A comparison study between Wiener and adaptive state estimation (STAP-ASE) algorithms for space time adaptive radar processing
Why this work is in the frame
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Bibliographic record
Abstract
Space Time Adaptive Processing (STAP) is a multi-dimensional adaptive signal processing technique, which processes the signal in spatial and Doppler domains for which a target detection hypothesis is to be formed. It is a sample based technique and based on the assumption of adequate number of Independent and Identically Distributed (i.i.d.) training data set in the surrounding environment. The principal challenge of the radar processing lies when it violates these underlying assumptions due to severe dynamic heterogeneous clutter (hot clutter) and jammer effects. This in turn degrades the Signal to Interference-plus-Noise Ratio (SINR), hence signal detection performance. Classical Wiener filtering theory is inadequate to deal with nonlinear and nonstationary interferences, however Wiener filtering approach is optimal for stationary and linear systems. But, these challenges can be overcome by Adaptive Sequential State Estimation (ASSE) filtering technique.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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