Distributed Tracking with Consensus on Noisy Time-varying Graphs with Incomplete Data

Abstract

In this paper we address the problem of distributed tracking with consensus on a time-varying graph with incomplete data and noisy communication links. We develop a distributed and collaborative tracking with consensus algorithm by combining distributed Kalman filtering with consensus updates to handle a time-varying network topology in which not every node has local observations to generate own local tracking estimates. We introduce the concepts of active node set and connectivity graph to characterize such a network, and by merging these two, an effective network graph is obtained. Simulation results and performance analysis of the proposed algorithm are given and compared with that of distributed local Kalman filtering with centralized fusion.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2010
Accession Number
ADA560381

Entities

People

  • R. S. Erwin
  • Sudharman K. Jayaweera
  • Yongxiang Ruan

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Computing System Architectures
  • Consensus Algorithms
  • Data Science
  • Filtration
  • Information Science
  • Kalman Filtering
  • Kalman Filters
  • Network Topology
  • Observation
  • Simulations
  • Space Objects
  • Spacecraft
  • Statistical Algorithms
  • Statistics
  • Topology

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Graph Algorithms and Convex Optimization.