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NASA NTRS2021

Best Practices Identified Through the Completion of UAS Flight Demonstrations

After several years of research into Detect and Avoid (DAA) and Command and Control (C2) systems for Unmanned Aircraft Systems (UAS), the National Aeronautics and Space Administration’s (NASA) UAS Integration into the National Airspace System project initiated a focused two-year effort along with the Federal Aviation Administration (FAA) and three industry partners to investigate remaining issues in the specification, test, certification and airspace integration to allow UAS operations in non-segregated airspace. The approach taken had the industry partners propose a flight demonstration approximating a commercial operation, while NASA helped, as needed, the partners through design and test phases and NASA observed interactions with the FAA. During this effort NASA collected best practices intended to be of value to similar UAS endeavors. These best practices can be divided into different sets, including practices that describe the relationship between business considerations to UAS design or describe several UAS development challenges. Another set includes best practices focused on navigating the UAS design and type certification processes. A third set includes best practices that relate to the design of the DAA system. Deploying DAA systems in this timeframe posed unique challenges. Commercial off-the-shelf DAA systems do not exist, necessitating custom development and, for two of the partners, the use of low-size, -weight, and -power (SWaP) sensors not completely specified for DAA. A fourth set of best practices relates to lost-link contingency planning. The final set of best practices relates to the design and testing of C2 systems and obtaining spectrum licenses. The UAS demonstrations were piloted remotely, and for all aspects of flight safety, a C2 system was required to communicate DAA and other UAS subsystem data to the remote pilot and to allow the pilot to issue commands to the vehicle. Throughout the course of this effort, the partners integrated prototype DAA and C2 systems into unmanned aircraft, tested those systems, and laid the groundwork for type certification programs that are expected to continue.

NASA↗

NASA NTRS1994

Using Virtual Reality for Science Mission Planning: A Mars Pathfinder Case

The Mars Pathfinder Project GDS Team has designed software that integrates virtual reality technology with existing JPL Navigational Ancillary Information Facilities (NAIF) and image processing capabilities. The result is an interactive, workstation-based application software that provides a high resolution 3-dimensional stereo display of Mars as if it were viewed through the lander camera. This paper describes the architecture and characteristics of this science mission planning software and discusses possible uses of this software by other planetary missions.

virtual↗

NASA NTRS2019

SSIM: NASA Mars rover robotics flight software simulation

The focus of SSim on MSL was the robotic flight software, including rover mobility and navigation, robotic arm manipulation, and sample acquisition, processing, and delivery. It can execute behaviors in simulation a thousand times faster than they execute in real time on the flight compute element. SSim is used by rover drivers to develop and validate command sequences throughout the planning cycle. SSim has been used to plan all of the Curiosity robotic operations since landing and is expected to continue to be used for the remaining life of the rover.

Leger, Chris↗

NASA NTRSDate not supplied

U.S. Spacesuit Knowledge Capture – Creation, Curation, and Dissemination

The U.S. spacesuit is a special system that has intrigued and fascinated the world since Neil Armstrong set foot on the Moon in 1969. With over 50 years since that momentous achievement, NASA is planning to land the first woman and next man on the Moon in the near future. This goal begets the need to build a new spacesuit, a spacesuit created from the legacy knowledge of the Extravehicular Mobility Unit (EMU), combined with knowledge gained from technology development over the decades. As NASA transitions to its new horizon, the U.S. Spacesuit Knowledge Capture (SKC) Program is poised to help. The SKC Program’s primary function has been to capture, curate, and disseminate spacesuit-related knowledge among scientists, engineers, and technicians. The SKC Program was created in 2007 to capture knowledge primarily from spacesuit subject-matter experts (SMEs) who were retiring from NASA. These SMEs had 30 to 50 years of spacesuit knowledge. Over the years, the SKC Program has evolved and expanded its scope with a current focus on complementing the buildup of the Exploration EMU (xEMU) at the Johnson Space Center. As part of this focus, the SKC Program recently teamed with the xEMU Community of Practice (CoP) for knowledge sharing. The xEMU CoP provides a forum where early career engineers, professionals new to human spaceflight, and the xEMU community can come together regularly to seek guidance, share knowledge, meet their peers, discover resources, and ask questions. The CoP created an environment where the knowledge can be easily and routinely captured and recorded. The recorded events are archived and curated in an SKC Program library and disseminated as appropriate. This paper details the roles that the SKC Program and CoP play in the xEMU buildup, along with the navigation of the creation, curation, and dissemination processes.

