Date of Award
12-1990
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering
Department
Department of Electrical and Computer Engineering
First Advisor
Steven K. Rogers, PhD
Abstract
The optical sensors of United States Air Force reconnaissance vehicles, such as satellites, are subject to temporary or permanent blinding from hostile (or threat) laser radiation. By detecting and determining the angle of arrival (AOA) of the hostile radiation, the reconnaissance vehicle may be able to protect its optical sensors by taking evasive maneuvers or by shutting down the optical sensor (such as closing a shutter) until the threat has passed. In addition, the vehicle can relay information to its ground terminal allowing the intelligence community to determine the source of the hostile laser radiation. This thesis demonstrated that an intensity pattern out of a short piece of optical fiber could be used to determine the angle of arrival (AOA), to within 0.1 deg, of the incident laser energy on the front of the optical fiber. The optical fiber was a one-inch-long, 3mm-diameter, multimode, step-index, plastic fiber. The optical fiber was mounted to the front end of a charge injection device (CID) camera. The CID camera's angle with respect to the incident laser energy, a uniform amplitude plan wave, would be varied by a computer controlled rotational stage. The output of the CID camera was captured by Spiricon software. Captured outputs representing various AOAs were processed to provide template or test feature vectors. The processing method used a fast Fourier transform routine to create a 24 component low frequency feature vector. Two classification methodologies were used: a Euclidean distance method and a radial basis function neural network.
AFIT Designator
AFIT-GE-ENG-90D-62
DTIC Accession Number
ADA230386
Recommended Citation
Thomas, Scott, "Angle of Arrival Detection Through Artificial Neural Network Analysis of Optical Fiber Intensity Patterns" (1990). Theses and Dissertations. 7979.
https://scholar.afit.edu/etd/7979