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Cobalt: Development and Maturation of GN&C Technologies for Precision Landing

The CoOperative Blending of Autonomous Landing Technologies (COBALT) instrument is a terrestrial test platform for development and maturation of guidance, navigation and control (GN&C) technologies for precision landing. The project is developing a third-generation Langley Research Center (LaRC) navigation doppler lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the Jet Propulsion Laboratory (JPL) lander vision system (LVS) for terrain relative navigation (TRN) position estimates. These technologies together provide precise navigation knowledge that is critical for a controlled and precise touchdown. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive vertical test bed (VTB) developed by Masten Space Systems, and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active).

Carson, John M.

Accelerating NASA GN&C Flight Software Development

When the guidance, navigation, and control (GN&C) system for the Orion crew vehicle undergoes Critical Design Review (CDR), more than 90% of the flight software will already be developed - a first for NASA on a project of this scope and complexity. This achievement is due in large part to a new development approach using Model-Based Design.

Tamblyn, Scott

Recent Advances in Commercial Memories and Potential Contribution to GN&C Miniaturation

The last few years have seen a surge in technology, device, and architecture introductions in commercial memories such as SDRAM and NAND driven by the explosion of handheld and portable electronics. Some of the resultant devices provide high density in very small and light packages, which may be possible to leverage for the miniaturization of future GN&C systems in addition to providing considerable memory capacity to enable advanced capabilities such as image-based navigation or adaptive/autonomous operations. We will show that these advanced SDRAM and NAND technologies are worth serious consideration for the next generation of GN&C needs by highlighting reliability and radiation effects results from some of these devices.

Yang-Scharlotta, Jean Y.

Orion GN&C Fault Management System Verification: Scope And Methodology

In order to ensure long-term ability to meet mission goals and to provide for the safety of the public, ground personnel, and any crew members, nearly all spacecraft include a fault management (FM) system. For a manned vehicle such as Orion, the safety of the crew is of paramount importance. The goal of the Orion Guidance, Navigation and Control (GN&C) fault management system is to detect, isolate, and respond to faults before they can result in harm to the human crew or loss of the spacecraft. Verification of fault management/fault protection capability is challenging due to the large number of possible faults in a complex spacecraft, the inherent unpredictability of faults, the complexity of interactions among the various spacecraft components, and the inability to easily quantify human reactions to failure scenarios. The Orion GN&C Fault Detection, Isolation, and Recovery (FDIR) team has developed a methodology for bounding the scope of FM system verification while ensuring sufficient coverage of the failure space and providing high confidence that the fault management system meets all safety requirements. The methodology utilizes a swarm search algorithm to identify failure cases that can result in catastrophic loss of the crew or the vehicle and rare event sequential Monte Carlo to verify safety and FDIR performance requirements.

Brown, Denise

Preliminary GN&C Design for the On-Orbit Autonomous Assembly of Nanosatellite Demonstration Mission

Small spacecraft autonomous rendezvous and docking (ARD) is an essential technology for future space structure assembly missions. The On-orbit Autonomous Assembly of Nanosatellites (OAAN) team at NASA Langley Research Center (LaRC) intends to demonstrate the technology to autonomously dock two nanosatellites to form an integrated system. The team has developed a novel magnetic capture and latching mechanism that allows for docking of two CubeSats without precise sensors and actuators. The proposed magnetic docking hardware not only provides the means to latch the CubeSats, but it also significantly increases the likelihood of successful docking in the presence of relative attitude and position errors. The simplicity of the design allows it to be implemented on many CubeSat rendezvous missions. Prior to demonstrating the docking subsystem capabilities on orbit, the GN&C subsystem should have a robust design such that it is capable of bringing the CubeSats from an arbitrary initial separation distance of as many as a few thousand kilometers down to a few meters. The main OAAN Mission can be separated into the following phases: 1) Launch, checkout, and drift, 2) Far-Field Rendezvous or Drift Recovery, 3) Proximity Operations, 4) Docking. This paper discusses the preliminary GN&C design and simulation results for each phase of the mission.

