A matrix inversion approach of computing T-matrix for axially symmetrical particles of extreme shape and dielectrically large dimension

The T-matrix method has been widely used in radar meteorology because hydrometeors approximate to spheroidal shapes and their sizes are comparable to the sensing wavelength. However, it is considered unsuitable to solve in remote sensing problems concerning vegetation because the particles of interest, leaves and branches, are considered extremely shaped and of large dielectric dimensions, therefore beyond the domain of direct T-matrix algorithms. By solving two linear equation sets, this paper proposes a matrix inversion approach to calculate indirectly the T-matrix of regularly shaped scatterers in the crown layer of canopies. We adopt an existing electromagnetic (EM) model to calculate the scattering amplitudes as the left hand side of the equations. The number of the unknowns in the equations decreases by almost half, thus reducing the kernel computation to a significant extent when we assume that the particles are symmetrical in most remote sensing applications. The observed consistency between the scattering coefficients computed by the obtained T-matrix and those by the EM model indicates that the valid aspect ratio of this proposed method spans from 0.02 to 200, although this ratio may possibly extend with further verification. The proposed T-matrix calculation method can work at either the far-zone or the near-zone. However, it should be noted that the T-matrix obtained in the far-zone could not yield correct scattering results in the near-zone; on the contrary, the T-matrix obtained from the near-zone can produce accurate scattering fields/coefficients in what is further than the region of matching.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000309137500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Astronomy & AstrophysicsGeochemistry & GeophysicsMeteorology & Atmospheric SciencesRemote SensingTelecommunicationsSCI(E)EI3ARTICLE4null4