Acceleration compensation for estimation of along-track velocity of ground moving target from single-channel SAR SLC data

Sang Wan Kim, Joong Sun Won

Research output: Contribution to journalArticle

Abstract

Across-track acceleration is a major source of estimation error of along-track velocity in synthetic-aperture radar (SAR) ground moving-target indication (GMTI). This paper presents the theory and a method of compensating across-track acceleration to improve the accuracy of alongtrack velocity estimated from single-channel SAR single-look complex data. A unique feature of the proposed method is the utilisation of phase derivatives in the Doppler frequency domain, which is effective for azimuth-compressed signals. The performance of the method was evaluated through experimental data acquired by TerraSAR-X and speed-controlled and measured vehicles. The application results demonstrate a notable improvement in along-track velocity estimates. The amount of along-track velocity correction is particularly significant when a target has irregular motion with a low signal-to-clutter ratio. A discontinuous velocity jump rather than a constant acceleration was also observed and verified through comparison between actual data and simulations. By applying this method, the capability of single-channel SAR GMTI could be substantially improved in terms of accuracy of velocity, and moving direction. However, the method is effective only if the correlation between the actual Doppler phase derivatives and a model derived from the residual Doppler rate is sufficiently high. The proposed method will be applied to X-band SAR systems of KOMPSAT-5 and-6.

Original languageEnglish
Article number1609
JournalRemote Sensing
Volume12
Issue number10
DOIs
Publication statusPublished - 2020 May 1

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Acceleration compensation for estimation of along-track velocity of ground moving target from single-channel SAR SLC data'. Together they form a unique fingerprint.

  • Cite this