Student Work

RSS-Based 3D Drone Localization and Performance Evaluation

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This project is motivated by identifying the location of a trespassing drone. A drone is often equipped with a wireless camera which makes it vulnerable to the misuse of harassment, stalking, and other illegal activities. To mitigate this issue, we are interested in determining the location of a drone based on channel modeling, which studies the characteristics of signal propagation between transmitters and receivers (base stations). We implemented three localization algorithms: maximum likelihood estimation, weighted centroid, and recursive least square. We also compared these algorithms with Cramer-Rao lower bound, a theoretical lower bound for an unbiased estimator.

  • This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
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Identifier
  • E-project-042717-084711
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Year
  • 2017
Date created
  • 2017-04-27
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