Engineering topics

Kruizinga, Gerhard L.

Publications and source records attributed to Kruizinga, Gerhard L..

10 records

NASA NTRS2013

Preliminary Results on Lunar Interior Properties from the GRAIL Mission

The Gravity Recovery and Interior Laboratory (GRAIL) mission has provided lunar gravity with unprecedented accuracy and resolution. GRAIL has produced a high-resolution map of the lunar gravity field while also determining tidal response. We present the latest gravity field solution and its preliminary implications for the Moon's interior structure, exploring properties such as the mean density, moment of inertia of the solid Moon, and tidal potential Love number k2. Lunar structure includes a thin crust, a deep mantle, a fluid core, and a suspected solid inner core. An accurate Love number mainly improves knowledge of the fluid core and deep mantle. In the future GRAIL will search for evidence of tidal dissipation and a solid inner core.

Williams, James G.↗

NASA NTRS2013

Properties of the Lunar Interior: Preliminary Results from the GRAIL Mission

The Gravity Recovery and Interior Laboratory (GRAIL) mission [1] has provided lunar gravity with unprecedented accuracy and resolution. GRAIL has produced a high-resolution map of the lunar gravity field [2,3] while also determining tidal response. We present the latest gravity field solution and its preliminary implications for the Moon's interior structure, exploring properties such as the mean density, moment of inertia of the solid Moon, and tidal potential Love number k(sub 2). Lunar structure includes a thin crust, a thick mantle layer, a fluid outer core, and a suspected solid inner core. An accurate Love number mainly improves knowledge of the fluid core and deep mantle. In the future, we will search for evidence of tidal dissipation and a solid inner core using GRAIL data.

moon gravity↗

NASA NTRS2013

Filter Strategies for Mars Science Laboratory Orbit Determination

The Mars Science Laboratory (MSL) spacecraft had ambitious navigation delivery and knowledge accuracy requirements for landing inside Gale Crater. Confidence in the orbit determination (OD) solutions was increased by investigating numerous filter strategies for solving the orbit determination problem. We will discuss the strategy for the different types of variations: for example, data types, data weights, solar pressure model covariance, and estimating versus considering model parameters. This process generated a set of plausible OD solutions that were compared to the baseline OD strategy. Even implausible or unrealistic results were helpful in isolating sensitivities in the OD solutions to certain model parameterizations or data types.

Mars Science Laboratory (MSL)↗

NASA NTRS2013

Mars Science Laboratory Orbit Determination Data Pre-Processing

The Mars Science Laboratory (MSL) was spin-stabilized during its cruise to Mars. We discuss the effects of spin on the radiometric data and how the orbit determination team dealt with them. Additionally, we will discuss the unplanned benefits of detailed spin modeling including attitude estimation and spacecraft clock correlation.

spin signature↗

NASA NTRS2013

Stackfile Database

This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

deVarvalho, Robert↗

NASA NTRS2012

Description and User Instructions for the Quaternion_to_Orbit_v3 Software

For a given inertial frame of reference, the software combines the spacecraft orbits with the spacecraft attitude quaternions, and rotates the body-fixed reference frame of a particular spacecraft to the inertial reference frame. The conversion assumes that the two spacecraft are aligned with respect to the mutual line of sight, with a parameterized time tag. The software is implemented in Python and is completely open source. It is very versatile, and may be applied under various circumstances and for other related purposes. Based on the solid linear algebra analysis, it has an extra option for compensating the linear pitch. This software has been designed for simulation of the calibration maneuvers performed by the two spacecraft comprising the GRAIL mission to the Moon, but has potential use for other applications. In simulations of formation flights, one needs to coordinate the spacecraft orbits represented in an appropriate inertial reference frame and the spacecraft attitudes. The latter are usually given as the time series of quaternions rotating the body-fixed reference frame of a particular spacecraft to the inertial reference frame. It is often desirable to simulate the same maneuver for different segments of the orbit. It is also useful to study various maneuvers that could be performed at the same orbit segment. These two lines of study are more timeand labor-efficient if the attitude and orbit data are generated independently, so that the part of the data that has not been changed can be recycled in the course of multiple simulations.

