Complex real-time signal and image processing applications require low-latency and high-performance hardware to achieve optimal performance. Building such a high-performance platform for space deployment is hampered by hostile environmental conditions and power constraints. Custom space-based FPGA coprocessors help alleviate these constraints, but their use is typically restricted by the need for TMR or radiation-hardened components. This paper 12 explores a framework that allows earth and space scientists to use FPGA resources through an abstraction layer. A synthetic aperture radar application is used to demonstrate the power of the system architecture. The performance of the application is shown to achieve a speedup of 19 when compared to a software solution and is able to maintain comparable data reliability. Projected speedups, for the same case study executing on the proposed flight system architecture, are several times better and also discussed.This work supports the Dependable Multiprocessor project at Honeywell and the University of Florida, a mission for the Space Technology 8 (ST-8) satellite of NASA's New Millennium Program.

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Commercial SRAM-based, field-programmable gate arrays (FPGAs) have the potential to provide space applications with the necessary performance to meet next-generation mission requirements. However, mitigating an FPGA’s susceptibility to single-event upset (SEU) radiation is challenging. Triple-modular redundancy (TMR) techniques are traditionally used to mitigate radiation effects, but TMR incurs substantial overheads such as increased area and power requirements. In order to reduce these overheads while still providing sufficient radiation mitigation, we propose a reconfigurable fault tolerance (RFT) framework that enables system designers to dynamically adjust a system’s level of redundancy and fault mitigation based on the varying radiation incurred at different orbital positions. This framework includes an adaptive hardware architecture that leverages FPGA reconfigurable techniques to enable significant processing to be performed efficiently and reliably when environmental factors permit. To accurately estimate upset rates, we propose an upset rate modeling tool that captures time-varying radiation effects for arbitrary satellite orbits using a collection of existing, publically available tools and models. We perform fault-injection testing on a prototype RFT platform to validate the RFT architecture and RFT performability models. We combine our RFT hardware architecture and the modeled upset rates using phased-mission Markov modeling to estimate performability gains achievable using our framework for two case-study orbits.

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