Statistical adaptive sensing by detectors with spectrally overlapping bands

Autor:	Sanjay Krishna, Unal Sakoglu, K. T. Posani, J. Scott Tyo, Philip Dowd, Senthil Annamalai, Majeed M. Hayat
Rok vydání:	2006
Předmět:	Physics Photocurrent business.industry Materials Science (miscellaneous) Detector Multispectral image Hyperspectral imaging Industrial and Manufacturing Engineering Noise Responsivity symbols.namesake Optics Semiconductor Fourier transform symbols Business and International Management business
Zdroj:	Applied Optics. 45:7224
ISSN:	1539-4522 0003-6935
Popis:	It has recently been reported that by using a spectral-tuning algorithm, the photocurrents of multiple detectors with spectrally overlapping responsivities can be optimally combined to synthesize, within certain limits, the response of a detector with an arbitrary responsivity. However, it is known that the presence of noise in the photocurrent can degrade the performance of this algorithm significantly, depending on the choice of the responsivity spectrum to be synthesized. We generalize this algorithm to accommodate noise. The results are applied to quantum-dot mid-infrared detectors with bias-dependent spectral responses. Simulation and experiment are used to show the ability of the algorithm to reduce the adverse effect of noise on its spectral-tuning capability.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::134b2be8c9cb01dad1378e417949cb6d https://doi.org/10.1364/ao.45.007224 Zobrazit plný text záznamu