arXiv subjects

Keidai Iiyama

Publications and source records attributed to Keidai Iiyama.

8 recordsLinked to original sources

arXiv2026

Full Stack Navigation, Mapping, and Planning for the Lunar Autonomy Challenge

We present a modular, full-stack autonomy system for lunar surface navigation and mapping developed for the Lunar Autonomy Challenge. Operating in a GNSS-denied, visually challenging environment, our pipeline integrates semantic segmentation, stereo visual odometry, pose graph SLAM with loop closures, and layered planning and control. We leverage lightweight learning-based perception models for real-time segmentation and feature tracking and use a factor-graph backend to maintain globally consistent localization. High-level waypoint planning is designed to promote mapping coverage while encouraging frequent loop closures, and local motion planning uses arc sampling with geometric obstacle checks for efficient, reactive control. We evaluate our approach in the competition's high-fidelity lunar simulator, demonstrating centimeter-level localization accuracy, high-fidelity map generation, and strong repeatability across random seeds and rock distributions. Our solution achieved first place in the final competition evaluation.

cs.RO↗

arXiv2026

GNSS-based Lunar Orbit and Clock Estimation With Stochastic Cloning UD Filter

This paper presents a terrestrial GNSS-based orbit and clock estimation framework for lunar navigation satellites. To enable high-precision estimation under the low-observability conditions encountered at lunar distances, we develop a stochastic-cloning UD-factorized filter and delayed-state smoother that provide enhanced numerical stability when processing precise time-differenced carrier phase (TDCP) measurements. A comprehensive dynamics and measurement model is formulated, explicitly accounting for relativistic coupling between orbital and clock states, lunar time-scale transformations, and signal propagation delays including ionospheric, plasmaspheric, and Shapiro effects. The proposed approach is evaluated using high-fidelity Monte-Carlo simulations incorporating realistic multi-constellation GNSS geometry, broadcast ephemeris errors, lunar satellite dynamics, and ionospheric and plasmaspheric delay computed from empirical electron density models. Simulation results demonstrate that combining ionosphere-free pseudorange and TDCP measurements achieves meter-level orbit accuracy and sub-millimeter-per-second velocity accuracy, satisfying the stringent signal-in-space error requirements of future Lunar Augmented Navigation Services (LANS).

cs.RO↗

arXiv2026

Ephemeris and Almanac Design for Lunar Navigation Satellites

This paper presents almanac and ephemeris message representation for lunar navigation satellites supporting the Lunar Augmented Navigation System (LANS). The proposed method combines osculating orbital elements, Chebyshev polynomials, and Fourier series to efficiently represent lunar satellite trajectories subject to complex perturbations from lunar gravity and third-body effects. For the ephemeris, a hybrid Chebyshev--Fourier formulation improves fitting accuracy over long arcs while maintaining message compactness under the data-size constraint of the LunaNet Interoperability Specification. For the almanac, a compact low-order polynomial and Fourier model is introduced to capture mid-term orbital variations over a 15-day fitting arc. The approach is validated for multiple orbit regimes, including 30-hour, 24-hour, and 12-hour elliptical lunar frozen orbits (ELFOs) and a 6-hour polar orbit. Results show that the proposed framework achieves sub-meter position and sub-millimeter-per-second velocity fitting errors within the 900-bit limit for 6-hour ephemeris arcs, and almanac fitting accuracy sufficient for reliable satellite-visibility identification in warm-start operations.

astro-ph.IM↗

arXiv2026

Satellite Autonomous Clock Fault Monitoring with Inter-Satellite Ranges Using Euclidean Distance Matrices

To address the need for robust positioning, navigation, and timing services in lunar environments, this paper proposes a novel onboard clock phase jump detection framework for satellite constellations using range measurements obtained from dual one-way inter-satellite links. Our approach leverages vertex redundantly rigid graphs to detect faults without relying on prior knowledge of satellite positions or clock biases, providing flexibility for lunar satellite networks with diverse satellite types and operators. We model satellite constellations as graphs, where satellites are vertices and inter-satellite links are edges. The proposed algorithm detects and identifies satellites with clock jumps by monitoring the singular values of the geometric-centered Euclidean distance matrix (GCEDM) of 5-clique sub-graphs. The proposed method is validated through simulations of a GPS constellation and a notional constellation around the Moon, demonstrating its effectiveness in various configurations.

cs.RO↗

arXiv2025

Trade-off Analysis for Lunar Augmented Navigation Service (LANS) Constellation Design

