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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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NASA NTRS1992

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and four resulting datasets are discussed. Finally the performance of the range estimation algorithm is explored in detail based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Phillip N.↗
NASA NTRS1993

Precision attitude control for tethered satellites

Tethered spacecraft are particularly well suited to serve as isolation platforms for space-borne observatories. It has previously been shown that, due to the relatively large tether force, conventional means of performing attitude control for tethered satellites are inefficient for any mission with pointing requirements more stringent than about 1 deg. A particularly effective method of implementing attitude control for tethered satellites is to use the tether tension force to generate control moments by moving the tether attach point relative to the subsatellite center of mass. This paper presents the development of a precision pointing control algorithm for tethered satellites and the simulation of the control system with laboratory hardware. The control algorithm consists of a linear quadratic regulator feedback law and a Kalman filter. The control algorithm has been shown to regulate the vehicle orientation to within 0.60 arcsec rms. This level of precision was achieved only after including a mass center estimator and accurately modeling the effects of the nonlinear attach point motion actuator.

Kline-Schoder, Robert J.↗
NASA NTRS1992

Analytic redundancy management for large flexible structures

An analytic redundancy management approach for on-line component failure detection is described and illustrated using a simulation of the NASA Langley Spacecaft Control Laboratory Experiment (SCOLE) research facility. The SCOLE experimental apparatus simulated is a functional model of the Space Shuttle with a large, flexible, offset-feed antenna cantilevered from the payload bay. This approach uses a single, active, Kalman filter selected from a bank of filters, each element of which was previously designed to accommodate a specific failure condition. The residuals of this active filter are processed through a sequential probability ratio test (SPRT) filter to identify the failure state of the system and, hence, closing the failure accommodation loop, to select the active filter. Results are presented that illustrate the ability of the system to detect and recover from failures introduced in the angular rate and linear acceleration sensors on the SCOLE facility.

Shenhar, J.↗
NASA NTRS1992

Control of the maneuvering SCOLE structure

This paper is concerned with the vibration control of the SCOLE structure while it undergoes a slewing maneuver. The control law is designed according to the linear quadratic regulator theory. In view of saturation limits on the actuators, the actual implementation is modified so as to observe these limits, resulting in suboptimal control. State estimation is carried out by means of a Kalman filter. The control and state estimation are carried out in discrete time. Numerical simulations for several cases of interest are presented.

Lim, S.↗
NASA NTRS1993

Feasibility of determining surface emissions of trace gases using an inverse method in a three-dimensional chemical transport model

The paper investigates the feasibility of using an inverse method based on a linear Kalman filter in a three-dimensional atmospheric transport model, for the determination of regional surface fluxes with rapid convergence, using data from a finite number of observation sites. It was found that the inverse method used was capable to accurately determine regional surface fluxes using the present ALE/GALE sites, and to converge to the correct solution within a year or two, using initial conditions very different from the final solution.

Hartley, Dana↗
NASA NTRS1993

Multiple degree of freedom force-state component identification

Force-state mapping is extended to allow the quasistatic characterization of realistic multiple degree of freedom systems whose constitutive relations are nonlinear, dissipative, coupled and depend on memory of past states. A general constitutive force-state model is formulated, which includes dynamic hysteresis phenomena typical of that found in deployable structures. A two step parameter identification approach is developed, which employs a linear extended Kalman filter and a nonlinear least squares fit. A six degree of freedom force-state testing device was constructed, and used to obtain data on one bay of a simple truss and on one bay of the MODE deployable truss.

Masters, Brett P.↗
NASA NTRS1993

On the estimation algorithm for adaptive performance optimization of turbofan engines

The performance seeking control (PSC) algorithm is designed to continuously optimize the performance of propulsion systems. The PSC algorithm uses a nominal propulsion system model and estimates, in flight, the engine deviation parameters (EDPs) characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated EDPs may not reflect the engine's actual off-nominal condition. This factor has a direct impact on the PSC scheme exacerbated by the open-loop character of the algorithm. In this paper, the effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the PSC algorithm to an F100 engine. An equivalence relation between the biases and EDPs stems from the analysis; therefore, it is undecided whether the estimated EDPs represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.

