Engineering topics
Lubey, Daniel
Publications and source records attributed to Lubey, Daniel.
3D Shape Reconstruction of Small Bodies from Sparse Features
The autonomous approach of spacecraft to a small body (comet or asteroid) relies on using all available information at each phase of the approach. This paper presents new algorithms for global shape reconstructions from sparse tracked surface points. These methods leverage estimates from earlier phases, such as rotation pole, as well as a priori knowledge, such as a genus-0 body (i.e. without boundaries or topological holes). A mapping algorithm is proposed, which performs faithful reconstructions while enforcing genus-0 output through spherical parameterization. To estimate the shape of permanently shadowed regions of the body, a symmetry reconstruction method is added to the reconstruction algorithms. This method is shown to substantially increase the reconstruction accuracy but is subject to the symmetry of the body perpendicular to the rotation pole. The proposed mapping algorithm is compared to stateof- the-practice surface reconstruction algorithms, assessing their accuracy and ability to correctly generate genus-0 shape models for 2400 datasets and three small bodies. The proposed spherical parameterization algorithm performed consistently with the state-of-the-practice while being the only algorithm to always produce genus-0 shape models.
Light-Robust Pole-from-Silhouette Algorithm and Visual-Hull Estimation for Autonomous Optical Navigation to an Unknown Small Body
We present an advanced Pole-from-Silhouette (PFS) algorithm, which is robust to illumination conditions and non-zero sun phase. PFS is an important step in the optical navigation pipeline for an autonomous small spacecraft to approach an unknown small body. The algo- rithm estimates the rotation pole and 3D shape (visual hull) of the small body using only the lit pixels within the silhouette of the small body, the body’s rotation rate, the spacecraft attitude, and the spacecraft-target relative distance, which is estimated from orbit determination. We present detailed numerical simulations and multiple sensitivity analyses to demonstrate the effectiveness of our proposed PFS algorithm in different scenarios and target bodies.
Light-Robust Pole-from-Silhouette Algorithm and Visual-Hull Estimation for Autonomous Optical Navigation to an Unknown Small Body
No abstract provided
Satellite-To-Satellite Imaging in Support of LEO Optical Navigation, Using the ASTERIA Cubesat
The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was a 6-unit CubeSat technology demonstration mission that was built at NASA’s Jet Propulsion Laboratory (JPL) and deployed from the International Space Station (ISS) on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations alongside science until end of mission in December 2019. At the end of its lifetime it was being used as a demonstration platform for several experiments, including low earth orbit (LEO) optical navigation operations. With its visible light astrometric camera and stable attitude control system, the ASTERIA spacecraft showed itself to be a capable platform for the imaging of geosynchronous satellites from LEO. This paper will describe the imagery attained in flight and also the image processing algorithms that were developed to render that imagery into navigation quality data. These algorithms dealt with hot pixel filtering, noise modeling, attitude registration, star signal rejection and satellite signal identification. Brightness prediction algorithms used for target selection will also be discussed.
Satellite-to-satellite imaging in support of LEO optical navigation, using the ASTERIA cubesat
No abstract provided
Osiris-Rex Shape Model Performance During the Navigation Campaign
The Navigation Campaign of the OSIRIS-REx mission began when the first image of Bennu was recorded by the PolyCam high-resolution imager on Au-gust 17, 2018. In the ensuing months, two teams began building shape models based on imagery taken during the Approach and Preliminary survey phases to be used for the transition to landmark navigation in the Orbital A phase. The orbit determination team began analyzing and characterizing the performance and errors associated with each shape model delivery working closely to iterate on the next shape model delivery. By the end of Orbital A, shape models produced by the Altimetry Working Group and JPL exceeded pre-launch performance re-quirements. This paper provides a summary of the analysis performed during operations.
Optical Navigation for Autonomous Approach of Small Unknown Bodies
State of the practice in navigation around small celestial bodies heavily relies on ground sup- port and human skill, in particular, for perception-based operations such as optical navigation and mapping. This leads to longer duration and more complex mission operations and sub- sequently higher cost. Furthermore, it imposes limitations for certain missions such as fast fly-bys or multi-agent operations. In this work, we present an autonomous navigation strat- egy suitable for approaching small unexplored bodies. During the approach, we estimate the body’s physical properties as well as the spacecraft’s relative trajectory and associated un- certainties. The autonomous navigation strategy, which is solely based on optical measure- ments, begins as soon as the body becomes resolved in the navigation camera and terminates at the start of proximity operations, when the spacecraft makes its first trajectory correction to stay in the vicinity of the body. Our strategy uses multiple image-processing algorithms: light-curve analysis for estimating the target body’s rotation rate, Shape-from-Silhouette for reconstructing the 3D shape and estimating its rotation pole, and feature tracking tailored to Small-Body images for estimating relative navigation parameters. We used the Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) developed by the Jet Propulsion Laboratory to evaluate the feasibility of this multi-phase navigation strategy using simulated images of an approach trajectory. We used the Rosetta mission data to generate photorealistic images to characterise the performance of this approach. This work is based on the assumptions that the spacecraft attitude is known, the body is a principal-axis rotator, a-priori estimates of ephemerides and scale are available, and the body is observed from a zero sun phase only during initial approach. Preliminary results show orbit determination performance that is on par with the human navigation from the Rosetta mission; albeit with a 1% bias in spacecraft-target radial distance estimate. The bias error is likely due to the robustness and accuracy of the visual tracking under dynamic lighting conditions and per- spective changes, which decrease accuracy.