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Lee, Charles

Publications and source records attributed to Lee, Charles.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Lunar Terrain Coverage Analysis Data Delivery Workflow

In this work, we are developing a lunar terrain database to enable fast rendering of sun illumination and earth visibility for a proposed coverage analysis tool. This development will advance lunar mission design and formulation for current and future communications architectures, and will aid in lunar surface mission planning and communications/navigation operations. Our effort can be described in three steps: (1) we parallelize a brute force algorithm, which computes elevation masks from laser altimetry data acquired by the Lunar Reconnaissance Orbiter’s (LRO) Lunar Orbiter Laser Altimeter (LOLA); (2) we investigate parallel I/O methods to store terrain mask information from step (1) into a parallel file system; and (3) we finally deliver data to the terrain coverage analysis tool.

Michels, Dominik↗
NASA NTRS2021

Assessing Relay Communications for Mars Sample Return Surface Mission Concepts

The Mars Sample Return (MSR) Campaign would be a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR would, for the first time ever, present a need to communicate with multiple surface assets that are co-located on Mars in a coordinated effort to accomplish the unified objective of fetching, transporting, and returning samples from Mars. Currently, Mars surface assets relay data to and from Earth using a number of orbiters in what’s known as the Mars Relay Network (MRN). This network is characterized by a small number of surface assets distributed across the Martian globe and a larger number of orbiters to provide relay services. As of June 2020, there are two surface assets for which five orbiters are providing relay. During the MSR Campaign, there would be two rovers and a lander that all would require relay communication from a small number of Mars orbiters to meet the aggressive MSR timeline. The inversion of the current MRN paradigm, a system of many surface assets requiring relay and few orbiters to provide relay, necessitates the unique challenge of optimally allocating relay passes to maximize the operational capability of all assets. The allocation must consider a large number of trade variables including Mars asset operational requirements and Earth ground system constraints, including staffing schedules, operations planning across time zones, and more. To address these telecommunication challenges, the Mars Asset Relay Mission Link Allocation Design Environment (MARMLADE) tool was developed. It is a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets and quantify the operational efficiency of each surface asset.MARMLADE uses a data set of simulated Mars relay orbiter geometry and telecommunication capabilities provided by JPL’s Telecom Orbit Analysis and Simulation Tool (TOAST) software to compute which asset should get each pass based on a series of heuristics and predictions of all assets’ states. Within MARMLADE, the user can provide inputs including the option for time-based pass splitting, fixed FWD data rate capabilities, DFE communication capabilities, and link parameters allowing for the assessment of complex operations and hardware trades using surface mission operational efficiency as a primary figure of merit. As the MSR mission concepts continue to mature, MARMLADE is being used to assess ability of all MSR elements to meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets.This paper will describe the motivation and design of the MARMLADE tool and how it is being used to perform campaign and mission level trades, generate requirements, and support development of the MSR surface mission scenarios.

