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Optimization of a LEO-PNT Constellation: Design Considerations and Open Challenges
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As launch and manufacturing costs have become affordable, the industrial
and academic interest in Low-Earth Orbit (LEO) satellites has increased
in recent years. With this interest, the concept of Low-Earth
Orbit-based Positioning, Navigation and Timing (LEO-PNT) has also gained
popularity as a complementary and/or standalone system in addition to
the already existing Global Navigation Satellite Systems (GNSS). This
article examines the LEO constellation optimization from the perspective
of a LEO-PNT design, identifies and discusses the state-of-art of the
LEO satellite constellation optimization approaches, introduces relevant
performance and feasibility related metrics and parameters, and
addresses key concepts and underlying trade-offs that must be considered
for any LEO-PNT system design. In addition, a case study for a LEO-PNT
constellation optimization is presented, where we showcase the discussed
trade-offs. We present optimization results obtained with the adaptive
weighting algorithm “ADaW” applied to the Pareto-optimization
algorithm “NSGA-III”. A detailed performance analysis is done for six
relevant scenarios with varying receiver location properties, namely by
considering indoor/outdoor, rural/urban and line of sight/non-line of
sight cases.
Title: Optimization of a LEO-PNT Constellation: Design Considerations and Open Challenges
Description:
As launch and manufacturing costs have become affordable, the industrial
and academic interest in Low-Earth Orbit (LEO) satellites has increased
in recent years.
With this interest, the concept of Low-Earth
Orbit-based Positioning, Navigation and Timing (LEO-PNT) has also gained
popularity as a complementary and/or standalone system in addition to
the already existing Global Navigation Satellite Systems (GNSS).
This
article examines the LEO constellation optimization from the perspective
of a LEO-PNT design, identifies and discusses the state-of-art of the
LEO satellite constellation optimization approaches, introduces relevant
performance and feasibility related metrics and parameters, and
addresses key concepts and underlying trade-offs that must be considered
for any LEO-PNT system design.
In addition, a case study for a LEO-PNT
constellation optimization is presented, where we showcase the discussed
trade-offs.
We present optimization results obtained with the adaptive
weighting algorithm “ADaW” applied to the Pareto-optimization
algorithm “NSGA-III”.
A detailed performance analysis is done for six
relevant scenarios with varying receiver location properties, namely by
considering indoor/outdoor, rural/urban and line of sight/non-line of
sight cases.
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