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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Flight evaluation of advanced navigation techniques for general aviation using frequency scanning

Experiments on an automatic multisensor navigation concept are being conducted in a Cessna 402B. The test system consists of VOR, DME, and air data sensors controlled by a Hewlett Packard 9820A electronic calculator which processes the data and, by means of a four-state Kalman filter, outputs position and ground and wind velocities to a map display. Novel features which make such a system potentially low-cost include frequency-scanning operation of a single VOR receiver and a single DME transceiver and use of a shed-vortex true airspeed sensor. Results obtained during flight in a local area where six to eight DME NAVAIDS were receivable yielded better than 1/4-mile accuracy.

Jackson, C. T., Jr.↗
NASA NTRS1976

Fixed-point single-precision estimation

Monte Carlo simulation of autonomous orbit determination has validated the use of an 18-bit NASA Standard Spacecraft Computer (NSSC) for the extended Kalman filter. Dimensionally consistent scales are chosen for all variables in the algorithm, such that nearly all of the onboard computation can be performed in single precision without matrix square root formulations. Allowable simplifications in algorithm implementation and practical means of ensuring convergence are verified for accuracies of a few km provided by star/vertical observations

Thompson, E. H.↗
NASA NTRS1976

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗
NASA NTRS1976

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

Analytic techniques have been developed for detecting and identifying abrupt changes in dynamic systems. The GLR technique monitors the output of the Kalman filter and searches for the time that the failure occured, thus allowing it to be sensitive to new data and consequently increasing the chances for fast system recovery following detection of a failure. All failure detections are based on functional redundancy. Performance tests of the F-8 aircraft flight control system and computerized modelling of the technique are presented.

Source record↗
NASA NTRS1977

The dynamics and optimal control of spinning spacecraft and movable telescoping appendages, part A

The problem of optimal control with a minimum time criterion as applied to a single boom system for achieving two axis control is discussed. The special case where the initial conditions are such that the system can be driven to the equilibrium state with only a single switching maneuver in the bang-bang optimal sequence is analyzed. The system responses are presented. Application of the linear regulator problem for the optimal control of the telescoping system is extended to consider the effects of measurement and plant noises. The noise uncertainties are included with an application of the estimator - Kalman filter problem. Different schemes for measuring the components of the angular velocity are considered. Analytical results are obtained for special cases, and numerical results are presented for the general case.

Bainum, P. M.↗
NASA NTRS1977

Development of a digital automatic control law for steep glideslope capture and flare

A longitudinal digital guidance and control law for steep glideslopes using MLS (Microwave Landing System) data is developed for CTOL aircraft using modern estimation and control techniques. The control law covers the final approach phases of glideslope capture, glideslope tracking, and flare to touchdown for automatic landings under adverse weather conditions. The control law uses a constant gain Kalman filter to process MLS and body-mounted accelerometer data to form estimates of flight path errors and wind velocities including wind shear. The flight path error estimates and wind estimates are used for feedback in generating control surface commands. Results of a digital simulation of the aircraft dynamics and the guidance and control law are presented for various wind conditions.

Halyo, N.↗
NASA NTRS1977

Shuttle program: Ground tracking data program document shuttle OFT launch/landing

The equations for processing ground tracking data during a space shuttle ascent or entry, or any nonfree flight phase of a shuttle mission are given. The resulting computer program processes data from up to three stations simultaneously: C-band station number 1; C-band station number 2; and an S-band station. The C-band data consists of range, azimuth, and elevation angle measurements. The S-band data consists of range, two angles, and integrated Doppler data in the form of cycle counts. A nineteen element state vector is used in Kalman filter to process the measurements. The acceleration components of the shuttle are taken to be independent exponentially-correlated random variables. Nine elements of the state vector are the measurement bias errors associated with range and two angles for each tracking station. The biases are all modeled as exponentially-correlated random variables with a typical time constant of 108 seconds. All time constants are taken to be the same for all nine state variables. This simplifies the logic in propagating the state error covariance matrix ahead in time.

Lear, W. M.↗
NASA NTRS1975

The stochastic control of the F-8C aircraft using the multiple model adaptive control /MMAC/ method

The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called MMAC method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the 'identification' aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.

Athans, M.↗
NASA NTRS1977

Failure detection by pilots during automatic landing - Models and experiments

A model is proposed to describe the pilot as a monitor of automatic landing systems. The failures treated are equivalent to the addition of a dynamic change in the mean of the observation process. The failure detection model of the pilot consists of two stages: a linear estimator (Kalman filter) and a decision mechanism based on sequential analysis. The filter equations are derived from a simplified version of the linearized dynamics of the airplane and the control loop. The perceptual observation noise is modified to include the effects of allocation of attention among the several instruments. The final result is a simple model consisting of a high-pass filter to produce the observation residuals and a decision function which is a pure integration of the residuals minus a bias term. The dynamics of a Boeing 707 were used to simulate the fully coupled final approach in a fixed-base simulator. Observers monitored the approaches and detected the failures; their performance was compared with the predictions of the model.

