Pseudolite interference mitigation and signal enhancements using an antenna array
Bibliographic record
Abstract
Several terrestrial communication systems use the same frequency spectrum as Global Navigation Satellite Systems (GNSS) or bands close to it. Pseudolites constitute one such system that generally uses the GNSS spectrum for signal propagation. The signals from pseudolites in the operating region play a crucial role in augmenting satellite based user navigation. These signal transmitters are deployed at ground stations for the majority of their applications. In the near region, pseudolites are overpowered and cause impediments to normal receiver operation due to an increase in the noise floor. Interference and jammers form another source of GNSS disruption. Interference could result from intentional jammers or unintentional signal disturbances from in-band or out-of-band high power sources. A GNSS user can experience interference from near region pseudolites as well as from other interferers. These interference sources may have directional coexistence with pseudolites or GNSS satellites. Such disruptions might completely block signal acquisition and lead to processing failure. The capability of antenna array space-time processing to counter the above mentioned scenario is demonstrated herein. In addition to interference mitigation, pseudolite signal recovery in the near region and subsequent enhancements are shown. Results that demonstrate improvement in measurement geometry for various antenna array configurations and different processing modes are also shown.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".