State Estimation of an Octorotor with Unknown Inputs. Application to Radar Imaging

被引：0

作者：

Chevet, Thomas ^{[1
]}

Makarov, Maria ^{[2
]}

Maniu, Cristina Stoica ^{[2
]}

Hinostroza, Israel ^{[3
]}

Tarascon, Pierre ^{[1
]}

机构：

[1] Cent Supelec, Dept Automat Control, F-91192 Gif Sur Yvette, France

[2] Univ Paris Saclay, Univ Paris Sud, Lab Signaux & Syst, Cent Supelec,CNRS, F-91192 Gif Sur Yvette, France

[3] Cent Supelec, SONDRA Lab, F-91192 Gif Sur Yvette, France

来源：

2017 21ST INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC) | 2017年

关键词：

UAV; State Estimation; Kalman Filter; Extended Kalman Filter; Synthetic Aperture Radar;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper focuses on the design of a linear Kalman filter and an extended Kalman filter for the estimation of an octorotor unmanned aerial vehicle's (UAV) state in the context of Synthetic Aperture Radar image reconstruction. A comparison to a linear interpolation method is also proposed. The Kalman filters are developed based on a complete nonlinear model of the UAV and its linearized form. A particularity of the considered platform is that the control signals are not measured and have to be estimated as well as the UAV's state. The proposed techniques are then tested on a UAV simulator and a radar imaging simulator.

引用

页码：723 / 728

页数：6

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