Chirp Transform in the Nonlinear Tracking Performance Analysis of the LMS Adaptive Predictors

Abstract

A chirp transform is defined for the A-step LMS adaptive predictors for linearly chirped signals embedded in additive white Gaussian noise. By converting the chirped signals to stationary baseband signals, this transform provides a different approach in analyzing the tracking performance of the LMS adaptive predictors. This transform also provides an approach of analyzing the nonlinear effects of the LMS adaptive predictor for nonstationary input signals. It is also shown that the chirp transform can be applied to the 1-step RLS predictor with chirped input signals.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2001
Accession Number
ADA506950

Entities

People

  • James R. Zeidler
  • Jun Han
  • Walter H. Ku

Organizations

  • Naval Information Warfare Systems Command

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Adaptive Filters
  • Additives (Chemicals)
  • Algorithms
  • Autocorrelation
  • Computers
  • Ecology
  • Equations
  • Filters
  • Frequency
  • Gaussian Noise
  • Information Theory
  • Noise
  • Signal Processing
  • Stationary
  • Statistical Analysis
  • Steady State
  • Transfer Functions

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Optical Physics and Photonics.