Cinda Chullen↗

NASA NTRS1980

Navigation accuracy analysis for the Halley flyby phase of a dual comet mission using ion drive

A dual comet (Halley Flyby/Tempel 2 Rendezvous) mission, making use of the solar electric propulsion system, is under consideration for a 1985 launch. This paper presents navigation accuracy analysis results for the Halley flyby phase of this mission. Orbit determination and guidance accuracies are presented for the baseline navigation strategy, along with the results of a number of sensitivity studies involving parameters such as data frequencies, data accuracies, ion drive thrust vector errors, comet ephemeris uncertainties, time lags associated with data processing and command sequence generation, probe release time, and navigation coast arc duration.

Wood, L. J.↗

NASA NTRS2004

Mars Exploration Rovers navigation results

The twin Mars Exploration Rovers, Spirit and Opportunity, were launched on June 10, 2003, and July 8, 2003, from Cape Canaveral, Florida. Spirit and Opportunity were targeted for landings at Gusev Crater (arrival on January 4, 2004) and Meridiani Planum (arrival on January 25, 2004). The primary navigation challenge was to deliver each spacecraft to the desired atmospheric entry interface point with sufficient accuracy such that each lander would touch down within a specified landing ellipse (about 70 km x 5 km) determined to be safe for landing and also judged to be scientifically interesting. In order to achieve landing within the target ellipse, precise control of the inertial entry flight path angle (FPA) at atmospheric entry was required. The maximum allowable errors in FPA following TCM-5 (trajectory correction maneuver #5) at Entry (E) -2 days were +/-0.12 deg(3 sigma) for Spirit and +/-0.14 deg(3 sigma) for Opportunity. Achieving these entry delivery accuracies necessitated significant improvements to the interplanetary navigation system used for MER. These improvements included new processes and software for orbit determination, propulsive maneuver design, and entry, descent, and landing (EDL) trajectory simulation. The actual achieved atmospheric entry accuracies for Spirit and Opportunity significantly exceeded the requirements. At the navigation data cutoff for the TCM-5 final design, the orbit determination FPA knowledge error was 0.028 deg(3 sigma) for Spirit and 0.035 deg(3 sigma) for Opportunity. Because of exceptionally accurate navigation performance, TCM-5 (E - 2 days) and TCM-6 (E - 4 hours) were canceled for both Spirit and Opportunity. The actual landing locations (determined from in-situ Doppler tracking between the MER rovers and the Mars Odyssey orbiter) differed from the target landing points by 10.1 km (downtrack) for Spirit and 24.6 km (downtrack) for Opportunity. The majority of the landing position offsets for both landers was primarily caused by variations in atmosphere and spacecraft aerodynamic modeling from what was predicted. The amount of the landing position offset caused by navigation-only errors was only 3.3 km (uptrack) for Spirit and 9.7 km (downtrack) for Opportunity.

Mars Exploration Rover (MER)↗

NASA NTRS1990

TDRSS Onboard Navigation System (TONS) experiment for the Explorer Platform (EP)

A TDRSS Onboard Navigation System (TONS) is currently being developed by NASA to provide a high-accuracy autonomous spacecraft navigation capability for users of TDRSS and its successor, the Advanced TDRSS. A TONS experiment will be performed in conjunction with the Explorer Platform (EP)/EUV Explorer mission to flight-qualify TONS Block I. This paper presents an overview of TDRSS on-board navigation goals and plans and the technical objectives of the TONS experiment. The operations concept of the experiment is described, including the characteristics of the ultrastable oscillator, the Doppler extractor, the signal-acquisition process, the TONS ground-support system, and the navigation flight software. A description of the on-board navigation algorithms and the rationale for their selection is also presented.

Gramling, C. J.↗

NASA NTRS1967

Conceptual nonorthogonal gyro configuration for guidance and navigation

Nonorthogonal sensor configuration using six single-degree-of-freedom inertial reference gyroscopes and a complete data processing and self-contained failure detection-and-isolation mechanism provides redundant capabilities to guidance and navigation systems. This system has been formulated in a strap-down configuration to attain maximum redundancy.

