Factor graph optimization is gaining attention from the community as is outperforming traditional positioning algorithms. Factor graph optimization may be used to replace the traditional Weighted Least Square (WLS) or Kalman Filter (KF)-based solutions, both in stand-alone and hybrid positioning solutions in combination with sensors. Thus, its application may be of interest for the derivation of…

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The INSPIRE project aims to design, develop, and validate a novel GNSS-based positioning architecture tailored for challenging environments such as urban canyons and deep-urban areas. The project leverages meta-signal processing, peer-to-peer ranging, and hybrid positioning to improve accuracy, robustness, and availability of GNSS-based solutions in scenarios where traditional positioning systems…

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The main purpose of this activity is to evaluate – through simulations and modelling – how the use of quantum sensors can benefit PNT systems. To meet this overall purpose, the following study objectives can be derived:  Design and develop sensor models that can provide representative measurements for quantum sensors,  Integrate those sensor models within a simulation environment…

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The VAIPOSA project aims to develop innovative methodologies for designing and implementing Positioning, Navigation, and Timing (PNT) components using AI and machine learning (ML), while ensuring safety, robustness, and resilience. It employs a realistic road environment simulator where an autonomous agent with an AI-based PNT system must adapt to changing conditions. The project enhances…

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The EPIC aims to address to develop algorithms and a SW simulator for combined usage of GNSS, LEO-PNT  and 5G terrestrial transmitters to achieve high precision PPP-IAR solutions even in urban environments.  The drivers for this activity are:  ▪ Usage of alternative-PNT (LEO-PNT, 5G) means, in case GNSS is partially or fully not available ▪ Usage of additional-PNT (LEO-PNT, 5G) means…

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Reliable Integer Ambiguity Resolution (IAR) of carrier-phase measurements is critical for Global Navigation Satellite Systems (GNSS) high accuracy positioning.  State-of-the-art IAR strategies employ well-established processes (float estimation, decorrelation and searching) which, however, cannot deem efficient for real-time kinematic applications. Analytically, by virtue of weak models, biases…

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Integer Ambiguity Resolution (IAR) concerns the successful resolution of unknown integer ambiguities present in carrier-phase measurements, which exhibit millimeter-level precision. In the context of Global Navigation Satellite System (GNSS) precise positioning and navigation, the IAR process is fundamental, as once ambiguities are correctly resolved, the phase data acts as ultra-precise…

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PNT, the focus of NAVISP, is not just today’s largest contributor to the global Space Economy through the revenues generated by PNT-enabled downstream applications and services, but also an essential utility for many other economic sectors. NAVISP stimulates novel PNT concepts, supports industrial competitiveness, attracts industry co-finance and supports national PNT-related policies. After six…

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The main objective of this project is to develop and implement a combined eLoran and GNSS receiver, and demonstrate in a number of realistic scenarios that these can be combined to provide a more robust and reliable navigation solution. The project will be 15-18 months in duration, and will involve technology and concept research, design of the software and hardware, build, testing and an…

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This project aims to address the increasing drone safety risks by developing redundant sensing with an integrated multi-sensor system to ensure drone Positioning, Navigation, and Timing (PNT) in various conditions. As GNSS becomes more vulnerable, there is a need for more resistant and robust drone PNT, which would maintain the accuracy even in the absence of GNSS. We will develop a…

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