Engineering Commons^™

Navigation Satellite Selection Using Neural Networks, Daniel J. Simon, Hossny El-Sherief

Electrical and Computer Engineering Faculty Publications

The application of neural networks to optimal satellite subset selection for navigation use is discussed. The methods presented in this paper are general enough to be applicable regardless of how many satellite signals are being processed by the receiver. The optimal satellite subset is chosen by minimizing a quantity known as Geometric Dilution of Precision (GDOP), which is given by the trace of the inverse of the measurement matrix. An artificial neural network learns the functional relationships between the entries of a measurement matrix and the eigenvalues of its inverse, and thus generates GDOP without inverting a matrix. Simulation results …

Equivalent Single Axleload Computer Program Enhancements, Jerry G. Pigman, David L. Allen, Jack A. Harison, Neil Tollner, David H. Cain

Kentucky Transportation Center Research Report

The objectives of the study were to review and modify previously used Equivalent Single Axleload (ESAL) prediction procedures and to develop a more efficient procedure. As part of the effort to simplify the procedure, a subtask was undertaken to reduce the number of highway functional classes being used to process data for the ESAL estimation procedure. Another objective was to develop a more definitive and accurate method for reflecting the effects of coal or heavy truck movements. Results of this task were documented as Research Report KTC-95-6.

Analyses were performed and validated to reduce the twelve functional classes to six …