Model Based Classification Using Multi-Ping Data

Abstract

This paper proposes a method of target classification using three dimensional (3-D) data. The data consists of multiple realizations (pings) of range versus bearing plots, so the three dimensions of the data are range, bearing and time (or pings). The data is assumed to consist of independent nonidentically distributed complex gaussian noise, and a target. The Target (TGT) is of known constant size (extent in range and bearing) and known speed. The TGT power, and heading are unknown. In the derivation of the classifier a normalization step is necessary and we propose an approach to the normalization of multidimensional (m-D) data. This paper contains the derivation of the classifier, a description of the normalizer, a description of the algorithm that follows from the classifier and simulation results.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA498291

Entities

People

  • Christopher P. Carbone
  • Steven Kay

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Computer Simulations
  • Computing-Related Activities
  • Data Science
  • Data Sets
  • False Alarms
  • Gaussian Noise
  • Geometry
  • Information Operations
  • Noise
  • Random Variables
  • Simulations
  • Three Dimensional
  • Two Dimensional
  • Undersea Warfare

Fields of Study

  • Engineering

Readers

  • Aerosol Science/Aerosol Physics
  • Radar Systems Engineering.
  • Statistical inference.