New Methods for Nonlinear Tracking and Nonlinear Chaotic Signal Processing

Abstract

The classic problem in signal processing is to identify a low strength signal in a noisy background. Even more difficult problems are to identify several signals in the noisy background, to determine the direction of the sources, and to track one or more of these multiple sources. In the next section we will give an overview of the techniques that we have developed for nonlinear signal identification. In the third section we will provide the details. In the fourth section we will give an overview of our nonlinear tracking methods, and in the fifth section we will give the details of the design of an array suitable for use with broadband signals. In the sixth section we will present the details of our nonlinear tracking algorithm for following a maneuvering vehicle. Classical, linear theory has been used extensively in solving these problems. However, if the signals have a broad frequency spectrum with no readily identifiable characteristics, standard spectral methods are inadequate. In Phase I, we have built upon some results of nonlinear dynamics to develop nonlinear algorithms to solve these problems, namely: (1) Classify sources of multiple signals in a noisy environment; (2) Determine the source direction if the receiver is an array; and (3) Perform tracking of a maneuvering vehicle.

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Document Details

Document Type
Technical Report
Publication Date
Dec 18, 1992
Accession Number
ADA259331

Entities

People

  • Jon A. Wright

Organizations

  • Northwest Research Associates

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Broadband
  • Detection
  • Detectors
  • Differential Equations
  • Equations
  • Frequency
  • Frequency Bands
  • Identification
  • Nonlinear Dynamics
  • Plane Waves
  • Power Spectra
  • Probability
  • Signal Processing
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Business Analytics
  • Operations Research
  • Radar Systems Engineering.