Characterization of GNSS measurement distortions due to antenna array processing in the presence of interference signals
Bibliographic record
Abstract
GNSS signals are relatively weak once they are received on the earth surface and due to which they are very much vulnerable to intentional and unintentional interferences. Antenna array processing is a very efficient method for combating interference and jamming effects. Controlled Reception Pattern Antennas (CRPA) are capable of controlling the reception pattern adaptively such that interference can be mitigated by steering null in the direction of interference. In spite of having these advantages, these systems suffer from measurement distortions which in turn affect the navigation solution. Sources contributing to the measurement distortions include mutual coupling between antennas, radio frequency front-end delays, spatial filtering techniques and receiver processing methods. In this paper, the effects of mutual coupling between antennas and different array processing techniques on measurement bias are analyzed. The analysis is carried out through simulations and real data collected using Novatel 501 antennas.
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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".