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

• Published in: IEEE transactions on geoscience and remote sensing Vol. 52; no. 10; pp. 6597 - 6614
• Main Authors: Wu, Junjie, Li, Zhongyu, Huang, Yulin, Yang, Jianyu, Liu, Qing Huo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 2-D spatial variation; 2-D Stolt mapping; Algorithms; Azimuth; Bistatic synthetic aperture radar (BSAR); Data processing; Doppler effect; Frequency-domain analysis; generalized Loffeld's bistatic formula (LBF) (GLBF); Geometry; Imaging; Invariants; Linearization; Mapping; Mathematical models; Omega-K algorithm; Phase error; Radar; Receivers; Synthetic aperture radar; Transformations; Transmitters; 2-D Stolt mapping; Omega-K algorithm; Bistatic synthetic aperture radar (BSAR); generalized Loffeld's bistatic formula (LBF) (GLBF); 2-D spatial variation
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2014.2299069

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.