Trajectory modeling and prediction with waypoint information using a conditionally Markov sequence
Information about the waypoints of a moving object, eg, an airliner in an air traffic control
(ATC) problem, should be considered in trajectory modeling and prediction. Due to the ATC …
(ATC) problem, should be considered in trajectory modeling and prediction. Due to the ATC …
Gaussian conditionally Markov sequences: Dynamic models and representations of reciprocal and other classes
Conditionally Markov (CM) sequences are powerful mathematical tools for modeling
problems. One class of CM sequences is the reciprocal sequence. In application, we need …
problems. One class of CM sequences is the reciprocal sequence. In application, we need …
Destination-directed trajectory modeling and prediction using conditionally Markov sequences
In some problems there is information about the destination of a moving object. An example
is an airliner flying from an origin to a destination. Such problems have three main …
is an airliner flying from an origin to a destination. Such problems have three main …
Track extraction with hidden reciprocal chains
This technical note (TN) develops Bayesian track extraction algorithms for targets modeled
as hidden reciprocal chains (HRC). HRC are a class of finite-state random process models …
as hidden reciprocal chains (HRC). HRC are a class of finite-state random process models …
Destination-directed trajectory modeling, filtering, and prediction using conditionally markov sequences
In some problems, there is information about the destination of a moving object. An example
is a flight from an origin to a destination. Such problems have three main components: an …
is a flight from an origin to a destination. Such problems have three main components: an …
State-space realizations and optimal smoothing for Gaussian generalized reciprocal processes
This technical note derives stochastic realization and optimal smoothing algorithms for a
class of Gaussian generalized reciprocal processes (GGRP). The note exploits the interplay …
class of Gaussian generalized reciprocal processes (GGRP). The note exploits the interplay …
Gaussian conditionally Markov sequences: Singular/nonsingular
Most existing results about modeling and characterizing Gaussian Markov, reciprocal, and
conditionally Markov (CM) processes assume nonsingularity of the processes. This …
conditionally Markov (CM) processes assume nonsingularity of the processes. This …
Gaussian conditionally Markov sequences: Theory with application
R Rezaie - 2019 - scholarworks.uno.edu
Markov processes have been widely studied and used for modeling problems. A Markov
process has two main components (ie, an evolution law and an initial distribution). Markov …
process has two main components (ie, an evolution law and an initial distribution). Markov …
Gaussian conditionally Markov sequences: Algebraically equivalent dynamic models
The conditionally Markov (CM) sequence contains different classes, including Markov,
reciprocal, and so-called CM L and CM F (two CM classes defined in our previous work) …
reciprocal, and so-called CM L and CM F (two CM classes defined in our previous work) …
Conditionally Markov modeling and optimal estimation for trajectory with waypoints and destination
On a grand scale, motion trajectories are usually defined by an origin, a sequence of
waypoints, and a destination. A typical example is in air traffic management (ATM), where a …
waypoints, and a destination. A typical example is in air traffic management (ATM), where a …