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At least 325 records · Page 18

Test Waveform Applications for JPL STRS Operating Environment

This software demonstrates use of the JPL Space Telecommunications Radio System (STRS) Operating Environment (OE), tests APIs (application programming interfaces) presented by JPL STRS OE, and allows for basic testing of the underlying hardware platform. This software uses the JPL STRS Operating Environment ["JPL Space Tele com - munications Rad io System Operating Environment,"(NPO-4776) NASA Tech Briefs, commercial edition, Vol. 37, No. 1 (January 2013), p. 47] to interact with the JPL-SDR Software Defined Radio developed for the CoNNeCT (COmmunications, Navigation, and Networking rEconfigurable Testbed) Project as part of the SCaN Testbed installed on the International Space Station (ISS). These are the first applications that are compliant with the new NASA STRS Architecture Standard. Several example waveform applications are provided to demonstrate use of the JPL STRS OE for the JPL-SDR platform used for the CoNNeCT Project. The waveforms provide a simple digitizer and playback capability for the SBand RF slice, and a simple digitizer for the GPS slice [CoNNeCT Global Positioning System RF Module, (NPO-47764) NASA Tech Briefs, commercial edition, Vol. 36, No. 3 (March 2012), p. 36]. These waveforms may be used for hardware test, as well as for on-orbit or laboratory checkout. Additional example waveforms implement SpaceWire and timer modules, which can be used for time transfer and demonstration of communication between the two Xilinx FPGAs in the JPLSDR. The waveforms are also compatible with ground-based use of the JPL STRS OE on radio breadboards and Linux.

Lux, James P.↗

Software Defined Radio with Parallelized Software Architecture

This software implements software-defined radio procession over multicore, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to approx.50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.

Heckler, Greg↗

Software Defined Radio with Parallelized Software Architecture

This software implements software-defined radio procession over multi-core, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to .50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.

Heckler, Greg↗

Physics of Failure Analysis of Xilinx Flip Chip CCGA Packages: Effects of Mission Environments on Properties of LP2 Underfill and ATI Lid Adhesive Materials

The Xilinx Virtex 4QV and 5QV (V4 and V5) are next-generation field-programmable gate arrays (FPGAs) for space applications. However, there have been concerns within the space community regarding the non-hermeticity of V4/V5 packages; polymeric materials such as the underfill and lid adhesive will be directly exposed to the space environment. In this study, reliability concerns associated with the non-hermeticity of V4/V5 packages were investigated by studying properties and behavior of the underfill and the lid adhesvie materials used in V4/V5 packages.

Suh, Jong-ook↗

Rad-Hard Structured ASIC Body of Knowledge

Structured Application-Specific Integrated Circuit (ASIC) technology is a platform between traditional ASICs and Field-Programmable Gate Arrays (FPGA). The motivation behind structured ASICs is to combine the low nonrecurring engineering costs (NRE) costs of FPGAs with the high performance of ASICs. This report provides an overview of the structured ASIC platforms that are radiation-hardened and intended for space application

Heidecker, Jason↗

Single Event Analysis and Fault Injection Techniques Targeting Complex Designs Implemented in Xilinx-Virtex Family Field Programmable Gate Array (FPGA) Devices

An informative session regarding SRAM FPGA basics. Presenting a framework for fault injection techniques applied to Xilinx Field Programmable Gate Arrays (FPGAs). Introduce an overlooked time component that illustrates fault injection is impractical for most real designs as a stand-alone characterization tool. Demonstrate procedures that benefit from fault injection error analysis.

Single Event Upset Testing↗

Space-Based Reconfigurable Software Defined Radio Test Bed Aboard International Space Station

The National Aeronautical and Space Administration (NASA) recently launched a new software defined radio research test bed to the International Space Station. The test bed, sponsored by the Space Communications and Navigation (SCaN) Office within NASA is referred to as the SCaN Testbed. The SCaN Testbed is a highly capable communications system, composed of three software defined radios, integrated into a flight system, and mounted to the truss of the International Space Station. Software defined radios offer the future promise of in-flight reconfigurability, autonomy, and eventually cognitive operation. The adoption of software defined radios offers space missions a new way to develop and operate space transceivers for communications and navigation. Reconfigurable or software defined radios with communications and navigation functions implemented in software or VHDL (Very High Speed Hardware Description Language) provide the capability to change the functionality of the radio during development or after launch. The ability to change the operating characteristics of a radio through software once deployed to space offers the flexibility to adapt to new science opportunities, recover from anomalies within the science payload or communication system, and potentially reduce development cost and risk by adapting generic space platforms to meet specific mission requirements. The software defined radios on the SCaN Testbed are each compliant to NASA's Space Telecommunications Radio System (STRS) Architecture. The STRS Architecture is an open, non-proprietary architecture that defines interfaces for the connections between radio components. It provides an operating environment to abstract the communication waveform application from the underlying platform specific hardware such as digital-to-analog converters, analog-to-digital converters, oscillators, RF attenuators, automatic gain control circuits, FPGAs, general-purpose processors, etc. and the interconnections among different radio components.

