Minimax Robust Matched Filters for Noise Uncertainty within 2-Alternating Capacity Classes

Abstract

In this paper, the author addresses the problem of designing matched filters that are robust against uncertainty in the statistics of the noise process. The design is based on a game-theoretic approach in which a filter is sought that has the maximum worst-case output signal-to-noise ratio possible over the class of allowable statistics. That is, the design is maximin signal-to-noise ratio. The problem is formulated and solved for both discrete-time and continuous-time matched filters with uncertainty in either the auto-correlation function or the spectral measure of the noise. For uncertainty models determined by 2-alternating Choquet capacities, explicit solutions are obtained that are characterized by the Huber-Strassen derivative of the capacity generating the class with respect to a Lebesgue-like measure on a suitable interval.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1987
Accession Number
ADA452266

Entities

People

  • Evaggelos A. Geraniotis

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Data Science
  • Electrical Engineering
  • Engineering
  • Filters
  • Information Operations
  • Information Science
  • Matched Filters
  • Statistical Analysis
  • Statistics
  • Uncertainty
  • Universities

Readers

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