Pei, Jing

Small Body GN&C Research Report: A G-Guidance Enhancement to Increase Mission Functionality

G-Guidance is a robust G&C (guidance and control) algorithm developed under the small-body GN&C task. The G-Guidance scheme utilizes a model predictive control approach, along with a convexification of the governing dynamics, control constraints, and trajectory/state constraints. This report details an enhancement to the FY2005 G-Guidance algorithm; the addition of a fire-second approach helps to nullify velocity errors and hit desired final velocities much more precisely than the original Fire-first scheme developed in FY2005. The enhancement preserves the primary benefit of the algorithm, which is to ensure required thruster silent times during trajectory maneuvers. The fire-second scheme increases the versatility of the algorithm for missions employing G-Guidance. For instance, a landing sequence could employ the fire-second scheme to ensure a null final velocity at landing, whereas an ascent sequence could utilize a fire-first scheme to ensure there is no drift of the spacecraft toward the ground at the beginning of the maneuver. Examples are provided within to demonstrate a fire-first versus fire-second guidance scheme. As in the existing G-Guidance algorithm, the examples and schemes incorporate gravity models and thruster firing times into discrete dynamics that are solved as a optimal control problem to minimize fuel consumption or thruster energy expenditure.

velocity errors

COBALT: Development of a Platform to Flight Test Lander GN&C Technologies on Suborbital Rockets

The NASA COBALT Project (CoOperative Blending of Autonomous Landing Technologies) is developing and integrating new precision-landing Guidance, Navigation and Control (GN&C) technologies, along with developing a terrestrial fight-test platform for Technology Readiness Level (TRL) maturation. The current technologies include a third- generation Navigation Doppler Lidar (NDL) sensor for ultra-precise velocity and line- of-site (LOS) range measurements, and the Lander Vision System (LVS) that provides passive-optical Terrain Relative Navigation (TRN) estimates of map-relative position. The COBALT platform is self contained and includes the NDL and LVS sensors, blending filter, a custom compute element, power unit, and communication system. The platform incorporates a structural frame that has been designed to integrate with the payload frame onboard the new Masten Xodiac vertical take-o, vertical landing (VTVL) terrestrial rocket vehicle. Ground integration and testing is underway, and terrestrial fight testing onboard Xodiac is planned for 2017 with two flight campaigns: one open-loop and one closed-loop.

Carson, John M., III

Shuttle ascent GN&C postflight results

The key features of the ascent and Guidance navigation, and control (GN and C) system are discussed. How well this system performed during the orbital flight test program is examined. Flight results are compared with preflight predictions and postflight reconstructions. Variations from expected performance are identified as well as flight-to-flight trends. The most notable variation was the lofted trajectory observed on the Space Transportation System 1 flight. The lessons learned from the orbital flight test program are being used to enhance the overall system performance for future Shuttle flights. Several of the planned GN and C system enhancements are discussed.

Mcswain, G.

GN&C fault protection

Addressing fault tolerance for spacecraft Guidance, Navigation, and Control has never been easy. Even under normal conditions, these systems confront a remarkable blend of complex issues across many disciplines, with primary implications for most essential system functions. Moreover, GN&C must deal with the peculiarities of spacecraft configurations, disturbances, environment, and other physical mission-unique constraints that are seldom under its full control, all while promising consistently high performance.

Rasmussen, Robert D.

Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing

A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor.

Carson, John M., III

GN&C Engineering Best Practices For Human-Rated Spacecraft Systems

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.

GN&C Engineering Best Practices for Human-Rated Spacecraft Systems

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.

GN&C Engineering Best Practices for Human-Rated Spacecraft System

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.

