Multi-Sensor Detection Study.

Abstract

The methods of complex Gaussian multivariate analysis are applied to the problem of detecting signals in noise using data from multiple sensors whose relative locations are arbitrary. Theory is used to predict detection performance in terms of minimum detectable signal (MDS). A computer program implementing the multivariate detection approach is described, demonstrating that computational requirements are modest and verifying theory by simulation. Significant improvements over single-sensor processing (reduction in MDS by a factor equal to the number of sensors) is shown for certain cases. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1980
Accession Number
ADA091954

Entities

People

  • Leonard E. Miller

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Asymptotic Series
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Databases
  • Detection
  • Detectors
  • False Alarms
  • Plastic Explosives
  • Probability
  • Signal Detection
  • Signal Processing
  • Statistics
  • Warning Systems
  • Waveforms

Readers

  • Quantum Chemistry
  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.