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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, Philip N.↗

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 one of four resulting datasets is briefly discussed. Finally the performance of the range estimation algorithm is explored based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Phillip N.↗

NASA NTRS1992

Vision-based range estimation using helicopter flight data

Smith, Phillip N.↗

NASA NTRS2001

Stable and verifiable state estimation methods and systems with spacecraft applications

The stability of a recursive estimator process (e.g., a Kalman filter is assured for long time periods by periodically resetting an error covariance P(t.sub.n) of the system to a predetermined reset value P.sub.r. The recursive process is thus repetitively forced to start from a selected covariance and continue for a time period that is short compared to the system's total operational time period. The time period in which the process must maintain its numerical stability is significantly reduced as is the demand on the system's numerical stability. The process stability for an extended operational time period T.sub.o is verified by performing the resetting step at the end of at least one reset time period T.sub.r whose duration is less than the operational time period T.sub.o and then confirming stability of the process over the reset time period T.sub.r. Because the recursive process starts from a selected covariance at the beginning of each reset time period T.sub.r, confirming stability of the process over at least one reset time period substantially confirms stability over the longer operational time period T.sub.o.

Li, Rongsheng↗

NASA NTRS1979

Evaluation of the IMP-16 microprocessor orbit determination system filter

The results of the numerical tests performed in evaluating the interplanetary monitoring platform-16 orbit determination system are presented. The system is capable of performing orbit determination from satellite to satellite tracking data in applications technology satellite range and range rate format. The estimation scheme used is a Kalman filter, sequential (recursive) estimator. Descriptions of the tests performed and tabulations of the numerical results are included.

Shenitz, C. M.↗

NASA NTRS1979

Applications of estimation theory to inverse problems in meteorology

The paper applies iterated and non-iterated extended Kalman filters to solve two practical meteorological inversion problems. Passive microwave satellite soundings are used to infer vertical temperature profiles and cloud parameters. In both cases it is shown that improvements can be obtained over presently used techniques. Finally, the results suggest that modern multivariate nonlinear recursive estimation techniques based in a Bayesian methodology can be a valuable tool in the area of remote sounding of atmospheric parameters.

Gustafson, D. E.↗

NASA NTRS1975

Parameter adaptive estimation of random processes

This paper is concerned with the parameter adaptive least squares estimation of random processes. The main result is a general representation theorem for the conditional expectation of a random variable on a product probability space. Using this theorem along with the general likelihood ratio expression, the least squares estimate of the process is found in terms of the parameter conditioned estimates. The stochastic differential for the a posteriori probability and the stochastic differential equation for the a posteriori density are found by using simple stochastic calculus on the representations obtained. The results are specialized to the case when the parameter has a discrete distribution. The results can be used to construct an implementable recursive estimator for certain types of nonlinear filtering problems. This is illustrated by some simple examples.

Caglayan, A. K.↗

NASA NTRS1968

Identification of a transition matrix of a Markov chain from noisy measurements.

Recursive estimation of transition matrix of Markov chain using noisy measurements

Kashyap, R. L.↗

NASA NTRS1969

Derivation of a matrix identity.

Matrix identity associated with linear digital filtering and recursive estimating determined using matrix projection operators and properties

Hemami, H.↗

NASA NTRS1972

A biased filter for linear discrete dynamic systems.

A recursive estimator, the ridge filter, was developed for the linear discrete dynamic estimation problem. Theorems were established to show that the ridge filter can be, on the average, closer to the expected value of the system state than the Kalman filter. On the other hand, Kalman filter, on the average, is closer to the instantaneous system state than the ridge filter. The ridge filter has been formulated in such a way that the computational features of the Kalman filter are preserved.

