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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 NTRS1974

Worst error analysis of batch filter and sequential filter in the approach phase of spacecraft navigation problems

The worst error performance of the sequential filter is compared with the performance of the batch filter which is still in general use in the deep space tracking. An approach phase of a spacecraft on a typical mission to the planet Mars is considered. The estimated parameters include the position and the speed of the spacecraft, nongravitational acceleration acting on the spacecraft, and the locations of the tracking stations.

Nishimura, T.↗
NASA NTRS1975

Worst-error analysis of batch filter and sequential filter in navigation problems

This paper proposes a worst-error analysis for dealing with problems of estimation of spacecraft trajectories in deep space missions. Navigation filters in use assume either constant or stochastic (Markov) models for their estimated parameters. When the actual behavior of these parameters does not follow the pattern of the assumed model, the filters sometimes result in very poor performance. To prepare for such pathological cases, the worst errors of both batch and sequential filters are investigated based on the incremental sensitivity studies of these filters. By finding critical switching instances of non-gravitational accelerations, intensive tracking can be carried out around those instances. Also the worst errors in the target plane provide a measure in assignment of the propellant budget for trajectory corrections. Thus the worst-error study presents useful information as well as practical criteria in establishing the maneuver and tracking strategy of spacecraft's missions.

Nishimura, T.↗
NASA NTRS1986

The Sequential Filter Imaging Radiometer (SFIR), a new instrument configuration for Earth observations

The sequential filter imaging radiometer (SFIR) concept is presented, contrasted with other sensor configurations, and its strengths and weaknesses discussed. In a pushbroom SFIR the optics images the scene onto a long, narrow area array. The length of the array defines the field of view. The spectral defining filters are sequentially placed over the full array, a sample of data for that band taken, and then the next filter placed in front of the array. All of the filters are placed over the array in the time that it takes the image of the scene to advance the array width. Thus the entire scene is observed in each band. Advantages of the SFIR are: spectral bands can be broad, narrow or overlap; it is easy to improve signal to noise ratio; and it is simple to make bands polarized. Its main disadvantage is that it requires more detectors than other instrument configurations.

Maxwell, M. S.↗
NASA NTRS1988

The sequential filter imaging radiometer (SFIR)- A new instrument configuration for earth observations

The sequential filter imaging radiometer (SFIR) concept is presented, contrasted with other sensor configurations, and its strengths and weaknesses discussed. In a pushbroom SFIR the optics images the scene onto a long, narrow area array. The length of the array defines the field of view. The spectral defining filters are sequentially placed over the full array, a sample of data for that band taken, and then the next filter is placed in front of the array. All filters are placed over the array in the time that it takes the image of the scene to advance the array width. Thus, the entire scene is observed in each band. Advantages of the SFIR are: spectral bands can be broad, narrow or overlap; it is easy to improve signal to noise ratio; and it is simple to make bands polarized. Its main disadvantage is that it requires more detectors than other instrument configurations.

Maxwell, Marvin S.↗
NASA NTRS1975

Sequential filtering applied to the determination of tracking station locations

The extended sequential filter has been applied to the problem of dynamically determining the geocentric coordinates of two laser satellite tracking stations. This filter provides significant advantages over the classical batch methods through (1) fewer iterations required for convergence, (2) wider radius of convergence, and (3) availability of the parameter estimate evolution. Processing the data sequentially readily identifies the data arcs required to minimize the effects of geopotential model errors. By means of the Smithsonian standard earth 2 and the Goddard earth model 1 geopotentials to reduce laser range observations of the Beacon Explorer-C satellite, it is demonstrated that a two-pass arc is optimal for estimating the height of one station and all coordinates of the second station while minimizing the effect of geopotential model error. These two-pass estimates are in good agreement with other determinations that utilize considerably more data as well as different satellites.

Schutz, B. E.↗
NASA NTRSDate not supplied

Sequential Filtering in the Presence of Uniform Measurement Errors

This paper presents a sequential filtering strategy using observations corrupted with uniform measurement noise. While the Kalman filter remains the best linear estimator of the state, other filtering techniques provide minimum variance optimal estimates, a trait only enjoyed by the Kalman filter when the underlying noises are, in fact, Gaussian. This work develops a new approximate optimal estimator for uniform measurement noises. The resulting recursion requires just slightly more computational time to complete a measurement update than the Kalman filter, which generally cannot be claimed by other optimal strategies such as the particle or Gaussian mixture filters.

James S. McCabe↗
NASA NTRSDate not supplied

Sequential Filtering in the Presence of Uniform Measurement Errors

This paper presents a sequential filtering strategy using observations corrupted with uniform measurement noise. While the Kalman filter remains the best linear estimator of the state, other filtering techniques provide minimum variance optimal estimates, a trait only enjoyed by the Kalman filter when the underlying noises are, in fact, Gaussian. This work develops a new approximate optimal estimator for uniform measurement noises. The resulting recursion requires just slightly more computational time to complete a measurement update than the Kalman filter, which generally cannot be claimed by other optimal strategies such as the particle or Gaussian mixture filters.

