Multi-baseline phase unwrapping algorithm based on the unscented Kalman filter

Access Full Text

Multi-baseline phase unwrapping algorithm based on the unscented Kalman filter

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Radar, Sonar & Navigation — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A new multi-baseline phase unwrapping algorithm based on the unscented Kalman filter (UKF) for SAR interferometry is proposed. This method is the result of combining a UKF with a path-following strategy and an omni-directional local phase slope estimator. This technology simultaneously performs noise filtering and phase unwrapping by an optimal data fusion approach. In addition, phase slope will be directly estimated from the sample frequency spectrum of the complex interferogram, by which the underestimation of phase slope is overcome. Results obtained with synthetic and real data validate the effectiveness of the proposed method.

Inspec keywords: radar interferometry; sensor fusion; Kalman filters; synthetic aperture radar

Other keywords: multibaseline phase unwrapping algorithm; omni-directional local phase slope estimator; sample frequency spectrum; unscented Kalman filter; SAR interferometry; noise filtering; path-following strategy; optimal data fusion approach

Subjects: Filtering methods in signal processing; Geophysical techniques and equipment; Radar equipment, systems and applications

References

    1. 1)
    2. 2)
      • Hui, L., Yinqing, Z., Huaping, X., Chunsheng, L.: `A simple implementation of multi-baseline INSAR', 2007 First Asian and Pacific Conf. on Synthetic Aperture Radar Proc., November 2007, Huangshan, China, p. 747–750.
    3. 3)
    4. 4)
    5. 5)
      • Julier, S.J.: `The scaled unscented transformation', Proc. American Control Conf., May 2002, Anchorage, USA, p. 4555–4559.
    6. 6)
    7. 7)
    8. 8)
      • Kim, M.G., Griffiths, H.D.: `Phase unwrapping of multibaseline interferometry using Kalman filtering', Image Processing and its Applications, Conf. IEE., 1999, p. 813–817.
    9. 9)
      • Wahl, D.E.: `Improved SAR interferometric processing using local phase-slope correction', Proc. SPIE – The Int. Society for Optical Engineering, April 2007, Orlando, USA, p. 103–107.
    10. 10)
      • Lombardini, F., Lombardo, P.: `Maximum likelihood array SAR interferometry', IEEE Digital Signal Processing Workshop, September 1996, Loen, Norway, p. 358–361.
    11. 11)
      • Ghiglia, D.C., Wahl, D.E.: `Interferometric synthetic aperture radar terrain elevation mapping from multiple observations', Proc. Sixth IEEE Digital Signal Processing Workshop, October 1994, Albuquerque, USA, p. 33–36.
    12. 12)
      • Lombardo, P., Lombardini, F.: `Multi-baseline SAR interferometry for terrain slope adaptivity', IEEE National Radar Conf. Proc., May 1997, New York, USA, p. 196–201.
    13. 13)
    14. 14)
    15. 15)
      • Nies, H., Loffeld, O., Wang, R.: `Phase unwrapping using 2D-Kalman filter potential and limitations', Proc. 2008 IEEE Int. Geoscience and Remote Sensing Symp., July 2008, Boston, USA, p. 1213–1216.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rsn.2010.0073
Loading

Related content

content/journals/10.1049/iet-rsn.2010.0073
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading