Multi-Sensor Architectures

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 110)

Abstract

The use of multiple sensors typically requires the fusion of data from different type of sensors. The combined use of such a data has the potential to give an efficient, high quality and reliable estimation. Input data from different sensors allows the introduction of target attributes (target type, size) into the association logic. This requires a more general association logic, in which both the physical position parameters and the target attributes can be used simultaneously. Although, the data fusion from a number of sensors could provide better and reliable estimation but abundance of information is to be handled. Therefore, more extensive computer resources are needed for such a system. The parallel processing technique could be an alternative for such a system. The main objective of this research is to provide a real time task allocation strategy for data processing using multiple processing units for same type of multiple sensors, typically radar in our case.

Keywords

Target tracking Data fusion Sensor level Parallel processing 

References

  1. 1.
    Blackman SS (1986) Multiple target tracking with radar applications. Dedham, MA, Artech House, Inc.Google Scholar
  2. 2.
    Farina A, Studer FA (1986) Radar data processing. Research Studies. Letchworth, England/ New York, Research Studies Press, Ltd./John Wiley and Sons, Inc.Google Scholar
  3. 3.
    Hall DL, McMullen SAH (2004) Mathematical techniques in multi-sensor data fusion. Artech house inc, USAGoogle Scholar
  4. 4.
    Akbar Hussain DM (1991) Some implementations of multiple target tracking algorithms on transputers. PhD thesisGoogle Scholar
  5. 5.
    Akbar Hussain DM, Ahmed Z, Khan MZ, Valente A (2011) Proceedings of the international multi-conference of engineers and computer scientists 2011 Vol. II, IMECS 2011, Hong Kong, 16–18 March 2011Google Scholar
  6. 6.
    Singer RA, Stein JJ (1971) An optimal tracking filter for processing sensor data of imprecisely determined origin in surveillance systems Prods. of the 1971 IEEE conference on decision and control, Dec. 1971, Miami beachGoogle Scholar
  7. 7.
    Bar-Shalom Y (1981) On the track to track correlation problem, IEEE Trans Automatic Control, 26:571–572CrossRefMATHMathSciNetGoogle Scholar
  8. 8.
    Bar-Shalom Y, Fortmann TE (1988) Tracking and data association. Academic PressGoogle Scholar
  9. 9.
    Bridgewater AW (1978) Analysis of second and third order steady state tracking filter. AGARD conference proceedings no. 252Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Energy TechnologyAalborg University DenmarkEsbjergDenmark
  2. 2.Pakistan Institute of Laser and OpticsRawalpindiPakistan

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