Optimum quantization.
Optimum uniform quantizer structures for digital data with known continuous probability density noting telemetering of stationary Gaussian Markov process functions
Kurtenbach, A. J.↗
SEARCH · Engineering Papers
Results for “MARKOV PROCESS”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Approximating properties of linear models for input output descriptions
Pade approximations for linear and dynamic programming using Markov processes and new algorithms
Holzmann, E. G.↗
Theory and Applications of Kalman Filtering
Kalman filtering applications in space navigation, underwater operations, surface navigation, and Gauss-Markov processes
C. T. Leondes↗
Time to cycle slip in first and second order phase lock loops
Markov process for time to cycle slip in first and second order phase lock loops
Schuchman, L.↗
Nonlinear analysis of generalized tracking systems.
Tracking systems synthesis and performance analysis based on continuous Markov processes theory, particularly Fokker-Planck equation
Lindsey, W. C.↗
The distribution of zero crossings for self- excited oscillators.
Self excited oscillators zero crossing times distribution for Markov process formulated as boundary value problem involving Kolmogoroff backward equation
Payne, H. J.↗
Detection, estimation, and modulation theory. Part 2 - Nonlinear modulations theory
Book on nonlinear modulation based on optimum estimation theory covering phase synchronization, analog data transmission, digital and analog systems performance, Markov processes, etc
Van Trees, H. L.↗
Navigation strategy and filter design for solar electric missions
Methods which have been proposed to improve the navigation accuracy for the low-thrust space vehicle include modifications to the standard Sequential- and Batch-type orbit determination procedures and the use of inertial measuring units (IMU) which measures directly the acceleration applied to the vehicle. The navigation accuracy obtained using one of the more promising modifications to the orbit determination procedures is compared with a combined IMU-Standard. The unknown accelerations are approximated as both first-order and second-order Gauss-Markov processes. The comparison is based on numerical results obtained in a study of the navigation requirements of a numerically simulated 152-day low-thrust mission to the asteroid Eros. The results obtained in the simulation indicate that the DMC algorithm will yield a significant improvement over the navigation accuracies achieved with previous estimation algorithms. In addition, the DMC algorithms will yield better navigation accuracies than the IMU-Standard Orbit Determination algorithm, except for extremely precise IMU measurements, i.e., gyroplatform alignment .01 deg and accelerometer signal-to-noise ratio .07. Unless these accuracies are achieved, the IMU navigation accuracies are generally unacceptable.
Tapley, B. D.↗
Analytical methods for performance evaluation of nonlinear filters.
In the investigation, the filtering problem is considered in the continuous time domain. The postulated simple suboptimal nonlinear filter structure closely parallels the structure of the Kalman-Bucy optimal linear filter algorithm. Two filter performance evaluation methods are developed based on the Kolmogorov equations for the transition density of Markov processes. The expansions in the approximations for the nonlinear system and observation functions are in effect carried out up to second-order terms in both methods. The description of the filter's performance is sought in terms of second-order statistics in both methods.
Bejczy, A. K.↗
Orbit determination in the presence of unmodeled accelerations.
In the investigation discussed here, the unmodeled acceleration is approximated as a first-order stationary Gauss-Markov process which can be separated into a time wise correlated component and a purely random component. An extended form of the Kalman-Bucy filter is used to estimate the state and the unmodeled accelerations at each observation epoch. Applications of the estimation algorithm to simulated data and to tracking data obtained during the Apollo 10 and 11 missions indicate that a more accurate estimate of the state is obtained using the algorithm and that the estimated values of the unmodeled accelerations can be correlated with physical phenomena neglected by the mathematical model.
Tapley, B. D.↗
A Markovian model for assessment of personnel hiring plans
As a result of the current economic environment, many organizations are having to operate with fewer resources. In the manpower area, these constraints have forced organizations to operate within well-defined hiring plans. Exceeding personnel ceilings is in most cases an intolerable situation. A mathematical model, based on the theory of Markov processes, is presented which can be used to assess the chances of success of personnel hiring plans. The model considers a plan to be successful if the final population size, at the end of the planning period, lies within a range specified by management. Although this model was developed to assess personnel hiring plans at the Goddard Space Flight Center, it is directly applicable wherever personnel hiring plans are used.
