Title :
An Omega-K Algorithm for Translational Invariant Bistatic SAR Based on Generalized Loffeld´s Bistatic Formula
Author :
Junjie Wu ; Zhongyu Li ; Yulin Huang ; Jianyu Yang ; Qing Huo Liu
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
In this paper, an omega-K imaging algorithm to focus the raw data of translational invariant (TI) bistatic synthetic aperture radar (BSAR) is proposed. The method utilizes a point target reference spectrum of generalized Loffeld´s bistatic formula (GLBF). Without the bistatic deformation term, GLBF is the latest development of Loffeld´s bistatic formula. It is comparable in precision with the method of series reversion (MSR), but it has a much simpler form than MSR and a similar form to a monostatic case. Based on the spatial linearization of GLBF, the Stolt transformation relationship is derived. The method can consider the linear spatial variation of Doppler parameters, which is always ignored in previous publications about bistatic omega-K algorithms. This method can handle the cases of TI BSAR with high squint angles and large bistatic degrees. 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.
Keywords :
Doppler radar; compensation; numerical analysis; radar imaging; synthetic aperture radar; Doppler parameter; GLBF; MSR; Stolt transformation relationship; TI BSAR; bistatic deformation term; bistatic omega-K imaging algorithm; compensation method; experimental data processing; generalized Loffeld bistatic formula; method of series reversion; numerical simulation; phase error; spatial linearization variation; translational invariant bistatic SAR; Approximation algorithms; Azimuth; Doppler effect; Imaging; Interpolation; Receivers; Transmitters; Bistatic synthetic aperture radar (BSAR); Stolt transformation; generalized Loffeld´s bistatic formula (GLBF); omega-K algorithm;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2014.2301433