skip to main content
10.1145/2348543.2348587acmconferencesArticle/Chapter ViewAbstractPublication PagesmobicomConference Proceedingsconference-collections
research-article

Faster GPS via the sparse fourier transform

Published:22 August 2012Publication History

ABSTRACT

GPS is one of the most widely used wireless systems. A GPS receiver has to lock on the satellite signals to calculate its position. The process of locking on the satellites is quite costly and requires hundreds of millions of hardware multiplications, leading to high power consumption. The fastest known algorithm for this problem is based on the Fourier transform and has a complexity of O(n log n), where n is the number of signal samples. This paper presents the fastest GPS locking algorithm to date. The algorithm reduces the locking complexity to O(n√(log n)). Further, if the SNR is above a threshold, the algorithm becomes linear, i.e., O(n). Our algorithm builds on recent developments in the growing area of sparse recovery. It exploits the sparse nature of the synchronization problem, where only the correct alignment between the received GPS signal and the satellite code causes their cross-correlation to spike.

We further show that the theoretical gain translates into empirical gains for GPS receivers. Specifically, we built a prototype of the design using software radios and tested it on two GPS data sets collected in the US and Europe. The results show that the new algorithm reduces the median number of multiplications by 2.2x in comparison to the state of the art design, for real GPS signals.

References

  1. FFTW 3.2.3. http://www.fftw.org.Google ScholarGoogle Scholar
  2. B. Buchli, F. Sutton, and J. Beutel. GPS-equipped wireless sensor network node for high-accuracy positioning applications. In EWSN 2012, Trento, Italy. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. N. Bulusu, J. Heidemann, and D. Estrin. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, Oct. 2000.Google ScholarGoogle ScholarCross RefCross Ref
  4. C. Cheng and K. Parhi. Low-cost fast VLSI algorithm for discrete fourier transform. IEEE Transactions on Circuits and Systems, April 2007.Google ScholarGoogle Scholar
  5. Dexter Industries. dGPS for LEGO MINDSTORMS NXT. http://dexterindustries.com.Google ScholarGoogle Scholar
  6. G. Djuknic and R. Richton. Geolocation and assisted GPS. Computer, 34(2):123 --125, feb 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. S. Electronics. Sige gn3s sampler v3. http://www.sparkfun.com.Google ScholarGoogle Scholar
  8. C. Fernandez-Prades, J. Arribas, P. Closas, C. Aviles, and L. Esteve. GNSS-SDR: an open source tool for researchers and developers. In ION GNSS Conference, 2011.Google ScholarGoogle Scholar
  9. G. Fleishman. How the iphone knows where you are. Macworld, Aug. 2011.Google ScholarGoogle Scholar
  10. G. Fleishman. Inside assisted GPS: helping GPS help you. Arstechnica, Jan. 2009.Google ScholarGoogle Scholar
  11. A. C. Gilbert, S. Muthukrishnan, and M. Strauss. Improved time bounds for near-optimal sparse fourier representations. In SPIE Wavelets XI, 2003.Google ScholarGoogle Scholar
  12. A. Goldsmith. Wireless Communications. Cambridge University Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. S. Gossett. GPS implant makes debut. WND, May 2003.Google ScholarGoogle Scholar
  14. H. Hassanieh, P. Indyk, D. Katabi, and E. Price. Nearly optimal sparse fourier transform. In STOC 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. H. Hassanieh, P. Indyk, D. Katabi, and E. Price. Simple and practical algorithm for sparse fourier transform. In SODA'12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Heiskala and J. Terry. OFDM Wireless LANs: A Theoretical and Practical Guide. Sams Publishing, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. A. Hepburn. Infographic: Mobile stats & facts 2011. Digital Buzz, April 2011.Google ScholarGoogle Scholar
  18. E. Inc. Universal software radio peripheral. http://ettus.com.Google ScholarGoogle Scholar
  19. J. L. Jani Jarvinen, Javier DeSalas. Assisted GPS: A low-infrastructure approach. GPSWorld, March 2002.Google ScholarGoogle Scholar
  20. E. D. Kaplan. Understanding GPS Principles and Applications. Artech House Publishers, Feb. 1996.Google ScholarGoogle Scholar
  21. M. Karim and M. Sarraf. W-CDMA and CDMA2000 for 3G mobile networks. McGraw-Hill, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. J. Matousek. On variants of the johnson-lindenstrauss lemma. Random Structures & Algorithms, 33(2), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Maxim IC. MAX2745 single-chip global positioning system front-end downconverter. http://www.maxim-ic.com.Google ScholarGoogle Scholar
  24. R. J. L. Mohamed Sahmoudi, Moeness G. Amin. Acquisition of weak gnss signals using a new block averaging pre-processing. In IEEE/ION Position, Location and Navigation Symposium 2008.Google ScholarGoogle Scholar
  25. D. Niculescu and B. Nath. Ad hoc positioning system (APS). In IEEE GLOBECOM, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  26. Nikon USA. Coolpix p6000. http://www.nikonusa.com.Google ScholarGoogle Scholar
  27. OProfile. Linux profiler. http://oprofile.sourceforge.net.Google ScholarGoogle Scholar
  28. OriginGPS. ORG447X series datasheet. http://www.acaltechnology.com.Google ScholarGoogle Scholar
  29. Perthold Engineering LLC. SkyTraq Venus 6 GPS Module. http://www.perthold.de.Google ScholarGoogle Scholar
  30. G. Pisier. The Volume of Convex Bodies and Banach Space Geometry. Cambridge University Press, May 1999.Google ScholarGoogle Scholar
  31. D. Plausinaitis. GPS receiver technology mm8. Danish GPS Center, http://kom.aau.dk.Google ScholarGoogle Scholar
  32. J. Rabaey, A. Chandrakasan, and B. Nikolic. Digital integrated circuits. Prentice-Hall, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. H. S. Ramos, T. Zhang, J. Liu, N. B. Priyantha, and A. Kansal. Leap: a low energy assisted GPS for trajectory-based services. In ACM Ubicomp 2011, pages 335--344, Beijing, China. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. D. Raskovic and D. Giessel. Battery-Aware embedded GPS receiver node. In IEEE MobiQuitous, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. T. Tan, G. Bi, Y. Zeng, and H. Tan. Dct hardware structure for sequentially presented data. Signal Processing, 81(11), 2001.Google ScholarGoogle Scholar
  36. A. C. Team. Fundamentals of Global Positioning System Receivers: A Software Approach. Wiley-Interscience, 2000.Google ScholarGoogle Scholar
  37. Ted Schadler. GPS: Personal Navigation Device. Texas Instruments. http://www.ti.com.Google ScholarGoogle Scholar
  38. A. Thiagarajan, L. Ravindranath, H. Balakrishnan, S. Madden, and L. Girod. Accurate, low-energy trajectory mapping for mobile devices. In NSDI 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. D. Van Nee and A. Coenen. New fast GPS code-acquisition technique using FFT. Electronics Letters, 27(2), Jan 1991.Google ScholarGoogle Scholar

Index Terms

  1. Faster GPS via the sparse fourier transform

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        Mobicom '12: Proceedings of the 18th annual international conference on Mobile computing and networking
        August 2012
        484 pages
        ISBN:9781450311595
        DOI:10.1145/2348543

        Copyright © 2012 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 22 August 2012

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate440of2,972submissions,15%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader