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Results for “Inertial Measurement Unit (IMU)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

6-DOF aerobraking trajectory reconstruction by use of inertial measurements unit (IMU) data for the improvement of aerobraking navigation

For any interplanetary mission, there are certain types of data that are used as a means of determining both the position and velocity of a spacecraft. The data types currently in use are Doppler, Range, Optical and VLBI. All of them are radiometric with the exception of the Optical data type. NASA's Deep Space Network is employed for the purpose of transmitting and receiving data to and from the spacecraft repsectively. For this exchange of information to take place, both the DSN and spacecrft high gain antennae must be pointed towards each other.

Lisano, Michael E.↗
NASA NTRS1975

Redundancy management of multiple KT-70 inertial measurement units applicable to the space shuttle

Results of an investigation of velocity failure detection and isolation for 3 inertial measuring units (IMU) and 2 inertial measuring units (IMU) configurations are presented. The failure detection and isolation algorithm performance was highly successful and most types of velocity errors were detected and isolated. The failure detection and isolation algorithm also included attitude FDI but was not evaluated because of the lack of time and low resolution in the gimbal angle synchro outputs. The shuttle KT-70 IMUs will have dual-speed resolvers and high resolution gimbal angle readouts. It was demonstrated by these tests that a single computer utilizing a serial data bus can successfully control a redundant 3-IMU system and perform FDI.

Cook, L. J.↗
NASA NTRS1975

Space Tug laser gyro IMU

A redundant inertial measuring unit (IMU) incorporating six strapdown laser gyros and six accelerometers, arranged so that sensitive axes are normal to the faces of a dodecahedron, provides enhanced reliability with reduced hardware weight. Software monitoring of sensor outputs senses failure of sensors and the system is designed for triple redundancy, with built-in test equipment. Attention is centered on redundancy and fail-safe features, and on the closed-path ring laser gyro arrangement.

Morrison, R.↗
NASA NTRS2006

Mars Aerobraking Spacecraft State Estimation by Processing Inertial Measurement Unit Data

Aerobraking is an efficient technique for orbit adjustment of planetary spacecraft, such as Magellan (Venus), Mars Global Surveyor, and Mars Odyssey. Determination of the vehicle state during the aerobraking phase has conventionally been performed using only radiometric tracking data prior to and following the atmospheric drag pass. This approach is sufficiently accurate and timely to meet current mission operational requirements; however, it is expensive in terms of ground support and leads to delayed results because ofthe need for post-drag pass data. This research presents a new approach to estimation of the vehicle state during the atmospheric pass that sequentially incorporates observations from an Inertial Measurement Unit (IMU) and models of the vehicle and environment. The approach, called Inertial Measurements for Aerobraking Navigation (IMAN), is shown to perform at a level comparable to the conventional methods in terms of navigation accuracy and superior to them in terms of availability of the results immediately after completion ofthe pass. Furthermore, the research shows that IMAN can be used to reliably predict subsequent periapsis times and locations over all aerobraking regimes. IMAN also yields accurate peak dynamic pressure and heating rates, critical for a successful corridor control strategy, comparable to navigation team reconstructed values. This research also provides the first instance of the utilization of the Unscented Kalman Filter for the purpose of estimating an actual spacecraft trajectory arc about another planet.

Unscented Kalman Filter↗
NASA NTRS2012

Integrated rate isolation sensor

In one embodiment, a system for providing fault-tolerant inertial measurement data includes a sensor for measuring an inertial parameter and a processor. The sensor has less accuracy than a typical inertial measurement unit (IMU). The processor detects whether a difference exists between a first data stream received from a first inertial measurement unit and a second data stream received from a second inertial measurement unit. Upon detecting a difference, the processor determines whether at least one of the first or second inertial measurement units has failed by comparing each of the first and second data streams to the inertial parameter.

Brady, Tye↗
NASA NTRS2013

Gesture-Based Robot Control with Variable Autonomy from the JPL Biosleeve

This paper presents a new gesture-based human interface for natural robot control. Detailed activity of the user's hand and arm is acquired via a novel device, called the BioSleeve, which packages dry-contact surface electromyography (EMG) and an inertial measurement unit (IMU) into a sleeve worn on the forearm. The BioSleeve's accompanying algorithms can reliably decode as many as sixteen discrete hand gestures and estimate the continuous orientation of the forearm. These gestures and positions are mapped to robot commands that, to varying degrees, integrate with the robot's perception of its environment and its ability to complete tasks autonomously. This flexible approach enables, for example, supervisory point-to-goal commands, virtual joystick for guarded teleoperation, and high degree of freedom mimicked manipulation, all from a single device. The BioSleeve is meant for portable field use; unlike other gesture recognition systems, use of the BioSleeve for robot control is invariant to lighting conditions, occlusions, and the human-robot spatial relationship and does not encumber the user's hands. The BioSleeve control approach has been implemented on three robot types, and we present proof-of-principle demonstrations with mobile ground robots, manipulation robots, and prosthetic hands.

