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Real-Time OcuSync Demodulator: A Software-Defined Radio Based Implementation

2025· article· W7130598407 on OpenAlexaff
Hyungwoo Lee, Jinwoo Jeong, Sangbom Yun, Junghyun Seo, Haewoon Nam

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicUAV Applications and Optimization
Canadian institutionsNexen (Canada)
FundersDefense Acquisition Program Administration
KeywordsTelecommunications linkDemodulationDecoding methodsDroneSIGNAL (programming language)Systems architectureArchitecture

Abstract

fetched live from OpenAlex

The increasing use of commercial drones and the evolution of communication protocols, such as DJI’s OcuSync, have raised concerns regarding unauthorized drone activities. While previous studies have examined downlink signals such as DroneID, the uplink Command and Control signals have received relatively little attention. This paper presents a real-time OcuSync demodulator built on a software-defined radio (SDR) platform with a parallel processing architecture. The system supports live signal reception, visualization, and uplink demodulation through an interactive graphical user interface. The architecture ensures responsive operation by distributing demodulation workloads across multiple processes. Future work includes decoding recovered bitstreams to analyze uplink payloads and support advanced counter-drone applications.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

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