Title :
Signal processing algorithms for hyperspectral remote sensing of chemical plumes
Author :
Manolakis, Dimitris
Author_Institution :
Lincoln Lab., MIT, Lexington, MA
fDate :
March 31 2008-April 4 2008
Abstract :
Long-wave infrared (LWIR) hyperspectral imaging sensors are widely used for the detection and identification of released chemical agents in many civilian and military applications. Current hyperspectral system capabilities are limited by variation in the background clutter as opposed to the physics of photon detection. Hence, the development of statistical models for background clutter and optimum signal processing algorithms that exploit these models are essential for the design of practical systems that satisfy user´s requirements. This paper describes a signal processing system for the detection and identification of released chemical agents developed at MIT Lincoln Laboratory. We discuss the underlying signal models, key detection and identification algorithms, and some areas where the signal processing community could contribute.
Keywords :
chemical sensors; image sensors; infrared imaging; remote sensing; signal detection; statistical analysis; LWIR imaging spectrometer; background clutter; chemical agent detection; chemical agent identification; chemical plumes; civilian applications; hyperspectral imaging sensors; hyperspectral remote sensing; long-wave infrared sensors; military applications; photon detection; signal processing algorithms; statistical models; Chemical processes; Chemical sensors; Hyperspectral imaging; Hyperspectral sensors; Infrared detectors; Infrared image sensors; Optoelectronic and photonic sensors; Physics; Remote sensing; Signal processing algorithms; Remote plume detection; adaptive signal detection; array signal processing; infrared spectroscopy;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4517995