Calibration, processing and quality assessment of NISAR L-band level-1 and level-2 science products

NASA-ISRO Synthetic Aperture Radar (NISAR) mission with a near-global coverage of land and cryosphere regions with 12 days repeat, will operationally produce level-1 and level-2 science products from L-band radar by the NASA data system at Jet Propulsion Laboratory. The products will be available to the users through the NASA's Data Active Archive Center (DAAC) at Alasak Satellite Facility (ASF). In this paper we present the algorithms to process, calibrate and assess the quality of the NISAR products after launch. We simulate NISAR raw data from different science modes and with NISAR L-band configurations (such as left looking, squinted beam and dithered data and the same transmit chirp and receive configuration as the L-band instrument) and process them through the NISAR standard processor to from level-1 and level-2 products. We quantify the quality of formed images and their derived level-2 products such as geocoded SLC, covariance and interferometry prpducts over point targets. We further evaluate the performance of the NISAR processor and algorithms using real L-band data acquired by ALOS-1 and ALOS-2 and reformatted to NISAR format. Finally we will demonstrate the performance of our algorithms using early NISAR L-band acquisitions during commissioning phase of the mission.

NASA-ISRO合成孔径雷达（NISAR）任务具备12天重访周期的近全球陆地与冰冻圈覆盖能力，将由美国国家航空航天局（NASA）喷气推进实验室（Jet Propulsion Laboratory, JPL）的数据系统依托L波段雷达在轨生成一级与二级科学产品。相关产品将通过美国国家航空航天局数据主动存档中心（Data Active Archive Center, DAAC）设于阿拉斯加卫星设施（Alaska Satellite Facility, ASF）的节点向用户开放。本文提出了任务在轨后针对NISAR产品进行处理、定标与质量评估的算法体系。研究团队基于多种科学工作模式及NISAR L波段配置（包括左视波束、斜视波束与抖动数据，且发射线性调频脉冲与接收配置与L波段载荷保持一致）模拟生成NISAR原始数据，并通过NISAR标准处理器将其处理为一级与二级科学产品。针对点目标场景下生成的图像及其衍生二级产品（如地理编码单视复数（Single Look Complex, SLC）数据、协方差与干涉测量产品），研究对其质量开展了量化分析。进一步地，团队利用ALOS-1与ALOS-2获取的真实L波段数据并重构为NISAR格式，对NISAR处理器与算法的性能进行了验证评估。最后，本文将借助任务调试阶段早期获取的NISAR L波段观测数据，演示所提算法的实际性能。