Skip to main content

Sensor Fusion

  • Chapter
  • First Online:
Micro-Optics and Energy

Abstract

The fusion of sensors or data is today often used for increasing precision in navigation, position and location of mobile objects in the shipping industry, GPS systems, and smartphones. This is due in part that some information may not be reliable when using the sensor data sources individually. By fusing several independent sensors containing individual information, their combined data may represent precise and usable information or distributions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Sarma VVS, Raju S (1991) Multisensor data fusion and decision support for airborne target identification. IEEE Trans Syst Man Cybern 21(5):1224–1230

    Article  Google Scholar 

  2. Hoover A, Olsen BD (2000) Sensor network perception for mobile robotics. In: Proceedings 2000 ICRA millennium conference IEEE international conference on robotics and automation symposia proceedings (Cat No 00CH37065). IEEE, pp 342–347

    Google Scholar 

  3. Lamb JJ, Bernard O, Sarker S, Lien KM, Hjelme DR (2019) Perspectives of optical colourimetric sensors for anaerobic digestion. Renew Sustain Energy Rev 111:87–96

    Google Scholar 

  4. Bishop G, Welch G (2001) An introduction to the Kalman filter. Proc SIGGRAPH, Course 8(27599–23175):41

    Google Scholar 

  5. Åström KJ, Wittenmark B (2013) Computer-controlled systems: theory and design. Courier Corporation, North Chelmsford

    Google Scholar 

  6. Shaked U, Theodor YH (1992) sub infinity/-optimal estimation: a tutorial. In: Proceedings of the 31st IEEE conference on decision and control. IEEE, pp 2278–2286

    Google Scholar 

Download references

Acknowledgements

The authors are grateful to the ENERSENSE programme and NTNU Team Hydrogen at the Norwegian University of Science and Technology (NTNU) for supporting and helping on this book project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jacob J. Lamb .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Muri, H.I., Wahl, M., Lamb, J.J., Snilsberg, R.K., Hjelme, D.R. (2020). Sensor Fusion. In: Lamb, J., Pollet, B. (eds) Micro-Optics and Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-43676-6_5

Download citation

Publish with us

Policies and ethics