DRASTIC IMPROVEMENT OF CHANGE DETECTION RESULTS WITH MULTILOOK COMPLEX SAR IMAGES APPROACH

Coherent Change Detection (CCD) is a powerful technique that uses Synthetic Aperture Radar (SAR) coherence to measure subtle ground changes in the imaged area. Unfortunately, the coherence estimator is biased for low coherence values, resulting in a highly degraded change detection performance. The spatial multilooking technique is typically used to improve coherence estimation but at the expense of spatial resolution. Actually, there are some SAR satellites that are able to deliver Multiple Look Complex (MLC) SAR images, which provide noticeable coherence bias reduction. In the present work, we investigate detection performance improvement that can be obtained through the use of MLC SAR images. The detection probability and false alarm are evaluated using experimental very high-resolution SAR data. After SAR image focusing and coherence estimation, the results indicate that the use of MLC SAR images with four looks allows for nearly 60% higher detection probability in the case of a low false alarm rate.

[1]  Xiaotao Huang,et al.  Novel Pre-Processing Techniques for Coherence Improving in Along-Track Dual-Channel Low Frequency SAR , 2012 .

[2]  Marc Acheroy,et al.  Improving Ccd Performance by the Use of Local Fringe Frequencies , 2012 .

[3]  Carlos López-Martínez,et al.  Coherence estimation in synthetic aperture radar data based on speckle noise modeling. , 2007, Applied optics.

[4]  K. Feigl,et al.  Radar interferometry and its application to changes in the Earth's surface , 1998 .

[5]  Mark A. Richards,et al.  Fundamentals of Radar Signal Processing , 2005 .

[6]  Douglas A. Gray,et al.  Detecting scene changes using synthetic aperture Radar interferometry , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Charles V. Jakowatz,et al.  A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[8]  John C. Curlander,et al.  Synthetic Aperture Radar: Systems and Signal Processing , 1991 .

[9]  Andrew Hooper,et al.  InSAR processing for volcano monitoring and other near‐real time applications , 2016 .

[10]  D. Massonnet,et al.  Imaging with Synthetic Aperture Radar , 2008 .

[11]  Ian G. Cumming,et al.  Interpretations of the omega-K algorithm and comparisons with other algorithms , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[12]  R. Goldstein,et al.  Topographic mapping from interferometric synthetic aperture radar observations , 1986 .

[13]  Duk-jin Kim,et al.  Damage-Mapping Algorithm Based on Coherence Model Using Multitemporal Polarimetric–Interferometric SAR Data , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Aichouche Belhadj-Aissa,et al.  Man-Made Change Detection Using High-Resolution Cosmo-SkyMed SAR Interferometry , 2016 .

[15]  Paris W. Vachon,et al.  Coherence estimation for SAR imagery , 1999, IEEE Trans. Geosci. Remote. Sens..

[16]  Marc Acheroy,et al.  InSAR Phase Filtering via Joint Subspace Projection Method: Application in Change Detection , 2014, IEEE Geoscience and Remote Sensing Letters.