A Comparison of Detection and Tracking Methods as Applied to OPIR Optics

Abstract

The objective of this research is to investigate and evaluate detection and tracking algorithms suitable for Overhead Persistent InfraRed (OPIR) coverage of moving ground targets. One of the largest hurdles is operating with a low signal-to-noise ratio (SNR) in a cluttered environment. The local contrast method (LCM) and principal component analysis (PCA) detection algorithms will be explored and tested while centroid and correlation tracking algorithms will be discussed. Kalman and alpha-beta filters will be compared and contrasted as viable track prediction techniques. This work will also provide a solid knowledge base for future research on the High Energy Laser (HEL) Beam Control Research Testbed that the Naval Postgraduate School is developing in partnership with Boeing Directed Energy Systems. While they are different applications, both HELs and OPIR share common detection and tracking strategies. Simulation results show that the LCM is superior to PCA. However, the best results are obtained by combining the two. Kalman and alpha-beta filters handle single targets with a constant velocity or acceleration with ease, but advanced tracking methods like the velocity matched filter to provide constraints would provide a more robust solution when performing multiple target tracking.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2014
Accession Number
ADA620559

Entities

People

  • Michael R. Krueger

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Detection
  • Detectors
  • Directed Energy Weapons
  • High Energy Lasers
  • Infrared Detection
  • Infrared Detectors
  • Lasers
  • Military Research
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Tactical High-Energy Lasers
  • Target Tracking
  • United States Central Command
  • Warfare
  • Weapon Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • Directed Energy