Special Sessions

This special session focuses on advanced navigation solutions for autonomous close proximity operations, including in-orbit servicing, in-orbit assembly, debris removal, and small bodies exploration. Topics of interest include, but are not limited to, relative navigation with cooperative/non-cooperative, known/unknown targets, navigation techniques for small body exploration, AI/ML-based approaches to state estimation, and the characterization of resident space objects. Contributions that include experimental validation, hardware-in-the-loop testing, or in-orbit demonstrations are encouraged. The session aims to provide an overview of the current capabilities and open challenges in autonomous navigation for proximity operations.

Low Earth orbit positioning navigation and timing (LEO PNT) is emerging as the next frontier in satellite-based navigation. LEO PNT can be classified into four categories: dedicated, dual-purposed, GNSS-integrated, and opportunistic. This Special Session will address fertile and timely research questions that are common across all categories, as well as specific to each category. Contributions will span theoretical developments, numerical simulations, and experimental demonstrations in the following topics: signal and constellation design, signal processing techniques and transceiver design, ephemeris generation and satellite tracking, timing and synchronization, error budget analysis and compensation techniques, and mitigation of cyber threats.

This special session will focus on cutting-edge developments in Global Navigation Satellite Systems (GNSS) and their innovative applications on Space, Lunar and beyond. Topics of interest include next-generation interoperable system architecturesfor Space, Lunar PNT and beyond, precise ODTS (Orbit Determination and Timing Synchronisation) techniques, lunar reference frames and timing reference frames, multi-sensor fusion navigation terminals. The session also aims to give an insight in ongoing activities in relevant programs such as ESA LCNS (Lunar Communication and Navigation Service) Moonlight, JAXA Lunar Navigation Satellite System (LNSS), NASA LCRNS (Lunar Communications Relay and Navigation System) or other international initiatives, or space agencies cooperation (LunaNet) to highlight innovations that will enable safer, more efficient exploration missions to the Moon and beyond.

This special session focuses on recent advances in learning-based state estimation and navigation, leveraging data-driven techniques such as deep learning and reinforcement learning, with applications spanning platforms such as unmanned aerial vehicles (UAVs), ground robots, smartphones, and wearable devices. Topics include learning-enhanced inertial navigation, visual navigation, multi-sensor fusion, wireless and GNSS-based localization, robust and safety-aware localization, and adaptive estimation frameworks. The session aims to highlight how learning techniques enable reliable and accurate navigation in complex environments, where conventional sensing modalities are often degraded or unavailable.

Cooperative navigation is a key enabler for autonomous networks, or swarms, operating in GNSS-challenged and unknown environments. By sharing information and jointly exploiting local PNT, sensing and communication signals, networked agents can significantly improve positioning accuracy, robustness, and situational awareness. This session focuses on cooperative and autonomous navigation, including integrated communication, navigation, sensing, signal design and distributed processing for navigation. Contributions span theory and practice, addressing distributed PNT, multi-agent localization, and real- world systems for robotics, UAVs, vehicular networks, and marine applications.

The introduction of GNSS in railway applications made major progresses during the last decade. Main challenges are to reach the stringent safety critical requirements as accuracy, availability and integrity, but also the development of methodologies for safety demonstration, simulation and on-site demonstration.

Escalating GNSS interference incidents globally, particularly in maritime environments, underscore the urgent need for Alternative Positioning, Navigation and Timing (A-PNT) solutions to improve resilience of maritime navigation. This special session explores the state of the art in maritime A-PNT, focusing on Enhanced Loran (eLoran) and Ranging Mode (R-Mode) via VDES and Medium Frequency (MF). Bringing together experts from maritime authorities, research institutions and industry, the session will showcase theoretical advancements, standardization efforts and real-world testbed results. Attendees will gain comprehensive insights into emerging terrestrial A-PNT infrastructures essential for safe, assured maritime operations in GNSS-denied or degraded environments.

Robust navigation is becoming a critical challenge as positioning systems operate in increasingly complex, contested, and non-ideal environments. This special session focuses on advanced robust estimation and signal processing techniques for navigation under model mismatch, non-Gaussian noise, multipath, interference, and faulty measurements. Topics include robust statistics, fault detection and exclusion, outlier mitigation, non-Gaussian filtering, integrity monitoring, and resilient estimation against GNSS threats. The session aims to gather researchers and practitioners developing theoretical advances and practical solutions to improve the reliability, integrity, and resilience of next-generation navigation systems.

Signal strength-based localization is becoming increasingly important as a complementary approach to GNSS which can be disrupted or is entirely unavailable indoors. This session presents advances across Bluetooth/WLAN RSSI, UWB, CSI, and magnetic field-based positioning methods. The papers employ modern machine learning and signal processing techniques, including Bayesian and graph neural networks, tensor decompositions, and compressed sensing, to approach various challenges: multipath mitigation, hardware impairments, correlated outliers, uncertainty quantification, and efficient map representation. Diverse applications ranging from indoor zone localization and asset tracking to railroad odometry show that with the proposed techniques, reliable navigation can be achieved across diverse environments.