Extended Target Frequency Response Estimation Using Infinite Hmm in Cognitive Radars
Why this work is in the frame
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Bibliographic record
Abstract
A cognitive radar adapts its waveform to match the extended target's frequency response (TFR) for optimized detection performance. In practice, the TFR is unknown and is usually estimated using the Kalman filter assuming a linear Gaussian model. However, this assumption is not always fulfilled and other filters as the particle filter should be used. In all cases, existing approaches require the complete knowledge of the statistical distributions of both the TFR and interference. In this paper, we present a novel formulation of the TFR estimation problem that allows us to use the infinite hidden Markov model (iHMM) to estimate and track the TFR without such prior knowledge. Monte Carlo simulations considering Gaussian and non-Gaussian distributions for TFR and interference as well as jamming effects show that the proposed iHMM-based method ameliorates the estimation accuracy compared to the conventional Bayesian filtering techniques.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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