Azimuth-Switched Quantization for SAR Systems and Performance Analysis on TanDEM-X Data

In synthetic aperture radar (SAR) applications, raw data quantization represents an aspect of primary importance, since the number of bits employed for radar signal digitization on one hand affects the on-board memory consumption and the data volume to be transmitted to the ground, but also on the other hand affects the quality of the SAR images. In this letter, we introduce a novel azimuth-switched quantization technique, which allows the implementation of non-integer quantization rates in a new, efficient way. This grants higher flexibility in terms of performance design and resource allocation, without increasing the complexity and the computational load of the quantization scheme. The presented results were obtained in the frame of the TanDEM-X mission.

[1]  Gerhard Krieger,et al.  Decorrelation effects in bistatic TanDEM-X data , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[2]  Pietro Guccione,et al.  A Space Adaptive Quantizer for Spaceborne SAR , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Robert Metzig,et al.  TerraSAR-X System Performance Characterization and Verification , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Ron Kwok,et al.  Block adaptive quantization of Magellan SAR data , 1989 .

[5]  Theo Algra,et al.  Data compression for operational SAR missions using entropy-constrained block adaptive quantisation , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[6]  Jaime Hueso Gonzalez,et al.  TanDEM-X: A satellite formation for high-resolution SAR interferometry , 2007 .

[7]  Ciro Cafforio,et al.  Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions , 2010, IEEE Geoscience and Remote Sensing Letters.

[8]  Sigurd Huber,et al.  The TanDEM-X mission: Overview and interferometric performance , 2009, 2009 European Radar Conference (EuRAD).

[9]  Marwan Younis,et al.  Determening the optimum compromise between SAR data compression and radiometric performance -An approach based on the analysis of TerraSAR -X data- , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.