3D Reflectivity Reconstruction by Means of Spatially Distributed Kalman Filters

  • G. F. Schwarzenberg
  • U. Mayer
  • N. V. Ruiter
  • U. D. Hanebeck
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 35)

Abstract

In seismic, radar, and sonar imaging the exact determination of the reflectivity distribution is usually intractable so that approximations have to be applied. A method called synthetic aperture focusing technique (SAFT) is typically used for such applications as it provides a fast and simple method to reconstruct (3D) images. Nevertheless, this approach has several drawbacks such as causing image artifacts as well as offering no possibility to model system-specific uncertainties. In this paper, a statistical approach is derived, which models the region of interest as a probability density function (PDF) representing spatial reflectivity occurrences. To process the nonlinear measurements, the exact PDF is approximated by well-placed Extended Kalman Filters allowing for efficient and robust data processing. The performance of the proposed method is demonstrated for a 3D ultrasound computer tomograph and comparisons are carried out with the SAFT image reconstruction.

Keywords

Data association Extended Kalman filter Synthetic aperture focusing technique 3D image reconstruction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • G. F. Schwarzenberg
    • 1
  • U. Mayer
    • 1
  • N. V. Ruiter
    • 1
  • U. D. Hanebeck
    • 2
  1. 1.Institute for Data Processing and Electronics (IPE)Forschungszentrum KarlsruheGermany
  2. 2.Intelligent Sensor-Actuator-Systems Laboratory (ISAS), Institute of Computer Science and Engineering, Universitaet Karlsruhe (TH)KarlsruheGermany

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