Performance-Optimized Quantization for InSAR Applications

Abstract

For present and next-generation spaceborne SAR missions, an increasing volume of onboard data is going to be demanded, which implies, from the mission design point of view, more stringent requirements in terms of onboard memory and downlink capacity. In this scenario, an efficient quantization of the SAR raw data is of primary importance, since the data rate employed for raw data digitization defines the amount of data to be stored and transmitted to the ground and directly affects the performance of the resulting SAR products. In this paper, a novel performance-optimized block-adaptive quantization (PO-BAQ) is introduced. PO-BAQ exploits state-of-the-art quantization algorithms for SAR systems, and aims at optimizing the resource allocation and, at the same time, the interferometric performance in the resulting InSAR products, by exploiting a priori knowledge of the local SAR backscatter statistics. Analyses on experimental TanDEM-X interferometric data are presented. The obtained results can be combined with the precise, high-resolution knowledge of the Earth's topography and backscatter characteristics, in order to provide a helpful tool for performance budget definition and optimization of the resource allocation strategies for future SAR missions.