Espana, Martin D.↗
NASA NTRS1994

Estimating Fluctuating Pressures From Distorted Measurements

Two algorithms extract estimates of time-dependent input (upstream) pressures from outputs of pressure sensors located at downstream ends of pneumatic tubes. Effect deconvolutions that account for distoring effects of tube upon pressure signal. Distortion of pressure measurements by pneumatic tubes also discussed in "Distortion of Pressure Signals in Pneumatic Tubes," (ARC-12868). Varying input pressure estimated from measured time-varying output pressure by one of two deconvolution algorithms that take account of measurement noise. Algorithms based on minimum-covariance (Kalman filtering) theory.

Whitmore, Stephen A.↗
NASA NTRS1993

On the estimation algorithm used in adaptive performance optimization of turbofan engines

The performance seeking control algorithm is designed to continuously optimize the performance of propulsion systems. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated engine deviation parameters may not reflect the engine's actual off-nominal condition. This factor has a necessary impact on the overall performance seeking control scheme exacerbated by the open-loop character of the algorithm. The effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the performance seeking control algorithm to an F100 engine. An equivalence relation between the biases and engine deviation parameters stems from an observability study; therefore, it is undecided whether the estimated engine deviation parameters represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.

Espana, Martin D.↗
NASA NTRS1992

Experiments with recursive estimation in astronomical image processing

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

Busko, I.↗
NASA NTRS1993

Next generation initiation techniques

Four-dimensional data assimilation strategies can generally be classified as either current or next generation, depending upon whether they are used operationally or not. Current-generation data-assimilation techniques are those that are presently used routinely in operational-forecasting or research applications. They can be classified into the following categories: intermittent assimilation, Newtonian relaxation, and physical initialization. It should be noted that these techniques are the subject of continued research, and their improvement will parallel the development of next generation techniques described by the other speakers. Next generation assimilation techniques are those that are under development but are not yet used operationally. Most of these procedures are derived from control theory or variational methods and primarily represent continuous assimilation approaches, in which the data and model dynamics are 'fitted' to each other in an optimal way. Another 'next generation' category is the initialization of convective-scale models. Intermittent assimilation systems use an objective analysis to combine all observations within a time window that is centered on the analysis time. Continuous first-generation assimilation systems are usually based on the Newtonian-relaxation or 'nudging' techniques. Physical initialization procedures generally involve the use of standard or nonstandard data to force some physical process in the model during an assimilation period. Under the topic of next-generation assimilation techniques, variational approaches are currently being actively developed. Variational approaches seek to minimize a cost or penalty function which measures a model's fit to observations, background fields and other imposed constraints. Alternatively, the Kalman filter technique, which is also under investigation as a data assimilation procedure for numerical weather prediction, can yield acceptable initial conditions for mesoscale models. The third kind of next-generation technique involves strategies to initialize convective scale (non-hydrostatic) models.

Warner, Tom↗
NASA NTRS1994

Design and application of electromechanical actuators for deep space missions

This progress report documents research and development efforts performed from August 16, 1993 through February 15, 1994 on NASA Grant NAG8-240, 'Design and Application of Electromechanical Actuators for Deep Space Missions.' Following the executive summary are four report sections: Motor Selection, Tests Stand Development, Health Monitoring and Fault Management, and Experiment Planning. Three specific motor types have been considered as prime movers for TVC EMA applications: the brushless dc motor, the permanent magnet synchronous motor, and the induction motor. The fundamental finding was that, in general, the primary performance issues were energy efficiency and thermal dissipation (rotor heating). In terms of all other issues, the three motor types were found to compare quite equally. Among the design changes made to the test stand since the last progress report is the addition of more mounting holes in the side beams. These additional holes allow the movable end beam to be attached in a greater number of positions than previously. With this change the movable end beam can move from full forward to full back in three inch increments. Specific mathematical details on the approach that have been employed for health monitoring and fault management (HMFM) have been reported previously. This approach is based on and adaptive Kalman filter strategy. In general, a bank of filters can be implemented for each primary fault type. Presently under consideration for the brushless dc machine are the following faults: armature winding open-circuits, armature winding short-circuits (phase-to-phase and phase-to-ground), bearing degradation, and rotor flux weakening. The mechanically oriented experiments include transient loading experiments, transverse loading experiment, friction experiment, motor performance experiment, and HMFM experiment.

