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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

LISA Parameter Estimation using Numerical Merger Waveforms

Coalescing supermassive black holes are expected to provide the strongest sources for gravitational radiation detected by LISA. Recent advances in numerical relativity provide a detailed description of the waveforms of such signals. We present a preliminary study of LISA's sensitivity to waveform parameters using a hybrid numerical/analytic waveform describing the coalescence of two equal-mass, nonspinning black holes. The Synthetic LISA software package is used to simulate the instrument response and the Fisher information matrix method is used to estimate errors in the waveform parameters. Initial results indicate that inclusion of the merger signal can significantly improve the precision of some parameter estimates. For example, the median parameter errors for an ensemble of systems with total redshifted mass of 10(exp 6) deg M solar mass at a redshift of z is approximately 1 were found to decrease by a factor of slightly more than two when the merger was included.

Thorpe, J. I.↗
NASA NTRS1976

Techniques for correcting transmission errors in video adaptive delta modulation channels

We investigated the effects of channel errors on an adaptive delta modulator used to encode video signals. The investigation revealed that channel errors caused a permanent shift in the dc level of the delta modulator's estimate. Errors in the step size, on the other hand, were transitory and had no noticeable effect on the received pictures. We then presented three error correction schemes to minimize the visibility of the channel errors in the received picture. The first scheme required the transmitter to periodically send the correct dc level of the estimate to the receiver. The second method employed a leaky integrator, and the third method used line-to-line interpolation

Scheinberg, N.↗
NASA NTRS1980

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Klein, V.↗
NASA NTRS2022

Deep Interacting Multiple Model Filtering

In this paper, a deep learning-based multiple model estimation framework is presented for the state estimation of hybrid dynamical systems from high dimensional observations such as camera images. A low dimensional vector which represents the measurement of the latent dynamical system and its corresponding variance are learned using a deep encoder neural network. An Interacting Multiple Model (IMM) filter is used to generate the latent state estimates and covariances using multiple dynamical models, which can be learned using backpropagation through time. The state estimates of the dynamical system and the corresponding covariance matrix are generated from the latent state estimates and covariance using a deep decoder neural network. The whole network is trained in an end-to-end manner using a loss function which minimizes the negative log-likelihood of the neural network parameters. Simulation results are presented using a 2D bouncing ball example and estimation error statistics are computed which demonstrates the accuracy and consistency of the estimation.

Ghananeel Rotithor↗
NASA NTRS1990

Ionospheric refraction effects on orbit determination using the orbit determination error analysis system

The influence of ionospheric refraction on orbit determination was studied through the use of the Orbit Determination Error Analysis System (ODEAS). The results of a study of the orbital state estimate errors due to the ionospheric refraction corrections, particularly for measurements involving spacecraft-to-spacecraft tracking links, are presented. In current operational practice at the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), the ionospheric refraction effects on the tracking measurements are modeled in the Goddard Trajectory Determination System (GTDS) using the Bent ionospheric model. While GTDS has the capability of incorporating the ionospheric refraction effects for measurements involving ground-to-spacecraft tracking links, such as those generated by the Ground Spaceflight Tracking and Data Network (GSTDN), it does not have the capability to incorporate the refraction effects for spacecraft-to-spacecraft tracking links for measurements generated by the Tracking and Data Relay Satellite System (TDRSS). The lack of this particular capability in GTDS raised some concern about the achievable accuracy of the estimated orbit for certain classes of spacecraft missions that require high-precision orbits. Using an enhanced research version of GTDS, some efforts have already been made to assess the importance of the spacecraft-to-spacecraft ionospheric refraction corrections in an orbit determination process. While these studies were performed using simulated data or real tracking data in definitive orbit determination modes, the study results presented here were obtained by means of covariance analysis simulating the weighted least-squares method used in orbit determination.

Yee, C. P.↗
NASA NTRS1996

Deconvolution Approach to Carrier and Code Multipath Error Elimination in High Precision GPS

This paper proposes a novel technique based on the deconvolution approach of the simultaneous estimation and compensation of the multipath estimation errors in both the carrier phase lock and the code delay lock loops in GPS receivers. Simulation results are presented showing that the proposed GPS receiver algorithm achieves high precision in the range and differential range estimation in various GPS precision applications such as spacecraft attitude control, even in a relatively severe multipath environment.

