Advanced Data Chain Technologies for the Next Generation of Earth Observation Satellites Supporting On-Board Processing for Rapid Civil Alerts

The growing number of planned Earth Observation (EO) satellites, together with the increase in payload resolution and swath, brings to the fore the generation of unprecedented volumes of data that needs to be downloaded, processed and distributed with low latency. This creates a severe bottleneck problem, which overloads ground infrastructure, communications to ground, and hampers the provision of EO products to the End User with the required performances. The EO-ALERT project (http://eo-alert-h2020.eu/), an H2020 European Union research activity, proposes the definition of next-generation EO missions by developing an on-board high speed EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, reaching latencies below 1 minute in some scenarios. The proposed architecture solves the above challenges through a combination of innovations in the on-board elements of the data chain and the communications link. Namely, the architecture introduces innovative technological solutions, including on-board reconfigurable data handling, on-board image generation and processing for generation of alerts (EO products) using Artificial Intelligence (AI), high-speed on-board avionics, on-board data compression and encryption using AI and reconfigurable high data rate communication links to ground including a separate chain for alerts with minimum latency and global coverage. Those key technologies have been studied, developed, implemented in software/hardware (SW/HW) and verified against previously established technologies requirements to meet the identified user needs. The paper presents the development of the innovative solutions defined during the project for each of the above mentioned technological areas and the results of the testing campaign of the individual SW/HW implementations within the context of two operational scenarios: ship detection and extreme weather observation (nowcasting), both requiring a high responsiveness to events to reduce the response time to few hours, or even to minutes, after an emergency situation arises. The technologies have been experimentally evaluated during the project using relevant EO historical sensor data. The results demonstrate the maturity of the technologies, having now reached TRL 4-5. Generally, the results show that, when implemented using COTS components and available communication links, the proposed architecture can generate alerts with a latency lower than five minutes, which demonstrates the viability of the EO-ALERT concept. The paper also discusses the implementation on an Avionic Test Bench (ATB) for the validation of the integrated technologies chain

EO-ALERT: NEXT GENERATION SATELLITE PROCESSING CHAIN FOR RAPID CIVIL ALERTS

In this paper, we provide an overview of the H2020 EU project EO-ALERT. The aim of EO-ALERT is to propose the definition and development of the next generation Earth observation (EO) data and processing chain, based on a novel flight segment architecture moving optimised key EO data processing elements from the ground segment to on-board the satellite. The objective is to address the need for increased throughput in EO data chain, delivering EO products to the end user with very low latency

EO-ALERT: A Novel Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Civil Alerts

Satellite Earth Observation (EO) data is ubiquitously used in many applications, providing basic services to society, such as environment monitoring, emergency management and civilian security. Due to the increasing request of EO products by the market, the classical EO data chain generates a severe bottleneck problem, further exacerbated in constellations. A huge amount of EO raw data generated on-board the satellite must be transferred to ground, slowing down the EO product availability, increasing latency, and hampering the growth of applications in accordance with the increased user demand. This paper provides an overview of the results achieved by the EO-ALERT project (http://eo-alert-h2020.eu/), an H2020 European Union research activity led by DEIMOS Space. EO-ALERT proposes the definition and development of the next-generation EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite, with the aim of delivering the EO products to the end user with very low latency (quasi-real-time). EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, reaching latencies below 1 minute in some scenarios. The proposed architecture solves the above challenges through a combination of innovations in the on-board elements of the data chain and the communications. Namely, the architecture introduces innovative technological solutions, including on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Artificial Intelligence (AI), on-board data compression and encryption using AI, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. The paper presents the proposed architecture, its performance and hardware, considering two different user scenarios; ship detection and extreme weather observation/nowcasting. The results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to ground with latency lower than five minutes, for both SAR and Optical missions, demonstrating the viability of the EOALERT concept and architecture. The paper also discusses the implementation on an avionics test bench for testing the architecture with real EO data, with the aim of demonstrating that it can meet the requirements of the considered scenarios in terms of detection performance and provides technologies at a high TRL (4-5). When proven, this will open unprecedented opportunities for the exploitation of civil EO products, especially in latency sensitive scenarios, such as disaster management