Ship Velocity Estimation in Airborne Along-Track Interferometric SAR Imagery Based on the Fractional Fourier Transform

Chao Chen,Yan Li,Linlin Zhang,Kewei Ouyang,Kuihua Huang,Yonghong Long,Chien-Jen Wang

doi:10.1155/2020/5835620

Abstract

Synthetic aperture radar (SAR) was originally exploited to image stationary scenes. However, it is important to derive target information of velocity for many applications. The fractional Fourier transform (FrFT) is a generalization of the classical Fourier transform and is well-known as a useful tool to estimate the chirp rate of linear frequency-modulated (LFM) signals. Motion compensation is critical to moving target imaging. It is difficult for us to obtain the actual motion parameters in real scenarios. Based on the moving target echo model in airborne along-track interferometric SAR (ATI-SAR) and expression of the ATI phase, a method is proposed to estimate the ship velocity by combining the ATI phase with FrFT. First, we use the FrFT to evaluate the chirp rate of the moving target echo. Then, we construct an equation to estimate the ship velocity using the chirp rate estimation, peak response time, and ATI phase. Finally, the simulation experiments are used to validate the effectiveness of the proposed method.

Highlights

Sea traffic monitoring is one of the most important applications of synthetic aperture radar (SAR) imagery
Estimated outputs are often a combination of range, bearing, and Doppler frequency. e moving target echo model has a huge impact on velocity estimation; that is, the model accuracy has a great influence on algorithm accuracy, and the along-track interferometry (ATI) phase has a proven ability to estimate radial velocity [35]. erefore, we provide a brief overview of the echo model for moving targets and expression of the ATI phase used in our proposed method
The SAR systems such as TanDEM-X could provide high-resolution complex image data [45], so the method implemented in image domain might have more practicability than the method achieved in RD domain. erefore, in the scope of this study, we consider the velocity estimation realized in image domain rather than RD domain

Summary

Introduction

Sea traffic monitoring is one of the most important applications of synthetic aperture radar (SAR) imagery. Moving ship detection is an important issue in sea traffic monitoring, and imagery quality has a great impact on detection performance. E performances of these imaging algorithms for moving targets worsen due to the motion of the target. SAR signatures of moving targets suffer from azimuthal displacement, smearing, defocusing caused by motion in the range direction, and loss of focus due to azimuthal velocity [2]. One solution that can address this problem for moving target imaging is motion compensation. By combining motion compensation with conventional imaging algorithms, it is possible to focus on moving targets. Motion compensation relies on the acquiring of motion parameters, i.e., velocities, for a target. Utilizing the Automatic Identification System (AIS) conveniently provides the motion parameters of a moving target. In many cases, no AIS data are available for moving targets. erefore, an alternative method to realize velocity estimations should be explored

Methods

Results

Conclusion