• DocumentCode
    1447605
  • Title

    Decentralised detection strategies under communication constraints

  • Author

    Gini, F. ; Lombardini, F. ; Verrazzani, L.

  • Author_Institution
    Dipt. di Ingegneria dell´´Inf., Pisa Univ., Italy
  • Volume
    145
  • Issue
    4
  • fYear
    1998
  • fDate
    8/1/1998 12:00:00 AM
  • Firstpage
    199
  • Lastpage
    208
  • Abstract
    Decentralised detection systems with parallel decision fusion topology have received significant attention, especially for surveillance radar systems. Typically, a deterministic test (DT) is employed, and the optimal local decision strategies and the fusion rule are determined according to the Neyman-Pearson (N-P) criterion. The authors show how, in practical applications, the communication bottle-neck may significantly limit the detection performance of distributed systems employing a conventional DT. A paradigm is introduced for decentralised detection under communication constraints, based on the concept of dependent randomisation (or scheduling) of the local decision and fusion rules. Numerical results show that the proposed approach provides improved performance over decentralised detection strategies based on deterministic tests, with a moderate increase in system complexity; the improvement is particularly noticeable in spiky (non-Gaussian) clutter environments
  • Keywords
    distributed processing; optimisation; radar clutter; radar detection; random processes; search radar; Neyman-Pearson criterion; communication bottleneck; communication constraints; decentralised detection systems; dependent randomisation; detection performance; deterministic test; distributed systems; fusion rule; nonGaussian clutter; optimal local decision; scheduling; spiky clutter environments; surveillance radar systems; system complexity;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar and Navigation, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2395
  • Type

    jour

  • DOI
    10.1049/ip-rsn:19982129
  • Filename
    731934