Date of Award
Master of Science
Department of Electrical and Computer Engineering
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.
DTIC Accession Number
Jans, Ryan M., "Testbed Creation to Study Noise Radar Network Weighting Models and Data Fusion with Radio Tomographic Imaging" (2022). Theses and Dissertations. 5323.