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This paper describes a rapid, top down requirements-driven design of an FPGA used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and store data from multiple sensors at multiple rates during launch, ascent, deployment and descent phases of the subsonic parachute test.
This paper describes a rapid, top down requirements-driven design of an FPGA used in an Earth qualification test program for a new Mars subsonic parachute. The FPGA is used to process and control storage of telemetry data from multiple sensors throughout; launch, ascent, deployment and descent phases of the subsonic parachute test.
Advances in Field Programmable Gate Array (FPGA) technologies enable the implementation of reconfigurable radio systems for both ground and space applications. The development of such systems challenges the current design paradigms and requires more robust design techniques to meet the increased system complexity. Among these techniques is the development of component libraries to reduce design cycle time and to improve design verification, consequently increasing the overall efficiency of the project development process while increasing design success rates and reducing engineering costs. This paper describes the reconfigurable radio component library developed at the Software Defined Radio Applications Research Center (SARC) at Goddard Space Flight Center (GSFC) Microwave and Communications Branch (Code 567). The library is a set of fixed-point VHDL components that link the Digital Signal Processing (DSP) simulation environment with the FPGA design tools. This provides a direct synthesis path based on the latest developments of the VHDL tools as proposed by the BEE VBDL 2004 which allows for the simulation and synthesis of fixed-point math operations while maintaining bit and cycle accuracy. The VHDL Fixed Point Reconfigurable Radio Component library does not require the use of the FPGA vendor specific automatic component generators and provide a generic path from high level DSP simulations implemented in Mathworks Simulink to any FPGA device. The access to the component synthesizable, source code provides full design verification capability:
Techniques and methodologies are developed for assuring and verifying FPGAs that adequately address the increased complexity of the devices required by today'\'s missions.
This paper presents the design and implementation of the Discrete Fourier Transform (DFT) algorithm on a reconfigurable processor system. While highly applicable to many engineering problems, the DFT is an extremely computationally intensive algorithm. Consequently, the eventual goal of this work is to enhance the execution of a floating-point precision DFT algorithm by off loading the algorithm from the computing system. This computing system, within the context of this research, is a typical high performance desktop computer with an may of field programmable gate arrays (FPGAs). FPGAs are hardware devices that are configured by software to execute an algorithm. If it is desired to change the algorithm, the software is changed to reflect the modification, then download to the FPGA, which is then itself modified. This paper will discuss methodology for developing the DFT algorithm to be implemented on the FPGA. We will discuss the algorithm, the FPGA code effort, and the results to date.
This presentation provides a NASA Electronic Parts and Packaging (NEPP) Program update of independent Single Event Upset (SEU) Field Programmable Gate Array (FPGA) testing including FPGA test guidelines, Microsemi RTG4 heavy-ion results, Xilinx Kintex-UltraScale heavy-ion results, Xilinx UltraScale+ single event effect (SEE) test plans, development of a new methodology for characterizing SEU system response, and NEPP involvement with FPGA security and trust.
We present SEU test and analysis of the Microsemi ProASIC3 FPGA. SEU Probability models are incorporated for device evaluation. Included is a comparison to the RTAXS FPGA illustrating the effectiveness of the overall testing methodology.
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Traditional design methodology dictates that an instrument electronics platform should consist of a printed circuit board (PCB)—often multiple boards—populated with many components and support electronics. More specifically, each subsystem is composed of numerous integrated circuits (ICs) spread across the board(s), connected with innumerable traces and wires. Additionally, it is often the case that the hardware and software design teams are quite separated—the hardware team designs a board and hands it to a software team, who must then deal with any hardware quirkiness and may need to rewrite software due to inadequately defined interfaces...
This paper will detail the use of SpaceCube in multiple space flight applications including the Hubble Space Telescope Servicing Mission 4 (HST-SM4), an International Space Station (ISS) radiation test bed experiment, and the main avionics subsystem for two separate ISS attached payloads. Each mission has had varying degrees of data processing complexities, performance requirements, and external interfaces. We will show the methodology used to minimize the changes required to the physical hardware, FPGA designs, embedded software interfaces, and testing.This paper will summarize significant results as they apply to each mission application. In the HST-SM4 application we utilized the FPGA resources to accelerate portions of the image processing algorithms more than 25 times faster than a standard space processor in order to meet computational speed requirements. For the ISS radiation on-orbit demonstration, the main goal is to show that we can rely on the commercial FPGAs and processors in a space environment. We describe our FPGA and processor radiation mitigation strategies that have resulted in our eight PowerPCs being available and error free for more than 99.99 of the time over the period of four years. This positive data and proven reliability of the SpaceCube on ISS resulted in the Department of Defense (DoD) selecting SpaceCube, which is replacing an older and slower computer currently used on ISS, as the main avionics for two upcoming ISS experiment campaigns. This paper will show how we quickly reconfigured the SpaceCube system to meet the more stringent reliability requirements
The Self-Powered Extravehicular Mobility Unit (EMU) Extravehicular Activity (EVA) Data Recorder (SPEEDR) is a field-programmable gate array (FPGA)-based device designed to collect high-rate EMU Primary Life Support Subsystem (PLSS) data for download at a later time. During EVA, the existing EMU PLSS data downlink capability is one data packet every 2 minutes and is subject to bad packets or loss of signal. Higher-rate PLSS data is generated by the Enhanced Caution and Warning System but is not normally captured or distributed. Access to higher-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Space Shuttle flights post Fiscal Year 2011 (FY11), and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both intravehicular activity (IVA) and EVA operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other International Space Station subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require store then forward methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer Universal Serial Bus (USB) port while data are being downloaded.
