Fast Hybrid Multiple Scattering Theory Method Applied to Multiple Scattering Problems

Multiple scattering problems in vegetation and forests have been of great interest in microwave remote sensing. The Soil Moisture Active Passive (SMAP) mission operating at L-band measures Earth’s soil moisture enabling us to monitor water cycle, drought, and wild fire. Accurate electromagnetic modeling of forests and vegetation is essential for microwave remote sensing to estimate vegetation and forest effects on microwaves. For decades, the Radiative Transfer Equation (RTE) has been used to obtain simplified solutions which ignore gaps among trees/plants. For accurate electromagnetic modeling, full-wave simulations of solving 3D Maxwell’s equations can be applied to multiple scattering problems in forests and vegetation. However, electromagnetic simulations of these areas involve large-scale simulation domains with hundreds of scatterers making full-wave simulations significantly limited by CPU time and memory requirements.

In this work, we propose Fast Hybrid Multiple Scattering Theory Method (FHMSTM) for accurate and fast full-wave simulations of forests and vegetation. The Foldy-Lax equation expressing the wave interaction among scatterers is used to efficiently solve 3D-Maxwell’s equations. The proposed method consists of three main steps: (1) the T-matrix extraction in (VCW) Vector Cylindrical Wave, (2) derivation of the Foldy-Lax multiple scattering equation using VCWs, and (3) application of a fast computation algorithm to solve the Foldy-Lax equation. The FHMSTM achieves the computational complexity O(NlogN) and memory O(N). The proposed method is successfully applied to 100 corn plants and 300 trees in Harvard forest. We systematically verify accuracies by using commercial software and GNSS-T measurement and estimate the forest effects on L-band signals.

CHAIR: Professor Leung Tsang