The general problem of multiple signal sources detection using an array of sensors, with the particular case of Synthetic Aperture Radar (SAR) Tomography is approached in this paper. A detection algorithm which generates accurate results but it's computationally demanding, sup-GLRT (Generalized Likelihood Ratio Test with support estimation), is discussed. Main objective consists in applying matrix algebra for optimization of 2D Non-Linear Least Squares (NLLS) search implementation, the most demanding part of the detector. Results of the detection algorithm on a dataset of high resolution SAR images are presented. Performance of the proposed optimization method is assessed by comparison of algorithm implementation times.
Optimization of NLLS Algorithm Using Matrix Algebra: Application on SAR Tomography
Pauciullo Antonio;Fornaro Gianfranco;
2017
Abstract
The general problem of multiple signal sources detection using an array of sensors, with the particular case of Synthetic Aperture Radar (SAR) Tomography is approached in this paper. A detection algorithm which generates accurate results but it's computationally demanding, sup-GLRT (Generalized Likelihood Ratio Test with support estimation), is discussed. Main objective consists in applying matrix algebra for optimization of 2D Non-Linear Least Squares (NLLS) search implementation, the most demanding part of the detector. Results of the detection algorithm on a dataset of high resolution SAR images are presented. Performance of the proposed optimization method is assessed by comparison of algorithm implementation times.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
