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At least 235 records · Page 13

Identification of dynamic systems, theory and formulation

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Maine, R. E.↗

Experimental investigation of an RNA sequence space

Modern rRNAs are the historic consequence of an ongoing evolutionary exploration of a sequence space. These extant sequences belong to a special subset of the sequence space that is comprised only of those primary sequences that can validly perform the biological function(s) required of the particular RNA. If it were possible to readily identify all such valid sequences, stochastic predictions could be made about the relative likelihood of various evolutionary pathways available to an RNA. Herein an experimental system which can assess whether a particular sequence is likely to have validity as a eubacterial 5S rRNA is described. A total of ten naturally occurring, and hence known to be valid, sequences and two point mutants of unknown validity were used to test the usefulness of the approach. Nine of the ten valid sequences tested positive whereas both mutants tested as clearly defective. The tenth valid sequence gave results that would be interpreted as reflecting a borderline status were the answer not known. These results demonstrate that it is possible to experimentally determine which sequences in local regions of the sequence space are potentially valid 5S rRNAs.

Lee, Youn-Hyung↗

Architecture Robustness in NASA’s Moon to Mars Capability Development – FY23 Data Results

In preparation for humanity’s return to the Moon, it is important to advance technologies and capabilities that will allow for sustainability on the lunar surface and prepare for human missions to Mars. As charged in Space Policy Directive-1, NASA’s Artemis program will advance and develop technologies on the lunar surface that can be leveraged towards a safe and successful human round-trip mission to Mars. NASA’s Exploration Systems Development Mission Directorate Capabilities Integration Team (ESDMD CIT) is advancing a continuous effort to identify and map gaps between capabilities and anticipated human spaceflight architecture elements. As upcoming exploration missions approach, the architectural design tradespace increasingly narrows. This paper provides an updated exploration of certain architectural and element design choices for upcoming missions to the Moon and Mars, comparing and contrasting capability gaps and classes of capability gaps that are architecture robust with those that are not. In doing so, we identify certain capabilities as relevant, and therefore robust, across varying architectural possibilities while identifying other capabilities as only applicable to specific architectural pathways. Capabilities that are applicable to multiple elements across the architecture have more architectural breadth because of their increased likelihood of remaining relevant even if changes are made to some elements they are mapped to. Correspondingly, capabilities that are applicable to specific elements across the architecture but are necessary under almost any eventuality have more architectural depth because of their increased likelihood of remaining relevant even if architecture changes are made. One of the key analyses in this paper is an exploration of architecture robustness as a function of capability area, as defined by the NASA Technology Taxonomy. These results are then evaluated and analyzed across human spaceflight architecture elements to gain a greater understanding of the relationships between exploration capabilities and the systems that will eventually be implemented. Additional insights regarding investment strategies are also considered. General conclusions about these relationships are drawn.

Gaps↗

The decision tree classifier - Design and potential

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Hauska, H.↗

Estimation of Aircraft Nonlinear Unsteady Parameters From Wind Tunnel Data

Aerodynamic equations were formulated for an aircraft in one-degree-of-freedom large amplitude motion about each of its body axes. The model formulation based on indicial functions separated the resulting aerodynamic forces and moments into static terms, purely rotary terms and unsteady terms. Model identification from experimental data combined stepwise regression and maximum likelihood estimation in a two-stage optimization algorithm that can identify the unsteady term and rotary term if necessary. The identification scheme was applied to oscillatory data in two examples. The model identified from experimental data fit the data well, however, some parameters were estimated with limited accuracy. The resulting model was a good predictor for oscillatory and ramp input data.

Klein, Vladislav↗

North Atlantic Aerosol Single Scattering Albedos: TARFOX and ACE-2 Results and Their Relation to Radiative Effects Derived from Satellite Optical Depths

Bergstrom and Russell estimated direct solar radiative flux changes caused by atmospheric aerosols over the mid-latitude North Atlantic Ocean under cloud-free and cloudy conditions. They excluded African dust aerosols, primarily by restricting calculations to latitudes 25-60 N. As inputs they used midvisible aerosol optical depth (AOD) maps derived from AVHRR satellite measurements and aerosol intensive properties determined primarily in the 1996 IGAC Troposheric Aerosol Radiative Forcing Observational Experiment (TARFOX). Those aerosol intensive properties, which included optical depth wavelength dependence and spectra of single scattering albedo (SSA) and scattering asymmetry parameter, were also checked against initial properties from the 1997 North Atlantic Aerosol Characterization Experiment (ACE 2). Bergstrom and Russell investigated the sensitivity of their derived flux changes to assumed input parameters, including midvisible AOD, SSA, and scattering asymmetry parameter. Although the sensitivity of net flux change at the tropopause to SSA was moderate over the ocean (e.g., a SSA uncertainty of 0.07 produced a flux-change uncertainty of 21%), the sensitivity over common land surfaces can be much larger. Also, flux changes within and below the aerosol layer, which affect atmospheric stability, heating rates, and cloud formation and persistence, are quite sensitive to aerosol SSA. Therefore, this paper focuses on the question: "What have we learned from TARFOX and ACE 2 regarding aerosol single scattering albedo?" Three techniques were used in TARFOX to determine midvisible SSA. One of these derived SSA as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from aerosol properties. Another technique combined airborne measurements of aerosol scattering and absorption by nephelometer and absorption photometer. A third technique obtained SSA from best-fit complex refractive indices derived by comparing vertical profiles of lidar backscatter, sunphotometer extinction, and relative size distribution. In ACE 2 midvisible SSA was determined both as a best-fit parameter in comparing measured and calculated flux changes at the surface and by combining nephelometer and absorption photometer measurements. The nephelometer/absorption-photometer results were obtained on the ACE 2 ship (10 m asl), at the Sagres, Portugal site at 50 m asl, and also on the Pelican aircraft. This paper presents and compares the TARFOX and ACE 2 SSA results from the above techniques for different situations (e.g., marine vs continental flows, "clean" vs polluted conditions). It also discusses the strengths and limitations of the techniques, including whether they describe the aerosol in its ambient state or as perturbed by sampling processes; whether they describe the aerosol at the surface, as a function of altitude, or integrated over a column; the ease of acquiring representative data sets; results obtained in tests of consistency with radiative flux changes, and the likelihood of various artifacts and errors.

Russell, P. B.↗

Are You In or Out: the Influence of Sea Ice Drift on Sea Ice Survivability

The state of Arctic sea ice influences aspects of many global systems including ecosystems, economies, geopolitics, and climate. And, it is in severe decline. Numerous studies have considered the factors that influence Arctic sea ice decline using monthly mean or gridded data. However, these methods struggle to cleanly separate the influences on sea ice melt because the sea ice cover is always moving; thus, different sea ice floes and sea ice regimes constitute the monthly average sea ice state within the Eulerian frame. This study uses a LaGrangian sea ice parcel tracking satellite database to investigate the factors that influence sea ice parcel survivability. The concept of sea ice survivability is defined as the likelihood that a sea ice parcel will last through the summer melt season. Survivability can be stratified in many ways to analyze how it changes as a function of sea ice regime, region, and sea ice characteristics. How is the survivability of first year (FY) and multi-year (MY) ice classes influenced by sea ice motion? This is the central question addressed in this presentation. Specifically, this analysis determines sea ice survivability as a function of distance traveled by sea ice parcels and compares the survivability statistics for sea ice parcels that stay in their starting region versus those that leave their starting region. The preliminary results indicate that the influence of sea ice movement on survivability depends strongly on which region the sea ice resides in at the beginning of the growth season. Lastly, we find substantial inter-annual variability in the regional distribution of sea ice survivability that seems to be strongly linked to sea ice parcel drift between regions of the Arctic Ocean. Moreover, we use these results to discuss the potential contribution of changes in sea ice motion on the observed slowdown in Arctic sea ice extent loss.

