A numerical comparison of discrete Kalman filtering algorithms: An orbit determination case study

The numerical stability and accuracy of various Kalman filter algorithms are thoroughly studied. Numerical results and conclusions are based on a realistic planetary approach orbit determination study. The case study results of this report highlight the numerical instability of the conventional and stabilized Kalman algorithms. Numerical errors associated with these algorithms can be so large as to obscure important mismodeling effects and thus give misleading estimates of filter accuracy. The positive result of this study is that the Bierman-Thornton U-D covariance factorization algorithm is computationally efficient, with CPU costs that differ negligibly from the conventional Kalman costs. In addition, accuracy of the U-D filter using single-precision arithmetic consistently matches the double-precision reference results. Numerical stability of the U-D filter is further demonstrated by its insensitivity of variations in the a priori statistics

Non spontaneous saccadic movements identification in clinical electrooculography using machine learning

In this paper we evaluate the use of the machine learning algorithms Support Vector Machines, K-Nearest Neighbors, CART decision trees and Naive Bayes to identify non spontaneous saccades in clinical electrooculography tests. Our approach tries to solve problems like the use of manually established thresholds present in classical methods like identification by velocity threshold (I-VT) or identification by dispersion threshold (I-DT). We propose a modification to an adaptive threshold estimation algorithm for detecting signal impulses without the need of any user input. Also, a set of features were selected to take advantage of intrinsic characteristics of clinical electrooculography tests. The models were evaluated with signals recorded to subjects affected by Spinocerebellar Ataxia type 2 (SCA2). Results obtained by the algorithm shows accuracies over 97%, recalls over 97% and precisions over 91% for the four models evaluated.Universidad de Málaga, Campus de excelencia de Andalucía Tec

Honeywell Enhancing Airplane State Awareness (EASA) Project: Final Report on Refinement and Evaluation of Candidate Solutions for Airplane System State Awareness

The loss of pilot airplane state awareness (ASA) has been implicated as a factor in several aviation accidents identified by the Commercial Aviation Safety Team (CAST). These accidents were investigated to identify precursors to the loss of ASA and develop technologies to address the loss of ASA. Based on a gap analysis, two technologies were prototyped and assessed with a formative pilot-in-the-loop evaluation in NASA Langleys full-motion Research Flight Deck. The technologies address: 1) data source anomaly detection in real-time, and 2) intelligent monitoring aids to provide nominal and predictive awareness of situations to be monitored and a mission timeline to visualize events of interest. The evaluation results indicated favorable impressions of both technologies for mitigating the loss of ASA in terms of operational utility, workload, acceptability, complexity, and usability. The team concludes that there is a feasible retrofit solution for improving ASA that would minimize certification risk, integration costs, and training impact

Shuttle GPS R/PA evaluation analysis and performance tradeoff study

Primary responsibility was understanding and analyzing the various GPS receiver functions as they relate to the shuttle environment. These receiver functions included acquisition properties of the sequential detector, acquisition and tracking properties of the various receiver phase locked loops, and the techniques of sequential receiver operation. In addition to these areas, support was provided in the areas of oscillator stability requirements, antenna management, and navigation filter requirements, including preposition aiding

Design and implementation of a compliant robot with force feedback and strategy planning software

Force-feedback robotics techniques are being developed for automated precision assembly and servicing of NASA space flight equipment. Design and implementation of a prototype robot which provides compliance and monitors forces is in progress. Computer software to specify assembly steps and makes force feedback adjustments during assembly are coded and tested for three generically different precision mating problems. A model program demonstrates that a suitably autonomous robot can plan its own strategy

NASA/MSFC ground experiment for large space structure control verification

Marshall Space Flight Center has developed a facility in which closed loop control of Large Space Structures (LSS) can be demonstrated and verified. The main objective of the facility is to verify LSS control system techniques so that on orbit performance can be ensured. The facility consists of an LSS test article which is connected to a payload mounting system that provides control torque commands. It is attached to a base excitation system which will simulate disturbances most likely to occur for Orbiter and DOD payloads. A control computer will contain the calibration software, the reference system, the alignment procedures, the telemetry software, and the control algorithms. The total system will be suspended in such a fashion that LSS test article has the characteristics common to all LSS