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At least 577 records · Page 32

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NASA NTRS1974

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented.

Kriegler, F. J.↗

NASA NTRS1974

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

Kriegler, F. J.↗

NASA NTRS1973

Evaluation of computer-aided procedure for detecting surface water

Results from an evaluation of a computer-aided procedure for processing ERTS-1 data to detect and locate surface water are presented. The procedure was evaluated using data from a study area in the vicinity of the Lake Somerville area in Washington County, Texas. The procedure consisted of (1) selecting water training fields, (2) aggregating the training samples together and clustering them into unimodal clusters, (3) computing the mean vector and covariance matrix for each cluster, (4) classifying all of the study area into classes corresponding to the clusters using the maximum likelihood classifier, and (5) thresholding out the nonwater pixels.

Source record↗

NASA NTRS1974

Burke County wheat feasibility study

A feasibility study was conducted to determine whether wheat could be distinguished from other small grain crops in a selected spring wheat growing area in Burke County, North Dakota using a maximum likelihood classification program and ERTS 1 multispectral band scanner data. ERTS 1 data scenes were selected from passes made on June 5, 1973 and June 23, 1973. The Univac 1108 computer and the LARSYS pattern recognition software package were used in performing the classification. Results of the analysis are provided.

Kunkel, W. A.↗

NASA NTRS1974

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 1: System description

The MIDAS System is described as a third-generation fast multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turnaround time and significant gains in throughput. The hardware and software are described. The system contains a mini-computer to control the various high-speed processing elements in the data path, and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 200,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation.

Kriegler, F. J.↗

NASA NTRS1973

Radar satellite altimetry and ocean wave height estimation

The design of a radar satellite altimeter having a plus or minus 10 cm topographic resolution at 20 meter (peak-to-trough) ocean wave heights is described. In addition to altimetry, the resulting design also provides a measurement of significant wave height over the range of 1.0 to 20 meters to within plus or minus 10%. A full deramp pulse compression technique followed by an analog filter bank to separate individual range returns is used in the radar transmitter/receiver design to reduce the A/D converter bandwidth from a rather impractical 330 MHz to less than 1 MHz. The altimeter design utilizes an onboard maximum likelihood estimate (MLE) processor to achieve the plus or minus 10 cm topographic resolution. It is shown that an MLE processor provides simultaneous optimum (minimum variance) estimates of satellite altitude, ocean wave height and electromagnetic ocean surface reflectivity.

Dooley, R. P.↗

NASA NTRS1973

Estimation of proportions of objects and determination of training sample-size in a remote sensing application

A multichannel scanning device may fail to observe objects because of obstructions blocking the view, or different categories of objects may make up a resolution element giving rise to a single observation. Ground truth will be required on any such categories of objects in order to estimate their expected proportions associated with various classes represented in the remote sensing data. Considering the classes to be distributed as multivariate normal with different mean vectors and common covariance, maximum likelihood estimates are given for the expected proportions of objects associated with different classes, using the Bayes procedure for classification of individuals obtained from these classes. An approximate solution for simultaneous confidence intervals on these proportions is given, and thereby a sample-size needed to achieve a desired amount of accuracy for the estimates is determined.

Chhikara, R. S.↗

NASA NTRS1973

Multivariate interactive digital analysis system /MIDAS/ - A new fast multispectral recognition system

The MIDAS system is a prototype, multiple-pipeline digital processor mechanizing the multivariate-Gaussian, maximum-likelihood decision algorithm operating at 200,000 pixels/second. It incorporates displays and film printer equipment under control of a general purpose midi-computer and possesses sufficient flexibility that operational versions of the equipment may be subsequently specified as subsets of the system.

Kriegler, F.↗

NASA NTRS1973

Case studies in Aircraft Parameter Identification

Three case studies in Aircraft Parameter Identification using simulated data for X-22 VTOL aircraft and flight test data for HL-10 and M2/F3 lifting bodies. After a brief discussion of the previous techniques and their limitations, a technique based on the Maximum Likelihood criterion is described. The problems of identifiability and uniqueness in determining the Stability and Control derivatives from flight test data are discussed and several methods for alleviating these problems are presented. The flight test data is analyzed in several different ways for obtaining physically meaningful estimates for the aircraft parameters.

Mehra, R. K.↗

NASA NTRS1973

Signature estimation from satellite multispectral scanner data

A method for estimating signatures from satellite multispectral scanner data for areas containing mixtures of specified object classes is presented and evaluated. Each signature is assumed to be a Gaussian distribution. The estimation procedure is simple, and the estimates represent maximum likelihood estimates. Formulae to compute variances for an estimated signature are also given.

