Remote Characterization of Chemical Vapor Plumes by Lwir Imaging Fabry-perot Spectrometry

Physical Sciences Inc. has developed and tested two long-wavelength infrared (LWIR) hyperspectral imaging spectroradiometers based on the insertion of a rapidly tunable Fabry-Perot etalon in the field of view of a HgCdTe focal plane array (FPA). The tunable etalon-based optical system enables a wide fieldof-view and the acquisition of narrowband (7 to 11 cm spectral resolution), radiometrically calibrated imagery throughout the 8 to 11 μm spectral region. The instruments function as chemical imaging sensors by comparing the spectrum of each pixel in the scene with reference spectra of target chemical species. We present results of recent field tests in this paper. INTRODUCTION In this paper we describe the results of chemical imaging experiments involving two LWIR imaging Fabry-Perot spectrometers developed by Physical Sciences Inc. (PSI). (The instruments are known as Adaptive InfraRed Imaging Spectroradiometers, AIRISTM, U.S. Patent 5,461,477.) The experiments involved imaging a series controlled chemical vapor releases at the U.S. Department of Energy's Nevada Test Site. Plumes were viewed from two fixed locations: 1.5 km and 1.9 km range from the plume release point. We present data acquired during the summers of 2000 and 2001. Passive sensing of chemical vapor plumes requires exploitation of both the spectral signatures of the target species as well as the radiance contrast between the vapor and the background scene. PSI’s imaging spectrometers are comprised of an LWIR focal plane array-based camera which views the far field through a low-order, tunable Fabry-Perot etalon. The tunable etalon provides the spectral resolution necessary to resolve structured absorption and emission from molecular vapors. The focal plane array (FPA) enables radiance measurements of sufficient accuracy that chemical vapors may be selectively detected with only several degrees effective temperature difference between the vapor and the background. We analyze chemical imaging data using algorithms developed at PSI. The results of the data analysis illustrate two key sensor capabilities: