Application of Mathematical Signal Processing Techniques to Mission Systems. (l'Application des techniques mathematiques du traitement du signal aux systemes de conduite des missions)

Abstract

Presents a whole range of perspectives for different levels of mathematical signal processing, based on some of the most promising techniques. Particular attention is paid to the following subjects: (1) Wavelet analysis: summary of the possibilities; application to detection in natural background radiation and extraction of primitive invariants. (2) The concept of Multirate Filter Banks in conjunction with the various transforms which this technique enables; applications to compressed video image and sequence transmission, to noise rejection, to jamming and to encoding. (3) Variational methods based on partial derivative equations for image processing and multi-scale video sequences; presentation of different image segmentation approaches; and (4) Multi-sensor processing based on the theory of evidence: processing of the functions of detection, classification, matching of ambiguous observations, or tracking, with the aim of solving problems such as data modelling, decision making, the management of non-uniform reference systems, or the integration of contextual knowledge.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1999
Accession Number
ADA372225

Entities

Organizations

  • NATO Science and Technology Organization

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computational Science
  • Data Compression
  • Data Science
  • Databases
  • Detection
  • Detectors
  • Frequency Bands
  • Image Processing
  • Information Processing
  • Information Science
  • Mathematical Filters
  • Modulation
  • Pattern Recognition
  • Statistical Algorithms
  • Three Dimensional
  • Two Dimensional

Readers

  • Control Systems Engineering.
  • Neural Network Machine Learning.
  • Small Business Innovation Research Program (SBIR) EDI Research and Innovation.