Haskew, Tim A.↗
NASA NTRS1993

X-31 aerodynamic characteristics determined from flight data

The lateral aerodynamic characteristics of the X-31 were determined at angles of attack ranging from 20 to 45 deg. Estimates of the lateral stability and control parameters were obtained by applying two parameter estimation techniques, linear regression, and the extended Kalman filter to flight test data. An attempt to apply maximum likelihood to extract parameters from the flight data was also made but failed for the reasons presented. An overview of the System Identification process is given. The overview includes a listing of the more important properties of all three estimation techniques that were applied to the data. A comparison is given of results obtained from flight test data and wind tunnel data for four important lateral parameters. Finally, future research to be conducted in this area is discussed.

Kokolios, Alex↗
NASA NTRS1993

Expansion-based passive ranging

This paper describes a new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they have been used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts--as well as the other parameters--can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline resulting in a proportionately higher depth accuracy.

Barniv, Yair↗
NASA NTRS1993

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Smith, Phillip N.↗
NASA NTRS1993

Validation of vision-based range estimation algorithms using helicopter flight data

The objective of this research was to demonstrate the effectiveness of an optic flow method for passive range estimation using a Kalman-filter implementation with helicopter flight data. This paper is divided into the following areas: (1) ranging algorithm; (2) flight experiment; (3) analysis methodology; (4) results; and (5) concluding remarks. The discussion is presented in viewgraph format.

Smith, Phillip N.↗
NASA NTRS1994

A data fusion algorithm for multi-sensor microburst hazard assessment

A recursive model-based data fusion algorithm for multi-sensor microburst hazard assessment is described. An analytical microburst model is used to approximate the actual windfield, and a set of 'best' model parameters are estimated from measured winds. The winds corresponding to the best parameter set can then be used to compute alerting factors such as microburst position, extent, and intensity. The estimation algorithm is based on an iterated extended Kalman filter which uses the microburst model parameters as state variables. Microburst state dynamic and process noise parameters are chosen based on measured microburst statistics. The estimation method is applied to data from a time-varying computational simulation of a historical microburst event to demonstrate its capabilities and limitations. Selection of filter parameters and initial conditions is discussed. Computational requirements and datalink bandwidth considerations are also addressed.

Wanke, Craig R.↗
NASA NTRS1994

The use of the AOA TTR-4P GPS receiver in operation at the BIPM for real-time restitution of GPS time

The Global Positioning System is an outstanding tool for the dissemination of time. Using mono-channel C/A-code GPS time receivers, the restitution of GPS time through the satellite constellation presents a peak-to-peak discrepancy of several tens of nanoseconds without SA but may be as high as several hundreds of nanoseconds with SA. As a consequence, civil users are more and more interested in implementing hardware and software methods for efficient restitution of GPS time, especially in the framework of the project of a real-time prediction of UTC (UTCp) which could be available in the form of time differences (UTCp - GPS time). Previous work, for improving the real-time restitution of GPS time with SA, to the level obtained without SA, focused on the implementation of a Kalman filter based on past data and updated at each new observation. An alternative solution relies upon the statistical features of the noise brought about by SA; it has already been shown that the SA noise is efficiently reduced by averaging data from numerous satellites observed simultaneously over a sufficiently long time. This method was successfully applied to data from a GPS time receiver, model AOA TTR-4P, connected to the cesium clock kept at the BIPM. This device, a multi-channel, dual frequency, P-code GPS time receiver, is one of the first TTR-4P units in operation in a civil laboratory. Preliminary comparative studies of this new equipment with conventional GPS time receivers are described in this paper. The results of an experimental restitution of GPS time, obtained in June 1993, are also detailed: 3 to 6 satellites were observed simultaneously with a sample interval of 15 s, an efficient smoothing of SA noise was realized by averaging data on all observed satellites over more than 1 hour. When the GPS system is complete in 1994, 8 satellites will be observable continuously from anywhere in the world and the same level of uncertainty will be obtained using a shorter averaging time.

Thomas, Claudine↗