An Integrated Approach to Indoor and Outdoor Localization

Abstract

We have developed a method of indoor localization and tracking that combines multiple sensor measurements to remove dependence on any one information source. A two-step process is proposed that performs an initial localization estimate, followed by particle filter based tracking. Initial localization is performed using WiFi and image observations. For tracking we fuse information from WiFi, magnetic, and inertial sensors. We demonstrate the feasibility of this system using fingerprint maps that are collected with single walk through the building at normal walking pace. In addition to a smartphone or tablet, only a foot mounted inertial measurement unit (IMU) is needed for database generation. Only a smart-phone is needed for positioning after database generation. The positioning method presented uses sensors available on most mobile devices and requires no new infrastructure to be placed in the building. We have tested our approach in two locations: the Stoneridge Mall in Pleasanton, California, and the Doe Library at the UC Berkeley campus. We achieve an average location error of 2.6m across both locations.

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Document Details

Document Type
Technical Report
Publication Date
Apr 17, 2017
Accession Number
AD1032535

Entities

People

  • Kannan Ramchandran

Organizations

  • University of California Regents

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force Research Laboratories
  • Change Detection
  • Computations
  • Databases
  • Detection
  • Detectors
  • Gaussian Processes
  • Global Positioning Systems
  • Inertial Measurement Units
  • Measurement
  • Mobile Devices
  • Mobile Phones
  • Navigation
  • Probability
  • Sequential Monte Carlo Methods
  • Smartphones

Fields of Study

  • Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Research Science/Academic Research
  • Sensor Fusion and Tracking Systems.