GPS↗
NASA NTRS1983

Filtering flight data prior to aerodynamic system identification

An algorithm for processing flight-test data to provide state estimates and instrument calibrations for aerodynamic or hydrodynamic system identification by the equation error estimation method is developed and demonstrated on synthesized data. The extended-Kalman-filter algorithm employs a locally level, north-pointing frame of reference, accounts for rotating ellipsoidal earth effects, and estimates sensor bias, scale factors, wind components, and process noise levels by maximum-likelihood parameters. The method is found to be most effective with navigation quality inertial input data. The algorithm is applied to data from a six-degree-of-freedom F-4 aircraft simulation and shown to produce state estimates in good agreement with the simulation values.

Trankle, T. L.↗
NASA NTRS1984

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES VISSR image pairs was developed, tested and configured for quasi-real time/research applications on a computing system which gives mesoscale wind estimates at the highest spatial/temporal resolution possible from the VISSR imagery down to a wind vector separation of 10 km. Preprocessing of imagery using IR resampling, VIS edge preserving filtering, and reduced VIS resolution averaging improved height assignments and vector extraction for 10, 15, and 30 min imagery. An objective quality control system provides much greater than 99% accuracy in eliminating questionable wind estimates. Automated winds generally have better spatial coverage and density, and have random error estimates half as large as the manual winds. Dynamical analysis of cloud wind divergence revealed temporally consistent convergence centers on the meso beta scale that are highly correlated with on going and future developing convective storms. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than one hour.

Wilson, G. S.↗
NASA NTRSDate not supplied

A Proposed Clock Synchronization Method for the Solar System Internet

Networked communications in space are necessary to achieve scalability in terms of the number of communicating nodes but also in terms of the overall system complexity. A key component to such a system is the ability to synchronize clocks, which is the focus of this paper. The so-called Solar System Internet (SSI) will be built upon Delay Tolerant Networking (DTN), which, in analogy to the Internet Protocol (IP), can be considered a suite of protocols necessary for networking in the space domain. Therefore, our goal is to extend this suite to include a DTN clock synchronization capability, analogous to the Network Time Protocol (NTP) used in the Internet. A motivating example of a network in space is NASA’s LunaNet, a vision for a multi-hop multi-path network extending to the moon wherein not all nodes will have direct connections to an authoritative reference clock. In this paper, we propose a general clock synchronization methodology and algorithm that could be used for LunaNet as well as more elaborate time-varying networks. In recent years, DTN has benefited from modeling efforts founded on the mathematical tool of sheaves. Here we continue this work to provide an approach to clock synchronization. Due to the time-varying nature of space networks, absolute consensus is not possible. However, the sheaf Laplacian provides a practical, distributed approach to approximating consensus by allowing data to diffuse through the network. In particular, the sheaf Laplacian is readily computable, lending our approach to implementation. Our approach is well suited to handle the difficulties of space networks. For instance, differences in clock accuracy mean certain nodes are more authoritative than others; we can account for these differences through hierarchies in the network, generalizing the strata in NTP. Furthermore, just as error estimation is an integral part of NTP, we are able to give concrete error bounds for our approach. Indeed, different applications (e.g., communications schedules, pointing, navigation, distributed science) will have different requirements, hence it is necessary to maintain clocks within a given tolerance. We outline some of the necessary steps to turn our approach into a practical network protocol that could be used in DTN, and we conclude the paper with suggestions for future research.

Michael Moy↗
NASA NTRS1988

The discrete correlation function: A new method for analyzing unevenly sampled variability data

A method of measuring correlation functions without interpolating in the temporal domain, the discrete correlation function, is introduced. It provides an assumption-free representation of the correlation measured in the data, and allows meaningful error estimates. This method does not produce spurious correlations at zero lag due to correlated errors. It is shown that physical interpretation of active galactic nuclei cross-correlation functions requires knowledge of the input function's fluctuation power spectrum, involves model-dependence in the form of symmetry assumptions, and must take into account intrinsic scale bias. This technique was used to find a correlation in published IUE data for NGC 4151, which indicates that the broad C IV feature emanates from a shell 15 to 75 light-days in radius, assuming spherical symmetry.

