Multilevel Data Integration with Applications in Sensor Networks

Abstract

This work considers a general system composed of multiple subsystems, where data can be collected at different levels of the system with possibly different probability distributions. Using the general formulations of the distributions and the principle of maximum likelihood estimation, we develop a method for estimating parameters, including uncertainty bounds on the estimates, associated with the relevant performance metric. The proposed method is demonstrated in two applications: (1) Detecting target locations by integrating data from both UAVs (unmanned aerial vehicles) and Doppler radar and (2) Detecting the position of markers" in a problem of aerial refueling.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2021
Accession Number
AD1149660

Entities

People

  • James C. Spall
  • Long Wang

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Applied Mathematics
  • Asymptotic Normality
  • Cartesian Coordinates
  • Coordinate Systems
  • Detection
  • Detectors
  • Doppler Radar
  • Information Science
  • Measurement
  • Physics Laboratories
  • Probability
  • Probability Distributions
  • Refueling
  • Refueling In Flight
  • Sensor Networks
  • Statistics
  • Unmanned Aerial Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Radar Systems Engineering.

Technology Areas

  • Autonomy