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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

SIRU utilization. Volume 1: Theory, development and test evaluation

The theory, development, and test evaluations of the Strapdown Inertial Reference Unit (SIRU) are discussed. The statistical failure detection and isolation, single position calibration, and self alignment techniques are emphasized. Circuit diagrams of the system components are provided. Mathematical models are developed to show the performance characteristics of the subsystems. Specific areas of the utilization program are identified as: (1) error source propagation characteristics and (2) local level navigation performance demonstrations.

Musoff, H.↗
NASA NTRS1989

Improving Estimates Of Phase Parameters When Amplitude Fluctuates

Adaptive inverse filter applied to incoming signal and noise. Time-varying inverse-filtering technique developed to improve digital estimate of phase of received carrier signal. Intended for use where received signal fluctuates in amplitude as well as in phase and signal tracked by digital phase-locked loop that keeps its phase error much smaller than 1 radian. Useful in navigation systems, reception of time- and frequency-standard signals, and possibly spread-spectrum communication systems.

Vilnrotter, V. A.↗
NASA NTRS1992

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

Source record↗
NASA NTRS2016

Orbit Determination Sensitivity Analysis for the Europa Multiple Flyby Mission Concept

This paper details the results of parametric variations on the notional Europa Mission Concept tour navigation strategy on orbit determination delivery and knowledge errors and the associated statistical ∆V consumption. Approach maneuver placement at encounter minus two and a half days and at encounter minus three and a half days is compared to the reference encounter minus three days location as well as variations to the data cutoff for approach maneuver design, which is baselined one day prior to maneuver execution. An execution error model with fixed and proportional components assigned to the magnitude and pointing directions is applied to each maneuver in a Monte Carlo simulation. Variations on the fixed and proportional contributions to both component errors are simulated and analyzed to show the effect of varying thruster characterization levels. The effects of varying levels of a priori satellite ephemeris errors are also characterized in this study.

Boone, Dylan R.↗
NASA NTRS2013

The Deep Space Atomic Clock: Ushering in a New Paradigm for Radio Navigation and Science

The Deep Space Atomic Clock (DSAC) mission will demonstrate the on-orbit performance of a high-accuracy, high-stability miniaturized mercury ion atomic clock during a year-long experiment in Low Earth Orbit. DSAC's timing error requirement provides the frequency stability necessary to perform deep space navigation based solely on one-way radiometric tracking data. Compared to a two-way tracking paradigm, DSAC-enabled one-way tracking will benefit navigation and radio science by increasing the quantity and quality of tracking data. Additionally, DSAC also enables fully-autonomous onboard navigation useful for time-sensitive situations. The technology behind the mercury ion atomic clock and a DSAC mission overview are presented. Example deep space applications of DSAC, including navigation of a Mars orbiter and Europa flyby gravity science, highlight the benefits of DSAC-enabled one-way Doppler tracking.

atomic clock↗
NASA NTRS1976

Space shuttle navigation analysis

A detailed analysis of space shuttle navigation for each of the major mission phases is presented. A covariance analysis program for prelaunch IMU calibration and alignment for the orbital flight tests (OFT) is described, and a partial error budget is presented. The ascent, orbital operations and deorbit maneuver study considered GPS-aided inertial navigation in the Phase III GPS (1984+) time frame. The entry and landing study evaluated navigation performance for the OFT baseline system. Detailed error budgets and sensitivity analyses are provided for both the ascent and entry studies.

Jones, H. L.↗
NASA NTRS1984

Pilot errors as a source of workload

A pilot opinion survey was conducted to develop a database for creating simulation scenarios that impose predetermined levels of pilot workload. Twelve pilots estimated the effect of 163 events and activities (which they had encountered during their previous flying experiences) on performance, effort, workload, and stress. The events, described in the context of flight scenario segments, included control, navigation and communications activities, aircraft and system failures, and pilot errors. In general, workload, stress, and effort ratings were significantly correlated with each other but not with performance ratings; however, some different response patterns were found as a function of flight segment (e.g., workload, stress, and performance, but not effort, ratings varied with flight phase) and type of event. Errors were rated as a significant source of change for workload, stress, and performance, suggesting that errors could be conceptualized as a cause of workload rather than as a symptom.

Hart, S. G.↗
NASA NTRS2021

Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts

Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.

Chen, Allen↗
NASA NTRS2000

Adaptive Interplanetary Navigation Using Genetic Algorithms

The problem of tuning trajectory determination models for interplanetary navigation is a complex task requiring an intensive search of multiple dynamical and nondynamical models that yield trajectory solutions with minimal errors.

adaptive↗
NASA NTRS2007

Proximity Navigation of Highly Constrained Spacecraft

Bandit is a 3-kg automated spacecraft in development at Washington University in St. Louis. Bandit's primary mission is to demonstrate proximity navigation, including docking, around a 25-kg student-built host spacecraft. However, because of extreme constraints in mass, power and volume, traditional sensing and actuation methods are not available. In particular, Bandit carries only 8 fixed-magnitude cold-gas thrusters to control its 6 DOF motion. Bandit lacks true inertial sensing, and the ability to sense position relative to the host has error bounds that approach the size of the Bandit itself. Some of the navigation problems are addressed through an extremely robust, error-tolerant soft dock. In addition, we have identified a control methodology that performs well in this constrained environment: behavior-based velocity potential functions, which use a minimum-seeking method similar to Lyapunov functions. We have also adapted the discrete Kalman filter for use on Bandit for position estimation and have developed a similar measurement vs. propagation weighting algorithm for attitude estimation. This paper provides an overview of Bandit and describes the control and estimation approach. Results using our 6DOF flight simulator are provided, demonstrating that these methods show promise for flight use.

Scarritt, S.↗
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 flight, 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 modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Holt, Greg N.↗
NASA NTRS1983

Redundant asynchronous microprocessor system for fault tolerant flight control and navigation

Unlike their synchronized counterparts, redundant channels in an asynchronous flight system can, under no-fault conditions, exhibit cross-channel data disparities. Sources of these errors are examined in terms of the general, individual functions of the flight control and navigation application in the asynchronous digital environment. The effects of asynchronism on trajectory programmers, dynamic control algorithms and data reconstruction processes are examined in terms of data skews, data latencies, and clock rate uncertainties. An example is presented in which time corrections are applied to reduce the data disparities. Practical limitations of the approach of the example are discussed.

Dunn, W. R.↗
NASA NTRS1996

Astrometric Calibration of Array Detectors

The high level of spatial uniformity in modern CCDs and other array detectors makes them excellent devices for astrometric and navigational systems. However, at the level of accuracy envisioned by the more ambitious projects, current technology produces devices with significant pixel registration errors. This paper describes a technique fot measuring relative pixel positions to an accuracy approaching 0.001 pixel. The technique has been applied to WF/PC II CCDs whicha re shown to have 500 nm step-and-repeat errors.

array detectors CCDs navigational systems astromet↗
NASA NTRS2015

Fast Light Optical Gyroscopes

Next-generation space missions are currently constrained by existing spacecraft navigation systems which are not fully autonomous. These systems suffer from accumulated dead-reckoning errors and must therefore rely on periodic corrections provided by supplementary technologies that depend on line-of-sight signals from Earth, satellites, or other celestial bodies for absolute attitude and position determination, which can be spoofed, incorrectly identified, occluded, obscured, attenuated, or insufficiently available. These dead-reckoning errors originate in the ring laser gyros themselves, which constitute inertial measurement units. Increasing the time for standalone spacecraft navigation therefore requires fundamental improvements in gyroscope technologies. One promising solution to enhance gyro sensitivity is to place an anomalous dispersion or fast light material inside the gyro cavity. The fast light essentially provides a positive feedback to the gyro response, resulting in a larger measured beat frequency for a given rotation rate as shown in figure 1. Game Changing Development has been investing in this idea through the Fast Light Optical Gyros (FLOG) project, a collaborative effort which began in FY 2013 between NASA Marshall Space Flight Center (MSFC), the U.S. Army Aviation and Missile Research, Development, and Engineering Center (AMRDEC), and Northwestern University. MSFC and AMRDEC are working on the development of a passive FLOG (PFLOG), while Northwestern is developing an active FLOG (AFLOG). The project has demonstrated new benchmarks in the state of the art for scale factor sensitivity enhancement. Recent results show cavity scale factor enhancements of approx.100 for passive cavities.

Smith, David D.↗
NASA NTRS2012

Improved Maneuver Reconstructions for the GRAIL Orbiters

Maneuver reconstructions for the Gravity Recovery and Interior Laboratory (GRAIL) A and B lunar orbiters were improved through updates to the orbit determination filter and dynamic models. Consistent reconstructions of the 27 GRAIL A and B maneuvers from the Trans-Lunar Cruise phase in the fall of 2011 through the Transition to Science Formation phase in February 2012 were performed. Standard methods of orbit determination were applied incorporating the latest dynamic models and filter strategies developed by the GRAIL Navigation and Science Teams, including a high resolution, 420 x 420 degree and order lunar spherical harmonic gravity field model. For Trans-Lunar Cruise for GRAIL-A (TLC-A), all maneuvers executed with delta V errors below 5.50 +/- 0.50 mm/s and pointing errors below 0.25 degrees. GRAIL-A lunar orbit maneuvers had delta V errors below 30.0 mm/s and pointing errors below 0.51 degrees. For TLC-B, all maneuvers executed with delta V errors below 8.60 +/- 1.41 mm/s and pointing errors below 0.300 degrees. GRAIL-B maneuvers in lunar orbit executed with maximum delta V errors of 25.0 mm/s and pointing error of 0.43 degrees. These maneuver reconstructions will enable the GRAIL Navigation Team to better characterize the main engine performance of each spacecraft. This will help the Navigation Team to navigate low (greater than 8 km) altitude orbits during the extended mission phase in the fall of 2012.

lunar mapping↗
NASA NTRS2004

Mars Exploration Rovers navigation results

The twin Mars Exploration Rovers, Spirit and Opportunity, were launched on June 10, 2003(dagger), 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 avigation 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 NTRS2008

Execution-error modeling and analysis of the Cassini-Huygens spacecraft through 2007

The Cassini-Huygens spacecraft arrived at Saturn in 2004, beginning a four-year tour. Much of mission’s continued success at Saturn can be attributed to the excellent performance of the propulsion systems and attitude control. In order to better understand this performance, the Cassini Navigation Team has continued to analyze and refine the execution-error models for the propulsion systems. This paper documents the evolution of the execution-error models employed for maneuvers, along with the analysis, procedures, and software associated with the model development.

Goodson, Troy D.↗
NASA NTRS2022

Vision-Based Precision Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft require perception systems for precision approach and landing systems (PALS) in urban, suburban, rural, and regional environments. The current state-of-the-art methods approved for automated approach and landing will be difficult to utilize in support of AAM operational concepts. However, there are technology and systems from other applications and lower-TRL research that use vision, IR, radar, and GPS methods to provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL to demonstrate a closed-loop baseline controller while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter. Combining IMU with vision creates a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS, and higher fidelity simulations will include computer graphics rendering and feature correspondence.

Evan Kawamura↗