Skip to main content
SpringerLink
Log in

De-noising of GPS Receivers Positioning Data Using Wavelet Transform and Bilateral Filtering

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The need for precise position and navigation aids in many areas of industry is becoming increasingly apparent. There are many errors associated with the navigation solution of the global positioning system (GPS), including satellite ephemeris error, satellite clock error, ionospheric delay, tropospheric delay, multipath, receiver measurement error and selective availability (SA). Noise can create an error between centimeters to several meters. In this paper, the proposed technique applied to smooth noise for GPS receiver positioning data is based upon the analysis of wavelet transform (WT), bilateral filter (BF) and diffusivity function. The WT is a powerful tool of signal processing for its multiresolutional possibilities. BF is a local, non-linear and non-iterative technique. It is applied to approximation subband. We decompose a GPS positioning data into low-frequency and high-frequency components and apply BF on the approximation coefficients and diffusivity function on the detail coefficients at each decomposition level for data smoothing. A single-frequency and low-cost commercial GPS receiver manufactured by Rockwell Company is used to test our method. The experimental results on measurement data demonstrate the effectiveness of the proposed method; so that the total root mean square (RMS) error reduces to less than 0.29 m with SA on and 0.15 m with SA off using Daubechie wavelet.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. MacDonald, J. T., Ucci, D. R., & LoCicero, J. L. (2008). Isolating multi-path effects from the position estimate residuals in GPS receivers. In IEEE conference on military communications, pp. 1–6.

  2. Fang B. T. (1990) Simple solutions for hyperbolic and related position fixes. IEEE Transactions on Aerospace and Electronic Systems 26(5): 748–753

    Article  Google Scholar 

  3. Koyama, Y., Liang, T. K., & Tanaka, T. (2009). High-precision GPS measurement for motorcycle trajectory using Kalman filter. In IEEE conference on networked sensing systems, pp. 1–4.

  4. Zhu, Z. S., Lu, D. J., & Wang, Q. (2008). Study on nerve-cell based real-time estimation method for gps multi-path error. In IEEE conference on machine learning and cybernetics, pp. 1455–1460.

  5. Shaw M., Sandhoo K., Turner D. (2000) Modernization of the global positioning system. GPS World 11(9): 36–44

    Google Scholar 

  6. Qiang, Q., Jiliu, Z., Kun, H., & Jian, L. (2005). Noise reduction based on wavelet transform under non-stationary environments. In IEEE conference on mechatronics and automation, pp. 2123–2129.

  7. Tomasi, C., & Manduchi, R. (1998). Bilateral filtering for gray and color images. In IEEE conference on computer vision, pp. 839–846.

  8. Anand, C. Sh., & Sahambi, J. S. (2008). MRI denoising using bilateral filter in redundant wavelet domain. In IEEE Conference on TENCON 2008, pp. 1–6.

  9. Lee, H. K. (2002). Time-propagated measurement fusion and its application to multipath detection and isolation, PhD dissertation, School of Electrical Engineering and Computer Science, Seoul National University.

  10. Hatch, R. R. (1982). The synergism of GPS code and carrier measurements. In Proceedings of the third international geodetic symposium on satellite doppler positioning (Vol. 2, pp. 1213–1232).

  11. Hwang P. Y. C., Brown R. G. (1990) GPS Navigation: Combining pseudorange with continuous carrier phase using a Kalman filter. Journal of the Institute of Navigation 37(2): 181–196

    Google Scholar 

  12. Bisnath, S. B., & Langley, R. B. (1999). Precise, efficient GPS-based geometric tracking of low earth orbiters. In Proceedings of the institute of navigation annual meeting, pp. 751–760.