Communications↗

Towards Real-time, On-board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) capability to continuously monitor sensors, software, and hardware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and/or software signals; (2) signal analysis, preprocessing, and advanced on the- fly temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software due to instrumentation. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual data from the NASA Swift UAS, an experimental all-electric aircraft.

System & Software Health Management↗

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

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.

Xilinx FPGA↗

Adapting the Reconfigurable SpaceCube Processing System for Multiple Mission Applications

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

SpaceCube↗

Fast and Adaptive Lossless On-Board Hyperspectral Data Compression System for Space Applications

Efficient on-board lossless hyperspectral data compression reduces the data volume necessary to meet NASA and DoD limited downlink capabilities. The techniques also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware, which makes it practical for flight implementations of pushbroom instruments. A prototype of the compressor (and decompressor) of the algorithm is available in software, but this implementation may not meet speed and real-time requirements of some space applications. Hardware acceleration provides performance improvements of 10x-100x vs. the software implementation (about 1M samples/sec on a Pentium IV machine). This paper describes a hardware implementation of the JPL-developed 'Fast Lossless' compression algorithm on a Field Programmable Gate Array (FPGA). The FPGA implementation targets the current state of the art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for Space applications.

image compression↗

Hardware Implementation of Lossless Adaptive and Scalable Hyperspectral Data Compression for Space

On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware. A modified form of the algorithm that is better suited for data from pushbroom instruments is generally appropriate for flight implementation. A scalable field programmable gate array (FPGA) hardware implementation was developed. The FPGA implementation achieves a throughput performance of 58 Msamples/sec, which can be increased to over 100 Msamples/sec in a parallel implementation that uses twice the hardware resources This paper describes the hardware implementation of the 'Modified Fast Lossless' compression algorithm on an FPGA. The FPGA implementation targets the current state-of-the-art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for space applications.

FPGA implementation↗

A High-Throughput, Adaptive FFT Architecture for FPGA-Based Space-Borne Data Processors

Historically, computationally-intensive data processing for space-borne instruments has heavily relied on ground-based computing resources. But with recent advances in functional densities of Field-Programmable Gate-Arrays (FPGAs), there has been an increasing desire to shift more processing on-board; therefore relaxing the downlink data bandwidth requirements. Fast Fourier Transforms (FFTs) are commonly used building blocks for data processing applications, with a growing need to increase the FFT block size. Many existing FFT architectures have mainly emphasized on low power consumption or resource usage; but as the block size of the FFT grows, the throughput is often compromised first. In addition to power and resource constraints, space-borne digital systems are also limited to a small set of space-qualified memory elements, which typically lag behind the commercially available counterparts in capacity and bandwidth. The bandwidth limitation of the external memory creates a bottleneck for a large, high-throughput FFT design with large block size. In this paper, we present the Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture for a moderately large block size (32K) with considerations to power consumption and resource usage, as well as throughput. We will also show that the architecture can be easily adapted for different FFT block sizes with different throughput and power requirements. The result is completely contained within an FPGA without relying on external memories. Implementation results are summarized.

Nguyen, Kayla↗

Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

reconfigurable computing↗

TOGA - A GNSS Reflections Instrument for Remote Sensing Using Beamforming

Remotely sensing the Earth's surface using GNSS signals as bi-static radar sources is one of the most challenging applications for radiometric instrument design. As part of NASA's Instrument Incubator Program, our group at JPL has built a prototype instrument, TOGA (Time-shifted, Orthometric, GNSS Array), to address a variety of GNSS science needs. Observing GNSS reflections is major focus of the design/development effort. The TOGA design features a steerable beam antenna array which can form a high-gain antenna pattern in multiple directions simultaneously. Multiple FPGAs provide flexible digital signal processing logic to process both GPS and Galileo reflections. A Linux OS based science processor serves as experiment scheduler and data post-processor. This paper outlines the TOGA design approach as well as preliminary results of reflection data collected from test flights over the Pacific ocean. This reflections data demonstrates observation of the GPS L1/L2C/L5 signals.

GPS↗

Single Event Effects in FPGA Devices 2014-2015

This presentation provides an overview of single event effects in FPGA devices 2014-2015 including commercial Xilinx V5 heavy ion accelerated testing, Xilinx Kintex-7 heavy ion accelerated testing. Mitigation study, and investigation of various types of triple modular redundancy (TMR) for commercial SRAM based FPGAs.

Single event upset (SEU)↗

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Robotics↗

Towards Real-Time, On-Board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS.

Unmanned Aerial System↗