Determining the Rank of a Noisy Square Matrix Using the Characteristic Coefficients.

Abstract

Determining the rank of a matrix has several important applications. In modern array processing, the rank can be used to determine the number of targets detected. Radar normally performs this operation prior to determining the direction and velocity of each air platform. Also, sonar performs this operation before it attempts to classify submarines. It is therefore essential that the rank of the signal matrix be determined efficiently and accurately. It is assumed that the signal matrix is square and free of a nilpotent part. Unfortunately, there is usually noise added to the elements of the signal matrix due to such factors as the background in which the signal is embedded or instrument uncertainty. This paper describes a method for predicting the rank of a signal matrix by analyzing the coefficients of the characteristic polynomial of the noisy version of this matrix. These coefficients can be computed from algebraic sums of products of the elements. Time consuming iterations, which take place in methods involving singular values, are avoided. Furthermore, the results are shown to compare favorably to those produced by a singular value approach.

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Document Details

Document Type
Technical Report
Publication Date
Jul 15, 1996
Accession Number
ADA313748

Entities

People

  • Peter F. Stiller
  • Robert M. Williams
  • Ronald F. Gleeson

Organizations

  • Naval Air Warfare Center Aircraft Divison

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aerial Warfare
  • Algorithms
  • Coefficients
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Programs
  • Equations
  • Fluid Dynamics
  • Mathematics
  • Military Research
  • Monte Carlo Method
  • Polynomials
  • Simulations
  • Standards
  • Statistical Analysis
  • Uncertainty

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Statistical inference.