The Self Powered EVA EMU Data Recorder (SPEEDR) is an FPGA (Field-programmable gate array) based device designed to collect high-rate EMU (Extravehicular Mobility Unit) PLSS (Primary Life Support Subsystem) data for download at a later time. The existing EMU PLSS data down-link capability during EVA is one data packet every 2 minutes and is subject to bad packets or loss of signal. High-rate PLSS data is generated by the ECWS (Enhanced Caution and Warning System) but is not normally captured or distributed. Access to high-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Shuttle flights post FY11, and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both IVA (Intravehicular Activity) and EVA (Extravehicular Activity) operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other ISS subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require "store then forward" methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer USB (Universal Serial Bus) port while data is being downloaded.
Due to the high quantity of operations that spaceborne processing systems must carry out in space, new methodologies and techniques are being presented as good alternatives in order to free the main processor from work and improve the overall performance. These include the development of ancillary dedicated hardware circuits that carry out the more redundant and computationally expensive operations in a faster way, leaving the main processor free to carry out other tasks while waiting for the result. One of these devices is SpaceCube, a FPGA-based system designed by NASA. The opportunity to use FPGA reconfigurable architectures in space allows not only the optimization of the mission operations with hardware-level solutions, but also the ability to create new and improved versions of the circuits, including error corrections, once the satellite is already in orbit. In this work, we propose the optimization of a common operation in remote sensing: the Multi-Spectral Euclidean Distance calculation. For that, two different hardware architectures have been designed and implemented in a Xilinx Virtex-5 FPGA, the same model of FPGAs used by SpaceCube. Previous results have shown that the communications between the embedded processor and the circuit create a bottleneck that affects the overall performance in a negative way. In order to avoid this, advanced methods including memory sharing, Native Port Interface (NPI) connections and Data Burst Transfers have been used.
Computing capabilities of space systems have in-creased onboard performance by orders of magnitude with the use of radiation-tolerant field-programmable gate arrays (FPGA)and processors. The incorporation of signal and power integrity analysis with printed circuit board (PCB) design in reliable computing architectures for space systems has become critical to enable future mission capabilities. Developers launch high-performance processors into a breadth of orbits and missions, running varying applications that create challenges for designing reliable computing hardware. Specifically, for these designs, academic and industry research has focused on component radiation performance, fault mitigation, and reliable architectures. How-ever, other design parameters including electromagnetic interference (EMI), PCB stackup, signal integrity (SI), voltage regulator module (VRM) design, and power distribution network (PDN)are often deprioritized or disregarded as the design matures. Since these characteristics are becoming more significant in high-performance processor designs, this research presents a hardware design and analysis methodology for high-performance, space-computing systems that focuses on a holistic design approach and PDN reliability. While these challenges exist across all space hardware, the reduced PCB dimensions imposed by SmallSats and CubeSats introduce additional hurdles, specifically to VRM and decoupling design. By examining the relationship between the PDN and radiation performance, an analytical relationship is developed that incorporates Total Ionizing Dose and Single-Event Transients to ensure reliability throughout the mission duration. The presented design methodology is applied to the SpaceCube v3.0 Mini, an FPGA-based on-board science data processing system developed at NASA Goddard Space Flight Center.
We present the challenges that arise when using redundant clock domains due to their clock-skew. Radiation data show that a singular clock domain (DTMR) provides an improved TMR methodology for SRAM-based FPGAs over redundant clocks.
We present a test methodology for estimating system error rates of Field Programmable Gate Arrays (FPGAs) mitigated with Triple Modular Redundancy (TMR). The test methodology is founded in a mathematical model, which is also presented. Accelerator data from 90 nm Xilins Military/Aerospace grade FPGA are shown to fit the model. Fault injection (FI) results are discussed and related to the test data. Design implementation and the corresponding impact of multiple bit upset (MBU) are also discussed.
A real-time high-performance and fault-tolerant FPGA-based hardware architecture for the processing of synthetic aperture radar (SAR) images has been developed for advanced spaceborne radar imaging systems. In this paper, we present the integrated design approach, from top-level algorithm specifications, system architectures, design methodology, functional verification, performance validation, down to hardware design and implementation.
This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.