Robust Detection of Fading Narrow-Band Signals in Non-Gaussian Noise

Abstract

In this report, we study procedures for robust detection of slowly fading narrowband signals in nearly Gaussian noise, a common model for radar/sonar systems. For the classical quadrature matched filter test, we introduce an uncertainty about the envelope statistic and develop a robust test for this one- sample situation. It is demonstrated that this test is capable of protecting only against relatively weak contaminations. With uncertainty taken directly on the noise samples, we develop an estimation-detection theoretic approach: The detection statistic preserves the structure of the quadrature matched filter, but in place of the linear sample mean, a minimax robust estimator of the random amplitude is substituted. This test is shown to be asymptotically maximin optimal (in the sense of Huber) for a wide family of decision rules and for several common target signal models. Originator supplied keywords include: robust detection; non-Gaussian detection; fading narrow-band signals; combined robust estimation-detection; scale invariance; and adaptive threshold.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1985
Accession Number
ADA152262

Entities

People

  • Matthew L. Weiss
  • S. C. Schwartz

Organizations

  • Princeton University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Computer Science
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • Estimators
  • False Alarms
  • Filters
  • Gaussian Noise
  • Information Science
  • Mathematical Filters
  • Military Research
  • Monte Carlo Method
  • Numerical Analysis
  • Probability
  • Statistics
  • Test And Evaluation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radio communications and signal processing.
  • Statistical inference.