In this paper we introduce a centralized scheduler that satisfies user requests for Positioning, Navigation, and Timing (PNT) services from ad-hoc, non-dedicated orbital constellations around the Moon. Traditional Global Navigation Satellite System (GNSS) networks consist of dedicated assets that provide service 24/7 that allow users to acquire localization services at-will. To reduce the cost of providing such services, ad-hoc PNT networks could be formed from satellites conducting independent science missions. But for such ad-hoc networks, a coordinated schedule is needed to satisfy the satellites' usage constraints, ensure quality of service for ground user localization, and reduce overall operational costs for the system. Our scheduler bridges this coordination gap. First, the scheduler takes inputs from the available orbital assets and the ground users. From these inputs, it determines the sets of orbital assets that could provide real time PNT service (i.e. four or more satellites in view) for each user service request at each time step. Next, the scheduler computes a standard, non-linear GNSS quality of service metric for each of these sets. The scheduler then incorporates these pre-computed non-linear metrics into a linear objective function and leverages Mixed-Integer Linear Programming (MILP) for the coordination and scheduling of the desired “as-needed” localization service. This scheduler can be used to evaluate the feasibility of a constellation for providing PNT service and the impact of tightened usage constraints of the constellation's assets on the quality of PNT service provided to ground users. To demonstrate these capabilities, this paper presents the analysis of two different constellation designs with four user scenarios based on the outputs from SSM. The resulting integrated capability will support the design of future ad-hoc Lunar PNT networks, enabling high-quality, low-cost Lunar exploration.


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    Title :

    Scheduling PNT Service Requests from Non-dedicated Lunar Constellations


    Contributors:


    Publication date :

    2022-03-05


    Size :

    6686219 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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