Performance Characterization of Hexagon|NovAtel’s Robust Dual-Antenna Receiver (RoDAR) during the Norwegian Jamming Trial 2022
Bibliographic record
Abstract
NovAtel has recently leveraged its expertise in both receiver design and anti-jam technology to develop solutions for space- and weight-constrained applications in challenged GNSS environments. Robust Dual-Antenna Receiver (RoDAR), is based on a commercial dual-antenna receiver, originally designed for attitude determination, and employs special firmware to mitigate jammers and spoofers without an increase in size or power consumption. With RoDAR, the multi-frequency, multi-constellation dual-antenna receiver is capable of null-steering at two different frequency bands (e.g., L1 and L5). In September 2022, the Norwegian Public Roads Administration hosted JammerTest, a live, over-the-air broadcast jamming and spoofing test. This paper presents the jamming and spoofing detection and mitigation performance of RoDAR during this live broadcast test. The interference detection provides spectrum monitoring and jamming characterization on all GNSS bands. The mitigation is carried out by steering a null formed on-board the receiver towards a jamming/spoofing source at GPS L1 and L5 bands. The null steering performance is characterized as a function of signal and position availability compared to a non-protected NovAtel receiver. The effectiveness of the anti-jam and anti-spoofing technology is demonstrated using representative complex spoofing and jamming test cases during this event.
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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".