Search NASA⌕ Search

SEARCH · Search NASA

Results for “sequential filters”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Evaluation of the IMP-16 microprocessor orbit determination system filter

The results of the numerical tests performed in evaluating the interplanetary monitoring platform-16 orbit determination system are presented. The system is capable of performing orbit determination from satellite to satellite tracking data in applications technology satellite range and range rate format. The estimation scheme used is a Kalman filter, sequential (recursive) estimator. Descriptions of the tests performed and tabulations of the numerical results are included.

Shenitz, C. M.↗
NASA NTRS1982

Methods of sequential estimation for determining initial data in numerical weather prediction

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter.

Cohn, S. E.↗
NASA NTRS1994

Advantages of estimating rate corrections during dynamic propagation of spacecraft rates: Applications to real-time attitude determination of SAMPEX

This paper describes real-time attitude determination results for the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX), a gyroless spacecraft, using a Kalman filter/Euler equation approach denoted the real-time sequential filter (RTSF). The RTSF is an extended Kalman filter whose state vector includes the attitude quaternion and corrections to the rates, which are modeled as Markov processes with small time constants. The rate corrections impart a significant robustness to the RTSF against errors in modeling the environmental and control torques, as well as errors in the initial attitude and rates, while maintaining a small state vector. SAMPLEX flight data from various mission phases are used to demonstrate the robustness of the RTSF against a priori attitude and rate errors of up to 90 deg and 0.5 deg/sec, respectively, as well as a sensitivity of 0.0003 deg/sec in estimating rate corrections in torque computations. In contrast, it is shown that the RTSF attitude estimates without the rate corrections can degrade rapidly. RTSF advantages over single-frame attitude determination algorithms are also demonstrated through (1) substantial improvements in attitude solutions during sun-magnetic field coalignment and (2) magnetic-field-only attitude and rate estimation during the spacecraft's sun-acquisition mode. A robust magnetometer-only attitude-and-rate determination method is also developed to provide for the contingency when both sun data as well as a priori knowledge of the spacecraft state are unavailable. This method includes a deterministic algorithm used to initialize the RTSF with coarse estimates of the spacecraft attitude and rates. The combined algorithm has been found effective, yielding accuracies of 1.5 deg in attitude and 0.01 deg/sec in the rates and convergence times as little as 400 sec.

Challa, M. S.↗
NASA NTRS1996

Attitude Accuracy Study for the Earth Observing System (EOS) AM-1 Spacecraft

Earth Observing System (EOS) spacecraft will take measurements of the Earth's clouds, oceans, atmosphere, land, and radiation balance. These EOS spacecraft are part of the National Aeronautics and Space Administration's Mission to Planet Earth, and consist of several series of satellites, with each series specializing in a particular class of observations. This paper focuses on the EOS AM-1 spacecraft, which is the first of three satellites constituting the EOS AM series (morning equatorial crossing) and the initial spacecraft of the EOS program. EOS AM-1 has a stringent onboard attitude knowledge requirement, of 36/41/44 arc seconds (3 sigma) in yaw/roll/pitch, respectively. During normal mission operations, attitude is determined onboard using an extended Kalman sequential filter via measurements from two charge coupled device (CCD) star trackers, one Fine Sun Sensor, and an Inertial Rate Unit. The attitude determination error analysis system (ADEAS) was used to model the spacecraft and mission profile, and in a worst case scenario with only one star tracker in operation, the attitude uncertainty was 9.7/ll.5/12.2 arc seconds (3 sigma) in yaw/roll/pitch. The quoted result assumed the spacecraft was in nominal attitude, using only the 1-rotation per orbit motion of the spacecraft about the pitch axis for calibration of the gyro biases. Deviations from the nominal attitude would show greater attitude uncertainties, unless calibration maneuvers which roll and/or yaw the spacecraft have been performed. This permits computation of the gyro misalignments, and the attitude knowledge requirement would remain satisfied.

Lesikar, James D., II↗
NASA NTRS1998

Attitude/attitude-rate estimation from GPS differential phase measurements using integrated-rate parameters

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Oshman, Yaakov↗
NASA NTRS1997

Vector Observation-Aided/Attitude-Rate Estimation Using Global Positioning System Signals

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Oshman, Yaakov↗
NASA NTRS1999

Elevation Change of the Southern Greenland Ice Sheet from Satellite Radar Altimeter Data

