Mitigating the Multipath Eects on Radio Tomographic Imaging

Abstract

Various radio tomographic imaging (RTI) models and reconstruction methods are equipped with capabilities to mitigate the effects of multipath interference. This thesis combined the network shadowing (NeSh) and weighting-g models in conjunction with Tikhonov regularization and low-rank and sparse decomposition (LRSD). MATLAB was used to implement the four combinations for six experimental data sets and produce attenuation images. The attenuation images were analyzed qualitatively and quantitatively to accomplish the goal of determining which combination performed best at locating human targets. After analyzing the results, it was determined that no single combination outperformed the others for at least three out of the five quantitative metrics. Therefore, a rating technique was used instead to normalize the average results of each metric and nd the mean across each combinations newly normalized average results. In accordance with the normalization scale, the lowest and best rating revealed the optimum combination was the weighting-g model implemented in conjunction with LRSD.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1132203

Entities

People

  • Destinee N Battle

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Algorithms
  • Applied Mathematics
  • Compressed Sensing
  • Data Sets
  • Detectors
  • Electrical Engineering
  • Engineering
  • Experimental Data
  • Gaussian Distributions
  • Governments
  • Information Science
  • Literature Surveys
  • Multipath Interference
  • Networks
  • Probability
  • Radio Frequency
  • Sensor Networks
  • Signal Processing
  • United States Government
  • Wireless Communications
  • Wireless Networks
  • Wireless Sensor Networks

Fields of Study

  • Physics

Readers

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