NASA SPLICE Project: Development and Testing of Precision Landing GN&C Technologies

NASA's technology advancement needs for entry, descent and landing call for high-precision, high-rate sensors that can improve navigation accuracy and vehicle control performance. Higher landing accuracy is required for any future human lander missions, and likely, for most robotic missions 1,2. Sensors and algorithms that significantly reduce navigation errors and can image the local terrain will enable landing at locations of high scientific interest that would otherwise pose significant risk to the vehicle. The Safe and Precise Landing-Integrated Capabilities Evolution project, or SPLICE, is developing precision landing and hazard avoidance (PL&HA) technologies for NASA and for potential commercial space flight missions. SPLICE technologies include sensors, algorithms, advanced space flight computing capabilities, and simulation tools used to integrate and study guidance, navigation, and control (GN&C) system performance. SPLICE efforts include hardware-in-the-loop (HWIL) simulation testing, ground testing, and flight testing, including reuse of hardware from the CoOperative Blending of Autonomous Landing Technologies (COBALT) suborbital flight-test payload3,4. Two of the precise navigation sensors that are being developed and matured within SPLICE are LiDARs. Since 2006, NASA Langley has been developing a Navigation Doppler LiDAR (NDL) for precise velocity measurements, and SPLICE is building an NDL engineering test unit (ETU) that will be brought up to TRL 6 following environmental and high-speed1,2 testing. NASA Goddard is developing a Hazard Detection LiDAR (HD LiDAR) engineering development unit (EDU) for SPLICE that has relevance to future human and robotic lander missions. The HD LiDAR will be flight test and matured to TRL 5.

Restrepo, Carolina I.

Lunar Reconnaissance Orbiter (LRO) Guidance, Navigation and Control (GN&C) Overview

The National Aeronautics and Space Administration s (NASA) Lunar Reconnaissance Orbiter (LRO) launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle and into a direct insertion trajectory to the oon. LRO, which was designed, built, and operated by the NASA Goddard Space Flight Center in Greenbelt, MD, is gathering crucial data on the lunar environment that will help astronauts prepare for long-duration lunar expeditions. The mission has a nominal life of 1 year as its seven instruments find safe landing sites, locate potential resources, characterize the radiation environment, and test new technology. To date, LRO has been operating well within the bounds of its requirements and has been collecting excellent science data images taken from the LRO Camera Narrow Angle Camera of the Apollo landing sites appeared on cable news networks. A significant amount of information on LRO s science instruments is provided at the LRO mission webpage. LRO s Guidance, Navigation and Control (GN&C) subsystem is made up of an onboard attitude control system (ACS) and a hardware suite of sensors and actuators. The LRO onboard ACS is a collection of algorithms based on high level and derived requirements, and reflect the science and operational events throughout the mission lifetime. The primary control mode is the Observing mode, which maintains the lunar pointing orientation and any offset pointing from this baseline. It is within this mode that all science instrument calibrations, slews and science data is collected. Because of a high accuracy requirement for knowledge and pointing, the Observing mode makes use of star tracker (ST) measurement data to determine an instantaneous attitude pointing. But even the star trackers alone do not meet the tight requirements, so a six-state Kalman Filter is employed to improve the noisy measurement data. The Observing mode obtains its rate information from an inertial reference unit (IRU) and in the event of an IRU failure, the rate data is be derived from the star tracker, but with degraded pointing performance. The Delta-V control mode responsibility is to maintain attitude pointing during the cruise trajectory, insertion burns and lunar orbit maintenance by adjustments made to the spacecraft s velocity magnitude and vector direction. The ACS also provides for a thruster based system momentum management algorithm (known as Delta-H) to maintain the system and wheel momentum to within acceptable levels. In the event an anomaly causes the LRO spacecraft to lose the ability to maintain its current attitude pointing, a Sun Safe mode is included in the ACS for the purpose of providing a known power and thermally safe coarse inertial sun attitude for an indefinite period of time, within the manageable limits of the reaction wheels. The Sun Safe mode is also the initial spacecraft control mode off of the launch vehicle and provides for a means to null tip-off rates immediately after separation. The nominal configuration is to use the IRU for rate information in the controller. In the event of a gyro failure a gyroless control mode was developed that computes rate information from the CSS data.