Gilmore, J. P.↗

NASA NTRS2011

Navigation Strategies for Primitive Solar System Body Rendezvous and Proximity Operations

A wealth of scientific knowledge regarding the composition and evolution of the solar system can be gained through reconnaissance missions to primitive solar system bodies. This paper presents analysis of a baseline navigation strategy designed to address the unique challenges of primitive body navigation. Linear covariance and Monte Carlo error analysis was performed on a baseline navigation strategy using simulated data from a· design reference mission (DRM). The objective of the DRM is to approach, rendezvous, and maintain a stable orbit about the near-Earth asteroid 4660 Nereus. The outlined navigation strategy and resulting analyses, however, are not necessarily limited to this specific target asteroid as they may he applicable to a diverse range of mission scenarios. The baseline navigation strategy included simulated data from Deep Space Network (DSN) radiometric tracking and optical image processing (OpNav). Results from the linear covariance and Monte Carlo analyses suggest the DRM navigation strategy is sufficient to approach and perform proximity operations in the vicinity of the target asteroid with meter-level accuracy.

Getzandanner, Kenneth M.↗

NASA NTRS2013

Challenges of Integrating NASA's Space Communications Networks

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a significant obstacle for integration. Over the past few decades of use, user missions and network personnel alike have grown accustomed to the processes by which services are provided by the NASA communications and navigation networks. The culture established by each network has created several challenges that need to be overcome in order to effectively integrate the networks. As with any change, there has been resistance, an apprehension to explore automation of existing processes, and a working environment that attempts to indirectly influence change without mandating compliance. Overcoming technical and cultural challenges is essential to successfully integrating the networks and although the challenges are numerous, the integration of the networks promises a more efficient space communications network for NASA and its customers, as well as potential long-term cost savings to the agency. This paper, Challenges of Integrating NASA Legacy Communications Networks, will provide a brief overview of the current NASA space communications networks as well as the an overview of the process implemented while performing the SCaN Trade Studies and an introduction to the requirements driving integration of the SCaN Networks. This paper will describe in detail the challenges experienced, both technical and cultural, while working with NASA space communications network-specific personnel. The paper will also cover lessons learned during the performance of architecture trade studies and provide recommendations for ways to improve the process.

Systems Integration↗

NASA NTRS2013

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Eure, Kenneth W.↗

NASA NTRS2012

Conceptual Design of a Communication-Based Deep Space Navigation Network

As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.

Anzalone, Evan J.↗

NASA NTRS2014

High-Fidelity Flash Lidar Model Development

NASA's Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Hines, Glenn D.↗

NASA NTRS2013

Tuning and Robustness Analysis for the Orion Absolute Navigation System

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test ight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modi cations since its inception, and continues as a work-in-progress. This paper seeks to show the e orts made to-date in tuning the lter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. The results generally show Monte Carlo error performance bounded by the lter uncertainty for all phases of ight. Some future items of investigation are presented related to suspected anomalies in the trajectory truth reference le.

Holt, Greg N.↗

NASA NTRSDate not supplied

Lidar-Based Safe Site Relative Navigation

Established Safe and Precise Landing–Integrated Capability Evolution (SPLICE) project precision landing requirements necessitate a navigation filter architecture and underlying models developed specifically with these needs in mind. To date, test flights to characterize SPLICE guidance and navigation (GN) system performance have not provided a means to divert from the a priori selected landing site (LS) due to hazardous conditions. With the inclusion of a new sensor type, the Hazard Detection Lidar (HDL) coupled with safe landing site selection algorithms, GN can divert from the originally planned trajectory and navigate relative to the new targeted landing site. This discussion covers the navigation filter developments necessary to perform this estimation and process the resulting HDL measurements to meet project safe landing goals.

Navigation↗

NASA NTRS2012

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

Brennan, Shane↗

NASA NTRS2003

Software for a GPS-Reflection Remote-Sensing System

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Lowe, Stephen↗

NASA NTRS2012

Autonomous Navigation for Deep Space Missions

Navigation (determining where the spacecraft is at any given time, controlling its path to achieve desired targets), performed using ground-in- the-loop techniques: (1) Data includes 2-way radiometric (Doppler, range), interferometric (Delta- Differential One-way Range), and optical (images of natural bodies taken by onboard camera) (2) Data received on the ground, processed to determine orbit, commands sent to execute maneuvers to control orbit. A self-contained, onboard, autonomous navigation system can: (1) Eliminate delays due to round-trip light time (2) Eliminate the human factors in ground-based processing (3) Reduce turnaround time from navigation update to minutes, down to seconds (4) React to late-breaking data. At JPL, we have developed the framework and computational elements of an autonomous navigation system, called AutoNav. It was originally developed as one of the technologies for the Deep Space 1 mission, launched in 1998; subsequently used on three other spacecraft, for four different missions. The primary use has been on comet missions to track comets during flybys, and impact one comet.

navigation↗