Nonlinear unmixing of simulated MightySat FTHSI data for target detection limits in a humid tropical forest scene

摘要

Abstract: In this paper we demonstrate the detection limits of the Kestrel Fourier transform hyper-spectral imager (FTHSI) on the MightySat II.I to detect target spectra in a complex natural scene. We simulate the MightySat II.I FTHSI data using a combination of landsat TM based endmember spectra derived from a scene of La Mosquitia, Honduras and library spectra measured in the field at 3 nm spectral resolution. The TM endmember images define the mixing space to produce a simulated hyper-spectral reflectance image. Fractions define how the field measured endmember spectra are mixed in order to produce the simulated hyper-cube. The HIMP model is used to predict the radiance as observed by the FTHSI. Results indicate that this technique allows the detection of tropical camouflage in a natural tropical background when the camouflage is mixed at one tenth of one percent with an accuracy of 95.7 percent. At one percent mixing ratio the detection accuracy rises to 99.7 percent. At five percent and beyond the detection accuracy is one hundred percent. This physically-based non-linear unmixing technique is two orders of magnitude more sensitive than traditional linear unmixing or matched filtering. !11