Browse Topic: Satellites
Rotorcraft continue to experience higher fatal accident rates compared to fixed-wing aircraft, primarily due to low altitude flight operations and reduced situational awareness in complex environments. A critical factor is the limited availability of accurate, up-to-date information on helipads and surrounding obstacles - such as trees, poles, and buildings - that pose significant risks during takeoff and landing. Existing resources, including the Federal Aviation Administration's heliport registry, are often outdated and incomplete, particularly for private or state-operated sites, and fail to report nearby obstacles. This lack of up-to-date data is largely due to privacy restrictions at certain locations and the high cost associated with comprehensive obstacle surveys. To address this challenge, we develop a deep learning (DL) framework that automatically detects helipads and nearby obstacles from high-resolution satellite imagery. Our approach combines Mask R-CNN for precise pixel-level helipad segmentation with Grounding DINO, a zero-shot vision-language model that identifies obstacles using flexible text prompts (e.g., "Pole", "Tree") without task-specific training. This text-guided, scalable detection method adapts to diverse and evolving operational settings. We validate our framework across helipads in the United States, and demonstrate strong performance in both helipad localization and obstacle detection. In addition, we build a web-based application that automates image processing, updates incorrect heliport coordinates, and provides obstacle reports. This work aims to enhance aviation safety, modernize infrastructure records, and deliver scalable tools to the aviation and machine learning communities.
Preparation for Powered Flight (PPF) is a critical phase for Dragonfly, the National Aeronautics and Space Administration (NASA) mission to Saturn’s moon Titan. During PPF the descending Lander is lowered below the Backshell and uses its rotors to remove or “despin” any residual yaw motion of the vehicle. A 1/2-scale model of the Dragonfly PPF configuration was tested in the National Full-Scale Aerodynamics Complex (NFAC) 80 by 120-foot wind tunnel to measure aerodynamic loads and surface pressures on the Lander and Backshell. The results were used to improve understanding of the complex aerodynamic interactions and provide validation data for the Computational Fluid Dynamics (CFD) simulations used to develop the aerodynamic databases for full-scale, Titan conditions. Configurations tested in the wind tunnel included Lander-alone-no-rotors (L), Lander-alone-with-rotors (LR), and Lander-with-Rotors-and-Backshell (LRB). Both LR and LRB configurations were tested at multiple descent velocities and pitch and roll attitudes. The eight powered rotors were operated in nine combinations of active and inactive rotors, using steps of increasing RPM from idle to maximum. The results were used to identify conditions that generated the desired yaw moment for despin as well as those that generated reduced or opposite sign moment. In parallel, CFD simulations applied the STAR-CCM+ toolset to the experimental geometry. Time-averaged virtual disks represented the rotors by adding spatially varying axial and rotational momentum to the flow. There was generally good agreement between experiment and CFD, but conditions having strong interactions between the rotors, Lander, and Backshell were found to be improved by use of more sophisticated time accurate and discrete blade models. The lessons from the experiment are being applied to the CFD for the full-scale Lander under Titan conditions.
The Dragonfly relocatable lander was selected as NASA's New Frontiers mission in 2019 to explore the organic-rich surface of Titan, Saturn's largest moon. The coaxial quadrotor vehicle will fly to multiple geologic sites covering a distance of over 50 miles near the Titan equator. At each site, Dragonfly will sample materials, determine the surface composition, and investigate how far prebiotic chemistry has progressed on Titan. Upon arrival, the lander will enter the Titan atmosphere protected inside an aeroshell, which will descend and decelerate with parachutes. At an altitude of approximately 1 km above the ground, the lander will separate from the backshell and perform a controlled transition to powered flight. Prior to separation from the backshell and after the heatshield has been ejected, the Preparation for Powered Flight (PPF) sequence will be initiated, which ensures the lander is in a safe and stable state for autonomous descent. A critical element of PPF is the de-spin maneuver, where diagonally opposing rotors rotate at maximum speed to reduce any residual angular momentum by creating a yaw moment in lander body axes. This paper presents high-fidelity computational fluid dynamics simulations of the Dragonfly rotorcraft lander during the PPF sequence. Aerodynamic performance predictions are compared with test data from the National Full-Scale Aerodynamics Complex to validate the simulations and build confidence in the PPF simulation results. Blade-resolved simulations capture the unsteady and complex flow behavior in Titan's dense, low-temperature atmospheric conditions during PPF. The results are analyzed, providing insight into aerodynamic performance and the aerodynamic moments critical for mission success.