James S McCabe↗
NASA NTRS1974

Sequential filter design for precision orbit determination and physical constant refinement

Earth-based spacecraft tracking data have historically been processed with classical least squares filtering techniques both for navigation purposes and for physical constant determination. The small, stochastic nongravitational forces acting on the spacecraft are described to motivate the use of sequential estimation as an alternative to the least squares fitting procedures. The stochastic forces are investigated both in terms of their effect on the tracking data and their influence on estimation accuracy. A flexible sequential filter design which leaves the existing trajectory, variational equations, data observable and partial computations undisturbed is described. A detailed filter design is presented that meets the precision demands and flexibility requirements of deep space navigation and of scientific problems.

Curkendall, D. W.↗
NASA NTRS1975

Performance of a finite phase state bit-synchronization loop with and without sequential filters

A discrete phase state bit-synchronization loop is proposed for synchronization and detection of a binary nonreturn-to-zero (NRZ) process. The general loop model is developed for 11 and 17 phase states with optional sequential loop filter. Loop performance is considered in terms of the phase error density function, rms phase error, and mean time to bit slippage. It is shown that satisfactory loop performance can be achieved at -3 dB SNR through use of sequential loop filters.

Ransom, J. J.↗
NASA NTRS2017

Precomputing Process Noise Covariance for Onboard Sequential Filters

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.

onboard↗
NASA NTRS1978

A triangular covariance factorization for sequential filtering algorithms

A method for propagating the square-root of the state error covariance matrix in lower triangular UDU form is described. This update method can be combined with the UDU transformation used by Bierman to obtain the equations of a square-root free triangular estimation algorithm. The method is compared with the state transition matrix time update algorithm on the basis of integration accuracy, computational efficiency and storage requirements.

Tapley, B. D.↗
NASA NTRS1987

Range filtering for sequential GPS receivers

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver.

Paielli, Russell↗
NASA NTRS2011

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions Based on a Bank of Norm-Inequality-Constrained Epoch-State Filters

Sequential probability ratio tests explicitly allow decision makers to incorporate false alarm and missed detection risks, and are potentially less sensitive to modeling errors than a procedure that relies solely on a probability of collision threshold. Recent work on constrained Kalman filtering has suggested an approach to formulating such a test for collision avoidance maneuver decisions: a filter bank with two norm-inequality-constrained epoch-state extended Kalman filters. One filter models 1he null hypothesis 1ha1 the miss distance is inside the combined hard body radius at the predicted time of closest approach, and one filter models the alternative hypothesis. The epoch-state filter developed for this method explicitly accounts for any process noise present in the system. The method appears to work well using a realistic example based on an upcoming highly-elliptical orbit formation flying mission.

Carpenter, J. R.↗
NASA NTRS1972

Earth-based navigation capabilities for outer planet missions.

The role of new Earth-based radio metric data types and of advanced estimation algorithms in navigating an outer planet spacecraft in the vicinity of Saturn has been analyzed. The data types included in the study consist of conventional range and range-rate measurements taken from a single station and simultaneous and nearly simultaneous measurements obtained from pairs of stations during overlapping viewing periods. The utility of a third data set that is produced by explicitly differencing the simultaneous points has also been investigated. The data was processed with a conventional least squares batch filter and with a sequential filter that estimated parameters describing small stochastic accelerations (process noise) acting on the spacecraft. It was found that process noise can produce large errors in the estimates obtained from batch filtering conventional and simultaneous data, and that the only batch filtered estimates that were reliable were those obtained from differenced data. The performance of the simultaneous data in the presence of process noise is greatly improved by sequential filtering.

Hildebrand, C. E.↗
NASA NTRS1987

Range filtering for sequential GPS receivers with external sensor augmentation

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver.

Paielli, Russell↗
NASA NTRS1973

Mariner/Jupiter/Saturn navigation in the presence of massive planetary satellites

Orbit determination accuracies attainable during a Mariner/Jupiter/Saturn encounter have been established by means of covariance analyses. Advanced earth-based multistation radiometric data, optical data consisting of star/satellite pictures provided by a narrow-angle TV camera on board the spacecraft, and batch sequential filtering methods were employed. An evaluation of sequential filter sensitivities to errors in modeling small nongravitational spacecraft accelerations is presented. Selected covariances developed in the orbit determination analysis are used in an investigation of the trajectory correction costs associated with a close Ganymede encounter. The 99 percentile Delta V contours in the Ganymede aiming plane are obtained for satellite encounters before or after Jupiter closed approach, and the sources of the dominant contributions to the Delta V costs are identified.

Hildebrand, C. E.↗