Power Variable Training STAP

Abstract

For GMTI radar processing space-time adaptive processing (STAP) is a standard technique to mitigate clutter while preserving moving targets. STAP relies on an accurately estimated covariance matrix which is traditionally computed from localized training around the range gate under test. This presentation suggests a new approach to covariance training. Power variable training combines phase-selective covariance training which restricts range gate training to the most powerful range gates that lie on the clutter ridge and a new technique that scales the covariance matrix power to prevent over-nulling. The new algorithm exhibits improved minimum detectable velocity (MDV) and fewer false alarms from clutter discretes as well as increased performance with extended-range targets. The proposed technique is demonstrated and compared to localized training on Tuxedo data.

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Document Details

Document Type
Technical Report
Publication Date
Mar 16, 2004
Accession Number
ADA432619

Entities

People

  • Charles M. Rader
  • Jacob D. Griesbach
  • Nicholas B. Pulsone
  • Steven I. Krich

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Angle Of Arrival
  • Contracts
  • Covariance
  • Detection
  • Detectors
  • Excision
  • False Alarms
  • Frequency
  • Radar
  • Radial Velocity
  • Ridges
  • Right Angles
  • Steering
  • Target Detection
  • Training
  • Warning Systems

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Radar Systems Engineering.

Technology Areas

  • Space
  • Space - Space Objects