Focusing inverse synthetic aperture radar images with higher-order motion error using the adaptive joint-time–frequency algorithm optimised with the genetic algorithm and the particle swarm optimisation algorithm – comparison and results
Why this work is in the frame
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Bibliographic record
Abstract
Algorithms based on the genetic algorithm (GA) and the particle swarm optimisation (PSO) algorithm were designed for focusing inverse synthetic aperture radar (ISAR) images that suffered from degradation because of Doppler smearing. These algorithms optimised the adaptive joint-time–frequency (AJTF) algorithm by replacing the exhaustive search as the primary search tool used to determine focusing parameters. The use of the PSO for ISAR image focusing is a unique application of this evolutionary search. Performance of the GA and the PSO were compared with the PSO producing the optimal results of being able to focus a 211 pulse ISAR image with second-order motion error in 9 s or 24% of the cost function calculations required for an exhaustive search. The PSO algorithm was then applied to a 211 pulse ISAR image with fourth-order motion error. The PSO algorithm was able to focus this image in 20 s with 33% of the cost function calculations required by the exhaustive search. This study also introduces a new method of determining basis function suitability using the fast Fourier transform.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it