Adaptive Radar Signal Processing-The Problem of Exponential Computational Cost

Abstract

This paper provides a survey of space-time adaptive processing for radar target detection. Specifically, early work on adaptive array processing from the point of view of maximum signal-to-noise-ratio and minimum mean squared error perspectives are briefly reviewed for motivation. The sample matrix inversion method of Reed, Mallet and Brennan is discussed with attention devoted to its convergence properties. Variants of this approach such as the Kelly GLRT, adaptive matched filter and ACE tests are considered. Extensions to handle the case of non-Gaussian clutter statistics are presented. Current challenges of limited training data support, computational cost, and severely heterogeneous clutter backgrounds are outlined. Implementation and performance issues pertaining to reduced rank and model-based parametric approaches are presented.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 04, 2003
Accession Number
ADP021389

Entities

People

  • Muralidhar (Murali) Rangaswamy

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Antenna Arrays
  • Computational Complexity
  • Covariance
  • Detection
  • Detectors
  • Digital Signal Processing
  • Engineering
  • False Alarms
  • Frequency
  • Matched Filters
  • Multiagent Systems
  • Radar Signals
  • Signal Processing
  • Statistical Analysis
  • Statistics
  • Target Detection

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.
  • Theoretical Analysis.

Technology Areas

  • Space
  • Space - Space Objects