Simultaneous Localization, Calibration, and Tracking in an ad Hoc Sensor Network

Abstract

We introduce Simultaneous Localization and Tracking (SLAT), the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter providing on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. When applied to a network of 27 sensor nodes, our algorithm can localize the nodes to within one or two centimeters.

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 2005
Accession Number
ADA467100

Entities

People

  • Ali Rahimi
  • Christopher Taylor
  • Howard Elliot Shrobe
  • Jonathan Bachrach

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Calibration
  • Computational Complexity
  • Computational Science
  • Computer Science
  • Detectors
  • Gaussian Distributions
  • Kalman Filters
  • Measurement
  • Networks
  • Probabilistic Models
  • Probability Distributions
  • Range Finding
  • Sensor Networks
  • Three Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Networking
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML