Skip to main content

The TDOA and FDOA Algorithm of Communication Signal Based on Fine Classification and Combination

  • Conference paper
  • First Online:
Communications, Signal Processing, and Systems (CSPS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 571))

  • 49 Accesses

Abstract

In order to solve the high precision and high time efficiency TDOA and FDOA estimation of communication signal in multi-station location system, we proposed an estimation algorithm based on fine classification and combination. Through the design of different fine classification series number, the algorithm can reduce the operation time effectively, and the estimation accuracy of TDOA and FDOA are developed by adopting the quadratic surface fitting. Simulation results show that when the carrier to noise ratio(CNR) is −5 to 5 dB, the estimation accuracy of TDOA is 20–100 ns, the estimation accuracy of FDOA is 45–100 MHz, which are improved by 3–4 times compared with the traditional estimation algorithm. Meanwhile, the operation time is reduced by more than one half according to the different fine classification series.

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 629.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 799.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 799.99
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. Ho KC, Chan YT (1997) Geolocation of a known altitude object from TDOA and FDOA measurements. IEEE Trans Aerosp Electron Syst 33(3):770–783

    Article  Google Scholar 

  2. Stein S (1981) Algorithms for ambiguity function processing. IEEE Trans Acoust Signal Process 29(3):1467–1472

    Google Scholar 

  3. Weiss LG (1994) Wavelets and wideband correlation processing. IEEE Signal Process Mag:13–32

    Google Scholar 

  4. Robert JU, Evaggelos G (1999) Wideband TDOA/FDOA processing using summation of short-time CAF’s. IEEE Trans Signal Process 47(12):193–200

    Google Scholar 

  5. Robert KO (1989) Frequency difference of arrival accuracy. IEEE Trans Acoust Signal Process 37(2):306–308

    Article  Google Scholar 

  6. Yeredor A, Angel E (2011) Joint TDOA and FDOA estimation: a conditional bound and its use for optimally weighted localization. IEEE Trans Signal Process 59(4):1612–1623

    Article  Google Scholar 

  7. Weiss AJ (2011) Direct geolocation of wideband emitters based on delay and doppler. IEEE Trans Signal Process 59(6):2513–2521

    Article  MathSciNet  Google Scholar 

  8. Ho KC (2012) Bias reduction for an explicit solution of source localization using TDOA. IEEE Trans Signal Process 60(5):2101–2114

    Article  MathSciNet  Google Scholar 

  9. Yu H, Huang G, Gao J et al (2012) An efficient constrained weighted least squares algorithm for moving source location using TDOA and FDOA measurements. IEEE Trans Wireless Commun 11(1):44–47

    Article  Google Scholar 

  10. Xu B, Sun G, Yu R et al (2013) High-accuracy TDOA-based localization without time synchronization. IEEE Trans Parallel Distrib Syst 24(8):1567–1576

    Article  Google Scholar 

  11. Meng W, Xie L, Xiao W (2013) Decentralized TDOA sensor pairing in multihop wireless sensor networks. IEEE Signal Process Lett 20(2):181–184

    Article  Google Scholar 

  12. Huang J, Wan Q (2012) Analysis of TDOA and TDOA/SS based geolocation techniques in a non-line-of-sight environment. J Commun Netw 14(5):533–539

    Article  Google Scholar 

  13. Hara S, Anzai D, Yabu T et al (2013) A perturbation analysis on the performance of TOA and TDOA localization in mixed LOS/NLOS environments. IEEE Trans Commun 61(2):679–689

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chi Zhang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, C. (2020). The TDOA and FDOA Algorithm of Communication Signal Based on Fine Classification and Combination. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_55

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-9409-6_55

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics