Novel Space-Time Adaptive Processing Methods for Gaussian and Non-Gaussian Radar Clutter

Abstract

Our work on this contract has four main thrusts. We addressed (1) the problem of optimal target detection of a rank one signal in additive non-Gaussian clutter modeled as a spherically invariant random process. Performance analysis of the optimal signal processor was carried out. However, practical implementation of the optimal processor requires know- ledge of the probability density function underlying the clutter, which is often unavailable. Hence, (2) we considered the performance of sub-optimum as well as ad-hoc approximations to the optimal processor. Next, (3) we concerned ourselves with the performance of parametric space-time adaptive processing methods in Gaussian interference and addressed issues of detection probability. constant false alarm rate and reduced training data support. Finally, (4) we provided a rigorous statistical analysis of the recently proposed non-homogeneity detector, which is useful for training data selection in STAP applications.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2001
Accession Number
ADA390662

Entities

People

  • Muralidhar Rangaswamy

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Data Science
  • Detection
  • Detectors
  • False Alarms
  • Goodness Of Fit Tests
  • Information Science
  • Military Research
  • Probability
  • Probability Density Functions
  • Radar Clutter
  • Random Variables
  • Signal Processing
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Engineering

Readers

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

Technology Areas

  • Space
  • Space - Space Objects