Session
Session 1: Big Data From Small Satellites 1
Abstract
Over the last decade, the development and use of small satellite missions for new space-born applications has grown dramatically. Small satellite driven missions are poised to become the largest growth market in space, driven by the upcoming “Commercial Space Gold Rush” and a true enabler of Big Data. A natural progression from technology and concept demonstration to operational missions has taken place in the Smallsat segment. This is not only true for the ever so popular CubeSats, but also for the micro-satellite segment. After having played an important role in changing space economics and demonstrating commercial mission capabilities, microsat platforms provide an interesting balance between capability, reliability and SWaP, allowing for an instrument/payload capability that can satisfy many different applications including constellation-based Earth Observation, Situational Awareness and Communications. Given the advances in (commercial re-usable) technology and concepts such as In-Orbit reconfiguration and the current state of the art in reconfigurable hardware such as FPGAs, System on Chip (SoC) and Massive Parallel Processing (MPP), the concept of a Software Defined Payload (SDP) becomes increasingly interesting and feasible. The Software Defined Payload approach does require changes to the traditional Mission, System Engineering and instrument development approach. It also imposes challenges on the technology used and when properly (and suitably) applied, can lead to standardization and re-use of building blocks in electronics and software. Besides flexibility, a more pressing reason for using reconfiguration is the need for on-board processing. Modern payloads and sensors (e.g. Hyperspectral, SAR, Wideband Data, Software Defined Radio) generate data at data rates and volumes, that not only require on-board (Mass Memory) data storage, but more and more rely on on-board processing to reduce, format, filter/select, compress, encrypt and meta-tag data as well as process it to a higher (smaller) data product level, before it is sent to the ground. HEAD Aerospace Netherlands’ answer to this “Big Data in Space” handling is a standardized framework of hardware and software that represent the on-board functionality for payload / instrument / sensor data handling and processing, referred to as the Payload Interface & Data Processor (PIDP).
Big Data in Space
Over the last decade, the development and use of small satellite missions for new space-born applications has grown dramatically. Small satellite driven missions are poised to become the largest growth market in space, driven by the upcoming “Commercial Space Gold Rush” and a true enabler of Big Data. A natural progression from technology and concept demonstration to operational missions has taken place in the Smallsat segment. This is not only true for the ever so popular CubeSats, but also for the micro-satellite segment. After having played an important role in changing space economics and demonstrating commercial mission capabilities, microsat platforms provide an interesting balance between capability, reliability and SWaP, allowing for an instrument/payload capability that can satisfy many different applications including constellation-based Earth Observation, Situational Awareness and Communications. Given the advances in (commercial re-usable) technology and concepts such as In-Orbit reconfiguration and the current state of the art in reconfigurable hardware such as FPGAs, System on Chip (SoC) and Massive Parallel Processing (MPP), the concept of a Software Defined Payload (SDP) becomes increasingly interesting and feasible. The Software Defined Payload approach does require changes to the traditional Mission, System Engineering and instrument development approach. It also imposes challenges on the technology used and when properly (and suitably) applied, can lead to standardization and re-use of building blocks in electronics and software. Besides flexibility, a more pressing reason for using reconfiguration is the need for on-board processing. Modern payloads and sensors (e.g. Hyperspectral, SAR, Wideband Data, Software Defined Radio) generate data at data rates and volumes, that not only require on-board (Mass Memory) data storage, but more and more rely on on-board processing to reduce, format, filter/select, compress, encrypt and meta-tag data as well as process it to a higher (smaller) data product level, before it is sent to the ground. HEAD Aerospace Netherlands’ answer to this “Big Data in Space” handling is a standardized framework of hardware and software that represent the on-board functionality for payload / instrument / sensor data handling and processing, referred to as the Payload Interface & Data Processor (PIDP).
