Journal article Open Access

Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications

Roberto Sabatini; Celia Bartel; Anish Kaharkar; Tesheen Shaid; Subramanian Ramasamy

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:creator>Roberto Sabatini</dc:creator>
<dc:creator>Celia Bartel</dc:creator>
<dc:creator>Anish Kaharkar</dc:creator>
<dc:creator>Tesheen Shaid</dc:creator>
<dc:creator>Subramanian Ramasamy</dc:creator>
<dc:date>2014-04-01</dc:date>
<dc:description>Two multisensor system architectures for navigation
and guidance of small Unmanned Aircraft (UA) are presented and
compared. The main objective of our research is to design a compact,
light and relatively inexpensive system capable of providing the
required navigation performance in all phases of flight of small UA,
with a special focus on precision approach and landing, where Vision
Based Navigation (VBN) techniques can be fully exploited in a
multisensor integrated architecture. Various existing techniques for
VBN are compared and the Appearance-Based Navigation (ABN)
approach is selected for implementation. Feature extraction and
optical flow techniques are employed to estimate flight parameters
such as roll angle, pitch angle, deviation from the runway centreline
VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU
(Micro-Electromechanical System Inertial Measurement Unit)
sensors, and the use of Aircraft Dynamics Model (ADM) to provide
additional information suitable to compensate for the shortcomings of
VBN and MEMS-IMU sensors in high-dynamics attitude
determination tasks. An Extended Kalman Filter (EKF) is developed
to fuse the information provided by the different sensors and to
provide estimates of position, velocity and attitude of the UA
platform in real-time. The key mathematical models describing the
two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM
(VIGA) system are introduced. The first architecture uses VBN
and GNSS to augment the MEMS-IMU. The second mode also
includes the ADM to provide augmentation of the attitude channel.
Simulation of these two modes is carried out and the performances of
the two schemes are compared in a small UA integration scheme (i.e.,
AEROSONDE UA platform) exploring a representative cross-section
of this UA operational flight envelope, including high dynamics
manoeuvres and CAT-I to CAT-III precision approach tasks.
Simulation of the first system architecture (i.e., VIG system) shows
that the integrated system can reach position, velocity and attitude
accuracies compatible with the Required Navigation Performance
(RNP) requirements. Simulation of the VIGA system also shows
promising results since the achieved attitude accuracy is higher using
the VBN-IMU-ADM than using VBN-IMU only. A comparison of
VIG and VIGA system is also performed and it shows that the
position and attitude accuracy of the proposed VIG and VIGA
systems are both compatible with the RNP specified in the various
UA flight phases, including precision approach down to CAT-II.</dc:description>
<dc:identifier>https://zenodo.org/record/1092255</dc:identifier>
<dc:identifier>10.5281/zenodo.1092255</dc:identifier>
<dc:identifier>oai:zenodo.org:1092255</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>doi:10.5281/zenodo.1092254</dc:relation>
<dc:relation>url:https://zenodo.org/communities/waset</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:subject>Lowcost
<dc:subject>MEMS Inertial Measurement Unit (IMU)</dc:subject>
<dc:subject>Unmanned Aerial Vehicle</dc:subject>
<dc:title>Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications</dc:title>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>publication-article</dc:type>
</oai_dc:dc>

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