Optimization of NLLS Algorithm Using Matrix Algebra: Application on SAR Tomography

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.