Lee, Charles↗
NASA NTRS2021

Assessing Relay Communications for Mars Sample Return Surface Mission Concepts

The Mars Sample Return (MSR) Campaign is a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR will, for the firsttime ever, present a need to communicate with multiple surfaceassets that are co-located on Mars in a coordinated effort toaccomplish the unified objective of fetching, transporting, andreturning samples from Mars. Currently, Mars surface assetsrelay data to and from Earth using a number of orbiters inwhat’s known as the Mars Relay Network (MRN). This networkis characterized by a small number of surface assets distributedacross the Martian globe and a larger number of orbiters toprovide relay services. As of June 2020, there are two surfaceassets for which five orbiters are providing relay. During theMSR Campaign, there will be two rovers and a lander that allwill require relay communication from a small number of Marsorbiters to meet the aggressive MSR timeline. The inversion ofthe current MRN paradigm, a system of many surface assetsrequiring relay and few orbiters to provide relay, necessitatesthe unique challenge of optimally allocating relay passes tomaximize the operational capability of all assets. The allocationmust consider a large number of trade variables includingMars asset operational requirements and Earth ground systemconstraints, including staffing schedules, operations planningacross time zones, and more. To address these telecommunicationchallenges, the Mars Asset Relay Mission Link AllocationDesign Environment (MARMLADE) tool was developed. Itis a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets andquantify the operational efficiency of each surface asset.MARMLADE uses a data set of simulated Mars relay orbitergeometry and telecommunication capabilities provided by JPL’sTelecom Orbit Analysis and Simulation Tool (TOAST) softwareto compute which asset should get each pass based on a seriesof heuristics and predictions of all assets’ states. WithinMARMLADE, the user can provide inputs including the optionfor time-based pass splitting, fixed FWD data rate capabilities,DFE communication capabilities, and link parameters allowingfor the assessment of complex operations and hardware tradesusing surface mission operational efficiency as a primary figureof merit. As the MSR mission concepts continue to mature,MARMLADE is being used to assess ability of all MSR elementsto meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets.

Lee, Charles↗
NASA NTRS2020

In Silico Methods for Space System Analysis: Optical Link Coding Performance and Lunar Terrain Masks

As deep space links migrate toward higher frequency bands like 𝐾𝑎 and optical, thor- ough trade-space exploration becomes increasingly valuable for designing reliable and efficient communications systems. In this contribution, we leveraged high-performance, concurrent simulations when the run-time complexity of simulation software overwhelms capabilities of ordinary desktop machines. The first part of this manuscript describes how to run error correcting code simulations concurrently on a high-performance supercomputer. The second part of this study describes a framework to produce azimuth and elevation terrain masks from imagery of the Lunar South Pole.

Michels, Dominik L↗
NASA NTRS2020

Feasibility of “Weak GPS” Real-Time Positioning/Timing at Lunar Distance

There are multiple Global Navigation Satellite Systems (GNSS’s), comprising over 100 navigation satellites in the Earth’s medium and high orbits. Most of these satellites have antennas that point Nadir to earth, and transmit navigation signals so vehicles on Earth’s surface and in its vicinity can perform trilateration and estimate its 3-dimenional (3D) positioning. The sidelobes of these antennas can occasionally point to the Moon. It is postulated that a lunar vehicle carrying a large enough receiving antenna can occasionally detects and receives four or more sidelobes of these weak GNSS signals, thus enabling the vehicle to perform 3D positioning using an onboard GNSS receiver. We propagate the orbits of the GNSS satellites from United States’ Global Positioning Satellite (GPS) constellation, the Europe’s Galileo constellation, and the Russia’s GLONASS constellation, a total of 81 satellites. We simulate the visibility of these satellites by a lunar vehicle in a Near Rectilinear Halo Orbit (NRHO), based on the assumption that the lunar vehicle is “in-view” of a GNSS satellite as long as it falls within the 40- degree beam-width of the satellite. We also simulate the 3D positioning performance as a function of satellites’ ephemeris errors and pseudo-range errors. The preliminary results show that the lunar vehicle can “see” 5 – 13 satellites, and achieve a 3D positioning error (one-sigma) of 200 – 300 meters based on reasonable ephemeris and pseudo- range error assumptions. We also consider the case of using relative positioning to mitigate the GNSS satellites’ ephemeris biases. That is, by assuming a reference receiver with accurately known positioning that is close to the lunar vehicle, and computing the relative position of the lunar vehicle relative to the reference.

Cheung, Kar-Ming↗
NASA NTRS2019

Navigation tracking with multiple baselines Part 1: high-level theory and system concepts

We describe a system concept that detects and locates dead and non-cooperatively spacecraft in the Geostationary Orbit (GEO). This can be done by making use of an existing GEO satellite with accurately known location as a reference, and/or by placing a dedicated “reference” spacecraft into an eccentric geosynchronous orbit over a region of interest (e.g. above North America).

Lee, Charles↗