Long-term changes in the thickness of the polar ice sheets are important indicators of climate change. Understanding the contributions to the global water mass balance from the accumulation or ablation of grounded ice in Greenland and Antarctica is considered crucial for determining the source of the about 2 mm/yr sea-level rise in the last century. Though the Antarctic ice sheet is much larger than its northern counterpart, the Greenland ice sheet is more likely to undergo dramatic changes in response to a warming trend. This can be attributed to the warmer Greenland climate, as well as a potential for amplification of a global warming trend in the polar regions of the Northern Hemisphere. In collaboration with Drs. Curt Davis and Craig Kluever of the University of Missouri, we are using data from satellite radar altimeters to measure changes in the elevation of the Southern Greenland ice sheet from 1978 to the present. Difficulties with systematic altimeter measurement errors, particularly in intersatellite comparisons, beset earlier studies of the Greenland ice sheet thickness. We use altimeter data collected contemporaneously over the global ocean to establish a reference for correcting ice-sheet data. In addition, the waveform data from the ice-sheet radar returns are reprocessed to better determine the range from the satellite to the ice surface. At JPL, we are focusing our efforts principally on the reduction of orbit errors and range biases in the measurement systems on the various altimeter missions. Our approach emphasizes global characterization and reduction of the long-period orbit errors and range biases using altimeter data from NASA's Ocean Pathfinder program. Along-track sea-height residuals are sequentially filtered and backwards smoothed, and the radial orbit errors are modeled as sinusoids with a wavelength equal to one revolution of the satellite. The amplitudes of the sinusoids are treated as exponentially-correlated noise processes with a time-constant of six days. Measurement errors (e.g., altimeter range bias) are simultaneously recovered as constant parameters. The corrections derived from the global ocean analysis are then applied over the Greenland ice sheet. The orbit error and measurement bias corrections for different missions are developed in a single framework to enable robust linkage of ice-sheet measurements from 1978 to the present. In 1998, we completed our re-evaluation of the 1978 Seasat and 1985-1989 Geosat Exact Repeat Mission data. The estimates of ice thickness over Southern Greenland (south of 72N and above 2000 m) from 1978 to 1988 show large regional variations (+/-18 cm/yr), but yield an overall rate of +1.5 +/- 0.5 cm/yr (one standard error). Accounting for systematic errors, the estimate may not be significantly different from the null growth rate. The average elevation change from 1978 to 1988 is too small to assess whether the Greenland ice sheet is undergoing a long-term change.

Haines, Bruce J.↗
NASA NTRS2001

Tracking and Data Relay Satellite (TDRS-3) Range Biases and Momentum Unload Modeling for Terra (EOS-AMI)

The Flight Dynamics Facility (FDF) reports its performance in meeting Tracking and Data Relay Satellite (TDRS) predicted ephemeris accuracy requirements with TDRS-3. The Terra (Earth Observing System AM-1) satellite has 3-sigma TDRS requirements of 75 m for total position accuracy predicted over one day onboard. The study sample includes selected cases over 21 months after Guam Remote Ground Terminal (GRGT) support started in June 1998. For daily solutions with a 1.5-day prediction span, predicted results of the study were below the Terra requirement by at least 12 m. Refined range bias estimation and modeled momentum unloads are needed to meet Terra's requirements for TDRS-3. Maintained at 275 W longitude over the zone of exclusion, TDRS-3 is analyzed separately from other TDRSs because of its unique tracking data. Only the Bilateration Ranging Transponder (BRT) at Alice Springs (ALS), Australia, and the Telemetry, Tracking and Command (TT&C) system at Guam are used for routine operational tracking data for TDRS-3. Simultaneous batch orbit solutions with three TDRSs and either the Compton Gamma Ray Observatory (GRO) or Terra were done with the Goddard Trajectory Determination System (GTDS) to periodically refine the TT&C and BRT System (BRTS) range biases. As new biases were determined, significant changes were made in estimating the absolute position. FDF achieved similar results using a sequential filter with all operational TDRSs and four user satellites. Definitive accuracy (3-sigma) is expected to be below 50 m. The White Sands Complex (WSC) performs momentum unloads to maintain three-axis stabilized attitude of TDRSs. The relationship between velocity changes (delta-V) and reaction wheel speed changes was empirically determined for roll/yaw unloads. A theoretical relationship was verified and used for pitch unloads. Modeling both pitch and roll/yaw momentum unloads is necessary to meet the 75-m requirement. Moving the orbit solution epoch an hour before a momentum unload can improve delta-V optimization and prediction accuracy over 1.5 days.

Ward, Douglas T.↗
NASA NTRS2004

Application Frontiers of "Designer Fluid Mechanics"--Visions Versus Reality or An Attempt to Answer the Perennial Question "Why Isn't It Used?"

Any new concept must successfully transit two sequential filters between research initiation and application, a technical filter (does it work?) and a technological filter (does it make sense in the real world? ). In general, the research community is not sufficiently knowledgeable regarding the myriad metrics of the technological filter and therefore non (application) useful research is conducted in some cases and in others the research is not carried far enough to allow technological evaluation. It is becoming imperative that the research community be more knowledgeable concerning, and in many cases work with, the application community.

