• DocumentCode
    2950341
  • Title

    Multi Sensor Data Fusion Methods Using Sensor Data Compression and Estimated Weights

  • Author

    Bardwaj, A. Anand ; Anandaraj, M. ; Kapil, K. ; Vasuhi, S. ; Vaidehi, V.

  • Author_Institution
    Anna Univ., Chennai
  • fYear
    2008
  • fDate
    4-6 Jan. 2008
  • Firstpage
    250
  • Lastpage
    254
  • Abstract
    When data fusion is performed in a distributed environment, it improves accuracy but the constraints are limited communication bandwidth and limited processing capability at the fusion center. So, it is crucial to compress the data at the fusion center. This is accomplished by reducing the dimension of the data. Based on the Linear Estimation and weighted least square fusion results, a method is presented for compressing data at each local sensor to improve the accuracy of the fused estimates. Another method for multi sensor data fusion with estimated weights is also suggested in this paper which also improves the accuracy of the fused estimates.
  • Keywords
    data compression; sensor fusion; fusion center; multisensor data fusion methods; sensor data compression; Covariance matrix; Data compression; Equations; Filters; Noise measurement; Performance evaluation; Radar tracking; Sensor fusion; Sensor systems; Target tracking; Multi sensor data fusion; covariance matching method; singular value decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communications and Networking, 2008. ICSCN '08. International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-1924-1
  • Electronic_ISBN
    978-1-4244-1924-1
  • Type

    conf

  • DOI
    10.1109/ICSCN.2008.4447198
  • Filename
    4447198