VDM-based UAV Attitude Determination in Absence of IMU Data

被引：0

作者：

Khaghani, Mehran ^{[1
]}

Skaloud, Jan ^{[1
]}

机构：

[1] Swiss Fed Inst Technol EPFL, Geodet Engn Lab TOPO, Lausanne, Switzerland

来源：

2018 EUROPEAN NAVIGATION CONFERENCE (ENC) | 2018年

关键词：

UAV; Navigation; Attitude Determination; Vehicle Dynamic Model; IMU failure; Kalman Filter; NAVIGATION;

D O I：

暂无

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The capability of a previously proposed VDM (vehicle dynamic model) based navigation method for UAVs is assessed in attitude determination without IMU data. This method utilizes the VDM as main process model within the navigation filter and treats data from IMU (if available) and other sensors as observations. Experimental results from a test flight and a Monte Carlo simulation are presented to compare the performance of the VDM-based navigation against the conventional INS-based navigation. While the attitude estimation performance of VDM/GNSS integration is comparable to that of INS/GNSS in simulations, experimental results reveal the need for improved VDM parameter calibration.

引用

页码：84 / 90

页数：7

共 19 条

[1] Bryson M., 2015, Handbook of Unmanned Aerial Vehicles, P433, DOI [10.1007/978-90-481-9707-1_3, DOI 10.1007/978-90-481-9707]
[2] BRYSON M, 2004, P AUSTR C ROB AUT CA
[3] Cork L., 2014, Aircraft dynamic navigation for unmanned aerial vehicles
[4] Dadkhah N., 2008, PROC 21 INT TECH M S, P545
[5] Ducard GJJ, 2009, ADV IND CONTROL, P1
[6] Gelb A., 1988, APPL OPTIMAL ESTIMAT
[7] Wavelet-Variance-Based Estimation for Composite Stochastic Processes
Guerrier, Stephane
Skaloud, Jan
Stebler, Yannick
Victoria-Feser, Maria-Pia
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2013, 108 (503) : 1021 - 1030
[8] Khaghani M, 2017, ROBOT AUTON SYST
[9] Khaghani M, 2016, I NAVIG SAT DIV INT, P1432
[10] Autonomous Vehicle Dynamic Model-Based Navigation for Small UAVs
Khaghani, Mehran
Skaloud, Jan
[J]. Navigation-Journal of the Institute of Navigation, 2016, 63 (03): : 345 - 358

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