LPI Radar Signal Detection Based on Autocorrelation Function and Wigner-Ville Distribution
Why this work is in the frame
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Bibliographic record
Abstract
Low probability of intercept (LPI) radar systems is designed "to see and not to be seen."Low peak power, low sidelobe antenna pattern, wide bandwidth, and spread spectrum waveform are their typical characteristics to prevent detection by noncooperative electronic warfare receivers.As a result, in terms of Electronic Warfare systems, the detection of an unknown LPI radar has great importance and requires special techniques.While a few studies have been done on this subject, many open points still need to be managed.This paper presents an LPI radar signal detection algorithm based on autocorrelation and time-frequency image-based moments.Detection does not require any prior information on radar signals.Detection performance for different types of LPI radar signal waveform is studied.The results showed that detection is possible under low SNR.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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