Chang, J. W.↗

NASA NTRS1974

Synthesis and evaluation of phase detectors for active bit synchronizers

Self-synchronizing digital data communication systems usually use active or phase-locked loop (PLL) bit synchronizers. The three main elements of PLL synchronizers are the phase detector, loop filter, and the voltage controlled oscillator. Of these three elements, phase detector synthesis is the main source of difficulty, particularly when the received signals are demodulated square-wave signals. A phase detector synthesis technique is reviewed that provides a physically realizable design for bit synchronizer phase detectors. The development is based upon nonlinear recursive estimation methods. The phase detector portion of the algorithm is isolated and analyzed.

Mcbride, A. L.↗

NASA NTRS1975

Ground truth applications to orbit refinements

A weighted least-squares recursive estimator program is reported for simulating spacecraft orbital position by analyzing earth and sun sensor data. The program uses constant time adjustment for a set of ephemeris data to eliminate intrack error and to improve attitude determination accuracy.

White, R. L.↗

NASA NTRS1976

On the computational cost of approximating and recognizing noise-perturbed straight lines and quadratic arcs in the plane

Recognition of underlying straight lines and quadratic arcs in line drawings, and approximation of very noisy data by such line/curve segments, is addressed as a subproblem of the more general problem of optimum recognition of complicated line/curve drawings. Some specific algorithms are presented with extensions and interpretations for more complicated applications, and a data generation model is developed for the problem. Data are generated as a perturbation of a single underlying straight line or an elliptic or hyperbolic arc. Recursive estimation techniques, minimization of central processing unit time, decision making with controlled error probabilities, and modeling and recognition of pictures consisting of noisy curves are dealt with. Applications envisaged include: picture data compression, contour line representation in maps, intelligent data searches, and ballistic missile decoy tracking.

Cooper, D. B.↗

NASA NTRS1992

Self-tuning control of attitude and momentum management for the Space Station

This paper presents a hybrid state-space self-tuning design methodology using dual-rate sampling for suboptimal digital adaptive control of attitude and momentum management for the Space Station. This new hybrid adaptive control scheme combines an on-line recursive estimation algorithm for indirectly identifying the parameters of a continuous-time system from the available fast-rate sampled data of the inputs and states and a controller synthesis algorithm for indirectly finding the slow-rate suboptimal digital controller from the designed optimal analog controller. The proposed method enables the development of digitally implementable control algorithms for the robust control of Space Station Freedom with unknown environmental disturbances and slowly time-varying dynamics.

Shieh, L. S.↗

NASA NTRS1993

Fault detection and isolation

Erroneous measurements in multisensor navigation systems must be detected and isolated. A recursive estimator can find fast growing errors; a least squares batch estimator can find slow growing errors. This process is called fault detection. A protection radius can be calculated as a function of time for a given location. This protection radius can be used to guarantee the integrity of the navigation data. Fault isolation can be accomplished using either a snapshot method or by examining the history of the fault detection statistics.

Bernath, Greg↗

NASA NTRS1995

Tracking magnetogram proper motions by multiscale regularization

Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.

Jones, Harrison P.↗

NASA NTRS1994

Parallel Processing Systems for Passive Ranging During Helicopter Flight

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Sridhar, Bavavar↗

NASA NTRS2004

Pseudo Linear Attitude Determination of Spinning Spacecraft

This paper presents the overall mathematical model and results from pseudo linear recursive estimators of attitude and rate for a spinning spacecraft. The measurements considered are vector measurements obtained by sun-sensors, fixed head star trackers, horizon sensors, and three axis magnetometers. Two filters are proposed for estimating the attitude as well as the angular rate vector. One filter, called the q-Filter, yields the attitude estimate as a quaternion estimate, and the other filter, called the D-Filter, yields the estimated direction cosine matrix. Because the spacecraft is gyro-less, Euler's equation of angular motion of rigid bodies is used to enable the estimation of the angular velocity. A simpler Markov model is suggested as a replacement for Euler's equation in the case where the vector measurements are obtained at high rates relative to the spacecraft angular rate.

Harman, Richard R.↗