The establishment of a sustainable human presence on the Moon demands robust positioning, navigation, and timing (PNT) services capable of supporting both surface and orbital operations. This paper presents a comprehensive trade-off analysis of lunar frozen-orbit constellations for the Lunar Augmented Navigation Service (LANS), focusing on how the number of satellites and orbital parameters influence coverage, position dilution of precision (PDOP), orbit determination accuracy, receiver noise, and orbit insertion cost. Three Walker-constellation families based on frozen elliptical and circular orbits are examined to characterize their relative advantages across different semi-major axes and inclinations. Results show that larger semi-major axes enhance both polar and global coverage, though the optimal inclination depends on the constellation type and target service region. The south elliptical lunar frozen orbit (ELFO) Walker constellation provides superior performance for polar coverage and PDOP, whereas the circular lunar frozen orbit (CLFO) Walker configuration achieves the best global uniformity. Orbit determination errors and receiver noise both increase with larger semi-major axes and higher inclinations, reflecting weaker geometric observability and reduced received signal power at apolune for eccentric orbits. Orbit insertion analysis reveals clear trade-offs among transfer duration, characteristic energy ($C_3$) at trans-lunar injection, and insertion $ΔV$: shorter transfers require higher insertion $ΔV$, while low-energy transfers achieve smaller $ΔV$ at the cost of months-long durations and higher $C_3$. These findings provide a systematic framework for designing LANS constellations for both regional and global coverage.

astro-ph.IM↗

arXiv2025

Ionospheric and Plasmaspheric Delay Characterization for Lunar Terrestrial GNSS Receivers with Global Core Plasma Model

Recent advancements in lunar positioning, navigation, and timing (PNT) have demonstrated that terrestrial GNSS signals, including weak sidelobe transmissions, can be exploited for lunar spacecraft positioning and timing. While GNSS-based navigation at the Moon has been validated recently, unmodeled ionospheric and plasmaspheric delays remain a significant error source, particularly given the unique signal geometry and extended propagation paths. This paper characterizes these delays using the Global Core Plasma Model (GCPM) and a custom low-cost ray-tracing algorithm that iteratively solves for bent signal paths. We simulate first-, second-, and third-order group delays, as well as excess path length from ray bending, for GNSS signals received at both lunar orbit and the lunar south pole under varying solar and geomagnetic conditions. Results show that mean group delays are typically on the order of 1 m, but can exceed 100 m for low-altitude ray paths during high solar activity, while bending delays are generally smaller but non-negligible for low-altitude ray paths. We also quantify the influence of signal frequency, geomagnetic $K_p$ index, and solar R12 index. These findings inform the design of robust positioning and timing algorithms that utilize terrestrial GNSS signals.

cs.RO↗

arXiv2024

Autonomous Constellation Fault Monitoring with Inter-satellite Links: A Rigidity-Based Approach

To address the need for robust positioning, navigation, and timing services in lunar environments, this paper proposes a novel fault detection framework for satellite constellations using inter-satellite ranging (ISR). Traditionally, navigation satellites can depend on a robust network of ground-based stations for fault monitoring. However, due to cost constraints, a comprehensive ground segment on the lunar surface is impractical for lunar constellations. Our approach leverages vertex redundantly rigid graphs to detect faults without relying on precise ephemeris. We model satellite constellations as graphs where satellites are vertices and inter-satellite links are edges. We identify faults through the singular values of the geometric-centered Euclidean distance matrix (GCEDM) of 2-vertex redundantly rigid sub-graphs. The proposed method is validated through simulations of constellations around the Moon, demonstrating its effectiveness in various configurations. This research contributes to the reliable operation of satellite constellations for future lunar exploration missions.

cs.RO↗

arXiv2021

Deep Reinforcement Learning for Safe Landing Site Selection with Concurrent Consideration of Divert Maneuvers

This research proposes a new integrated framework for identifying safe landing locations and planning in-flight divert maneuvers. The state-of-the-art algorithms for landing zone selection utilize local terrain features such as slopes and roughness to judge the safety and priority of the landing point. However, when there are additional chances of observation and diverting in the future, these algorithms are not able to evaluate the safety of the decision itself to target the selected landing point considering the overall descent trajectory. In response to this challenge, we propose a reinforcement learning framework that optimizes a landing site selection strategy concurrently with a guidance and control strategy to the target landing site. The trained agent could evaluate and select landing sites with explicit consideration of the terrain features, quality of future observations, and control to achieve a safe and efficient landing trajectory at a system-level. The proposed framework was able to achieve 94.8 $\%$ of successful landing in highly challenging landing sites where over 80$\%$ of the area around the initial target lading point is hazardous, by effectively updating the target landing site and feedback control gain during descent.

cs.RO↗