Strekalov, Dmitry V.↗

NASA NTRS2012

Mars Science Laboratory Orbit Determination

This paper describes the orbit determination process, results and filter strategies used by the Mars Science Laboratory Navigation Team during cruise from Earth to Mars. The new atmospheric entry guidance system resulted in an orbit determination paradigm shift during final approach when compared to previous Mars lander missions. The evolving orbit determination filter strategies during cruise are presented. Furthermore, results of calibration activities of dynamical models are presented. The atmospheric entry interface trajectory knowledge was significantly better than the original requirements, which enabled the very precise landing in Gale Crater.

orbit determination↗

NASA NTRS2009

Estimating Thruster Impulses From IMU and Doppler Data

A computer program implements a thrust impulse measurement (TIM) filter, which processes data on changes in velocity and attitude of a spacecraft to estimate the small impulsive forces and torques exerted by the thrusters of the spacecraft reaction control system (RCS). The velocity-change data are obtained from line-of-sight-velocity data from Doppler measurements made from the Earth. The attitude-change data are the telemetered from an inertial measurement unit (IMU) aboard the spacecraft. The TIM filter estimates the threeaxis thrust vector for each RCS thruster, thereby enabling reduction of cumulative navigation error attributable to inaccurate prediction of thrust vectors. The filter has been augmented with a simple mathematical model to compensate for large temperature fluctuations in the spacecraft thruster catalyst bed in order to estimate thrust more accurately at deadbanding cold-firing levels. Also, rigorous consider-covariance estimation is applied in the TIM to account for the expected uncertainty in the moment of inertia and the location of the center of gravity of the spacecraft. The TIM filter was built with, and depends upon, a sigma-point consider-filter algorithm implemented in a Python-language computer program.

Lisano, Michael E.↗

NASA NTRS2009

Trajectory Reconstruction of the ST-9 Sounding Rocket Experiment Using IMU and Landmark Data

This paper presents trajectory reconstruction of the ST-9 sounding rocket experiment using the onboard IMU data and descent imagery. The raw IMU accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are pre-processed using a map-matching algorithm and unique landmarks for each image are created. Using the converted IMU data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the GPS measurements. Then, both the IMU data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the GPS data and the corresponding formal uncertainties are presented. The result shows that IMU data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pin-point landing.

Park, Ryan S.↗

NASA NTRS2008

The NASA Phoenix 2007 Mars Lander Thruster Calibration Estimator: Design and Validation

The NASA Phoenix 2007 Mars Lander mission, launched in August 2007 on its mission to land near the north pole of Mars in May 2008, had a driving need for entry-corridor delivery precision, which parlayed into stringent requirements on deep space navigation accuracy. This, in turn, necessitated in-cruise calibration of the three-axis thrust force vectors produced by each of the vehicle's four reactioncontrol system (RCS) thrusters during frequent daily low-catalyst-bed-temperature firings done to maintain the 3-axis attitude deadbands. A novel recursive sigmapoint consider-covariance filter was designed, validated and ultimately utilized extensively during flight operations, to estimate the RCS force vectors, per individual thruster. The estimate was achieved through ground-based processing of Deep Space Network (DSN) and telemetered gyroscope data from the spacecraft's inertial measurement unit (IMU), using a novel sigma-point consider filter (SPCF) formulation. During early-cruise active calibration, the spacecraft was flown in attitudes chosen, using this filter, to maximize observability of all thruster axes, to an extent constrained by vehicle thermal and communication considerations. The design of the Phoenix thruster calibration filter, and its validation through processing of archived Mars Odyssey thruster calibration radiometric data, and simulated sets of data, are discussed in this paper. The paper concludes with the formulation of the thruster calibration campaign and a summary of the thruster calibration campaign results. The SPCF algorithm is summarized in the Appendix.

sigma-point filter↗