Range and Velocity Estimation for Multi-symbol OFDM-based Integrated Radar and Communications Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the integrated radar and communications (IRC) systems, accurate range and velocity estimation results can improve radar detection performance and reduce communication bit error rate. In order to better fit the integrated echo signal based on orthogonal frequency division multiplexing (OFDM), it is necessary to approximate the terms in the receiving signal as little as possible. This paper first establishes a receiving model of the IRC echo signal, including all terms. Using this model, we propose a least square weighted (LSW) method for range and velocity estimation separately. The proposed method takes the partial derivative of the LSW estimation error with respect to the range term and replaces it. The estimated velocities are substituted into the error to estimate the ranges of the targets. The search space is greatly reduced compared with that in the range-velocity dimension because the spectral peaks are searched in the velocity and range dimensions. Theoretical analysis and simulation results verify the effectiveness of the proposed method.
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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