BioSleeve↗
NASA NTRS1978

Orbit IMU alinement interpretation of onboard display data

The space shuttle inertial measurement unit (IMU) alinement algorith was examined to determine the most important alinement starpair selection criterion. Three crew displayed parameters were considered: (1) the results of the separation angle difference (SAD) check for each starpair; (2) the separation angle of each starpair; and (3) the age of each star measurement. It was determined that the SAD for each pair cannot be used to predict the IMu alinement accuracy. If the age of each star measurement is less than approximately 30 minutes, time is a relatively unimportant factor and the most important alinement pair selection criterion is the starpair separation angle. Therefore, when there are three available alinement starpairs and all measurements were taken within the last 30 minutes, the pair with the separation angle closest to 90 degrees should be selected for IMU alinement.

Corson, R.↗
NASA NTRS1980

Orbit IMU alignment: Error analysis

A comprehensive accuracy analysis of orbit inertial measurement unit (IMU) alignments using the shuttle star trackers was completed and the results are presented. Monte Carlo techniques were used in a computer simulation of the IMU alignment hardware and software systems to: (1) determine the expected Space Transportation System 1 Flight (STS-1) manual mode IMU alignment accuracy; (2) investigate the accuracy of alignments in later shuttle flights when the automatic mode of star acquisition may be used; and (3) verify that an analytical model previously used for estimating the alignment error is a valid model. The analysis results do not differ significantly from expectations. The standard deviation in the IMU alignment error for STS-1 alignments was determined to the 68 arc seconds per axis. This corresponds to a 99.7% probability that the magnitude of the total alignment error is less than 258 arc seconds.

Corson, R. W.↗
NASA NTRS1976

Space Shuttle Earth Observation sensors pointing and stabilization requirements study

The shuttle orbiter inertial measurement unit (IMU), located in the orbiter cabin, is used to supply inertial attitude reference signals; and, in conjunction with the onboard navigation system, can provide a pointing capability of the navigation base accurate to within plus or minus 0.5 deg for earth viewing missions. This pointing accuracy can degrade to approximately plus or minus 2.0 deg for payloads located in the aft bay due to structural flexure of the shuttle vehicle, payload structural and mounting misalignments, and calibration errors with respect to the navigation base. Drawbacks to obtaining pointing accuracy by using the orbiter RCS jets are discussed. Supplemental electromechanical pointing systems are developed to provide independent pointing for individual sensors, or sensor groupings. The missions considered and the sensors required for these missions and the parameters of each sensor are described. Assumptions made to derive pointing and stabilization requirements are delineated.

Source record↗
NASA NTRS2004

Qualification and Reliability for MEMS and IC Packages

Advanced IC electronic packages are moving toward miniaturization from two key different approaches, front and back-end processes, each with their own challenges. Successful use of more of the back-end process front-end, e.g. microelectromechanical systems (MEMS) Wafer Level Package (WLP), enable reducing size and cost. Use of direct flip chip die is the most efficient approach if and when the issues of know good die and board/assembly are resolved. Wafer level package solve the issue of known good die by enabling package test, but it has its own limitation, e.g., the I/O limitation, additional cost, and reliability. From the back-end approach, system-in-a-package (SIAP/SIP) development is a response to an increasing demand for package and die integration of different functions into one unit to reduce size and cost and improve functionality. MEMS add another challenging dimension to electronic packaging since they include moving mechanical elements. Conventional qualification and reliability need to be modified and expanded in most cases in order to detect new unknown failures. This paper will review four standards that already released or being developed that specifically address the issues on qualification and reliability of assembled packages. Exposures to thermal cycles, monotonic bend test, mechanical shock and drop are covered in these specifications. Finally, mechanical and thermal cycle qualification data generated for MEMS accelerometer will be presented. The MEMS was an element of an inertial measurement unit (IMU) qualified for NASA Mars Exploration Rovers (MERs), Spirit and Opportunity that successfully is currently roaring the Martian surface

inertial measurement unit↗
NASA NTRS1980

Onorbit IMU alignment error budget

The Star Tracker, Crew Optical Alignment Sight (COAS), and Inertial Measurement Unit (IMU) from a complex navigation system with a multitude of error sources were combined. A complete list of the system errors is presented. The errors were combined in a rational way to yield an estimate of the IMU alignment accuracy for STS-1. The expected standard deviation in the IMU alignment error for STS-1 type alignments was determined to be 72 arc seconds per axis for star tracker alignments and 188 arc seconds per axis for COAS alignments. These estimates are based on current knowledge of the star tracker, COAS, IMU, and navigation base error specifications, and were partially verified by preliminary Monte Carlo analysis.

Corson, R. W.↗
NASA NTRS1980

Shuttle orbit IMU alignment. Single-precision computation error

The source of computational error in the inertial measurement unit (IMU) onorbit alignment software was investigated. Simulation runs were made on the IBM 360/70 computer with the IMU orbit alignment software coded in hal/s. The results indicate that for small IMU misalignment angles (less than 600 arc seconds), single precision computations in combination with the arc cosine method of eigen rotation angle extraction introduces an additional misalignment error of up to 230 arc seconds per axis. Use of the arc sine method, however, produced negligible misalignment error. As a result of this study, the arc sine method was recommended for use in the IMU onorbit alignment software.

