Background Simulation and Filter Design Using Iterated Function Systems

Abstract

Design of filters which detect known signals in unknown backgrounds are considered from a deterministic viewpoint. Backgrounds which appear in Nature rather than being smooth, may appear fractal within a given waveband of interest. In this paper, derivations are given for the design of filters for both smooth backgrounds, and fractal backgrounds. The main theoretical tool for the fractal design is the Iterated Function System (IFS). It is shown how the IFS models generalize the smooth models of the background and the corresponding filters. Derivations of the false alarm rate in terms of the filters are given. Numerical examples demonstrating background simulation as well as convolution of the filters with signals embedded in noise having fractal dimension are presented.

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Document Details

Document Type
Technical Report
Publication Date
Feb 19, 1991
Accession Number
ADA232632

Entities

People

  • Ira B. Schwartz
  • Laurie Reuter

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Convolution
  • Detection
  • Detectors
  • False Alarms
  • False Signals
  • Feature Extraction
  • Filtration
  • Information Theory
  • Mathematical Filters
  • Probability
  • Random Variables
  • Signal Processing
  • Simulations
  • Stochastic Processes
  • Three Dimensional
  • Warning Systems

Readers

  • Artificial Intelligence
  • Calculus or Mathematical Analysis
  • Radio communications and signal processing.