Katz, L. G.↗
An Adaptive Technique for a Redundant-Sensor Navigation System
An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.
Chien, T. T.↗
Analysis of a Multiprocessor Guidance Computer
The design of the next generation of spaceborne digital computers is described. It analyzes a possible multiprocessor computer configuration. For the analysis, a set of representative space computing tasks was abstracted from the Lunar Module Guidance Computer programs as executed during the lunar landing, from the Apollo program. This computer performs at this time about 24 concurrent functions, with iteration rates from 10 times per second to once every two seconds. These jobs were tabulated in a machine-independent form, and statistics of the overall job set were obtained. It was concluded, based on a comparison of simulation and Markov results, that the Markov process analysis is accurate in predicting overall trends and in configuration comparisons, but does not provide useful detailed information in specific situations. Using both types of analysis, it was determined that the job scheduling function is a critical one for efficiency of the multiprocessor. It is recommended that research into the area of automatic job scheduling be performed.
Maltach, E. G.↗
Worst error performance of continuous Kalman filters
The worst error performance of estimation filters is investigated for continuous systems in this paper. The pathological performance study, without assuming any dynamical model such as Markov processes for perturbations, except for its bounded amplitude, will give practical and dependable criteria in establishing the navigation and maneuver strategy in deep space missions.
Nishimura, T.↗
Time-controlled descent guidance in uncertain winds
A procedure has been developed for constructing a statistical model of the altitude-dependent mean wind profile from the historical record of wind measurements at particular locations. The model is constructed by fitting a Markov process, with altitude as the stage variable, to the historical wind data. The wind model, together with the aircraft dynamics and the error characteristics of the navigation system, are incorporated in the design of a state estimator, which gives the minimum variance estimate of the aircraft state and the wind vector. The state and wind estimates are used as inputs to a linear feedback law for guiding the aircraft along the nominal trajectory. An example design of a time-constrained (4D RNAV) descent guidance system is presented, showing tracking accuracy, control activity, and probability of arrival time with and without the wind estimator.
Menga, G.↗
Estimation of unmodeled forces on a low-thrust space vehicle
The application of a sequential estimation algorithm, which compensates for random errors in the dynamic model, to the problem of estimating the state of a continuously thrusting solar electric propulsion space vehicle is investigated. The dynamic model errors, due to random anomalies in the propulsion system, are approximated successfully by both first order and second order Gauss-Markov processes to obtain a more accurate and stable orbit determination algorithm. The importance of correct dynamic and measurement modeling in achieving accurate estimates is demonstrated.
Tapley, B. D.↗
Discrete estimation of continuous angle-modulated signals over multipath channels for aeronautical communication
The multipath channel for communication between an aerospace vehicle and a ground terminal is modeled by a multiplicative first-order Markov process. The multiplicative process is treated as a component of the message model and the discrete-time demodulation algorithms using the extended Kalman nonlinear estimation technique are developed for continuous-time angle-modulated signals. The equivalent baseband form of the demodulator structure is derived. Two examples of the message process are discussed for an FM system. The simulation results are presented for various values of the bandwidth expansion ratio and the additive SNR. The performance of the baseband algorithms is discussed.
Takhar, G. S.↗
Simulating an aerospace multiprocessor
The paper describes a simulator which was used to evaluate the architecture of an aerospace multiprocessor. The simulator models interactions among the processors, memories, the central data bus, and a possible 'job stack'. Special features of the simulator are discussed, including the use of explicitly coded and individually distinguishable 'job models' instead of a statistically defined 'job mix' and a specialized Job Model Definition Language to automate the detailed coding of the models. Some results are presented which show that when the simulator was employed in conjunction with queuing theory and Markov-process analysis, more insight into system behavior was obtained than would have been with any one technique alone.
Mallach, E. G.↗