Performance-Optimized Quantization for SAR and InSAR Applications
Michele Martone, Nicola Gollin, Paola Rizzoli, Gerhard Krieger
Abstract
For the design of present and next-generation spaceborne SAR missions, constantly increasing data rates are being demanded, which impose stringent requirements in terms of onboard memory and downlink capacity. In this scenario, the efficient quantization of SAR raw data is of primary importance, since the utilized compression rate is directly related to the volume of data to be stored and transmitted to the ground and, at the same time, it affects the resulting SAR imaging performance. In this paper, we introduce the performance-optimized block-adaptive quantization (PO-BAQ), a novel approach for SAR raw data compression which aims at optimizing the resource allocation and, at the same time, the quality of the resulting SAR and InSAR products. This goal is achieved by exploiting the a priori knowledge of the local SAR backscatter statistics, which allows for the generation of high-resolution bitrate maps that can be employed to fulfill a predefined performance requirement. Analyses on experimental TanDEM-X interferometric data are presented, which demonstrate the potentials of the proposed method as a helpful tool for performance budget definition and data rate optimization of present and future SAR missions.