@inproceedings{7e717386bdd74995872c1563b8e19bd1,
title = "Mathematical Modeling and Optimal Inference of Guided Markov-Like Trajectory",
abstract = "A trajectory of a destination-directed moving object (e.g. an aircraft from an origin airport to a destination airport) has three main components: an origin, a destination, and motion in between. We call such a trajectory that end up at the destination destination-directed trajectory (DDT). A class of conditionally Markov (CM) sequences (called CML) has the following main components: a joint density of two endpoints and a Markov-like evolution law. A CML dynamic model can describe the evolution of a DDT but not of a guided object chasing a moving guide. The trajectory of a guided object is called a guided trajectory (GT). Inspired by a CML model, this paper proposes a model for a GT with a moving guide. The proposed model reduces to a CML model if the guide is not moving. We also study filtering and trajectory prediction based on the proposed model. Simulation results are presented.",
keywords = "Conditionally Markov sequence, destination-directed trajectory, dynamic model, filtering, guided trajectory, moving guide, prediction",
author = "Reza Rezaie and Li, \{X. Rong\}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020 ; Conference date: 14-09-2020 Through 16-09-2020",
year = "2020",
month = sep,
day = "14",
doi = "10.1109/MFI49285.2020.9235241",
language = "英语",
series = "IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "26--31",
booktitle = "2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020",
}