Frame-based SAR processing and automatic moving targets parameters extraction

Synthetic aperture radar is a very popular and widely used instrument for various remote sensing tasks. In the paper, we propose several novel ideas for improvement of the efficiency of the modern SAR systems. At first, the problem of the automatic image stitching is considered. Instead of the common cross-correlation based solution the local features detection and description techniques are proposed. Secondly, we analyze the problem of the moving target parameters estimation. It is shown that the optical flow techniques can be used for the automatic extraction of the moving target shifts from the sequence of SAR looks. Experimental examples with real SAR data are illustrated and comprehensively discussed.

[1]  Oleksandr O. Bezvesilniy,et al.  EFFECTS OF LOCAL PHASE ERRORS IN MULTI-LOOK SAR IMAGES , 2013 .

[2]  Krzysztof S. Kulpa,et al.  Coherent MapDrift Technique , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[3]  O. O. Bezvesilniy,et al.  X-band SAR system for light-weight aircrafts , 2014, 2014 15th International Radar Symposium (IRS).

[4]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[5]  Chibiao Ding,et al.  A Novel Motion Parameter Estimation Algorithm of Fast Moving Targets via Single-Antenna Airborne SAR System , 2012, IEEE Geoscience and Remote Sensing Letters.

[6]  W. Carrara,et al.  Spotlight synthetic aperture radar : signal processing algorithms , 1995 .

[7]  Martin Kirscht.  Detection and imaging of arbitrarily moving targets with single-channel SAR , 2003 .

[8]  Ian G. Cumming,et al.  Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation , 2005 .

[9]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[10]  Ievgen Gorovyi,et al.  Multi-look SAR processing with road location and moving target parameters estimation , 2015, 2015 16th International Radar Symposium (IRS).

[11]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[12]  Yan Sun,et al.  Automatic ice motion retrieval from ERS-1 SAR images using the optical flow method , 1996 .

[13]  Pierrick Coupé,et al.  Nonlocal Means-Based Speckle Filtering for Ultrasound Images , 2009, IEEE Transactions on Image Processing.

[14]  O. O. Bezvesilniy,et al.  Estimation of phase errors in SAR data by Local-Quadratic map-drift autofocus , 2012, 2012 13th International Radar Symposium.

[15]  Aurélien Plyer,et al.  A New Coregistration Algorithm for Recent Applications on Urban SAR Images , 2015, IEEE Geoscience and Remote Sensing Letters.

[16]  T. Lindeberg,et al.  Scale-Space Theory : A Basic Tool for Analysing Structures at Different Scales , 1994 .

[17]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[18]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.

[19]  Joachim Ender,et al.  Cognitive radar - enabling techniques for next generation radar systems , 2015, 2015 16th International Radar Symposium (IRS).

[20]  Riccardo Lanari,et al.  Synthetic Aperture Radar Processing , 1999 .