Edelson, R. A.↗
NASA NTRS1992

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

Bayard, D. S.↗
NASA NTRS2017

SMAP Level 4 Surface and Root Zone Soil Moisture

The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

SMAP↗
NASA NTRS1977

Navigating the Viking landers

On July 20, 1976, Viking Lander 1 became the first unmanned spacecraft to land and operate successfully on the planet Mars. This was followed by a second successful landing on September 3, 1976. This paper gives a detailed description of the autonomous on-board navigation process to perform the guidance, control, and entry navigation functions. Also, the functions performed on the ground to generate and validate the guidance commands sent to the spacecraft prior to descent are described. In-flight measures of navigation system performance are compared against a-priori error estimates to show that the descents were completely nominal in all respects. The final landing errors were 25 km and 10 km for Missions 1 and 2, respectively.

Euler, E. A.↗
NASA NTRS1983

Performance appraisal of VAS radiometry for GOES-4, -5 and -6

The first three VISSR Atmospheric Sounders (VAS) were launched on GOES-4, -5, and -6 in 1980, 1981 and 1983. Postlaunch radiometric performance is assessed for noise, biases, registration and reliability, with special attention to calibration and problems in the data processing chain. The postlaunch performance of the VAS radiometer meets its prelaunch design specifications, particularly those related to image formation and noise reduction. The best instrument is carried on GOES-5, currently operational as GOES-EAST. Single sample noise is lower than expected, especially for the small longwave and large shortwave detectors. Detector to detector offsets are correctable to within the resolution limits of the instrument. Truncation, zero point and droop errors are insignificant. Absolute calibration errors, estimated from HIRS and from radiation transfer calculations, indicate moderate, but stable biases. Relative calibration errors from scanline to scanline are noticeable, but meet sounding requirements for temporarily and spatially averaged sounding fields of view. The VAS instrument is a potentially useful radiometer for mesoscale sounding operations. Image quality is very good. Soundings derived from quality controlled data meet prelaunch requirements when calculated with noise and bias resistant algorithms.

Chesters, D.↗
NASA NTRS2002

Linear Parameter Varying Control for Actuator Failure

A robust linear parameter varying (LPV) control synthesis is carried out for an HiMAT vehicle subject to loss of control effectiveness. The scheduling parameter is selected to be a function of the estimates of the control effectiveness factors. The estimates are provided on-line by a two-stage Kalman estimator. The inherent conservatism of the LPV design is reducing through the use of a scaling factor on the uncertainty block that represents the estimation errors of the effectiveness factors. Simulations of the controlled system with the on-line estimator show that a superior fault-tolerance can be achieved.

Shin, Jong-Yeob↗
NASA NTRS1989

Two novel automatic frequency tracking loops

Two automatic-frequency-control (AFC) loops are introduced and analyzed in detail. The algorithms are generalizations of the well known cross-product AFC loop with improved performance. The first estimator uses running overlapping discrete Fourier transforms to create a discriminator curve proportional to the frequency estimation error, whereas the second one preprocesses the received data and then uses an extended Kalman filter to estimate the input frequency. The algorithms are tested by computer simulations in a highly dynamic environment at low carrier/noise ratio (CNR). The algorithms are suboptimum tracking schemes with a larger frequency-error variance compared to an optimum strategy, but they offer simplicity of mechanization and a CNR with a very low operating threshold.

Aguirre, Sergio↗
NASA NTRS1976

Performance analysis of digital FM demodulators for fading channels in the threshold region

The quasi-optimum digital FM demodulators for fading channels reported earlier (1975) reflected the system performance accurately under high signal to noise ratio conditions. In this paper, the prediction of the system performance for low SNR values is considered. A new set of error variance algorithms is developed from the filter algorithm assuming a Gaussian distribution for the state estimation errors and taking the effect of high frequency terms into consideration. Simulation analysis for an FM system with Rician fading channel shows that these algorithms predict the system performance accurately in the threshold region.

Dharamsi, M. T.↗