Robust beamforming for jammers suppression in MIMO radar
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Bibliographic record
Abstract
Robust beamforming for multiple-input multiple-output (MIMO) radar in the background of powerful jamming signals is investigated in this paper. We design two minimum variance distortionless response (MVDR) type beamformers with adaptiveness/robustness against the powerful jammers for colo-cated MIMO radar. Specifically, the MVDR beamformer is firstly designed for known jammers in the sector-of-interest, which maintains distortionless response towards the direction of the target while imposing nulls towards the directions of jammers. Then the adaptive/robust MVDR beamformer is designed for the general case of unknown in-sector jammers and/or out-of-sector interfering sources. Convex optimization techniques are used in both of the designs. Moreover, we derive a closed-form solution to the simplified second design. Based on this solution, we derive efficient power estimates of the desired and/or interfering sources in the context of powerful jammers and non-ideal factors such as array calibration errors and target steering vector mismatches. We demonstrate that the capability of efficient jammers suppression using these designs is unique in MIMO radar.
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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