Modeling the Doppler Shift in Cislunar Environment with Gaussian Mixture Models
Bibliographic record
Abstract
This study investigates the RF-based Doppler shift distribution characterization of the Lunar South Pole (LSP) based inter-satellite link (ISL) in varying inclination. Doppler shift in parts per million (ppm) is determined and analyzed, as it provides an independence from the carrier frequency. Due to unknown relative velocity states duration, the Gaussian Mixture Model (GMM) is found to be the best fitting distribution for ISLs with 1° inclination interval Doppler shift with respect to a predetermined satellite. Goodness-of-fit is investigated and quantified with Kullback–Leibler (KL) divergence and weighted mean relative difference (WMRD) error metrics. Simulation results show that ISL Doppler shifts reach up to ±1.89 ppm as the inclination of the other orbit deviates higher from the reference orbit, inclining 80°. Regarding the error measurements of GMM fitting, the WMRD and KL divergence metrics for ISL take values up to 0.6575 and 2.2963, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".