A generalized omega-K algorithm to process translationally variant bistatic-SAR data based on two-dimensional stolt mapping

Published

Journal Article

In translationally variant (TV) bistatic synthetic aperture radar (BSAR), 2-D spatial variation is a major problem to be tackled. In this paper, a generalized Omega-K imaging algorithm to deal with this problem is proposed. The method utilizes a point target reference spectrum of the generalized Loffeld's bistatic formula (LBF) (GLBF). Without the bistatic-deformation term, GLBF is the latest development of LBF. Similar to the monostatic case, it has a much simpler form than other point target reference spectra. Based on the spatial linearization of GLBF, the Stolt mapping relationship is derived. Different from the traditional Omega-K algorithms for monostatic SAR and translationally invariant BSAR, this approach uses a 2-D Stolt frequency transformation. Through this transformation, the method can deal with the 2-D spatial variation. It can also consider the linear spatial variation of Doppler parameters, which is usually not considered in the previous publications on bistatic Omega-K algorithms. This method can handle the cases of TV-BSAR with different trajectories, different velocities, high squint angles, and large bistatic angles. In addition, a compensation method for the phase error caused by the linearization is discussed. Numerical simulations and experimental data processing verify the effectiveness of the proposed method. © 1980-2012 IEEE.

Full Text

Duke Authors

Cited Authors

  • Wu, J; Li, Z; Huang, Y; Yang, J; Liu, QH

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 52 / 10

Start / End Page

  • 6597 - 6614

International Standard Serial Number (ISSN)

  • 0196-2892

Digital Object Identifier (DOI)

  • 10.1109/TGRS.2014.2299069

Citation Source

  • Scopus