Bushnell, Dennis M.↗
NASA NTRS2015

Position Estimation Using Image Derivative

This paper describes an image processing algorithm to process Moon and/or Earth images. The theory presented is based on the fact that Moon hard edge points are characterized by the highest values of the image derivative. Outliers are eliminated by two sequential filters. Moon center and radius are then estimated by nonlinear least-squares using circular sigmoid functions. The proposed image processing has been applied and validated using real and synthetic Moon images.

Mortari, Daniele↗
NASA NTRS2016

Center of Mass Estimation for a Spinning Spacecraft Using Doppler Shift of the GPS Carrier Frequency

A sequential filter is presented for estimating the center of mass (CM) of a spinning spacecraft using Doppler shift data from a set of onboard Global Positioning System (GPS) receivers. The advantage of the proposed method is that it is passive and can be run continuously in the background without using commanded thruster firings to excite spacecraft dynamical motion for observability. The NASA Magnetospheric Multiscale (MMS) mission is used as a test case for the CM estimator. The four MMS spacecraft carry star cameras for accurate attitude and spin rate estimation. The angle between the spacecraft nominal spin axis (for MMS this is the geometric body Z-axis) and the major principal axis of inertia is called the coning angle. The transverse components of the estimated rate provide a direct measure of the coning angle. The coning angle has been seen to shift slightly after every orbit and attitude maneuver. This change is attributed to a small asymmetry in the fuel distribution that changes with each burn. This paper shows a correlation between the apparent mass asymmetry deduced from the variations in the coning angle and the CM estimates made using the GPS Doppler data. The consistency between the changes in the coning angle and the CM provides validation of the proposed GPS Doppler method for estimation of the CM on spinning spacecraft.

Spacecraft↗
NASA NTRS2016

Center of Mass Estimation for a Spinning Spacecraft Using Doppler Shift of the GPS Carrier Frequency

A sequential filter is presented for estimating the center of mass (CM) of a spinning spacecraft using Doppler shift data from a set of onboard Global Positioning System (GPS) receivers. The advantage of the proposed method is that it is passive and can be run continuously in the background without using commanded thruster firings to excite spacecraft dynamical motion for observability. The NASA Magnetospheric Multiscale (MMS) mission is used as a test case for the CM estimator. The four MMS spacecraft carry star cameras for accurate attitude and spin rate estimation. The angle between the spacecraft nominal spin axis (for MMS this is the geometric body Z-axis) and the major principal axis of inertia is called the coning angle. The transverse components of the estimated rate provide a direct measure of the coning angle. The coning angle has been seen to shift slightly after every orbit and attitude maneuver. This change is attributed to a small asymmetry in the fuel distribution that changes with each burn. This paper shows a correlation between the apparent mass asymmetry deduced from the variations in the coning angle and the CM estimates made using the GPS Doppler data. The consistency between the changes in the coning angle and the CM provides validation of the proposed GPS Doppler method for estimation of the CM on spinning spacecraft.

Estimation↗
NASA NTRS1976

Performance of the square root information filter for navigation of the Mariner 10 spacecraft

The use is described of a sequential least squares filter in the orbit determination for the Mariner Venus-Mercury (Mariner 10) spacecraft. The orbit determination strategy outlining the use of both the sequential filter and a conventional batch filter is given. Highlighted are the mission events from launch to the first Mercury encounter with emphasis on the sequential filter performance. Advantages to the mission derived from the sequential filter are pointed out.

Christensen, C. S.↗
NASA NTRS1974

Sequential square root filtering and smoothing of discrete linear systems

A square root information filter/smoother is derived using recursive least-squares arguments. The combined filter/smoother algorithm has the following attributes: (1) it has a square root structure, which enhances numerical accuracy; (2) filter and smoother mechanizations are identical in form, facilitating implementation of the smoother; and (3) storage and computation requirements are modest compared with other smoothing algorithms. Partitioning the results to separate bias parameters provides further computational economies and reduction of storage requirements.

Bierman, G. J.↗
NASA NTRS1987

Discrete filtering techniques applied to sequential GPS range measurements

The basic navigation solution is described for position and velocity based on range and delta range (Doppler) measurements from NAVSTAR Global Positioning System satellites. The application of discrete filtering techniques is examined to reduce the white noise distortions on the sequential range measurements. A second order (position and velocity states) Kalman filter is implemented to obtain smoothed estimates of range by filtering the dynamics of the signal from each satellite separately. Test results using a simulated GPS receiver show a steady-state noise reduction, the input noise variance divided by the output noise variance, of a factor of four. Recommendations for further noise reduction based on higher order Kalman filters or additional delta range measurements are included.

Vangraas, Frank↗
NASA NTRS2012

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Nearing, Grey S.↗