Adaptive Detection and Parameter Estimation for Multidimensional Signal Models

Abstract

The problem of target detection and signal parameter estimation in a background of unknown interference is studied, using a multidimensional generalization of the signal models usually employed for radar, sonar, and similar applications. The required techniques of multivariate statistical analysis are developed and extensively used throughout the study, and the necessary mathematical background is provided in Appendices. Target detection performance is shown to be governed by a form of the Wilks' Lambda statistic, and a new method for its numerical evaluation is given which applies to the probability of false alarm of the detector. Signal parameter estimation is shown to be directly related to known techniques of adaptive nulling, and several new results relevant to adaptive nulling performance are obtained.

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Document Details

Document Type
Technical Report
Publication Date
Apr 19, 1989
Accession Number
ADA208971

Entities

People

  • E. J. Kelly
  • K. M. Forsythe

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Complex Variables
  • Detection
  • Detectors
  • Distribution Functions
  • Estimators
  • False Alarms
  • Hypergeometric Functions
  • Notation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Real Variables
  • Shell Scripts
  • Statistical Analysis
  • Vector Spaces
  • Warning Systems
  • Wishart Matrices

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radar Systems Engineering.
  • Regression Analysis.