Experiment design-based robust spatial spectral analysis techniques for enhanced imaging with remote sensing data

Abstract

A new approach to optimization of the signal processing techniques for enhanced imaging with remote sensing (RS) data based on the concept of descriptive experiment design regularization (DEDR) is addressed. The RS imaging problem is treated as a nonlinear statistical inverse problem of reconstructing the spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment via processing the RS data signals distorted in the stochastic measurement channel. We propose to aggregate the paradigms of statistical estimation theory, experiment design and descriptive regularization to solve the SSP reconstruction problem with the system-level and model-level uncertainties attributed to imperfect system calibration and random signal perturbations in inhomogeneous propagation medium. Advanced robust adaptive signal processing techniques that employ the proposed DEDR method for enhanced RS imaging in both certain and uncertain operational scenarios are developed and evaluated through computer simulations.