Optimal Smoothing and Estimation for Hybrid State Processess,

Abstract

Document considers the estimation and smoothing problem for a hierarchical Markov process. The supremal state evolves autonomously; infemal dynamics and observations may be statistically dependent on the supremal state. This class of processes has more structure than a general Markov process; the implications of this structure are developed here. Of special interest is the case of hybrid systems, where the supremal state is discrete and the infemal dynamics are linear and Gaussian. This structure commonly appears in diverse applications, including failure detection, maneuvering target tracking, and digital communications on analog channels. It is also the structure for which the most useful conclusions can be drawn. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA124907

Entities

People

  • F. Bruneau
  • R. R. Tenney

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Computations
  • Covariance
  • Detection
  • Engineering
  • Failure Mode And Effect Analysis
  • Filters
  • Filtration
  • Hybrid Systems
  • Kalman Filters
  • Markov Processes
  • Mathematical Analysis
  • Probability
  • Sequences
  • Statistics
  • Trajectories

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.