Adaptive CFAR Detection and Reduced-Rank Space-Time Adaptive Processing.

Abstract

A new approach to adaptive CFAR detection and reduced rank space time adaptive processing is introduced. A general methodology is developed for the design and analysis of reduced rank detectors with known and unknown covariance. The detection and false alarm probabilities are explicitly calculated and a cross spectral metric is introduced for rank reduction. This metric is demonstrated to result in a low rank detector which outperforms the principal components technique. The cross spectral metric provides subspace dimensionality robustness and allows for the dimension of the detector to be reduced beneath the dimension of the noise subspace eigenstructure without significant performance loss.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1997
Accession Number
ADA323841

Entities

People

  • Irving S. Reed
  • J. S. Goldstein

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Covariance
  • Cross Correlation
  • Data Science
  • Detection
  • Detectors
  • False Alarms
  • Filters
  • Frequency
  • Information Processing
  • Information Science
  • Probability
  • Steady State
  • Target Detection
  • Three Dimensional
  • Warning Systems

Fields of Study

  • Engineering

Readers

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

Technology Areas

  • Space
  • Space - Space Objects