Persistent standoff tracking guidance using constrained particle filter for multiple UAVs

Hyondong Oh

doi:10.1016/j.ast.2018.10.016

2019-01-01

PRE

Hyondong Oh *

Seungkeun Kim

DOI：10.1016/j.ast.2018.10.016

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摘要

En 中文

This paper presents a new standoff tracking framework of a moving ground target using UAVs with limited sensing capabilities and motion constraints. To maintain persistent track of the target even in case of target loss for a certain period, this study predicts the target existence area using the particle filter and produces control commands that ensure that all predicted particles can stay within the field-of-view of the UAV sensor at all times. To improve target position prediction and estimation accuracy, the road information is incorporated into the constrained particle filter where the road boundaries are modelled as inequality constraints. Both Lyapunov vector field guidance and nonlinear model predictive control-based methods are applied, and the characteristics of them are compared using numerical simulations. (C) 2018 Elsevier Masson SAS. All rights reserved.

Keyword:

Unmanned aerial vehicle

Standoff tracking

Vector field

Nonlinear model predictive control

Particle filter

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期刊

Aerospace Science and Technology

IF:

5.8

论文数:

1.0W

被引数:

3.0W

机构

Chungnam National University

学者数:

1.5W

论文数: 1.4W

被引数: 1.2W

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