Crane, R. B.↗

NASA NTRS1974

Binary signaling over channels containing quadratic nonlinearities

This paper examines the transmission of binary data signals over channels which contain quadratic nonlinearities and additive Gaussian noise. We consider the case where the channel is nonlinear with memory and where the signal is passed through an input receiver filter and sampled once every signaling interval. The samples are represented by a discrete Volterra series and a special case where the received sample contains a single quadratic distortion term is examined. The optimum (maximum-likelihood) receiver (processor) is derived and upper and lower performance bounds obtained. The performance of a practical, suboptimum receiver is examined by means of computer simulation and is shown to be very close to the lower bound of the optimum receiver. Next we examine the case where the received sample contains two quadratic distortion terms. Again, upper and lower performance bounds are obtained.

Lawless, W. J.↗

NASA NTRS1974

Ambiguity resolution in systems using Omega for position location

The lane ambiguity problem prevents the utilization of the Omega system for many applications such as locating buoys and balloons. The method of multiple lines of position introduced herein uses signals from four or more Omega stations for ambiguity resolution. The coordinates of the candidate points are determined first through the use of the Newton iterative procedure. Subsequently, a likelihood function is generated for each point, and the ambiguity is resolved by selecting the most likely point. The method was tested through simulation.

Frenkel, G.↗

NASA NTRS1974

An analysis and demonstration of clock synchronization by VLBI

A prototype of a semi-real time system for synchronizing the Deep Space Net station clocks by radio interferometry was successfully demonstrated on August 30, 1972. The system utilized an approximate maximum likelihood estimation procedure for processing the data, thereby achieving essentially optimum time sync estimates for a given amount of data, or equivalently, minimizing the amount of data required for reliable estimation. Synchronization accuracies as good as 100 ns rms were achieved between Deep Space Stations 11 and 12, both at Goldstone, Calif. The accuracy can be improved by increasing the system bandwidth until the fundamental limitations due to baseline and source position uncertainties and atmospheric effects are reached. These limitations are under 10 ns for transcontinental baselines.

Hurd, W. J.↗

NASA NTRS1974

Numerical modelling of instantaneous plate tectonics

Assuming lithospheric plates to be rigid, 68 spreading rates, 62 fracture zones trends, and 106 earthquake slip vectors are systematically inverted to obtain a self-consistent model of instantaneous relative motions for eleven major plates. The inverse problem is linearized and solved iteratively by a maximum-likelihood procedure. Because the uncertainties in the data are small, Gaussian statistics are shown to be adequate. The use of a linear theory permits (1) the calculation of the uncertainties in the various angular velocity vectors caused by uncertainties in the data, and (2) quantitative examination of the distribution of information within the data set. The existence of a self-consistent model satisfying all the data is strong justification of the rigid plate assumption. Slow movement between North and South America is shown to be resolvable.

Minster, J. B.↗

NASA NTRS1974

Free distance bounds for convolutional codes

The best asymptotic bounds presently known on free distance for convolutional codes are presented from a unified point of view. Upper and lower bounds for both time-varying and fixed codes are obtained. A comparison is made between bounds for nonsystematic and systematic codes which shows that more free distance is available with nonsystematic codes. This result is important when selecting codes for use with sequential or maximum-likelihood (Viterbi) decoding since the probability of decoding error is closely related to the free distance of the code. An ancillary result, used in proving the lower bound on free distance for time-varying nonsystematic codes, furnishes a generalization of two earlier bounds on the definite decoding minimum distance of convolutional codes.

Costello, D. J., Jr.↗

NASA NTRS1974

Parameter estimation using an a posteriori criterion

A procedure for system parameter estimation from noisy data is presented that is based on an a posteriori criterion. It is compared with a maximum likelihood approach for a process-noise case. Both methods yield identical results when the process noise is not modeled.

Bach, R. E., Jr.↗

NASA NTRS1974

Absorption of trapped particles by Jupiter's moons

Inclusion of absorption effects of the four innermost moons in the radial transport equations for electrons and protons in Jupiter's magnetosphere. It is found that the phase space density n at 2 Jupiter radii for electrons with equatorial pitch angles less than 69 deg is reduced by a factor of 42,000 when lunar absorption is included in the calculation. For protons with equatorial pitch angles less than 69 deg the corresponding reduction factor is 2,300,000. The effect of the satellites becomes progressively weaker for both electrons and protons as equatorial pitch angles of 90 deg are approached, because the likelihood of impacting a satellite becomes progressively smaller. The large density decreases found at the orbits of Io, Europa, and Ganymede result in corresponding particle flux decreases that should be observed by spacecraft making particle measurements in Jupiter's magnetosphere. The characteristic signature of satellite absorption should be a downward-pointing vertex in the flux versus radius curve at the L value corresponding to each satellite.

Hess, W. N.↗

NASA NTRS1974

Estimation of nonlinear aerodynamic derivatives of a variable geometry fighter aircraft from flight data

This paper is concerned with the estimation of stability and control parameters of a high performance fighter aircraft from data obtained from high angle of attack flight. The estimation process utilizes a maximum likelihood algorithm derived for the case of a nonlinear aerodynamic force and moment model. The aircraft used was a high speed variable sweep heavy weight fighter with twin vertical tails. Comparisons of results from the nonlinear analysis are made with linear theory and wind tunnel results when available.

Ramachandran, S.↗