Applying Random Search Algorithms to Target Motion Analysis.

Abstract

This report addresses the use of random search algorithms for estimating contact state parameters. Specifically, simulated annealing and genetic algorithms are developed and their performance is examined. In addition, a method is presented for using these algorithms as either stand-alone target state estimation techniques, or as methods for initializing gradient or grid-based estimation techniques in a hybrid system. Performance of these algorithms is examined via Monte Carlo simulation using surface ship active data.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 1995
Accession Number
ADA305972

Entities

People

  • A. H. Silva
  • D. J. Ferkinhoff
  • K. F. Gong
  • S. E. Hammel

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Annealing
  • Data Science
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Heuristic Methods
  • Hybrid Systems
  • Information Science
  • Mathematics
  • Monte Carlo Method
  • Simulations
  • Statistical Algorithms

Fields of Study

  • Computer science
  • Engineering

Readers

  • Approximation Theory.
  • Operations Research
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Biotechnology