Patrick C Taylor↗

Gamma-ray observations of Ophiuchus with EGRET: The diffuse emission and point sources

Observations of the Ophiuchus region made with the Energetic Gamma-Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory (CGRO) during the first 2 1/2 years of operation show the diffuse emission from the interstellar gas in Ophiuchus as well as variable emission from two point sources. The gamma-ray emission is modeled in terms of cosmic-ray interactions with atomic and molecular hydrogen in Ophiuchus and with low-energy photons along the line of sight. The model also includes the flux from the two point sources and an isotropic diffuse contribution. The cosmic-ray density is assumed to be uniform. The derived ratio of molecular hydrogen column density to integrated CO intensity is (1.1 +/- 0.2) x 10(exp 20) H-mols/sq cm (K km/s)(exp -1). At the sensitivity and resolution of the gamma-ray data, no variation of this ratio over the modeled region is discernible, nor are any regions of enhanced cosmic-ray density apparent. The model was fitted to seven narrow energy bands to obtain the energy depedence of the gamma-ray production function and the spectra of the point sources. The derived production function is in good agreement with theoretical calculations and the local cosmic-ray electron and proton spectra. The positions of the point sources were determined from maximum likelihood analysis of the gamma-ray emission observed in excess of the diffuse model. We identify one point source with the quasar PKS 1622-253, which has an average flux, E greater than 100 MeV, of (2.5 +/- 0.5) x 10(exp -7) photons/sq cm/s and photon spectral index -1.9 +/- 0.3. The other source, denoted GRO J1631-27, has not yet been identified at other wavelengths. Its average flux, E greater than 100 MeV, is (1.1 +/- 0.4) x 10(exp -7) photons/sq cm/s; however, its spectral index is poorly determined. The spectral index and intensity of the isotropic contribution to the model agree well with the extragalactic diffuse emission derived from the SAS 2 data.

Hunter, S. D.↗

Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal processing of the photocurrent processes at the outputs of the two detectors is to perform log-matched filtering followed by a summation and peak detection. This implies that neither difference detection, nor Fourier-domain peak detection, which are the staples of the state-of-the-art systems, is optimal when a weak local oscillator is employed.

Erkmen, Baris I.↗

Data & Reasoning Fabric Minimum Viable Product

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of air mobility by providing all data and reasoning where they are needed. The DRF provides a marketplace based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the complex and dense airspace operations required to achieve advanced air mobility goals. The DRF marketplace is decentralized and will not be owned by any single party. To deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of DRF and associated standards, DRF activities will collaboratively test these technologies, open standards and architectures, and an integrated framework with end-users. The DRF activity is developing a Minimum Viable Product (MVP) called the DRF Accelerator which will enable the rapid deployment of candidate data and reasoning services to test and evaluate the DRF core system functionality. The DRF Project is engaging with government and industry end-users and stakeholders, to: (1) assess the technical feasibility of the DRF Accelerator; (2) assess the likelihood of adoption, through shared test and evaluation; and (3) identify what data and services can be shared across DRF.

DRF↗

A Dynamic Risk Model for Evaluation of Space Shuttle Abort Scenarios

The Space Shuttle is an advanced manned launch system with a respectable history of service and a demonstrated level of safety. Recent studies have shown that the Space Shuttle has a relatively low probability of having a failure that is instantaneously catastrophic during nominal flight as compared with many US and international launch systems. However, since the Space Shuttle is a manned. system, a number of mission abort contingencies exist to primarily ensure the safety of the crew during off-nominal situations and to attempt to maintain the integrity of the Orbiter. As the Space Shuttle ascends to orbit it transverses various intact abort regions evaluated and planned before the flight to ensure that the Space Shuttle Orbiter, along with its crew, may be returned intact either to the original launch site, a transoceanic landing site, or returned from a substandard orbit. An intact abort may be initiated due to a number of system failures but the highest likelihood and most challenging abort scenarios are initiated by a premature shutdown of a Space Shuttle Main Engine (SSME). The potential consequences of such a shutdown vary as a function of a number of mission parameters but all of them may be related to mission time for a specific mission profile. This paper focuses on the Dynamic Abort Risk Evaluation (DARE) model process, applications, and its capability to evaluate the risk of Loss Of Vehicle (LOV) due to the complex systems interactions that occur during Space Shuttle intact abort scenarios. In addition, the paper will examine which of the Space Shuttle subsystems are critical to ensuring a successful return of the Space Shuttle Orbiter and crew from such a situation.

