SIGNAL PROCESSING USING INCOHERENT ELECTRO-OPTICS.

Abstract

The subject of this dissertation is an electro-optical processing (EOP) concept which, in its basic configuration, computes a discrete linear transform such as Fourier, Laplace, Hilbert, etc., as well as convolutions and correlations. It accepts input signals through an incoherent light source, performs high speed analog multiplications via a two-dimensional array of apertures in a chrome mask on the surface of a charge-coupled device (CCD), shifts and integrates intermediate results within the CCD, and presents the transformed signal as a data stream from the output shift register of the CCD. The EOP concept is described in detail where both serial and parallel configurations are developed. It is seen to be an efficient computer of matrix-vector products, matrix-matrix products, and multichannel correlations. The inclusion of feedback and a changeable CCD mask yields an architecture for higher order matrix operations such as matrix inversion, solution of simultaneous equations, etc. A functional model of an EOP matrix-vector multiplier is presented which describes the accumulated effect of errors in system elements from the LED through the CCD. Also described is removal of error introduced by biasing required of input and mask modulation functions in order that they represent bipolar quantities. An EOP spectrum analyzer based upon direct implementation of the discrete Fourier transform (DFT) is described and use of a Kaiser-Bessel window function applied to the CCD mask is described as a solution to the "spectral leakage" problem caused by sharp discontinuities at each end of a normal window of sampled data. Finally, application of a parallel EOP configuration to the synthetic aperture radar (SAR) problem is offered. An architecture utilizing separate in-phase and quadrature EOP channels is described. The system shows potential for providing at least modest resolution SAR imagery with an economy of size, weight, and power consumption.