A Robust Motion Error Estimation Method Based on Raw Data

Abstract

High-resolution airborne synthetic aperture radar (SAR) systems are very sensible to deviations of the aircraft from the reference track. In high-resolution imagery, the improvement of range resolution increases the difficulty of implementing range cell migration correction (RCMC), while a wider synthetic aperture increases the cumulative time of motion errors which will affect the image quality. To enable accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, due to the limit of accuracy of such systems, motion errors are hard to be compensated correctly, causing mainly the resolution decrease in final image. Moreover, in large swath mode, the range-dependent phase errors are difficult to be compensated by using the conventional autofocus algorithm only. In this paper, we propose a robust motion error estimation method based on raw SAR data. To apply this estimation method, we first estimate the double phase gradients in subaperture. Second, a filtering method based on curve fitting was proposed to reduce the phase estimation errors caused by low signal-to-clutter ratio (SCR). Finally, we propose a weighted total least square method to calculate the motion errors using the filtered phase gradients. Because the proposed algorithm is nonparametric, it can estimate high-order motion errors. This is very important for the airborne SAR, particularly the light aircraft SAR platform, due to their more complicated movement in air turbulence. The versatility that the proposed method can be used in any imaging algorithms is another advantage. The processing of large number of raw SAR data shows that the algorithm is as robust and practical as phase gradient autofocus and can generate better focused images.Index Terms-Autofocus, motion error estimation, phase gradient filtering, synthetic aperture radar (SAR), weighted total least square (WTLS) method.

Integrated Data Processing Methodology for Airborne Repeat-pass Differential SAR Interferometry

“…The residual motion errors estimation methods from individual imagery can also help to improve the focusing quality in the azimuth, when the estimated residual errors are applying back to the imaging processing. Many studies have been reported on the airborne SAR motion compensation (Fornaro 1999;Fornaro, Franceschetti, and Perna 2005;Li et al 2013;Prats, Reigber, and Mallorqui 2005;Li et al 2012). Howerver, few literatures just focuse on the residual motion errors estimation from the individual SAR imagery.…”

A new method for consistent intensity adjustment on azimuth in SAR images of low altitude platforms

“…In practice, the normalization factor is the average of data within the center part of one line. The traditional method to compute the normalization factor is expressed as formula (1).…”

“…But the unsteadiness is the generally shortcoming of these low altitude platforms [1]~ [7]. The unsteadiness of the low altitude platforms leads to the instability of the antenna beam center.…”

Along-Track Motion Compensation for Strip-Map Sar Based on Resampling

“…However, one of the problems is that the data rate of INU or GPS is usually much lower than the azimuth sampling frequency, while the interpolation may bring about extra errors and reduce the precision. The other commonly used way to obtain the motion error is to estimate the trajectory deviation directly from the raw data [7][8][9][10][11][12][13][14][15][16][17]. It is based on the concept that the uniformly azimuth-sampled data without motion errors has its intrinsic coherence, while the motion error is random.…”