MétaCan
Menu
Back to cohort
Record W7111284056 · doi:10.26077/mh55-6542

Deployable Antennas for Small Satellite Constellation Missions

2025· other· W7111284056 on OpenAlexaff

Bibliographic record

VenueDigital Commons - USU (Utah State University) · 2025
Typeother
Language
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConstellationSpacecraftSatellite constellationSatelliteAntenna (radio)Communications satelliteSpace explorationRadio frequencyRange (aeronautics)International Space Station

Abstract

fetched live from OpenAlex

The Space Flight Laboratory (SFL) and HawkEye 360 have optimized the radio frequency (RF) design end the corresponding geometric requirements for the mechanical design of a deployable discone antenna. This high-performance deployable discone antenna maximizes its utility per volume of the small satellite for which it has been designed and built. Deployables on small satellite constellation missions should be low-cost, manufacturable, and high-performance. This means that deployables must be capable of repeated stowage performed during test deployments without hindering performance or flight qualification. This deployable antenna will be launched and commissioned April 2024, making it the first ever on-orbit wideband deployable discone antenna to gain flight heritage. The rise of constellation missions in recent years has been enabled by the ever-increasing accessibility to space technology. More specifically, through the employment of small, low-cost, yet high-performance small satellites, constellation missions allow for space technology to have an exponentially larger impact than a single spacecraft through increased coverage and reduced revisit intervals. The data collected form constellation missions contributes to global monitoring and surveillance, security and defense, environmental monitoring, and communication and connectivity. HawkEye 360 employs a constellation of satellites to deliver commercially available precision mapping of radio frequency emissions. This unique ability to identify and geolocate sources of radio frequencies from space reveals previously invisible knowledge about activities around the world. The range of possible components on small satellites is limited by spacecraft surface area and volume, especcially so with respect to antennas. Antennas require specific geometry, volume, and surface area in order to meet performance requirements. One solution to these limitations of smaller satellites is to incorporate the use of deployable mechanisms. In the context of antennas, deployables allow for a much wider range of possibilities in terms of RF performance and coverage which can be flown on a smaller spacecraft. Small satellites work with a large number of design constraints that can make the addition of wideband RF coverage a mechanical challenge. Small satellites equipped with a deployable wideband antenna like the discone antenna have the capability to substantially expand RF coverage of low-cost constellation missions. This paper will describe SFL's role in the building of a microsat-compatible deployable discone antenna as well as the observations made on-orbit when it gains flight heritage in April 2024. Moreover, it will discuss SFL and HawkEye 360's vital contributions to RF constellation missions, the launch of the first spacecraft to have discone antennas, and the on-orbit deployment behaviour of this new innovation built and integrated by SFL.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.190
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDigital Commons - USU (Utah State University)Same topicStructural Analysis and OptimizationFrench-language works237,207