A Generalized Omega-K Algorithm to Process Translationally Variant Bistatic-SAR Data Based on Two-Dimensional Stolt Mapping

作者：Wu, Junjie^*; Li, Zhongyu; Huang, Yulin; Yang, Jianyu; Liu, Qing Huo

来源：IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(10): 6597-6614.

DOI：10.1109/TGRS.2014.2299069

• Bistatic synthetic aperture radar (BSAR)
• generalized Loffeld's bistatic formula (LBF) (GLBF)
• Omega-K algorithm
• 2-D spatial variation
• 2-D Stolt mapping

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.

• 出版日期2014-10
• 单位电子科技大学