Gai, E. G.↗
NASA NTRS1976

Specific failure identification algorithms for the F-8

Analytical redundancy is applied to the pitch axis of an aircraft to enhance sensor fault detection. Three different designs based on monitoring Kalman filter residuals or likelihood functions were developed. Sensor failures were simulated to evaluate the performance of the algorithms on a nonlinear simulation of an F-8C aircraft. Based on requirements for sensor fault detection and preliminary simulator performance it is concluded that these algorithms have the potential for reducing the level of sensor redundancy in a digital flight control system without compromising performance.

Hartmann, G. L.↗
NASA NTRS1976

Digital controllers for VTOL aircraft

Using linear-optimal estimation and control techniques, digital-adaptive control laws have been designed for a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for non-zero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.

Stengel, R. F.↗
NASA NTRS1977

Flight data processing with the F-8 adaptive algorithm

An explicit adaptive control algorithm based on maximum likelihood estimation of parameters has been designed for NASA's DFBW F-8 aircraft. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm has been implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer and surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software. The software and its performance evaluation based on flight data are described

Hartmann, G.↗
NASA NTRS1977

Inversion of passive microwave remote sensing data from satellites

Global passive microwave observations from earth-orbiting satellites have mapped humidity and liquid water over ocean, temperature profiles, ice and snow, and other geophysical parameters. In most applications, the inversion problem is adequately approximated as linear with jointly Gaussian statistics, and, thus, a linear retrieval performs well. In some cases, the problem is typically factored into a decision process followed by appropriate linear or quasilinear processes. Certain problems, however, require more powerful nonlinear or nonstationary procedures, such as Kalman filtering.

Staelin, D. H.↗
NASA NTRS1977

Use of sensitivity analysis to predict pilot performance as a function of different displays

A technique for objectively evaluating different displays by sensitivity analysis is described. First, the mathematical model used to analyze static displays is developed. The technique is based on formulating functional relationships between the state variables and the variables observable in the display. The matrix of the partial derivatives of the display variables with respect to the state variables, together with the observer's acuity function, is used to calculate expected errors in the state vector estimation. The technique is expanded by the use of Kalman filtering to process a time series of observation vectors. This provides a tool for analyzing displays of dynamic processes by means of a dynamic display evaluation computer program. Results are reported using this program to simulate an Instrument Landing System approach.

Mout, M. L.↗
NASA NTRS1977

Navigation for IUS deployment. TDRSS navigation accuracy in support of IUS deployment, phase 1

The navigation accuracy for tracking the orbiter prior to interim upper stage (IUS) deployment using the tracking data relay satellite system (TDRSS) was studied. The orbiter navigation accuracy for both one and two TDRSS satellites, for short and long data arcs, and for Doppler-only and Doppler-plus range solutions was examined. All test cases were run with the orbiter in a 150-n. mi. circular orbit, 28.5 degree inclination, at the time interval from the completion of the orbital maneuvering system (OMS)-2 maneuver to OMS-2 plus 2 hours (approximate time for IUS deployment). The data used were simulated by the simulation navigation (SIMNAV) program. The software tool used to process the TDRS data was the Shuttle Navigation Analysis Program (SNAP), a Kalman filter tool used to solve for the orbiter position and velocity. Results summarize the expected navigation accuracy using the TDRS system. It was concluded that: (1) data from both TDRS satellites were essential for accurate navigation results: (2) range data were essential for the short arc test case but were not needed for the long arc test case; and (3) with Doppler and range data from both TDRS satellites, the results converged to a reasonable solution after 5 to 10 minutes of data.

Wylie, A. D.↗
NASA NTRS1978

A parameter estimation subroutine package

Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. In this report we document a library of FORTRAN subroutines that have been developed to facilitate analyses of a variety of estimation problems. Our purpose is to present an easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given along with examples of how these routines can be used. The following outline indicates the scope of this report: Section (1) introduction with reference to background material; Section (2) examples and applications; Section (3) subroutine directory summary; Section (4) the subroutine directory user description with input, output, and usage explained; and Section (5) subroutine FORTRAN listings. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.

Bierman, G. J.↗
NASA NTRS1978

An analysis of the multiple model adaptive control algorithm

Qualitative and quantitative aspects of the multiple model adaptive control method are detailed. The method represents a cascade of something which resembles a maximum a posteriori probability identifier (basically a bank of Kalman filters) and a bank of linear quadratic regulators. Major qualitative properties of the MMAC method are examined and principle reasons for unacceptable behavior are explored.

Greene, C. S.↗
NASA NTRS1978

A parameter estimation subroutine package

Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. A library of FORTRAN subroutines were developed to facilitate analyses of a variety of estimation problems. An easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage are presented. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.

Bierman, G. J.↗