124 - Optimisation of PVT engines for LEO measurement diversity

LEO-PNT stands out among the very promising evolutions of spaceborne PNT systems towards Multi-Layer Satellite Systems (MLSS), leveraging differentiators such as:

•  Whitening of measurements, in particular multipath;
•  More diverse opportunities to exploit doppler measurements in addition to ranging;
•  Faster transition between LOS and NLOS status, beneficial to the awareness of the signal LOS nature;
•  Shorter cycles between obstructed and unobstructed signals, which can be exploited to optimise the fusion with drifting dead-reckoning.

So far, most works that showcase LEO-PNT differentiators have derived LEO-PNT performances based on GNSS PVT engines (assuming atomic clocks on board satellite, Code Division Multiple Access and four simultaneous ranging measurements) processing LEO-PNT measurements, or tailoring GNSS models to LEO measurements in synthetic scenarios. Despite outstanding performances and availability resulting from R&D capitalised over 30 years and more, these engines have been optimised with and for MEO measurements, which are likely sub-optimal for LEO and therefore possibly not exploiting the full benefits of LEO measurement diversity and the aforementioned differentiators.

The objectives of the activity are to study, design, and demonstrate optimal PVT engines exploiting measurements diversity of LEO-PNT in challenging environments, for standalone and hybrid (dead reckoning) concepts of operations. Two design approaches will be implemented and compared: conventional design featuring Kalman Filtering, and use of AI/ML allowing to exploit potentially unknown or unexpected behaviour of LEO measurements.

The activity will complement the ongoing and planned upstream activities in Europe (R&D, demonstration and in-orbit preparation) by maturing further downstream technologies suitable for the prospects of both commercial and institutional LEO-PNT systems.

The tasks to be performed shall include:

•  Survey the state-of-the-art for LEO-PNT signal processing and positioning engines;
•  Investigate the various nature and potential benefits of LEO-PNT measurements diversity, such as multipath whitening, optimal use of Doppler, exploitation of the higher transition rates between NLOS/LOS and obstructed/unobstructed signals, for standalone and hybrid (dead-reckoning) concepts of operations;
•  Implement two design approaches: 1) a conventional design featuring Kalman Filtering, and 2) an AI/ML-based design allowing to exploit potentially unknown or unexpected behaviour of LEO measurements;
•  Compare the two novel design approaches against a more traditional MEO GNSS-based design with a measurement campaign in the field (either in real time or post processing depending on the opportunities).

The main outputs of the activity will consist of:

•  State of the art, optimal design of PVT engines exploiting LEO-PNT measurement diversity;
•  Breadboard, benchmark against a PVT engine devised based on MEO GNSS principles, performance test report;
•  Roadmap for commercialization, including potential Navisp EL2 activities and lessons- learned / feedback to pursue optimal design of European’s LEO-PNT systems.

It is noted that no Participating State expressed their opt-out for this activity (EL1-124).