Estimation with Multisensor Fusion

Abstract

Our work dealt with the development of practical advanced algorithms for optimal processing of the information obtained from various remote sensing devices (radar, ESM or electro-optical) for surveillance and tracking targets. The processing consists of integration/filtering of the sensor data across time and fusion across sensors with the main goal being overcoming the inherent limitations of real-world sensors (accuracy and reliability) due to noise which cause false alarms - and other factors, such as low observable (LO) targets - which lead to low detection probability.

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Document Details

Document Type
Technical Report
Publication Date
Jul 24, 2006
Accession Number
ADA456852

Entities

People

  • Yaakov Bar-Shalom

Organizations

  • University of Connecticut

Tags

Communities of Interest

  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Data Association
  • Data Processing
  • Detection
  • Detectors
  • Estimators
  • Multiple Hypothesis Tracking
  • Multisensors
  • Multitarget Tracking
  • Optimal Estimators
  • Passive Sensors
  • Probability Hypothesis Density Filters
  • Signal Processing
  • Target Recognition
  • Target Tracking
  • Unmanned Aerial Vehicles

Fields of Study

  • Engineering

Readers

  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design