Mcclain, C. R.↗
NASA NTRS1982

Redundancy management of the Space Shuttle inertial measurement units

A description is given of the inertial measurement unit (IMU) redundancy management (RM) techniques for automatic in-flight monitoring of inertial instrument performance by the Space Shuttles primary onboard guidance, navigation, and control computers. The techniques and rationale for detecting and identifying faulty instruments are discussed. Special attention is given to the design philosophy, thresholds, and error propagation characteristics of the IMU RM system. The derivation of thresholds is described from the viewpoint of reliability and the safety of the vehicle and crew.

Thibodeau, J. R.↗
NASA NTRS2025

Temperature Variation Analysis of the STIM300 Inertial Measurement Unit

A key navigation instrument found on most autonomous and semi-autonomous platforms is the inertial measurement unit (IMU). This type of sensor is a combination of microelectromechanical systems (MEMS) that provide inertial information to the navigation system. Typical MEMS hardware include a gyroscope and an accelerometer (for rates and accelerations, respectively) within a single platform. The Near Earth Asteroid (NEA) Scout mission, slated to launch in October of 2018 (Author’s note: NEA Scout ultimately launch on November 16, 2022), carries an on-board IMU from Sensonor. This particular model has yet to see spaceflight, and questions about its on-orbit reliability remain. Dynamic tests were produced in the summer of 2016 by a visiting faculty member from Arkansas Tech University, Daniel Bullock. During these experiments, concerns about the noise characteristics of the sensor were raised, specifically relating to how temperature fluctuations affected the unit. It was found that the IMU took an extended period of time before reaching an internal steady state temperature. These tests often displayed large temperature variations, making the calculation of noise characteristics, such as bias drift, difficult to attribute entirely to noise. Static and dynamic tests were re-performed under more stringent constraints on temperature. Tests reported herein conclude that the IMU is adequately capable of providing inertial information for the NEA Scout mission.

Ivan Rodrigues Bertaska↗
NASA NTRS2015

Star Tracker Performance Estimate with IMU

A software tool for estimating cross-boresight error of a star tracker combined with an inertial measurement unit (IMU) was developed to support trade studies for the Integrated Radio and Optical Communication project (iROC) at the National Aeronautics and Space Administration Glenn Research Center. Typical laser communication systems, such as the Lunar Laser Communication Demonstration (LLCD) and the Laser Communication Relay Demonstration (LCRD), use a beacon to locate ground stations. iROC is investigating the use of beaconless precision laser pointing to enable laser communication at Mars orbits and beyond. Precision attitude knowledge is essential to the iROC mission to enable high-speed steering of the optical link. The preliminary concept to achieve this precision attitude knowledge is to use star trackers combined with an IMU. The Star Tracker Accuracy (STAcc) software was developed to rapidly assess the capabilities of star tracker and IMU configurations. STAcc determines the overall cross-boresight error of a star tracker with an IMU given the characteristic parameters: quantum efficiency, aperture, apparent star magnitude, exposure time, field of view, photon spread, detector pixels, spacecraft slew rate, maximum stars used for quaternion estimation, and IMU angular random walk. This paper discusses the supporting theory used to construct STAcc, verification of the program and sample results.

Error Budget↗
NASA NTRS2022

Vision-based Velocimetry over Unknown Terrain with a Low-Noise IMU

This paper presents a novel approach to terrain-relative navigation with a visual camera and Inertial Measurement Unit (IMU). The proposed algorithm uses an Extended Kalman Filter (EKF) to combine an IMU propagated state estimate with batch correction estimates computed over a sliding window of measurements. The batch correction algorithm follows the Maximum Likelihood Estimation (MLE) approach used in other Bundle Adjustment systems. Unlike other systems, the proposed system parameterizes the state over the entire window in terms of the state at a single epoch. By ignoring IMU error over the window duration, we obtain a state epoch MLE that jointly estimates the epoch state and terrain parameters with drastically reduced computationally cost. This paper presents the general architecture which can be adapted for various state parameterizations and measurement inputs. For space applications with high-accuracy IMUs, the reduction in computational cost comes with only a modest increase in estimation errors. The increase in error is quantified via a linear covariance analysis presented in this paper. Furthermore, we present simulation results which show the applicability of this algorithm to planetary landing problems.

San Martin, A. Miguel↗
NASA NTRS2016

Sampling and Control Circuit Board for an Inertial Measurement Unit

A circuit board that serves as a control and sampling interface to an inertial measurement unit ("IMU") is provided. The circuit board is also configured to interface with a local oscillator and an external trigger pulse. The circuit board is further configured to receive the external trigger pulse from an external source that time aligns the local oscillator and initiates sampling of the inertial measurement device for data at precise time intervals based on pulses from the local oscillator. The sampled data may be synchronized by the circuit board with other sensors of a navigation system via the trigger pulse.

Chelmins, David T↗