A Moving Target Velocity Estimation Method Based on the MC-MASA SAR Mode

Imaging position shift based on the multiple azimuth squint angles (MASA) mode is effective for target azimuth velocity estimation, whereas accuracy is low when target range velocity is high. In this paper, the estimation problem for both target azimuth and range velocities is considered based on the multi-channels MASA (MC-MASA) mode. Firstly, the acquisition geometry of MC-MASA mode and Doppler characteristics of a moving target are analyzed in detail, especially in squint mode. Then, for better moving target estimation, the stationary background clutter is removed using the displacement phase center antenna (DPCA) technique, and the failure in range velocity estimation with sequential SAR images is also discussed. Furthermore, a modified along-track interferometry (ATI) is proposed to preliminarily reconstruct the azimuth-and-range velocity map based on the MC-MASA mode. Since the velocity estimation accuracy is dependent on squint angle and signal-to-clutter ratio (SCR), the circumstances are divided into three cases with different iteration estimation strategies, which could expand the scene application scope of velocity estimation and achieve a high estimation accuracy along both azimuth and range directions. Finally, the performance of the proposed method is demonstrated by experimental results.

[1]  Adriano Camps,et al.  Dual-beam interferometry for ocean surface current vector mapping , 2001, IEEE Trans. Geosci. Remote. Sens..

[2]  João R. Moreira,et al.  A new MTI-SAR approach using the reflectivity displacement method , 1995, IEEE Trans. Geosci. Remote. Sens..

[3]  Xiaolan Qiu,et al.  Research on Turning Motion Targets and Velocity Estimation in High Resolution Spaceborne SAR , 2020, Sensors.

[4]  Han-Kyu Park,et al.  High level SW and HW mapping method of the space-based SAR processor using RDA , 2004, Signal Process..

[5]  Wei Liu,et al.  A Wide-Swath Spaceborne TOPS SAR Image Formation Algorithm Based on Chirp Scaling and Chirp-Z Transform , 2016, Sensors.

[6]  Weiming Tian,et al.  Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR , 2021, Remote. Sens..

[7]  Anna Scaglione,et al.  Product high-order ambiguity function for multicomponent polynomial-phase signal modeling , 1998, IEEE Trans. Signal Process..

[8]  Benjamin Friedlander,et al.  Asymptotic statistical analysis of the high-order ambiguity function for parameter estimation of polynomial-phase signals , 1996, IEEE Trans. Inf. Theory.

[9]  R. P. Perry,et al.  SAR imaging of moving targets , 1999 .

[10]  Chibiao Ding,et al.  A Method of Marine Moving Targets Detection in Multi-Channel ScanSAR System , 2020, Remote. Sens..

[11]  Richard Klemm,et al.  Introduction to space-time adaptive processing , 1998 .

[12]  Xiaoling Zhang,et al.  Ground Moving Target Tracking and Refocusing Using Shadow in Video-SAR , 2020, Remote. Sens..

[13]  R. Keith Raney,et al.  Precision SAR processing using chirp scaling , 1994, IEEE Trans. Geosci. Remote. Sens..