Application of Multiband Acoustooptical Filtering of Radiation to Solution of the Object Remote Identification Problems by the Method of Programmed Linear Separation of Multispectral Optical Signals in the Case of Reflection of a Wideband Light from Objects with A Priori Known Reflection Coefficients


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Resumo

A new approach to solution of the problem of remote determination of spectrally complex optical signals and identification on this base of two objects out of a set of possible spatially inseparable objects located in one small ground pixel is considered. Computer simulation is performed; it is shown that the results of measurements of the mean powers of filtered signals at the outputs of two (or more) selected reference multiband acoustooptical filters (MAOFs) can ensure subsequent programmed (digital) separation of spectrally complex optical signals and identification of the objects corresponding to these signals. By the example of an arbitrarily chosen group of ten types of objects and three types of the background, computer verification of the new method is carried out with the use of realizable parameters of modern MAOFs. It has been found that, in conditions of the actual accuracy of setting and/or measuring of the energy of the main components of the problem (~1%), this method can provide unambiguous correct decision about the type of the object located on part of a pixel with a probability of ~99.9%.

Sobre autores

O. Byshevski-Konopko

Kotel’nikov Institute of Radio Engineering and Electronics (Fryazino Branch)

Autor responsável pela correspondência
Email: byshevski@ms.ire.rssi.ru
Rússia, Fryazino, Moscow oblast, 141190

V. Proklov

Kotel’nikov Institute of Radio Engineering and Electronics (Fryazino Branch)

Email: byshevski@ms.ire.rssi.ru
Rússia, Fryazino, Moscow oblast, 141190

A. Lugovskoi

Kotel’nikov Institute of Radio Engineering and Electronics (Fryazino Branch)

Email: byshevski@ms.ire.rssi.ru
Rússia, Fryazino, Moscow oblast, 141190


Declaração de direitos autorais © Pleiades Publishing, Inc., 2018

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