  13. Ford T. J., Hamilton J. (2003) A new positioning filter: Phase smoothing in the position domain. Journal of the Institute of Navigation 50(2): 65–78

    Google Scholar 

  14. Lee H. K., Rizos C., Jee G. I. (2004) Design of kinematic DGPS filters with consistent error covariance information. IEE Proceedings on Radar, Sonar and Navigation 151(6): 382–388

    Article  Google Scholar 

  15. Lee H. K., Rizos C. (2008) Position-domain hatch filter for kinematic differential GPS/GNSS. IEEE Transactions on Aerospace and Electronic Systems 44(1): 30–40

    Article  Google Scholar 

  16. Nunes F. D., Leitão J. M. N., Sousa F. M. G. (2009) Nonlinear filtering in GNSS pseudorange dynamics estimation combining code delay and carrier phase. IEEE Journal of Selected Topics in Signal Processing 3(4): 639–650

    Article  Google Scholar 

  17. Kaplan E. D. (1996) Understanding GPS: Principle and applications. Artech House Publishers, Boston

    Google Scholar 

  18. Thipparthi, S. N. (2004). Improving positional accuracy using carrier smoothing techniques in inexpensive GPS receivers, M.S. Thesis, New Mexico State University.

  19. Kamarudin, N., & Amin, Z. M. (2004). Multipath error detection using different GPS receiver’s antenna. In 3rd FIG regional conference, pp. 1–11.

  20. Wu C. H., Su W. H., Ho Y. W. (2010) A study on GPS GDOP approximation using support-vector machines. IEEE Transactions on Instrumentation and Measurement, 60(1): 137–145

    Article  Google Scholar 

  21. Alkan, R. M., & Arslan, E. (2002). GPS standard positioning service performance after selective availability turned off. In International Symposium on GIS, pp. 1–9.

  22. Lilong, L., Hongyan, W., & Bin, L. (2010). Mitigation of systematic errors of gps positioning based on wavelet denoise. In Second WRI global congress on intelligent systems, pp. 253–255.

  23. Du, P., Lin, S. M., Kibbe, W. A., & Wang, H. (2007). Application of wavelet transform to the ms-based proteomics data preprocessing. In IEEE conference on bioinformatics and bioengineering, pp. 680–686.

  24. Zang M., Gunturk B. K. (2008) Multiresolution bilateral filtering for image denoising. IEEE Transactions on Image Processing 17(12): 2324–2333

    Article  MathSciNet  Google Scholar 

  25. Mustafa, Z. A., & Kadah, Y. M. (2011). Multi resolution bilateral filter for MR image denoising. In IEEE conference on biomedical engineering, pp. 180–184.

  26. Mrazek P., Weickert J., Steidl G. (2003) Correspondences between wavelet shrinkage and nonlinear diffusion. Lecture Notes in Computer Science 2695: 101–116

    Article  Google Scholar 

  27. Weickert J., ter Romeny B. M., Viergever M. A. (1998) Efficient and reliable schemes for nonlinear diffusion filtering. IEEE Transactions on Image Processing 7(3): 398–410

    Article  Google Scholar 

  28. Zodiac GPS Receiver Family Designer’s Guide. Rockwell Semiconductor Systems, GPS-33. (1996).

  29. Vizireanu D. N. (2011) A simple and precise real-time four point single sinusoid signals instantaneous frequency estimation method for portable DSP based instrumentation measurement. Journal of Measurement 44(2): 500–502

    Article  Google Scholar 

  30. Azami, H., Mosavi, M. R., & Sanei, S. (2012). Classification of GPS satellites using improved back propagation training algorithms. Journal of Wireless Personal Communications doi:10.1007/s11277-012-0844-7.

  31. Reis J., Sanguino J., Rodrigues A. (2012) Baseline influence on single-frequency GPS precise heading estimation. Journal of Wireless Personal Communications 64: 185–196

    Article  Google Scholar 

  32. Mosavi M. R. (2009) GPS data smoothing. Journal of Remote Sensing 22: 21–35

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846-13114, Iran

    M. R. Mosavi & I. EmamGholipour

Authors
  1. M. R. Mosavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. I. EmamGholipour
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. R. Mosavi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mosavi, M.R., EmamGholipour, I. De-noising of GPS Receivers Positioning Data Using Wavelet Transform and Bilateral Filtering. Wireless Pers Commun 71, 2295–2312 (2013). https://doi.org/10.1007/s11277-012-0936-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-012-0936-4

Keywords

Search

Navigation