuth-range) image from radar pulses collected equally-spaced along a linear áight path. One 3-D scenerio collects these pulses at each collection point along the path from a linear (elevation) array orthogonal to the áight path. From this 3-D data set images (to a pixel accuracy) or array processing (to subpixel accuracy) allows strong scatterers to be located. Streamlined algorithms are needed for such practical image and volume reáectively function formation. Sacchini, Steedly and Moses (1993)3 presents a 2-D Total Least Squares (TLS) Prony method that robustly identiÖes 2-D scatterer locations in SAR images. In this method scatterer coordinates are matched by Ötting the data in each dimension, Ötting the resultant amplitudes in the cross-dimension and then matching the highest energy pairs in both these sets. This matching can produce excellent results for TLS Prony and for other 1-D scatterer localization algorithms. The algorithm is extended here to supply 3-D scatterer locations for simulated 3-D SAR data. Previous results for 3-D data show good localization using 2-D TLS Prony on azimuth-elevation slices and interpolating the range location between slices. Thresholding of the highest energy points, however, is required to Önd the actual location of scatterers. Range accuracy is also limited due to use of only the two closest range samples. Consistency of results is di§erent for di§erent amplitude scatterers. This paper produces results for a new 3-D TLS Prony method. Algorithm accuarcy, bias, robustness in di§erent scenarios are examined.
Matthew Pepin, "Three-dimensional total least square Prony method for 3D synthetic aperture scatterer localization," Proc. SPIE 10647, Algorithms for Synthetic Aperture Radar Imagery XXV, 106470I (Presented at SPIE Defense + Security: April 19, 2018; Published: 27 April 2018); https://doi.org/10.1117/12.2304057.
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