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NISAR is a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission.

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Data return is a metric that is commonly publicized for all space science missions. In the early days of the Space Program, this figure was small, and could be described in bits or maybe even megabits. But now, missions are capable of returning data volumes two or three orders of magnitude larger. For example, Voyager 1 and 2 combined produced a little over 5 Terabits of data in 39 years of operation. In contrast, the Cassini mission, launched two decades after Voyager, produced about one and a half times those data volumes in half the time. NISAR, an Earth Science Mission currently in implementation, plans to produce over 28 Petabits of raw data in just 3 years. This means that NISAR will produce about as many data in 30 days as the combined data production of nearly all planetary missions to date. These increases in capability are a result of technology enhancements in two main areas: telecommunications architecture (both space and ground segments) and data storage technology. This paper describes the progression of these two technologies over the course of more than three decades of space missions and provides additional insight into the design of the end-to-end NISAR Data System Architecture. Trends in the data are briefly explored and compared to Moore’s Law which provides only a qualitative model for memory growth but not for data production. In summary, early missions are found to be driven by unrefined processes while later missions, having utilized earlier lessons learned, focus more on improvements to flight and ground capabilities. Data return seems to fall into three categories. First, deep space missions are driven by the large distances that limit data return to the Earth. Next, the orbiter infrastructure around Mars helps these missions generate more data than other deep space spacecraft. Finally, near-Earth missions have the greatest capabilities for the studied metrics due to their close proximity to Earth and the ground network availability.

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The Mars Reconnaissance Orbiter is the most complex spacecraft that has ever been sent to investigate the Red Planet. A major part of what makes this mission so complex is the suite of instruments that were selected. The instruments on MRO vary from a simple imaging system, not much larger than a pocket knife to the largest camera ever flown to another planet. Not only does the size of the instruments vary, so do the scientific investigations associated with each instrument. In order to ensure that this payload suite would be able to satisfy all of its science objectives, a major effort was put forth by the MRO Project to ensure these instruments were well calibrated prior to the start of the Primary Science Phase. The in-flight calibration plan for MRO proved to be quite challenging, given the often conflicting requirements due to the varying capability of each of the instruments and the desire to constrain the workload on the Mission Operations personnel. The quality of data returned by MRO since the start of the Primary Science Phase is a tribute to the effort that was put forth to characterize the in-flight performance of the instruments. This paper will describe the challenges associated with the planning and implementation of the various calibration events on MRO, and will exhibit some of the results from those calibrations.

This paper describes the Mars Reconnaissance Orbiter Mission Plan with emphasis on major mission activities and key challenges in mission design, spacecraft design, and science data acquisition.