Ryan M. Jans

Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Richard K. Martin, PhD


Significant research has been conducted on RTI weighting models; however, very little comparative research has been conducted for NRN weighting methods. In order to create comparative weighting methods for NRN, it is necessary to create a testbed which allows for RTI and NRN research to be conducted simultaneously and allow for data fusion methods to also be researched. After creating the testbed and analyzing results, the newly proposed weighting method provides an up to 33% performance increase in target localization accuracy when compared to the previous weighting model used for NRN. The attenuation image resolution improvements resulted in a 79% performance increase in target localization accuracy for the MAP estimate. In addition to the performance increase, the newly proposed weighting method has the capability to provide a foundation for future research into NRN weighting methods. The testbed created allows for seamless interchanging of data sets, weighting models, and experimental conditions.

AFIT Designator


DTIC Accession Number