Separation and reconstruction of the rigid body and micro‐Doppler signal in ISAR part I – theory
Bibliographic record
Abstract
In radar imaging, the micro‐Doppler effect is caused by fast movements of some scattering points on the target. These movements correspond to highly non‐stationary components in the time–frequency domain of the signal. The rigid body can be considered as stationary at one range location during the processing time. This property is used to separate the micro‐Doppler signal from the rigid body using the L‐statistics. Since the rigid body can be considered as a sparse signal, its values can be fully recovered at the positions where the micro‐Doppler and rigid body components overlap. The recovery is based on the compressive sensing theory and methods. After an overview of the methods, a quantitative analysis of the improvements achieved in the time–frequency‐based separation is done. Moreover, a comparison with both the time and the frequency domain analysis is provided. Analysis of small additive noise influence to the reconstruction accuracy is done.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".