Fusion Artificial Intelligence Link Synchronization Array for eVTOL Systems (FAILSAFES™) is a resilient and redundant timing and positioning architecture based on low Size, Weight, Power, and Cost (SWaP-C) RF Ranging links for eVTOL systems navigating with Global Navigation Satellite System (GNSS) in degraded or denied environments. This paper describes the overall FAILSAFES™ concept and discusses the underlying Complementary Positioning, Navigation, and Timing (CPNT) capabilities based on ENSCO's PicoRangerTM Array technology (PRAT). PRAT provides an array of low-cost RF ranging links between FAILSAFES™ ground stations and aircrafts to support navigation and timing distribution in GNSS degraded or denied environments. This paper will explore components of FAILSAFES™ and discuss initial PRAT based fusion results with respect to frequency and time stability.
ABSTRACT
Dragonfly is an X-8 octocopter designed to explore Saturn's moon Titan, and is currently under development for launch in 2026. Titan is a uniquely favorable body for atmospheric flight, in that it has a low gravity (1/7 Earth's) and a dense atmosphere (4x Earth's) which reduce the energetic requirements for heavier-than-air flight. Dragonfly will make multiple (autonomous) flights over several years with ranges of the order of 10km to explore different sites on Titan. The key features of the Titan environment are reviewed. These include the characteristics of the landing site terrain, resembling dune fields in terrestrial deserts. Winds are generally very low, ∼ 1m/s. Stronger winds, and methane rainfall, can occur in rare rainstorms, but these are not expected at the latitude and season of Dragonfly's arrival. Brownout and triboelectric charging due to surface dust lofted by rotor downwash is possible, and these hazards and their mitigations are discussed.
Flight power and energy requirement models were developed for Titan Aerial Daughtercraft (TAD) mission concepts, in which a small-scale (e.g. ≤ 10 kg) VTOL aircraft would conduct multiple sorties on Titan from a mothership (lander or balloon), recharging batteries from a radioisotope power source (RPS) on the mothership between sorties. The current study considers two design configurations for the TAD, a quadcopter and a tailsitter, and examines potential flight duration and range for lander-based scenarios, as well as allowable payload mass fraction and surface exploration range for balloon-based scenarios. To quantitatively compare the performance of these different configurations, a conceptual design analysis was developed. In a lander-based scenario, assuming a payload mass fraction of 25 percent and a conservative battery model, the estimated flight endurance at Titan's surface for a 10 kg quadcopter and tailsitter was estimated to be 7.6 hours and 11.7 hours respectively. Maximum flight radius from a lander across Titan's surface was found to be 82 km and 108 km, respectively. Modeling of balloon-based scenarios estimated allowable payload mass as a function of the total TAD mass and the float altitude of the balloon. For a balloon floating at 10 km altitude and a 10 kg TAD, the model estimated available payload mass of about 2.8 kg for a quadcopter and 3.5 kg for a tailsitter. The possible exploration range for the same balloon altitude and TAD system mass was computed to be 42 km for a quadcopter and 65 km for a tailsitter. The information estimated in the current mission analysis would yield initial insight for the entire mission architecture design; for example, selection of a landing point or balloon altitude that enables efficient and effective scientific activities over diverse surface features on the biggest moon of Saturn.
NASA is preparing for the next generation of CubeSats that are propelled and will make directional maneuvers. The new gimbal mount provides a seat for the motor, and controls the position of the thrusters that propel the CubeSat as it moves about and/or changes orbits.
This software reads MLS Level 1 products — the Earth Observing System (EOS) Microwave Limb Sounder (MLS) calibrated measurements of microwave radiance products and operational meteorological data — and produces a set of estimates of atmospheric temperature and composition. The software features are driven by the instrument and its unique capabilities to measure the atmospheric temperatures and composition at the Earth's limb. By careful and judicious choice of signal bands, and by dividing the computing into chunks and phases, scientifically useful products can be produced with wide spatial and temporal coverage. The software includes a highly developed forward model algorithm and an inverse model that makes efficient use of memory.
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