Garrick, Joseph

COBALT: A GN&C Payload for Testing ALHAT Capabilities in Closed-Loop Terrestrial Rocket Flights

The COBALT (CoOperative Blending of Autonomous Landing Technology) payload is being developed within NASA as a risk reduction activity to mature, integrate and test ALHAT (Autonomous precision Landing and Hazard Avoidance Technology) systems targeted for infusion into near-term robotic and future human space flight missions. The initial COBALT payload instantiation is integrating the third-generation ALHAT Navigation Doppler Lidar (NDL) sensor, for ultra high-precision velocity plus range measurements, with the passive-optical Lander Vision System (LVS) that provides Terrain Relative Navigation (TRN) global-position estimates. The COBALT payload will be integrated onboard a rocket-propulsive terrestrial testbed and will provide precise navigation estimates and guidance planning during two flight test campaigns in 2017 (one open-loop and closed- loop). The NDL is targeting performance capabilities desired for future Mars and Moon Entry, Descent and Landing (EDL). The LVS is already baselined for TRN on the Mars 2020 robotic lander mission. The COBALT platform will provide NASA with a new risk-reduction capability to test integrated EDL Guidance, Navigation and Control (GN&C) components in closed-loop flight demonstrations prior to the actual mission EDL.

Carson, John M., III

Discriminative Methodology using the Unscented Transform in Special Euclidean Group SE(3) for Autonomous GN&C

Kalman filtering techniques usually compare a known dynamic model with some process noise to an updated, noisy measurement. Both sources of noise are generally assumed to be Gaussian and are filtered to obtain a more accurate estimate of the state of the system of interest. However, these methods assume that a relatively accurate dynamical model already exists. By including discriminative methodology to interpret differences in the predictive model and the measured states over time, an incorrect model can be corrected overtime, allowing a spacecraft to learn about its environment and adapt to changing conditions. In this paper, a discriminative unscented Kalman filter (DUKF) is introduced on the special Euclidean group SE(3) formulation framework. A spacecraft is initialized near a small body with no knowledge of its parameters, and using several consecutive conditional models the environment is studied and the filter is updated. The case study of a spacecraft in a slightly elliptical, inclined, relatively tight orbit around the irregular moon Phobos is simulated and discussed. The accuracy of this approach is quantifying the differences between the true state, the UKF with a poor model, and the DUKF.

GN&C

Robust Trajectory Optimization and GN&C Performance Analysis for NRHO Rendezvous

This paper evaluates several candidate Near-Rectilinear Halo Orbits (NRHO) rendezvous trajectory designs using linear covariance (LinCov) analysis and determines the optimal locations for NRHO rendezvous translational maneuver locations. The performance of several candidate relative trajectory designs are determined as a function of relative navigation accuracy (angles only), inertial optical navigation (OpNav), range observability maneuvers, maneuver execution errors, relative maneuver targeting, and environment uncertainties. Further, the optimal locations of rendezvous maneuvers are determined for each of the candidate reference trajectories. The long-term goal of this research is to utilize LinCov and a genetic optimization algorithm (GA) to determine a complete end-to-end optimal NRHO trajectory design that is robust to navigation errors, maneuver execution errors, and environment uncertainties. This paper represents a first step toward this goal. Three candidate rendezvous trajectories with varying numbers of range-observability maneuvers are evaluated for their robustness to uncertainties, errors, and total trajectory correction delta-v performance. Some key elements of this analysis include relative navigation performance in an NRHO, relative trajectory dispersion performance, and total 3-sigma delta-v performance. This development provides the foundation to then determine an optimal and robust end-to-end NRHO rendezvous trajectory, including the determination of the optimal locations of range observability maneuvers, if needed.

Linear Covariance Analysis