Henderson, Edward M.↗

A Bayesian Analysis of SDSS J0914+0853, a Low-mass Dual AGN Candidate

We present the first results from Bayesian AnalYsis of Multiple AGN in X-rays (BAYMAX), a tool that uses a Bayesian framework to quantitatively evaluate whether a given Chandra observation is more likely a single or dual point source. Although the most robust method of determining the presence of dual active galactic nuclei (AGNs) is to use X-ray observations, only sources that are widely separated relative to the instrumentʼs point-spread function are easy to identify. It becomes increasingly difficult to distinguish dual AGNs from single AGNs when the separation is on the order of Chandraʼs angular resolution (<1″). Using likelihood models for single and dual point sources, BAYMAX quantitatively evaluates the likelihood of an AGN for a given source. Specifically, we present results from BAYMAX analyzing the lowest-mass dual AGN candidate to date, SDSS J0914+0853, where archival Chandra data shows a possible secondary AGN ∼ 0"3 from the primary. Analyzing a new 50 ks Chandra observation, results from BAYMAX shows that SDSS J0914+0853 is most likely a single AGN with a Bayes factor of 13.5 in favor of a single point source model. Further, posterior distributions from the dual point source model are consistent with emission from a single AGN. We find a very low probability of SDSS J0914+0853 being a dual AGN system with a flux ratio f>0.3 and separation r>0"3. Overall, BAYMAX will be an important tool for correctly classifying candidate dual AGNs in the literature, as well as studying the dual AGN population where past spatial resolution limits have prevented systematic analyses.

Active galaxies↗

Development of an LSI maximum-likelihood convolutional decoder for advanced forward error correction capability on the NASA 30/20 GHz program

The particular coding option identified as providing the best level of coding gain performance in an LSI-efficient implementation was the optimal constraint length five, rate one-half convolutional code. To determine the specific set of design parameters which optimally matches this decoder to the LSI constraints, a breadboard MCD (maximum-likelihood convolutional decoder) was fabricated and used to generate detailed performance trade-off data. The extensive performance testing data gathered during this design tradeoff study are summarized, and the functional and physical MCD chip characteristics are presented.

Clark, R. T.↗

Recursive estimation of prior probabilities using the mixture approach

The problem of estimating the prior probabilities q sub k of a mixture of known density functions f sub k(X), based on a sequence of N statistically independent observations is considered. It is shown that for very mild restrictions on f sub k(X), the maximum likelihood estimate of Q is asymptotically efficient. A recursive algorithm for estimating Q is proposed, analyzed, and optimized. For the M = 2 case, it is possible for the recursive algorithm to achieve the same performance with the maximum likelihood one. For M 2, slightly inferior performance is the price for having a recursive algorithm. However, the loss is computable and tolerable.

Kazakos, D.↗

A Dynamic Testing Complexity Metric

This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

Voas, Jeffrey↗

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

Mark, W. D.↗

More than you want to know about maximum likelihood estimation

The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic estimation concepts. Some of these basic concepts are presented. The maximum likelihood estimator is briefly discussed and the aircraft equations of motion that the estimator uses. The basic concepts of minimization and estimation are examined for a simple computed aircraft example. The cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation from flight data is discussed. Some of the major conclusions for the computed example are also developed for the analysis of flight data.

Iliff, K. W.↗

Optimal design and use of retry in fault tolerant real-time computer systems

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Lee, Y. H.↗